Melanoma is the most aggressive and deadly form of skin cancer, and its incidence has been steadily increasing over the past few decades, particularly in the Caucasian population [1]. Current treatment strategies, the combination of BRAF and MEK inhibitors (BRAF/MEKi) in BRAFV600 mutant melanoma, and immune checkpoint inhibitors (ICI), have changed the clinical evolution of this disease [2]. However, a significant percentage of patients do not benefit from these therapies. Therefore, to improve patient selection, it is imperative to look for novel biomarkers. Immune subsets, particularly the quantification of lymphoid populations, could contribute to the identification of ICI responders. The aim of this review is to thoroughly examine significant published data on this topic in melanoma patients and to evaluate the potential role of lymphoid subsets as prognostic and predictive response biomarkers.

Clear cell renal cell carcinoma (ccRCC) is a highly aggressive subtype of renal cancer, often associated with poor prognosis and high mortality rates. In this study, we identified Nicotinamide N-methyltransferase (NNMT) as a key gene involved in the pathogenesis of ccRCC through RNA sequencing analysis of tumor and normal tissues from 14 patients. NNMT was among the top five upregulated genes, and its high expression was significantly correlated with reduced overall, progression-free, and disease-specific survival in patients, as well as advanced pathological stages and higher histologic grades. Gene ontology (GO) enrichment analysis revealed NNMT's role in biological processes such as signal transduction and immune response. Immune cell infiltration analysis indicated that high NNMT expression was associated with increased infiltration of activated NK cells and macrophages, while low expression correlated with a higher presence of regulatory T cells. Functional studies using siRNA-mediated NNMT knockdown in ccRCC cell lines demonstrated a significant reduction in cell proliferation, with further analysis revealing altered gene expression profiles related to cell adhesion and calcium ion binding. These findings suggest that NNMT not only plays a pivotal role in ccRCC aggressiveness but also may serve as a valuable prognostic biomarker and a potential therapeutic target for improving clinical outcomes in patients with this malignancy.

A previous report showed that the urine output of HPLBII-P in patients with diabetes mellitus and SARS-Cov-2 infection was increased as a sign of glomerular dysfunction. . The aim of this report was to investigate the relation of urine output of HPLBII-P to diabetes mellitus in two large community-based elderly populations i.e. the ULSAM and PIVUS cohorts. Methods HPLBII-P was measured by ELISA in the urine of a community-based cohort of 839 men (ULSAM) collected at 77 years of age and in urine of a community-based cohort of 75-year-old men, n=387, and women, n=401 (PIVUS). KIM-1, NGAL and Albumin were measured in urine and Cathepsin S and Cystatin C in serum. Results HPLBII-P was significantly raised among males with diabetes in the ULSAM (p

Backgound: Exosomes are extracellular nanovesicles, carriers of different biomolecules such as lipids, proteins, nucleic acids. Their composition and the fact that their release dramatically increases in case of tumorigenesis, opens different scenarios on the possible application in the research for new biomarkers.Methods: The most widely applied methodologies include ultracentrifugation techniques, size-based techniques, immunoaffinity capture-based techniques (mainly ELISA) and precipitation. To optimize the acquisition of exosomes from the reference sample, more techniques can be applied in sequence for a single extraction, determining an increase in labor time and costs. Results: The analysis of PSA-expressing exosomes provides an incredibly accurate way to discriminate between healthy patients and those with prostate disease. Specifically, IC-ELISA alone method achieved 98.57% sensitivity and 80.28% specificity in discriminating prostate cancer (PC) from benign prostatic hyperplasia (BPH).An immunocapture-based ELISA assay was performed to quantify and characterize carbonic anhydrase (CA) IX expression in exosomes. The results revealed that CA IX positive exosomes were 25-fold higher in plasma samples from PC patients than in those from healthy control. Conclusions: The analysis of PC-linked exosomes represents a promising diagnostic model that can effectively distinguish patients with PC from those with non-malignant prostatic disease, However, the use of exosome analysis in clinical practice is currently limited by several issues, including a lack of standardization in the analytical process and high costs, which are still too high for a large-scale use.

The pig is an important source of meat production and provides a valuable model for certain human diseases. MicroRNA (miRNA), which is non-coding RNA and regulates gene expression at the posttranscriptional level, plays a critical role in various biological processes. Studies on identification and function of mature miRNAs in multiple pig tissues are increasing, yet the literature is limited. Therefore, we reviewed current research to determine the miRNAs expressed in specific pig tissues that are involved in carcass values (including muscle and adipocytes), reproduction (including pituitary, testis, and ovary), and development of some solid organs (e.g., brain, lung, kidney, and liver). We also discuss the possible regulating mechanisms of miRNA. Finally, as pig organs are suitable candidates for xenotransplantation, biomarkers of their miRNA in xenotransplantation were evaluated.

Galectin-3 (Gal-3) is a lectin associated with fibrosis and inflammation, and increased circulating concentrations are considered a risk factor for atrial fibrillation (AF) in humans. This retrospective study aimed to evaluate the serum concentration of Gal-3 in dogs with cardiac disease, both with and without AF. Dogs with AF associated with congenital and acquired heart diseases were selected, while clinically healthy dogs and dogs with heart diseases but without AF served as controls. We statistically compared the serum concentration of Gal-3, assessed using a commercial canine-specific ELISA kit, among healthy dogs and dogs with heart disease with and without AF. Additionally, associations between Gal-3 and clinical and echocardiographic variables were evaluated. A total of 80 dogs were included, of which 17/80 (21.2%) were clinically healthy and 63/80 (78.8%) had heart disease, with 30/63 (47.6%) having AF. No significant difference in Gal-3 concentration was found between healthy dogs (3.90 ± 0.38 ng/mL) and dogs with heart disease, either with or without AF (3.45 ± 0.28 ng/mL, P=0.226 and 4.46 ± 0.27 ng/mL, P=0.286, respectively). Gal-3 showed a significant positive correlation with age (r=0.46, P < 0.001). The results of this study suggest that Gal-3 does not have predictive value for the development of AF in dogs, but it is associated with advanced age.

Background: The clinical spectrum of fibrotic interstitial lung diseases (ILD) is highly heterogeneous. We aimed to evaluate the prognostic value of widely available baseline biomarkers for improvement of lung function in patients with fibrotic ILD. Methods: This registry-based study included 142 patients with fibrotic ILD as defined by presence of reticulation, traction bronchiectasis or honeycombing on initial high-resolution computed tomography (HRCT). Functional improvement at 1 year was defined as relative increase of 5% in forced vital capacity (FVC) or of 10% in diffusion capacity for carbon monoxide (DLCO). The prognostic value of baseline biomarkers was evaluated for all patients and the subgroup with anti-inflammatory treatment. Results: At one year, 44 patients showed improvement while 73 progressed. Multivariate analyses found prognostic significance for age <60 years (OR 5.4; 95%CI 1.9-15.4; p=0.002), lactate dehydrogenase (LDH) >250U/L (OR 2.5; 95%CI 1.1-5.8; p=0.043) and blood monocyte count <0.8G/L (OR 3.5; 95%CI 1.1-11.3; p=0.034). In 84 patients undergoing anti-inflammatory treatment, multivariate analysis revealed age <60 years (OR 8.5 (95%CI 2.1-33.4; p=0.002) as the only significant variable. Conclusion: Younger age, higher LDH and lower blood monocyte count predicted functional improvement in fibrotic ILD patients, while in those treated with anti-inflammatory drugs, only age had significant implications.

Ovarian cancer is the third most common female genital cancer. Therefore, the timely diagnosis and comprehensive treatment of postmenopausal patients with benign ovarian tumors remains crucial in the field of gynecology. The significance of ovarian tumors depends on their frequency and their effects on the quality of life of a woman, as well as the possible development of ovarian cancer. Most ovarian cancers are diagnosed late and as a result are difficult to treat and often carry a poor prognosis. Currently there is no clear algorithm available for examining and accurately diagnosing patients with postmenopausal ovarian tumors; moreover, reliable criteria allowing dynamic observation and determining surgical access and optimal surgical intervention measures in postmenopausal patients is lacking.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. The paucity of early detection and disease progression biomarkers also seems to present a major obstacle to AD drug development. The current established readouts based on expression levels of amyloid beta, tau and phospho tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, CSF or other biofluids that can facilitate early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry, are now being increasingly applied to study AD disease mechanisms, identify drug targets and novel disease biomarkers. In this report, we describe applications of the quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD and discuss development and validation of new predictive and diagnostic disease biomarkers.

Analyzing synovial fluid from joints affected by the pathological process of psoriatic arthritis is part of the overall patient examination, since it may have differential diagnostic significance. The purpose of this study was to assess the presence of crystals in the synovial fluid of psoriatic arthritis patients as biomarkers for disease activity. Materials and methods: The synovial fluid of 156 patients with proven PSA diagnosis (patients covered CASPAR criteria) was analyzed over 24 months and compared to 50 patients with activated gonarthrosis. The Leica DM4500P polarization microscope (Leica Microsystems, Germany) was used for crystal detection. Pain and disease activity measures were also evaluated (PSA VAS for pain, DAPSA, PASDAI, mCPDAI, and HAQ-DI). The statistical analysis was carried out using SPSS version 26 with a significance set at p < 0.05. Results: The macroscopic appearance of synovial fluid from patients with psoriatic arthritis was clear in 84.6% of the patients. Synovial fluid crystals were found in 23.71% of patients with psoriatic arthritis - predominantly monosodium urate (67.58%) but also calcium pyrophosphate (21.62%) and lipid drops (5.4%). The presence of monosodium urate crystals significantly correlates with all pain and disease activity measures – VAS for pain, DAPSA, PASDAI, mCPDAI, and HAQ-DI. In 67.56% of patients with established crystals treatment with an anti-TNF blocker was started at the discretion of the treating rheumatologist due to high levels of disease activity. Conclusion: Examining the synovial fluid in PSA patients is a necessary minimally invasive procedure in cases of joint effusion, since the presence of synovial fluid crystals is a significant indicator of disease severity. The current analyses demonstrate that the presence of synovial fluid crystals in PSA patients can be used as a biomarker for disease severity and the necessity to commence biological treatment (most often TNF-a-blocker).

Depressive disorder in childhood and adolescence is a highly prevalent mood disorder that tends to recur throughout life. Untreated mood disorders can adversely impact a patient's quality of life and cause socioeconomic loss. Thus, an accurate diagnosis and appropriate treatment is crucial. However, until now, diagnoses and treatments are conducted according to clinical symptoms. Objective and biological validation are lacking. This may result in a poor outcome for patients with depressive disorder. Research has been conducted to identify the biomarkers that are related to depressive disorder. Cumulative evidence has revealed that certain immunologic biomarkers in-cluding brain-derived neurotrophic factor (BDNF) and cytokines, gastrointestinal biomarkers, hormones, oxidative stress, and certain hypothalamus-pituitary axis biomarkers are associated with depressive disorder. This article reviews the biomarkers related to the diagnosis and treatment of pediatric depressive disorders. To date, clinical biomarker tests are not yet available for diagnosis or for the prediction of treatment prognosis. However, cytokines such as Interleukin-2, interfer-on-gamma, tumor necrosis factor-alpha, and BDNF have shown significant results in previous studies of pediatric depressive disorder. These biomarkers have the potential to be used for diagnosis, prognostic assessment, and group screening for those at high risk.

The dysregulation of cellular metabolism is a hallmark of ageing. To understand the metabolic changes that occur as a consequence of the ageing process and to find biomarkers for age-related diseases, we conducted a metabolomic analysis of brain, heart, kidney, liver, lung and spleen in young (9-10 weeks) and old (96-104 weeks) wild type (mixed genetic background of 129/J and C57BL/6) mice using NMR spectroscopy. We found differences in metabolic fingerprints of all tissues and identified several metabolites to be altered in most tissues, suggesting that they may be universal biomarkers of ageing. In addition, we found distinct tissue-clustered sets of metabolites throughout the organism. The associated metabolic changes may reveal novel therapeutic targets for the treatment of ageing and age-related diseases. Moreover, the identified metabolite biomarkers could provide a sensitive molecular read-out to age determine the age of biologic tissues and to validate the effectiveness and potential off-target effects of senolytic drug candidates on both a systemic and tissue-specific level.

Tear fluid is emerging as a valuable resource for biomarker discovery, but its low sample volume and dynamic composition pose significant challenges for analytical testing. Most tear proteomics studies have focused on samples collected with Schirmer strips, while capillary tube collection has received less attention. To address these challenges, we developed a novel in-capillary trypsin digestion workflow that requires as little as 0.5 μL of tear fluid for bottom-up shotgun proteomics. This method uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify a higher number of proteins with enhanced efficiency compared to previously reported methods, which typically required 5-10 μL of pooled tear fluid. Using the same microcentrifuge tube for both tear collection and sample processing, this streamlined workflow simplifies sample handling and minimizes both sample loss and experimental errors associated with sample transfer. This method also efficiently reduced sample processing time to under 2 hours prior to overnight trypsin digestion, compared to the 5-8 hours required by other methods. With this workflow, we identified 500-800 proteins per 0.5 μL sample without the need for fractionation, allowing for at least three technical replicates. This optimized workflow greatly enhances the efficiency of tear proteomics for biomarker discovery.

Gastric cancer has become one of the most common cancers in the world.Immunotherapy, especially immune point inhibitors targeting programmed cell death 1 or its ligand PD-L1, has been successfully applied in the clinical treatment of GC. However, only a small number of cancer patients experience persistent clinical responses during immunotherapy. In this review, we discussed the current status of immunotherapy for colorectal cancer, elucidated the mechanisms mediating immunotherapy resistance, predicted biomarkers for immunotherapy resistance, and strategies for improving immunotherapy efficacy.

Asthma is a complex syndrome with multiple phenotypes and endotypes, and current diagnostic tools often fail to address this, therefore there is an increasing need for new predicting biomarkers for asthma which can enable personalized treatment strategies. Biomarkers can facilitate earlier diagnosis of asthma, potentially identifying the disease before clinical symptoms appear. This allows for early intervention, which can prevent asthma progression and complications and improve long-term outcomes. Reliable biomarkers can help in monitoring disease activity and treatment efficacy in real-time and can also lead to better disease management, reducing hospitalizations, emergency visits, and overall healthcare costs associated with poorly controlled asthma. Severe asthma patients often do not respond well to standard treatments. New biomarkers can help identify these patients and guide the development of novel therapeutic approaches specifically for severe asthma. In this review we summarize different candidate biomarkers on several levels of investigation: Genetic, subclinical inflammatory, allergen-specific immune response, and trained immunity, which could be promising for the early detection of asthma and better management of exacerbation and severity of symptoms in children.

Pancreatic cancer (PC) is the most lethal type of cancer, it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC’s insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited use for early diagnosis. An in-creasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results for the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in existing biomarkers and explore novel strategies for the early detection of PC.

Pancreatic cancer is the most lethal cancer, it has lowest 5-year survival rate among other types of cancers. More than half of pancreatic cancer are diagnosed at distant stage due to its insidious and non-specific symptoms. Surgery is the most effective treatment to date, but only 10-20% are resectable upon diagnosis. Currently, the only biomarker approved by the United States Food and Drug Administration (US-FDA) for pancreatic cancer is carbohydrate antigen 19-9 (CA19-9); however, it has limited use for early diagnosis. An increasing number of studies have a combination of biomarkers. Recently, the application for liquid biopsy has drawn a lot of attention, such as the use of microRNA (miRNA), circulating tumor DNA (ctDNA), and circulating tumor cells (CTC). Screening for pancreatic cancer is indicated for high-risk patients; studies of new diagnostic models combined with biomarkers for early detection also showed promising results to aid clinicians in deciding on whether to start screening. This review aims to summarize the progress on current biomarkers and new potential strategies for early detection of pancreatic cancer.

There is no routine approach to identify patients with gynecologic malignancies at high risk for chemotherapy-resistance. Circulating tumor DNA (ctDNA) tumor fraction (TFx) represents a minimally-invasive approach to tumor profiling, with as yet limited data on utility in gynecologic malignancies. The objective was to investigate the use of ctDNA TFx in a cohort of patients with ovarian and endometrial cancer. Plasma samples from patients with biopsy-proven ovarian or endometrial cancer collected between 4/2018 and 4/2020 were subjected to shallow whole genome sequencing with determination of TFx via ichorCNA package. The association of TFx to continuous and categorical baseline clinicopathologic factors and progression-free survival was assessed. 210 plasma samples from 78 patients with gynecologic cancers were analyzed. Mean TFx for ovarian cancer was 5.5% and endometrial cancer 2.4% and there was no significant difference in TFx among histology either for endometrial or ovarian cancers. Grade was associated with significant difference in ‘sentinel’ TFx among ovarian cancers but not endometrial cancers. ctDNA TFx dynamics over time demonstrated rapid clearance of ctDNA in most patients with ovarian cancer, while endometrial cancer had consistently low TFx. ctDNA TFx is feasible in ovarian and endometrial cancers and may be a valuable important tool for prognostication.

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningioma, with a focus on Neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in preoperative and postoperative decision-making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

(1) Background: Alcohol consumption during pregnancy is a major concern, particularly in Europe and North America. Its prevalence has been so far under researched. In most of the studies the determination of this consumption may be underestimated, as it is based on the information obtained from questionnaires rather than from biomarkers, which will provide a much reliable approach. The main objective in this study was the comparison of prevalence of consumption during pregnancy assessed by a questionnaire and a hair biomarker. (2) Method: Cross-sectional study with a random sample of 425 pregnant women treated in public hospital consultations in Seville (Spain) and in the 20th week of their pregnancy, orally interviewed through a questionnaire elaborated ad hoc which evaluated sociodemographic, obstetric, and alcohol consumption variables. Additionally, the ethyl glucuronide metabolite (EtG) was tested on a hair sample in 252 pregnant women who agreed to facilitate it. Once data obtained through the questionnaire and the hair testing were analyzed, the level of metabolites and the self-reported alcohol consumption were contrasted. (3) Results: The prevalence of self-reported alcohol consumption (questionnaire) was 20.7% and real consumption (metabolite analysis) was 20.2%. In 16.8% of pregnant women who declared not consuming alcohol during their pregnancy a noticeable consumption was detected according to the metabolite testing. No relevant level of variability in estimated alcohol consumption was detected in the biomarker with respect to the studied sociodemographic and obstetric variables.

Background: Alcohol-associated Liver Disease (ALD) is the most common disorder of prolonged drinking. Mechanisms underlying cirrhosis in such patients remain unclear. MicroRNAs play regulatory role in several diseases, are affected by alcohol and may be important players in alcohol use disorders, such as cirrhosis. Methods: We investigated serum samples from heavy chronic alcohol users (80g/d (M) and 50g/d (F) for ≥10 years) that were available from our previously reported GenomALC study. A subset of drinkers with liver cirrhosis (cases, n=24) and those without significant liver disease (controls, n=23) were included. Healthy controls (HC, n=5) were volunteers in the study. Global microRNA profiling was performed using high-throughput real-time quantitative PCR to identify the microRNA signatures. Ingenuity Pathway Analysis software (IPA) was utilized to identify target mRNAs of significantly altered microRNAs and molecular pathways were analysed. Identified microRNAs were analysed for correlation with traditional liver disease biomarkers and risk gene variants previously reported from GenomALC genome-wide association study. Results: The expression of 81 and 21 microRNAs was significantly downregulated in cases compared to HC and controls, respectively (p<0.05, Ct >1.5-fold). Most microRNAs showed lower abundance in alcohol users compared with HC. Seven microRNAs (miR-16, miR-19a, miR-27a, miR-29b, miR-101, miR-130a, & miR-191) had a highly significant correlation (p<0.001) with INR, bilirubin and MELD score. Three microRNAs (miR-27a, miR-130a and miR-191) significantly predicted cases with AUC-ROC 0.8, 0.78 and 0.85, respectively (P<0.020), however, INR performed best (0.97, p<0.001). A different set of 6 microRNAs (miR-19a, miR-26a, miR-101, miR-151-3p, miR-221, & miR-301) showed positive correlation (ranging 0.32-0.51, p<0.05) with rs10433937:HSD17B13 gene variant, associated with risk of cirrhosis. IPA analysis revealed mRNA targets of the significantly altered microRNAs associated with cell death/necrosis, fibrosis and increased steatosis, particularly triglyceride metabolism related mRNA targets. Conclusions: MicroRNA signatures in drinkers distinguished those with liver cirrhosis from those without liver disease. We identified mRNA targets in liver functions that were enriched for disease pathogenesis pathways.

SARS-CoV-2 infection triggers distinct patterns of disease development, characterized by significant alterations in host regulatory responses. Severe cases exhibit profound lung inflammation and systemic repercussions. Remarkably, critically ill patients display a "lipid storm", influencing the inflammatory process and tissue damage. Sphingolipids (SL) play pivotal roles in various cellular and tissue processes, including inflammation, metabolic disorders, and cancer. In this study, we employed high-resolution mass spectrometry to investigate SL metabolism in plasma samples obtained from control subjects (n=55), COVID-19 patients (n=204), and convalescent individuals (n=77). These data were correlated with inflammatory parameters associated with the clinical severity of COVID-19. Additionally, we utilized RNAseq analysis to examine the gene expression of enzymes involved in the SL pathway. Our analysis revealed the presence of thirty-eight SL species from seven families in the plasma of study participants. The most profound alterations in the SL species profile were observed in patients with severe disease. Notably, the predominant sphingomyelin (SM d18:1) species emerged as a potential biomarker for COVID-19 severity, showing decreased levels in the plasma of convalescent individuals. Elevated SM levels were positively correlated with age, hospitalization duration, clinical score, neutrophil count, as well as the production of IL-6 and IL-8. Intriguingly, we identified a putative protective effect against disease severity mediated by SM (d18:1/24:0), while ceramide (Cer) d18:1/24:1 and d18:1/24:0 was associated with increased risk. Moreover, we observed enhanced expression of key enzymes involved in SL pathway, in blood cells from severe COVID-19 patients, suggesting a primary flow towards Cer generation in tandem with SM synthesis. These findings underscore the potential of SM as a prognostic biomarker for COVID-19 and highlight promising pharmacological targets. By targeting sphingolipid pathways, novel therapeutic strategies may emerge to mitigate the severity of COVID-19 and improve patient outcomes.

The methyltransferase, KMT5A has been proposed as an oncogene in prostate cancer and therefore represents a putative therapeutic target. To confirm this hypothesis we have performed a microarray study in a prostate cancer cell line model of androgen independence following KMT5A knockdown in the presence of transcriptionally active androgen receptor (AR) to understand which genes and cellular processes are regulated by KMT5A in the presence of an active AR. We observed that 301 genes were down-regulated whilst 408 were up-regulated when KMT5A expression was reduced. KEGG pathway and Gene Ontology analysis revealed apoptosis and DNA damage signaling are up-regulated in response to KMT5A knockdown whilst protein folding and RNA splicing were down-regulated. Under these conditions, the top non-AR regulated gene was found to be CDC20, a key regulator of the spindle assembly checkpoint with an oncogenic role in several cancer types. Further investigation revealed that KMT5A regulates CDC20 in a methyltransferase dependent manner to modulate both histone H4K20 methylation within its promoter region and indirectly via the p53 signalling pathway. A positive correlation between KMT5A and CDC20 expression was also observed in clinical prostate cancer samples further supporting this association. Therefore, we conclude that KMT5A is a valid therapeutic target for the treatment of prostate cancer and CDC20 could potentially be utilized as a biomarker for effective therapeutic targeting.

We investigated the diagnostic capacity of selected circulating biomarkers (CBMs) for the early detection of bone metastasis (BMets) in patients with pancreatic neuroendocrine neoplasms (PanNENs). 115 patients with PanNENs and 40 controls were enrolled. We measured the serum levels of ferritin, cytokeratin 18 (CY18), CA19-9, CA125, AFP, CEA, and beta-2 microglobulin (B2M). 8 PanNENs patients developed BMets, and 107 remained BMets-free. We observed a significantly higher level of CA125 and CY18 in BM-PanNENs patients vs. non-BM-PanNENs patients (p = 0.01 and p = 0.04, respectively). CA125, CY18, and B2M area under receiver operator characteristic (AUROC) analyses differentiated BM-PanNENs from non-BM-PanNENs patients; CA125 area under the curve (AUC) 0.77, p < 0.01; CY18 AUC data were 0.72, p = 0.03, and B2M AUC 0.67, p = 0.02. Based on CBMs metrics in both subgroups, we reached a sensitivity/specificity for CA125 of 75/76%; for CY18 of 75/69%, for B2M of 100/50%, for CA125 and CY18 combination 93/90%, respectively. The useful CBMs for BM-PanNENs patients detection were CA125, CY18, and B2M. They seem to have the diagnostic capacity as a fair single biomarker and CA125&CY18 combination panel for the detection of BMets.

Every year around 800 000 people commit suicide, this represents one death every 40 seconds. In the search for possible biological biomarkers associated with suicide and/or psychiatric disorders, serum cholesterol levels have been extensively explored. Several studies have indicated that cholesterol and associated proteins, especially apolipoproteins (Apos), may play an important role in the diagnosis, prognosis, and susceptibility of suicide. Here, we describe the current knowledge and findings in the relationship between apolipoproteins and suicide.

Cancer is a complex systemic disease that changes the entire proteome. The analysis of this transformation makes it possible to determine tumor markers, that is, the most characteristic biomacromolecules produced by tumor cells. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Unfortunately, none of the tumor markers, even those used in the clinic, has all these characteristics. Despite this, many tumor markers have demonstrated excellent clinical relevance for monitoring the effectiveness of different treatments for cancer patients. The use of markers also aids in the early detection of cancer recurrence and prognosis. Therefore, the situation in this area can be improved in two ways – by attempting to find an ideal single tumor marker or generating panels of different markers. In both cases, proteomics certainly plays a major role. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers digging very deep plasma proteome. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. Here, we present data about these profiles generated by two-dimensional electrophoresis with the following mass-spectrometry and immunodetection.

Neurofilament light chain (Nf-L) is a well-known biomarker for axonal damage, however the corresponding circulating Nf-L analyte in CSF is poorly characterized. We, therefore, isolated new monoclonal antibodies against synthetic peptides, and these monoclonals were characterized for their specificity on brain-specific intermediate filament proteins. Two highly specific antibodies, ADx206 and ADx209, were analytically validated for CSF applications according to well-established criteria. Interestingly, using three different sources of purified Nf-L proteins, a significant impact on interpolated concentrations was observed. With a lower limit of analytical sensitivity of 100 pg/ml using bovine Nf-L as the calibrator, we were able to quantify the Nf-L analyte in each sample and these Nf-L concentrations were highly correlated to the Uman diagnostics assay (Spearman rho= 0.97, P<0.001). In the clinical diagnostic groups, the new Nf-L ELISA could discriminate patients with Alzheimer’s disease (AD, n=20) from frontotemporal lobe dementia (FTD, n=20) and control samples with subjective cognitive decline (SCD, n=20). Henceforth, this novel Nf-L ELISA with well-defined specificity and epitopes can be used to enhance our understanding of harmonizing the use of Nf-L as a clinically relevant marker for neurodegeneration in CSF.

Background: Esophageal cancer was hardly diagnosed in early stage, and more potential biomarkers should be found. Methods: 252 patients and normal controls which recruited in Renmin Hospital of Wuhan University, were divided into esophageal carcinoma group (105 cases), disease control group (75 cases) and the control group of healthy people (72 cases). Moreover, TISIDB and GEPIA databases were used to investigate the different expression of EC and normal tissues, and explore the roles of C1q in tumor-immune system interactions in EC. Results: The concentration of serum C1q in EC group is 196.8(180~219.4) mg/L, which is higher than the level of DC [178.10(153.70~200.85) mg/L]and HC [183.00(167.75~201.00) mg/L] (P<0.05). A higher expression level of C1q was observed in Ⅲ and Ⅳ grades [214(192~237.3) mg/ml] than grades Ⅰ and Ⅱ [180.95(172.03~193.85) mg/L] (P<0.05). C1q was positively correlated with eosinophils, active CD8 T cells, myeloid derived suppressor cells, natural killer cells, monocytes and macrophages (r = 0.373; r = 0.659; r = 0.846; r = 0.760; r = 0.499; r = 0.757; P<0.05). Conclusion: The concentrations of C1q increased in EC and related to the severity of EC, which had potential value of diagnosis of EC. There were correlations in C1q and tumor-infiltrating lymphocytes.

Although, severe acute respiratory syndrome coronavirus – 2 (SARS-CoV 2) represents one of the biggest challenges in the world today, the exact immunopathogenic mechanism that leads to severe or critical Coronavirus Disease 2019 (COVID-19) has remained incompletely understood. Several studies have indicated that high systemic plasma levels of inflammatory cytokines result in the so-called “cytokine storm”, with subsequent development of microthrombosis, disseminated intravascular coagulation, and multiorgan-failure. Therefore, we reasoned that elevated inflammatory cytokine might act as prognostic factors. Here, we analyzed 245 serum samples of patients with COVID-19, collected at hospital admission. We assessed the levels of heat shock protein 27 (HSP27), soluble suppressor of tumorigenicity- 2 (sST2), caspase cleaved cytokeratin 18 (cCK18), 20S proteasome, and tumor necrosis factor receptor 1 (TNFR-1) and explored their associations with overall-, 30-, 60-, 90-day- and in-hospital mortality. Moreover, we investigated their association with the risk of ventilation. We demonstrated that increased serum sST2 was uni- and multivariably associated with all endpoints. However, we also identified 20S proteasome as independent prognostic factor for in-hospital mortality. Furthermore, elevated HSP27, sST2, and 20S proteasome levels at hospital admission were univariably associated with higher risk of invasive ventilation. These findings could help to identify high-risk patients early in the course of COVID-19.

Discovery of novel variants from data derived from local population provides confident targets for developing biomarkers for personalized medicine. Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. We identified the need to generate high quality sequencing data from local population and understand the pattern of occurrence of variants in colorectal cancer patients. In this report, we used archived samples from Saudi Arabia and used Ampliseq Comprehensive Cancer panel to identify novel somatic variants. We report a comprehensive analysis of next generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in large intestine. APC, RET and EGFR genes were most frequently mutated. Higher number of variants were identified in left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.

Peach is the third most important temperate fruit crop considering fruit production and harvested area in the world. Exporting peaches represents a challenge due to the long-distance export markets. This requires fruit to be placed in cold storage for a long time, which can induce a physiological disorder known as chilling injury (CI). The main symptom of CI is mealiness which is perceived as non-juicy fruit by consumers. The purpose of this work was to identify and compare the metabolic and lipid profile between two siblings from a contrasting population for juice content, at harvest and after 30 days at 0°C. A total of 119 metabolites and 189 lipids were identified, which showed significant differences of abundance including mainly in amino acids, sugars and lipids. Our results indicate that some of the top metabolites and lipids could be used as biomarkers associated with mealiness at harvest and after cold storage.

The development of biosensors with high sensitivity and low-detection limits provides a new direction for medical and personal care. Graphene and graphene derivatives have been used to prepare various types of biosensors due to their excellent sensing performance (e.g. high specific surface area, extraordinary electronic properties, electron transport capabilities and ultrahigh flexibility). This perspective review focuses on graphene-based biosensors for quantitative detection of cancer related biomarkers such as DNA, miRNA, small molecules and proteins by integrating with different signal outputting approaches including fluorescent, electrochemistry, surface plasmon resonance, surface enhanced Raman scattering etc. The article also discussed their challenges and potential solutions along with future prospects.

As lung cancer shows the highest mortality in cancer related death, serum biomarkers are demanded for the lung cancer diagnosis and its treatment. To discover lung cancer protein biomarkers, secreted proteins from primary cultured lung cancer and adjacent normal tissues from patients were subjected to LC/MS-MS proteomic analysis. Quescin sulfhydryl oxidase(QSOX1) was selected as a biomarker candidate from the proteins enriched in the secretion of lung cancer cells. QSOX1levels were higher in 82% (51 of 62 tissues) of lung cancer tissues compared to adjacent normal tissues. Importantly, QSOX1 serum levels were significantly higher in cancer patients (p<0.05, AUC=0.89), when measured by multiple reaction monitoring(MRM). Higher levels of QSOX1 are also uniquely detected in lung cancer tissues among several other solid cancers by immunohistochemistry. QSOX1 knock-downed Lewis lung cancer (LLC) cells was less viable from oxidative stress and had reduced migration and invasion. In addition, LLC mouse models with QSOX1 knock-down also proved that QSOX1 functions in promoting cancer metastasis. In conclusion, QSOX1 might be a lung cancer tissue-derived biomarker and involved in the promotion of lung cancers, and thus can be a therapeutic target for lung cancers.

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival and other prognostic endpoints in multiple cancer types, including Lower-Grade Gliomas (LGG), Breast Invasive Carcinoma (BRCA) and many others. We also showed significant association of MNAI with genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Futhermore, we found that patients with high MNAI benefit more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated on LGG and BRCA that the multimodal integration of MNAI and the AI-empowerd Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

Alzheimer’s disease (AD) is a progressive irreversible neurodegenerative disorder that represents a major global public health concern. Traditionally, AD is diagnosed using cerebrospinal fluid biomarker analysis or brain imaging modalities. Recently, less burdensome, more widely available blood biomarker (BBM) assays for amyloid-beta (Aβ42/40) and phosphorylated-tau concentrations have been found to accurately identify the presence/absence of brain amyloid plaques and tau tangles and have helped to streamline AD diagnosis. However, few BBMs have been rigorously analytically validated. Herein, we report the analytical validation of a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for quantifying plasma phosphorylated-tau217 (p-tau217) and non-phosphorylated-tau217 (np-tau217) peptide concentrations. We combined the p-tau217/np-tau217 concentrations ratio (%p-tau217) and the previously validated LC-MS/MS assay for plasma Ab42/40 into a new multiple analyte blood test and algorithm (PrecivityAD2™) that identifies brain amyloid status based on brain amyloid positron emission tomography. We found: (a) the %p-tau217 assay is precise, accurate, sensitive, linear over a wide analytical measurement range, and free from carryover and interference; (b) the pre-analytical specimen collection, processing, storage and shipping conditions that maintain plasma tau peptide stability; and (c) using the measured analytical imprecision for plasma Aβ42/40 and p-tau217/np-tau217 levels in a worst-case scenario model, the PrecivityAD2 test algorithm for amyloid pathology classification changed for only 3.5% of participants from brain amyloid positive to negative, or negative to positive. The plasma sample preparation and LC-MS/MS methods underlying the PrecivityAD2 test are suitable for use in the clinical laboratory and valid for the test’s intended purpose: to aid in the diagnostic evaluation of individuals aged 55 and older with signs or symptoms of mild cognitive impairment or dementia.

Pseudopregnancy (PPG) is a common reproductive disorder in dairy goats, characterized by the accumulation of sterile fluid in the uterus and persistence of a corpus luteum, leading to temporary infertility and reduced farm efficiency. This study mainly aimed to determine the profile of pregnancy-associated glycoproteins (PAGs) in dairy goats, and to evaluate the potential of the PAGs/P4 ratio as a novel biomarker for PPG diagnosis. A total of 605 Saanen and crossbreed goats were evaluated via transabdominal ultrasonography, at 34.5 ± 0.5 days after bucks´ removal, in four intensive dairy farms, and presenting an overall incidence of 7.8%. Blood samples from PPG (n = 47), non-pregnant (NPG; negative control; n = 11) and pregnant (PG; positive control; n=10) does were collected for PAG and P4 analysis. Plasmatic levels of PAGs of PPG was similar (0.08 ± 0.02) to NPG (0.13 ± 0.04; p &gt;0.05), but lower than PG group (1. 45 ± 0.04 S-N OD; p &lt;0.001). PAGs/P4 ratio was lower in PPG (0.01 ± 0.11; p &lt; 0.001)) than in NPG (0.24 ± 0.23) and PG (0.18 ± 0.23) groups. The sensitivity and specificity of this biomarker to diagnosis PPG was 98.8% and 100%, respectively. The area under the survival curve (AUC) was 99.6 for cut-off of 0.04 and 97.9% of sensibility and specificity. This study suggests that the PAGs/P4 ratio can serve as a reliable biomarker for PPG diagnosis, helping to distinguish it from pregnancy and non-pregnancy, and improving reproductive management in dairy goats.

Background/Objectives: Chemerin, which is a multifunctional cytokine and adipokine, has been implicated in inflammatory and metabolic processes and might play a role in upper gastrointes-tinal (GI) malignancies, particularly gastric and esophageal cancer. The aim of this review is to explore the role of chemerin in the pathophysiology of upper GI cancers, as well as its potential as a biomarker for early detection and as a therapeutic target. Methods: A comprehensive review of recent studies about chemerin's biochemical properties and interaction with its receptors, as well as its effects on inflammatory responses, immune regulation and metabolic processes was con-ducted. Clinical implications of chemerin on gastric and esophageal cancer were analyzed, whereas the potential therapeutic strategies targeting chemerin were discussed. Results: Elevated chemerin levels are associated with poor prognosis in gastric cancer and promote invasiveness and metastasis in esophageal cancer. Chemerin receptor antagonists show promising results in inhibiting cancer cell migration, invasion and progression. Conclusions: Chemerin could repre-sent a valuable prognostic biomarker and therapeutic target for upper GI cancers. Future observa-tional studies should validate its clinical applications and investigate the efficacy of chemerin in-hibitors as potential therapeutic targets.

Background/Objectives: Survival prospects following SARS-CoV-2 infection may extend beyond the acute phase, influenced by various factors including age, health conditions, and infection se-verity. However, this topic has not been studied in detail. We therefore investigated mortality risk post-acute COVID-19 in the CRIT-COV-U cohort. Methods: We could retrieve survival data from 651 patients and also assess the association between urinary peptides and future death. Data spanning until December 2023 were collected from six countries, comparing mortality trends with age- and sex-matched non-infected controls. A death prediction classifier was developed and validated using pre-existing urinary peptidomics datasets. Results: Notably, 13.98% of post-COVID-19 patients succumbed during the follow-up, with mortality rates significantly higher than non-infected controls, particularly evident in younger individuals (&lt;65 years). These data for the first time demonstrate that SARS-CoV-2 infection highly significantly increases the risk of mortality not only during the acute phase of the disease, but also beyond, for a period of about one year. In our study we were further able to identify 201 Urinary peptides linked to mortality, and integrated these into a predictive classifier (DP201). Higher DP201 scores, alongside age and BMI, significantly predicted death. Conclusions: Our findings underscore the utility of urinary peptides in prognosticating post-acute COVID-19 mortality, offering insights for targeted interventions. Our data also suggest that mortality should be considered as one possible symptom or conse-quence of post-acute sequelae of SARS-CoV-2 infection, a fact that is currently overlooked.

Background and Objectives: Proteomics encompasses the exploration of protein composition, regulation, function, and pathways. Its influence spans diverse clinical fields and holds promise in addressing various women’s health conditions, including cancers, osteoporosis, and cardiovascular disorders. However, no comprehensive summary of proteomics and menopausal health exists. Our objective was to summarize proteomic profiles associated with diseases and disorders in peri and postmenopausal women. Materials and Methods: We conducted a comprehensive search of databases including PubMed, Google Scholar, Cochrane database, Elsevier, and ScienceDirect until 2022. A total of 253 studies were identified, 41 studies met the inclusion criteria to identify data of interest. These included study design, disease, and proteomics/proteins of significance as described by the authors. Results: The 41 studies, covered diverse areas including bone disorders (10 studies), cardiovascular diseases (5 studies), oncological malignancies (10 studies), and conditions such as obesity, nonalcoholic liver disease, the effects of hormone replacement therapy, and neurological diseases (16 studies). Results of our study indicate that proteomic profiles correlate with heart disease in peri- and postmenopausal women, with distinct sex differences. Furthermore, proteomic profiles significantly differed between women with and without osteoporosis. Additionally, patients with breast, ovarian, and endometrial cancer exhibited notable variations in proteomic profiles compared to those without these conditions. Conclusions: Proteomics has the potential to enhance risk assessment and disease monitoring in peri- and postmenopausal women. By analyzing unique protein profiles, clinicians can identify individuals with heightened susceptibility to specific diseases or those already affected by established conditions. This review suggests that there is sufficient preliminary data for proteomics in peri- and postmenopausal women for early identification of cardiovascular disease, osteoporosis, and cancers, in disease monitoring, and in tailoring individualized therapies. Rigorous validation studies involving large populations are essential before drawing definitive conclusions regarding the clinical applicability of proteomic findings.

The macular pigment optical density (MPOD) signifies a vital component of macular well-being and high-resolution visual acuity. MPOD can serve as a reliable biomarker for assessing the retinal defense mechanisms against oxidative stress and the deleterious effects of excessive light exposure. Elevated MPOD levels offer robust protection against the onset and progression of age-related macular degeneration (AMD) a prevalent cause of vision impairment among the elderly population. MPOD's implications in diverse ocular conditions, including diabetic retinopathy and glaucoma, have been explored and indicate a real need for clinical measurement of MPOD. This review looks at the potential of MPOD as a modifiable biomarker influencing the progression and onset of these conditions, particularly in the context of oxidative stress and retinal ischemia. The integration of MPOD measurement into routine eye examinations presents an unparalleled opportunity for early disease detection, precise treatment planning, and longitudinal disease monitoring. Emerging technologies and longitudinal investigations promise to elucidate the dynamic nuances of MPOD in the context of age-related ocular diseases.

Premalignant lesions in the bronchial epithelium represent early stages of squamous cell lung carcinoma, challenging to detect with conventional methods. While previous studies have focused on gene expression, here we examine transcriptomic alterations associated with lesion development with the emphasis on protein-coding transcripts. We reanalyzed publicly available RNAseq dataset on airway epithelial cells from 82 smokers with and without premalignant lesions. Transcript abundances were quantified using kallisto, and differential expression and transcript usage analysis was conducted using the sleuth and RATs packages. Functional characterization included overrepresentation analysis (clusterProfiler), weighted co-expression network analysis (WGCNA), and network analysis (Enrichr-KG). We detected 5,906 differentially expressed transcripts, with significant enrichment in pathways related to oxidative phosphorylation and mitochondrial function. Transcript-level WGCNA identified single module correlated with dysplasia status, enriched in cilium-related biological processes. Analysis of hubs within this module highlighted key genes including RABL2B, DNAH1, EFHC1 and VWA3A, and revealed transcription factors such as FOXJ1 and ZNF474 as potential regulators. Our findings underscore the value of transcript-level analysis in uncovering novel insights into premalignant lesion biology. By examining transcripts rather than genes, we identified potential biomarkers associated with early lung carcinogenesis.

Introduction: This study aims to elucidate the clinical diagnostic value of S100 Calcium Binding Protein beta (S100B) in epilepsy, a topic of ongoing debate among European and Asian epilepsy research centres.Methods and analysis: A structured long-term research plan was developed, comprising three phases. Phase one involves observational studies investigating the correlation between S100B levels in serum or cerebrospinal fluid and epilepsy. Phase two integrates observational and randomised controlled data to establish baseline S100B levels across diverse epilepsy demographics, underpinning the predictive value of S100B for epilepsy. Phase three focuses on randomised controlled trials to evaluate the diagnostic accuracy of S100B as an epilepsy biomarker.Ethics and dissemination: All enrolled patients will provide written consent. The ethics committee of the Second People’s Hospital of Gansu Province, Affiliated Hospital of Northwest Minzu University, China, approved the study (GSSEY2022-KY009-01).Registration: The study is registered with PROSPERO (CRD42023425431).

Blood-based biomarkers for early detection of recurrence have a significant clinical impact on the improved management of breast cancer patients, as cancer recurrence results in poor prognosis. This study aimed to investigate if the measurement of blood endocan in breast cancer patients with high ESM1 expression could be an effective tool to detect postoperative recurrence compared with existing tumor markers. Blood was collected before and after the tumor resection from the mouse models of breast cancer, and endocan levels were measured while visualizing metastatic recurrence with noninvasive luminescence imaging. In clinical settings, blood was withdrawn from 16 breast cancer patients before and after the tumor resection, and the effect of lumpectomy on blood endocan level was evaluated. Additionally, the blood endocan from 20 patients diagnosed with postoperative recurrence was measured, and their positivity rate for endocan was compared with that for serum carcinoembryonic antigen (CEA) or cancer antigen 15-3 (CA15-3). Our preclinical and clinical experiments revealed that blood endocan levels reflected tumor burden. Furthermore, over 60% of patients suffering from postoperative recurrence who tested negative for CEA or CA15-3 were positive for endocan. Our results support the clinical significance of endocan in breast cancer patients for detecting breast cancer recurrence.

Background: Previous data indicate a role of IL-1 and IL-1RA imbalance in bladder carcinoma (BC) and inhibition of IL-1 signaling might be considered a treatment option. Objective: To assess expression patterns and the prognostic role of IL-1ß and IL-1RA in invasive BC and to evaluate their interaction with AKT signaling and proliferation. Design, Setting, and Participants: The study included two independent cohorts of n=92 and n=102 patients who underwent radical cystectomy for BC. Specimen from BC and benign urothelium (n=22 and n=39) were processed to a tissue microarray and immunohistochemically stained for IL-1ß, IL-1RA, AKT and Ki-67. Expression scores were correlated to clinical variables and Ki-67 and AKT expression. Outcome measurements and statistical analysis: Association with outcome was assessed using Wilcoxon Kruskal-Wallis tests, Chi-square tests or linear regression, dependent on the variable’s category. Kaplan–Meier and Cox proportional hazard analyses were used to estimate recurrence-free (RFS), cancer-specific (CSS) and overall survival (OS). Results: Both, IL-1ß and IL-1RA were significantly overexpressed in invasive BC compared to benign urothelium in both cohorts (p&lt;0.005). IL-1ß was associated with vascular invasion (210 vs. 183, p&lt;0.02), lymphatic invasion (210 vs. 180, &lt;0.05) and G3 cancer (192 vs. 188, &lt;0.04). Survival analysis revealed favorable RFS, CSS, and OS in case of high IL-1ß expression (p&lt;0.02, &lt;0.03 and &lt;0.006, respectively). Multivariate analyses revealed an independent impact of (low) IL1ß expression on RFS, CSS and OS. IL-1ß and IL-1ß/IL-1RA ratio were positively correlated to AKT expression (p&lt;0.05 and &lt;0.01, respectively). Additionally, high expression of Ki-67 (&gt;15%) correlated with higher levels of IL-1β (p=0.01). Conclusions: Overexpression of IL-1ß and IL-1RA is frequently found in BC, with a prognostic significance observed for IL-1ß protein expression. The observed link between the IL-1ß / IL-1RA axis and AKT signaling may indicate possible autophagy activation processes beside the known tumor-promoting effects of AKT.

Background and Objectives: Stroke is a main leading cause for mortality and morbidity worldwide. Treat-ment of this pathology is still under development and its risk factors remain the main target to be reached. Therefore, we aim to determine the role of interleukin 1 beta in atheromatosis, as risk factor for stroke and the reole of this biomarker in stroke prognosis. Materials and Methods: The study conducted enrolled 56 patients diagnosed with ischemic stroke in the anterior (AVT) and posterior vascular territory (PVT). All patients had venous blood collected at admission and 7 days after the onset of the cerebral ischemia in order to determine plasma concentration for interleukin 1 beta. At the same time an extracranial carotid ultrasound was performed. Results: Interleukin 1 beta collected at admission was positively correlated with NIHSS at admission (Pearson index 0,424) and both measurements were corelated with carotid stenosis (Spearmen correlation index 0,529, respectively 0,653). Conclusion: Interleukin 1 beta could be a reliable biomarker for stroke prognosis and carotid atheromatosis development.

Lipidomics provides comprehensive study of all lipid components in cells, serum, plasma or tissues of organisms, aiming to the discovery of diagnostic, prognostic and predictive biomarkers of diseases such as malignancies. This systematic review evaluates studies, where lipidomics applies to the diagnosis, prognosis, prediction of ovarian cancer (OC) and the discrimination between malignant and benign ovarian masses. Literature search was conducted in PubMed, Science Direct and SciFinder. Only publications written in English language after 2012 were included. From the reference lists of primary included studies, relevant citations were identified and were also added in our list. All studies included referred to the application of lipidomics in serum/plasma samples of human cases with OC, whereby few of them included also tumor tissue samples. In some of the included studies metabolomic analysis was also involved where other metabolites besides lipids were identified. Qualitative data were assessed and risk of bias was determined using the ROBINS-I tool. In total, 29 studies were included, 15 of which applied non-targeted, 7 targeted lipidomics and 7 were reviews relevant to our aim. Most studies concerned the possible application of lipidomics in OC diagnosis, exhibiting phospholipids and sphingolipids as the most significantly altered during development of the disease. In conclusion, this systematic review highlights the potential contribution of lipids as biomarkers in OC management.

Background: The incidence of prostate cancer (PC) has been risen annually. Despite the diagnosis is made mainly with non-metastatic PC, mortality is explained by the metastatic disease (mPC). Without a doubt there is an intermediate scenario in which patients have no mPC but will have initiated a metastatic cascade through an epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict what patients will progress in the future to non-localized clinical disease or already have micrometastatic disease, and therefore, will clinically progress after primary treatment. Biomarkers for predicting mPC are still under development; there are few studies and not much evidence of their usefulness. Summary: This review is focused on tissue-based genomic biomarkers (TBGB) for predicting metastatic disease. We developed four main research questions that will attempt to answer according to the current evidence. Why is important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are current prostate cancer treatments? Key Messages: Knowing useful predict tools could help determine which patients may need multimodal or adjuvant treatment even with a localized disease, and in consequence, what patients do not need more than a single modality of treatment. The importance of predicting metastasis is fundamental, given that once metastasis is diagnosed, the quality of life (QoL) and survival drop dramatically.

Transitional waters are fragile ecosystems with high ecological values, representing the breeding and resting sites for rare and threatened species. They deserve particular concern for protection, undergoing numerous threats from anthropogenic nature. The present review aims to analyze the recent literature on Aphanius fasciatus, nowadays considered one of the most strictly estuarine-dependent fish species, and as such affected by the degradation of lagoon habitats, and to discuss its suitability as sentinel species of the quality of transitional water environments. The analysis and discussion highlight the potential applicability of the molecular, cellular, and physiological responses of this species as diagnostic tools for detecting the subtle effects induced by environmental pollution on the biota in transitional water environments. Moreover, the suitability of the responses of this species is suggested in the wider framework of the One Health Perspective which considers human and animal health and the environmental state highly interconnected, sharing common aspects. To date, omics technologies show very great potential in reacquiring novel knowledge on the responses of the organisms to environmental changes and to the alterations of the environmental health status. Therefore, considering the relevant potential of this species as sentinel species, many efforts are needed in the next future to improve the quantity and quality of the -omics tools that refer to A. fasciatus.

Background: As pediatric BOLD SV is relatively novel, there is a need to provide a foundational framework that gives researchers an entry point into engaging with the topic. This begins with clarifying the definition of BOLD variability by identifying and categorizing the various metrics utilized to measure BOLD SV; Methods: A systematic review of the literature was conducted. Inclusion criteria were restricted to studies utilizing any metric of BOLD signal variability (BOLD SV) and with individuals younger than 18 in the study population. The definition of BOLD SV was any measure of intra-individual variability in the BOLD signal. Five databases were searched: Psychinfo, Healthstar, Medline, Embase, and Scopus; Results: Seventeen observational studies, including male (n =1796) and female (n =1324) pediatric participants were included. Eight studies quantified variability as the amount of deviation from average BOLD signal, 7 used complexity-based metrics, 3 used correlation measures of variability, and 1 used structure of the hemodynamic response function. Ten methods of quantifying signal variability were identified. Associations and trends in BOLD SV were commonly found with age, factors specific to mental and/or neurological disorders like attention deficit disorder, epilepsy, psychotic symptoms, and performance on psychological and behavioral tasks. Conclusions: BOLD SV is a potential biomarker of neurodevelopmental and neurological conditions and symptom severity in mental disorders for defined pediatric populations. Studies that establish clinical trends and identify the mechanisms underlying BOLD SV with a low risk of bias are needed before clinical applications can be utilized by physicians

Mesothelin is a protein that is expressed in the mesothelial cell lining in the pleura, peritoneum, and pericardium. The gene of mesothelin encodes a precursor protein that is processed to yield mesothelin, which is attached to the cell membrane by a glycophosphatidylinositol linkage and a shred fragment named the megakaryocytic-potentiating factor. The biological functions of this substance in normal cells are still unknown. Experimental studies on knockout mice suggest that this substance does not play an important role in development and reproduction. In contrast, it has been observed that mesothelin is produced in abnormal amounts in several malignant neoplasms, such as mesotheliomas and pancreatic adenocarcinomas. Given that mesothelin is overexpressed in many solid tumours and has antigenic properties, this molecule could be considered a tumour marker or an antigenic target for many malignancies. Many molecular studies also have demonstrated that mesothelin is overexpressed in serous ovarian carcinomas and may bind to ovarian cancer antigen Ca-125, favouring the spread of the tumour in the abdominal cavity. 3 Here, we discuss the current knowledge of mesothelin and focus on its role in clinical and pathological diagnoses as well as its impact on the prognosis in serous ovarian carcinomas. We also briefly discuss the latest progress of mesothelin-targeting therapies for this aggressive and lethal neoplasm.

Glioblastoma (GBM) is the most common primary brain tumor in adults, with few available therapies and a 5-year survival rate of 7.2%. Hence, strategies for improving GBM prognosis are urgently needed. The translocator protein 18kDa (TSPO) plays crucial roles in essential mito-chondria-based physiological processes and is a validated biomarker of neuroinflammation, which is implicated in GBM progression. The TSPO gene has a germline single nucleotide pol-ymorphism, rs6971, which is the most common SNP in the Caucasian population. High TSPO gene expression is associated with reduced survival in GBM patients; however, the relation between the most frequent TSPO genetic variant and GBM pathogenesis is not known. The present study ret-rospectively analyzed the correlation of the TSPO polymorphic variant rs6971 with overall and progression-free survival in GBM patients using three independent cohorts. TSPO rs6971 poly-morphism was significantly associated with shorter overall survival and progression-free survival in male GBM patients but not in females in one large cohort of 441 patients. We observed similar trends in two other independent cohorts. These observations suggest that the TSPO rs6971 pol-ymorphism could be a significant predictor of poor prognosis in GBM, with a potential for use as a prognosis biomarker in GBM patients. These results reveal for the first time a biological sex-specific relation between rs6971 TSPO polymorphism and GBM.

Despite rapid progress in the treatment of many cancers, glioblastoma remains a devastating disease with dismal prognosis. The aim of this study was to identify immune-related biomarkers that more effectively predict outcome of glioblastoma. Since heat shock protein 70 (Hsp70) and IL-2 are known to increase the expression of activatory NK cell receptors, recognizing aggressive human tumor cells that present Hsp70 on their cell surface, extracellular Hsp70 levels were determined in glioma patients together with activatory NK cell receptors. All gliomas are membrane Hsp70-positive (mHsp70+) and high grade gliomas more frequently show an overexpression of Hsp70 in the nucleus and cytosol. Significantly increased extracellular Hsp70 levels are detected predominantly in glioblastomas with large necrotic areas. Overall survival (OS) is more favorable in patients with low Hsp70 serum levels indicating that a high Hsp70 expression is associated with an unfavorable prognosis. Elevated frequencies of NK cells are associated with a more favorable outcome. Of caution, a glucocorticoid therapy reduces the prevalence of NK cells. In summary, elevated frequencies of Hsp70-reactive NK cells at diagnosis and lower Hsp70 levels predict a more favorable prognosis in glioblastoma patients.

Despite the increasing number of individuals affected by Alzheimer’s disease (AD) every year, no effective therapy has been developed to treat this neurodegenerative disease yet. The current methods for AD diagnosis are effective for clinical confirmation of the disease only when symptoms become apparent, years after molecular damage started within the patients’ brains. As higher expression of a conformationally altered p53 has been correlated with AD, we developed a mass spectrometry-based method for highly sensitive, specific, and reproducible quantification of a p53 conformational variant in plasma samples of patients with known clinical outcome. In particular, we tested the prognostic performance of an AD-specific 2D3A8-immunoselected p53 peptide (AZ 284™) in different sets of individuals progressing from both cognitively unimpaired (CU) and mild cognitive impairment (MCI) patients progressing to AD dementia. Our data showed that quantitative analysis of AZ 284™ is a reliable tool for predicting AD progression up to 6 years prior to dementia onset with AUC >90%. Taken together, these results support the implementation of p53 conformational variant quantification as an affordable and powerful diagnostic tool for early, non-invasive AD diagnosis.

Purpose: Recently introduced molecules namely long non-coding RNAs (lncRNAs) are associated with various diseases, including breast cancer, and they may have the potential to act as biomarkers. Invasive ductal carcinoma (IDC) is a frequently observed type of breast cancer that diagnosis through immunohistochemical methods. However, no reliable non-invasive markers such as circulating markers have been introduced for it, so far. Materials and methods: The relative quantitation (RQ) of two lncRNAs, RP11-445H22.4 and TINCR, was measured in tumoral tissues and paired adjacent non-tumoral tissues (PANTs) as well as in plasma samples using real-time polymerase chain reaction (RT-PCR). Furthermore, promoter methylation of the two lncRNAs genes was assessed using methylation-specific PCR (MSP). In order to compare the diagnostic values, plasma levels of CA 15-3 were measured as a conventional circulating biomarker using ELISA. The receiver operating characteristic (ROC) curve was used to illustrate the sensitivity and specificity of the potential biomarkers. Results: The RP11-445H22.4 and TINCR genes were upregulated in tumor tissues compared to PANTs (RQ_{RP11-445H22.4} = 2.7, RQ_TINCR = 4.4). Furthermore, the presence of RP11-445H22.4 and TINCR in the plasma of patients was significantly more than healthy controls (RQ_{c.RP11-445H22.4} = 4.12, RQ_c.TINCR = 4.16, P<0.001). The promoters of RP11-445H22.4 and TINCR genes were hypomethylated in the tumoral tissues with a negative correlation with their gene expression. Conclusion: Based on the findings, it can be speculated that the expression levels of these two lncRNAs as well as their promoter methylation can be considered as a therapeutic target and potential biomarker for breast carcinoma.

Circulating tumor DNA (ctDNA) in fluids has gained attention because ctDNA seems to identify tumor-specific abnormalities, which could be used for diagnosis, follow-up of treatment, and prognosis: the so-called liquid biopsy. Liquid biopsy is a minimally invasive approach and presents the sum of ctDNA from primary and secondary tumor sites. It has been possible not only to quantify the amount of ctDNA but also to identify (epi)genetic changes. Specific mutations in genes have been identified in the plasma of patients with several types of cancer, which highlights ctDNA as a possible cancer biomarker. However, achieving detectable concentrations of ctDNA in body fluids is not an easy task. ctDNA fragments present a short half-life, and there are no cut-off values to discriminate high and low ctDNA concentrations. Here, we discuss the use of ctDNA as a cancer biomarker, the main methodologies, the inherent difficulties, and the clinical predictive value of ctDNA.

Sarcopenia, the degenerative and systemic loss of skeletal muscle mass, indicates patient frailty and impaired physical function. Sarcopenia can be caused by multiple factors, including advanced age, lack of exercise, poor nutritional status, inflammatory diseases, endocrine diseases, and malignancies. Recently, growing evidence has indicated the importance of sarcopenia in the management of patients with various cancers. Sarcopenia is associated with not only higher rates of treatment-related complications but also worse prognosis in cancer-bearing patients. In this article, we conducted a systematic literature review regarding the significance of sarcopenia as a prognostic biomarker of bladder cancer. We also reviewed recent studies focusing on the prognostic role of changes in skeletal muscle mass during the course of treatment in bladder cancer patients.

Despite increasing research efforts, there is a lack of consensus on defining aging or health. To understand the underlying processes, and to foster the development of targeted interventions towards increasing one’s health, there is an urgent need: (1) to find a broadly acceptable and useful definition of health, based on a list of features (which may or may not be molecular); (2) to operationalize features of health so that it can be measured; (3) to identify predictive biomarkers and (molecular) pathways of health, and (4) to suggest interventions, such as nutrition and exercise, targeted at putative causal pathways and processes. Based on a survey of the literature, we propose to define health as a state of an individual characterized by the core features of (a) physiological function, (b) cognitive function and (c) physical function, amended, specifically in case of humans, by (d) lack of disease, and by (e) reproductive function. Often used concepts such as lack of frailty, allostatic load, or self-reported health (in case of human), and indices such as the Healthy Aging Index can be viewed as projections or surrogates of our definition. We further define aging as the set of all processes in an individual that reduce its “wellbeing”, that is, its health or survival or both. We define biomarkers of health by their attribute of predicting future health better than chronological age. We define healthspan pathways as molecular features of health that relate to each other, specifically by belonging to the same molecular pathway. Our conceptual framework may integrate diverse operationalizations of health and guide precision prevention efforts that are a key to reducing the need for medical and nursing care.

The development of reliable Food Frequency Questionnaires (FFQs) requires detailed information about the level and variation of dietary food intake of the target population. However, these data are often limited. To facilitate the development of new high quality FFQs and validation of existing FFQs, we developed a comprehensive National Dietary Assessment Reference Database (NDARD) detailing information about the level and variation in dietary food intake of people 20-70 years old in the general Dutch population. This paper describes the methods and characteristics of the population included in the NDARD database. 1063 men and 985 women agreed to participate in this research. Dietary intake data were collected using different FFQs, web-based and telephone-based 24-hour recalls, as well as blood and urine-based biomarkers. The baseline FFQ was completed by 1647 participants whose mean BMI was 26±4 kg/m2; 1117 participants completed telephone-based recalls and 1781 participants completed web-based recalls. According to the baseline FFQ, the mean energy intake was 2051±605 kcal/day. The percentage of total energy intake from protein was 15±2 En%, from carbohydrates was 43±6 En%, and from fat was 36±5 En%. This database will enable researchers to validate existing FFQs and to develop new high quality dietary assessment methods.

To screen and validate immunosuppressive factors in luminal- and basal-like breast cancer cell lines and tissue samples associated with malignant phenotypes. The mRNA microarray datasets, GSE40057 and GSE1561, were downloaded and remodelled. Differentially expressed genes (DEGs) were identified. Enrichment analyses performed and the online resources, GOBO and Kaplan-Meier Plotter, were employed to screen for immunosuppressive factors associated with breast cancer malignant phenotypes. qRT-PCR and western blot were used to validate the expression of CD274 and IL8 in cell lines and immunohistochemical detected the MIF and VEGFA on tissue microarrays. The results showed that CD274 and IL8 were both upregulated in basal-like cell lines. That MIF expression was dramatically increased in patients with breast cancer metastases (p<0.05) and that VEGFA expression positively correlates with breast cancer pathologic grade (p<0.05).During the formation and development of breast cancer, immune-related genes are always activated, and immunosuppressive factors CD274, IL8, MIF and VEGFA are upregulated. Such molecules could be used as biomarkers for breast cancer prognosis. However, because individual immune-related factors can play several biological roles, the mechanistic relationship between immunosuppressive factors and breast cancer malignant phenotypes and the feasibility of their application as drug targets require further investigation.

Background/Objectives: Endometriosis represents substantial direct and indirect healthcare costs impacted by absent accurate, non-invasive uniformly diagnostic tools. We endeavored to demonstrate gastrointestinal myoelectrical activity (GIMA) biomarkers unique to endometriosis allow noninvasive, uniformly accurate diagnosis or exclusion of endometriosis. Methods: Prospective open-label comparative study of 154 patients, age &gt;18, with or without diagnosed endometriosis. Population included 62 non-endometriosis controls (Cohort 1), 43 subjects with surgically histologically-confirmed endometriosis (Cohort 2), and 49 subjects with abdominal pain and negative imaging (Cohort 3). Electroviscerography (EVG) recorded GIMA biomarkers from three abdominal electrodes before and 30-minutes post water-load protocol. Cohort 2 had postoperative EVG and Cohort 3 had preoperative EVG. Calculated specificity, sensitivity, NPV, PPV and predictive probability or C-Statistic used univariate, multivariate, linear and logistical regression analyses of the area under the curve (AUC) at all frequency and time points, including age and pain covariants. Results: Non-endometriosis cohort differed significantly from endometriosis cohorts (p&lt;0.001) for median (IQR), and AUC percent frequency distribution of power at baseline, 10-minute, 20-minute, and 30-minute post water-load at all frequency ranges 15-20cpm, 30-40cpm and 40-50cpm. Endometriosis cohorts were statistically similar (p&gt;0.05). GIMA biomarker threshold scoring demonstrated 95%/91% sensitivity and PPV, 96%/95% specificity and NPV and C-statistic of &gt;99%/98% respectively for age subsets. GIMA biomarkers in Cohort 3 predicted 47/49 subjects positive and 2/49 negative for endometriosis, confirmed surgically. Hormonal therapy, surgical stage, nor pain score affected diagnostic accuracy. Conclusions: Non-invasive electroviscerography with GIMA biomarker detection distinguished participants with and without endometriosis based upon endometriosis specific GIMA biomarkers threshold scoring.

Background: Parenteral nutrition (PN) is a nutrient solution administered intravenously (IV) to premature babies. PN causes elevations of some amino acids in blood samples that are also biomarkers used in newborn screening (NBS). Therefore, PN status must be annotated on dried blood spot (DBS) cards by clinicians to reduce NBS laboratory burdens associated with potential false results, however, NBS laboratories continue to receive DBS with misannotated PN status. N-acetyltyrosine (NAT), a water-soluble tyrosine analog used to increase tyrosine bioavailability in PN solutions, can be used as a blood-based biomarker of PN administration in NBS assays. Methods: Residual DBS specimens and manufactured DBS were used in analyses. The assay was developed and validated using flow injection analysis tandem mass spectrometry (FIA-MS/MS) for detection of NAT. Results: NAT was only present in neonate DBS with annotated PN administration, and was multiplexed into first-tier newborn screening assays. NAT was highly correlated with amino acids present in PN solutions such as arginine, leucine, methionine, phenylalanine, and valine. In our sample cohort, we determined an NAT cutoff could aid identification of misannotated neonates administered PN. We also report the Amadori rearrangement product valine-hexose (Val-Hex) was quantifiable in neonates administered PN, which we suspect forms in the PN solution and/or IV lines. Conclusions: Here we present the first known use of NAT as a biomarker for PN administration, which is currently being piloted by two U.S. NBS laboratories. NAT and Val-Hex can aid identification of misannotated DBS from neonates administered PN, thus, decreasing false positive rates.

There is currently no clinically valid biomarker for predicting the growth and prognosis of abdominal aortic aneurysms (AAA). The most promising candidates with highest diagnostic values are plasma D-dimers and markers of activated neutrophils, i.e. myeloperoxidase (MPO) or cell-free DNA. So far, case-control studies on these markers were almost exclusively performed by using healthy individuals for control. To validate the value of these markers in the clinical setting of a vascular surgery department, we analysed the diagnostic and prognostic potential of plasma D-dimers and MPO in 177 AAA patients versus 138 non-AAA patients with different vascular diseases. Significantly elevated levels of D-dimers were recorded for AAA patients compared with non-AAA patients, although the difference between the two groups was significantly smaller than in other studies comparing AAA patients with healthy controls. Surprisingly, MPO levels were significantly higher in non-AAA patients than in AAA patients. After adjusting for the confounding factors sex, peripheral artery disease (PAD) and internal carotid stenosis in multivariate regression models, neither D-dimers nor MPO remained independent correlates of AAA. In contrast, D-dimer plasma levels correlated well with the maximal aortic diameter. Combined analysis of D-dimers and circulating cell-free DNA levels derived from a previous study, failed to improve the predictive values for the maximal aortic diameter. In conclusion, our data show that D-dimers and MPO are no suitable biomarkers for monitoring AAA in a real-world setting of mixed vascular surgery patients.

Abstract: Background The incidence of Heart failure is increasing across the world. Over one million people in the UK have heart failure and around 200,000 new diagnoses are made every year (Conrad et al, 2018).Estimates suggest that, further 385,000 people with heart failure who are currently undetected, undiagnosed and, consequently, are missing out on life-preserving treatments. Most of the heart failure cases are of elderly population. The prevalence of heart failure slowly increases with age until about 65 years of age, and then more rapidly. In United Kingdom, the prevalence of heart failure in elderly population is estimated to be about [NICE, 2018a] 1 in 35 people who are aged between 65 – 74 years of age and 1 in 15 people who are aged 75 – 84 years of age. The average age at first diagnosis is 76 years of age [NICE, 2018a]. As per the statistics, heart failure accounts for 2% of bed occupancy in entire NHS as well as accounts for 5% of all NHS emergency admissions. Hospitalization for decompensated heart failure (DHF) carries a poor prognosis, with frequent readmissions. As per the updated NICE guidelines, B-type natriuretic peptide (BNP) is used in the diagnostic criteria and management of heart failure. BNP is secreted by overloaded left ventricle as a response to fluid overload. This study is to evaluate the prognostic value of BNP in elderly population with decompensated heart failure. Methods We conducted a retrospective observational cohort study of 88 elderly patients who were admitted with decompensated heart failure between September 2023 to April 2024 in Lagan valley hospital – Lisburn and Ulster Hospital – Dundonald, Northern Ireland. Suspected heart failure admissions were randomly selected as snapshots of each month. Among these admissions, 88 Heart failure cases were identified based on echocardiogram findings and NT- pro BNP levels performed on initial admission. The same cohort was followed up for 12 weeks period for specific end points. The end points that were considered were readmissions with heart failure or deaths. Furthermore, Heart failure follow ups were also assessed during post discharge as well. A fraction of patients had repeat BNP checked during the follow up and their clinical features were correlated. All cases were categorized in to two main cohorts as HFrEF cohort and HFpEF cohort. Patients with left ventricular ejection fraction ≥50% were categorized as HFpEF, while those with <40% as were categorized as HFrEF. Each cohort was subdivided to further 3 sub categories depending on the BNP values. Prognostic values and all-cause mortality after discharge were assessed separately in patients with HFpEF and HFrEF by multivariable adjusted Cox regression analysis. Comorbidities were compared between heart failure groups. ROC curve was carried out to establish the cutoff level of BNP and the mortality analysis was done utilizing Kaplan Meier curves. Results In this cohort study, two major heart failure cohorts were analyzed for specific end points under six main sub-cohorts. The data analysis shows that mortality rate is 29.1% when NT Pro BNP values is more than 2000. The heart failure readmission rate is 45.6% when NT Pro BNP value is more than 2000. 66.6% re-admission rate was demonstrated with rising NT-Pro BNP values during heart failure follow up. This was much lower with patients who had declining NT- Pro -BNP values during heart failure follow u which was 33.3% Satisfactory statistical power of the study, which demonstrated that NT- Pro BNP can be used as prognostic marker for mortality in elderly patients with heart failure irrespective of their ejection fraction. Conclusions NT Pro BNP can be used as a prognostic biomarker for elderly patients with heart failure. Satisfactory statistical evidence was shown on this study to prove that higher BNP values on admission predicts higher mortality rate. Significant evidence was demonstrated in this study to show that there are higher re-admission rates with higher NT pro BNP levels specially in elderly population. Furthermore, the study demonstrated that, there is higher mortality and morbidity rate with rising NT Pro BNP levels during heart failure follow up. In conclusion, all these three parameters shows that NT Pro- BNP levels can be used as a prognostic bio marker for elderly patients with heart failure, irrespective of their ejection fraction status. Furthermore, we would like to indicate that monitoring NT Pro BNP levels in all heart failure cases could be beneficial to prevent mortality and morbidity. Furthermore, it would be an aid to optimize heart failure medications prior to have an episode of decompensation of heart failure as well.

Transactive response DNA-binding protein of 43 kDa (TDP-43) is a major component of pathological inclusions in various neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The detection of TDP-43 in biofluids is crucial for the development of diagnostic and prognostic indicators of disease and therapeutic development for TDP-43 related proteinopathies. Despite its potential as a biomarker for numerous neurological disorders, the lack of a sensitive and reproducible TDP-43 assay hinders progress in TDP-43-based therapy development, underscoring the need for an effective and standardized method for accurate quantification. In this study, we developed and validated a sensitive immunoassay for the detection of TDP-43 in human biofluids using the Meso Scale Discovery (MSD) platform. We used this immunoassay to quantify TDP-43 levels in the plasma and serum of healthy controls and ALS patients. Our results indicate a reduction of total TDP-43 in the blood of ALS patients compared to healthy controls.

Background/Objectives: The global burden of colorectal cancer (CRC) is projected to increase by 2040, highlighting the need for prevention strategies, early detection and adequate follow. The aim of this study was to provide an overview of the progress in personalized medicine of CRC in Serbia, with results and insights from the Institute for Oncology and Radiology of Serbia (IORS), and to propose guidance for tackling observed challenges in the future. Methods: Epidemiological data was derived from official global and national cancer registries and IORS electronic medical records. Germline genetic testing for Lynch syndrome was performed by Next Generation Sequencing. RAS and BRAF mutation analyses were performed using qPCR diagnostic kits. Results: Epidemiology and risk factors, prevention and early detection programs, as well as treatment options and scientific advances have been described in detail. Out of 103 patients who underwent germline testing for Lynch syndrome, 19 (18.4%) had a pathogenic or likely pathogenic mutation in one of the MMR genes, and 8 (7.8%) in other CRC-associated genes (APC, CHEK2, MUTYH). Of 6369 tested patients, 50.43% had a mutation in KRAS or NRAS genes, while 9.54% had the V600 mutation in the BRAF gene. Conclusions: Although significant improvements in CRC management have occurred globally in recent years, the high incidence of young-onset CRC and the growing elderly population due to a rise in life expectancy require a strategic approach leading to population-based systemic solutions, especially important for countries with limited health care resources as Serbia.

Bipolar disorder (BD) is a complex mental health condition characterized by alternating periods of mania and depression. This review provides a comprehensive overview of BD, focusing on its genetics, causal hypotheses, clinical signs and evolution, potential biomarkers with an emphasis on electroencephalography (EEG), and treatment options. Genetic studies have identified several susceptibility genes and polygenic risk scores, highlighting the heritable nature of BD. Various causal hypotheses, including monoamine dysregulation, kindling, circadian rhythm disruptions, and neuroinflammation, have been proposed to explain its pathophysiology. The clinical course of BD is characterized by recurrent episodes of mania/hypomania and depression, with significant heterogeneity among individuals. EEG and other biomarkers hold promise for improving diagnosis, predicting treatment response, and elucidating the neurobiological underpinnings of BD. Current treatment options include pharmacotherapy, psychotherapy, and neuromodulation techniques, which can be tailored to individual needs based on clinical presentation and response to treatment. Future research should focus on identifying more specific biomarkers, developing novel treatments, and optimizing existing therapies to improve outcomes for individuals with BD.

Attention Deficit Hyperactivity Disorder (ADHD) diagnosis poses significant challenges due to its heterogeneous nature and reliance on subjective assessments. This study leverages deep learning to develop a robust diagnostic model by integrating a comprehensive set of EEG biomarkers. We incorporate parameters such as theta/beta ratio, coherency measures, delta power, event-related potentials (ERPs), power spectral density (PSD), microstates, entropy measures, fractal dimension, and source localization. Our convolutional neural network (CNN) model, designed to process these diverse features, demonstrates high accuracy and stability in distinguishing ADHD patients from controls, from all ages. The model's architecture includes convolutional layers for spatial feature extraction, followed by dense layers that integrate additional EEG parameters. The results indicate that deep learning, coupled with a rich feature set, can significantly enhance the predictive accuracy of ADHD diagnosis, offering a promising tool for clinical application.

ABSTRACT：Background: Diagnosing rhabdomyolysis has usually defined at least five or ten times the upper limit creatine kinase level; but it is conservative for Exertional rhabdomyolysis. The aim was to analysis the biomarkers during a military operation in an extreme environment with high physical demand. Material and Methods: Seventeen male military personnel (age: 27.83 ± 2.96 years; weight: 76.31 ± 7.67 kg; and height 174.92 ± 5.91 cm) participated for this investigation. The creatine kinase (CK); blood urea nitrogen (BUN); creatinine (Cr); sodium (Na); potassium (K); aspartate amino transferase (AST) and alanine amino transferase (ALT) were analyzed. Urine specific gravity (USG) the hydration status was monitored. The Generalized Linear Models for repeated measures and the Friedman’s two-way test were used to comparative moments. Results: The BUN; Cr; Na; and K mean values showed a nonsignificant. The statistical significance of the test was found in CK and AST. There was considerable variability of CK between subjects during the operation. The moderate correlation between CK and Cr was found during study. Conclusion: Elevated CK levels after the operation were characterized as physiological pattern. These results reinforce that CK values are not predictors of renal function in activities with intense and continuous physical demand

Lately, radiomic studies featuring the development of a signature to use in prediction models in diagnosis or prognosis outcomes are being published increasingly. While the results are shown to be promising, these studies still have many pitfalls and limitations. One of the main issues of this methodology is that radiomic features depend on how the images are preprocessed before their computation. Since, in widely known and used software for radiomic features calculation, it is possible to set these preprocessing parameters before the calculation of the radiomic feature, there are ongoing studies assessing the stability and repeatability of radiomic features to find the most suitable preprocessing parameters for every used imaging modality. This review examines the impact of preprocessing parameters on the reproducibility and reliability of radiomic features extracted from multimodality imaging (CT, MRI, CBCT, PET/CT). Standardized preprocessing is crucial for consistent radiomic feature extraction. Key preprocessing steps include voxel resampling, normalization, and discretization, which influence feature robustness and reproducibility. From our work, we highlighted the need to harmonize the use of preprocessing parameters and their values, especially in light of future studies of prospective studies, which are still lacking in the current literature.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole. Letrozole inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. Letrozole resistance is increasingly being observed, which poses a unique problem for patients. We reanalyzed transcriptomic data comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two genes that significantly differed between these patients; with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 as the top transcriptional biomarkers for ER+ treatment resistance. Many of the other significant gene products play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified do not have a characterized role in ER+ breast cancer. Our analysis identified a set of genes that warrant further research to elucidate the molecular mechanism of Letrozole resistance in this patient population, as well as novel high-performing biomarkers. We anticipate that these findings could contribute to improved therapeutic outcomes in human patients.

Background: Galectins are innate immune system regulators, associated with disease progression in cancer. This paper aims to investigate the correlation between mutated cancer-critical genes and galectin levels in breast cancer patients to determine whether galectins and genetic profiles can be used as biomarkers for disease and potential therapy targets. Materials and Methodology: Prisma Health Cancer Institute’s Biorepository provided seventy-one breast cancer patient samples, including all four stages as well as major molecular subtypes and histologies of breast cancer. Hotspot mutation statuses of cancer-critical genes were determined using multiplex PCR in tumor samples from the same patients by Precision Genetics and the University of South Carolina Functional Genomics Core Facility. The galectin levels of patients’ sera were analyzed using enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of galectins-1, -3, and -9. Analysis was performed using JMP software to compare mean and median serum galectin levels between samples with and without specific cancer-critical genes including pooled t-test, Wilcoxon test, ANOVA, Tukey’s range test, and Steel Dwass Method (α=0.05). Results: Our analysis indicates that KIT mutations correlate with elevated serum levels of galectin-1 and -9 in patients with breast cancer. In patients with Luminal A subtype, FLT3 mutation correlates with lower serum galectin-1 and -9 levels and TP53 mutations correlate with higher serum galectin-3 levels. Patients with invasive ductal carcinoma had significantly higher serum galectin-3 levels than patients with ductal carcinoma in situ. Patients with both TP53 and PIK3CA mutations exhibit elevated serum galectin-3 levels, while patients with one or neither mutation show no significant difference in serum galectin-3 levels. In addition, metastatic breast cancer samples were more likely to have KIT or PIK3CA mutation compared to primary breast cancer samples. Conclusion: The relationship between genetic mutations and galectin levels has the potential to identify appropriate candidates for combined therapy, targeting genetic mutations and galectins. Further understanding of the effect of genetic mutations and galectin levels on cancer progression and metastasis could aid in the search for biomarkers for breast cancer diagnosis, disease progression, and prognosis.

Background: Systemic autoimmune rheumatic diseases (SARDs), including Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA), are characterized by chronic inflammation and autoimmunity. Identifying reliable biomarkers is crucial for enhancing diagnosis, monitoring disease progression, and evaluating therapeutic responses. This study explores the potential of serum Syndecan-1 (SDC-1) as a biomarker for these conditions and concurrently examines its relationship with free light chain (FLC) expression levels in the same patients. Methods: A retrospective analysis was performed on serum samples from 120 patients (60 RA, 60 SLE), alongside 50 healthy donors (HD). Serum levels of κ and λ FLCs were determined by turbidimetric assay, while SDC-1 levels were measured using ELISA. Statistical analyses, including the Kruskal-Wallis test, Wilcoxon-Mann-Whitney U test, multivariable linear regression and Spearman’s correlation, were employed to compare biomarker levels across groups and to explore correlations among them. Results: Significantly increased levels of SDC-1, κ-FLC, and λ-FLC were observed in patients diagnosed with RA and SLE compared to HD (p < 0.001), while no significant differences in the κ/λ ratio were noted among the groups (p = 0.4). A statistically significant difference in subject age was also identified. However, multivariate regression analysis indicated that RA and SLE statuses are significantly associated with the levels of these markers, with minimal confounding by age. A significant correlation was observed separately in all groups between the FLC markers. Conversely, no correlation was detected between SDC-1 and FLCs, nor between these markers and age. Conclusion: Elevated serum levels of FLCs and SDC-1 in RA and SLE patients compared to healthy controls underscore their potential as biomarkers for SARDs. The findings also suggest sustained plasma cells activation, supporting the SDC-1 role in the pathogenesis of these conditions.

Background: Chronic Myeloid Leukemia (CML) is initiated in bone marrow due to chromosomal translocation t(22;9) leading to fusion oncogene BCR-ABL. Targeting BCR-ABL by tyrosine kinase inhibitors (TKI) have changed fatal CML into an almost curable disease. Despite that, TKIs lose their effectiveness due to disease progression. Unfortunately, mechanism of CML progression is poorly understood and common biomarkers for CML progression are unavailable. This study was conducted to find out novel biomarkers of CML progression by employing whole exome sequencing (WES).Materials and Methods: WES of accelerated phase (AP-) and blast crisis (BC-) CML patients was carried out, with chronic phase CML (CP-CML) patients as control. After DNA library preparation and exome enrichment, clustering and sequencing was carried out using Illumina platforms. Statistical analysis was carried out using [SAS/STAT] software version 9.4 and R package employed to find mutations shared exclusively by all AP-/BC-CML. Confirmation of mutations was carried out using Sanger sequencing and protein structure modelling using I-Tasser followed by mutant generation and visualization using PyMOL. Results: Three novel genes (ANKRD36, ANKRD36B and PRSS3) were mutated exclusively in all AP-/BC-CML patients. Only ANKRD36 gene mutations (c.1183_1184 delGC and c.1187_1185 dupTT) were confirmed by Sanger sequencing. Protein modelling studies showed that mutations induce structural changes in ANKRD36 protein. Conclusions: Our studies show that ANKRD36 is a potential common biomarker and drug target of early CML progression. ANKRD36 is yet uncharacterized in human. It has the highest expression in bone marrow, specifically myeloid cells. We recommend carrying out further studies to explore the role of ANKRD36 in biology and progression of CML.

Coproporphyrins I and III (CP-I and CP-III) are established as substrates of hepatic sinusoidal organic anion transporting polypeptides (Oatps), multidrug resistance-associated protein 3 (Mrp3), and canalicular transporter Mrp2. We aimed to evaluate the potential of plasma CP-I and CP-III concentrations to indicate functional changes in hepatic transporters in nonalcoholic stea-tohepatitis (NASH) rodent models using modeling and simulation approach. Mechanistic copro-porphyrins (CP-I and CP-III) models in rats and mice were constructed based on metabolism, transport, and elimination pathways in rodents. To parameterize the rat mechanistic model, we measured CP concentrations in plasma, liver, bile, and urine in healthy control Sprague Dawley rats. The mouse mechanistic model was parameterized using published data. The rat and mouse CP models described the steady-state levels of CP-I and CP-III in plasma, liver, and bile. The model recapitulated the observed high plasma CP-III / CP-1 ratio (9- and 3-fold in rats and mice, respec-tively) and elimination pathways of CP-I (>90% via biliary secretion) and CP-III (equal via bile and urine). Rat CP model was further validated with the published rat fistula model. The simulated increased plasma CP-I concentrations (4-fold), resulted from decreased Oatp activity (0.6-fold) and increased Mrp3 activity (3-fold) were comparable to those observed in bile-duct ligated NASH model. Sensitivity analysis revealed that 90% inhibition of Oatp and Mrp2 leads to a 4-fold and 2.5-fold increase in plasma CP-I levels, respectively. Additionally, we demonstrated the utility of the mechanistic CP models in testing hypothesis and understanding the mechanisms of the ob-served plasma CPs disposition in the Oatp knockout (KO) mice, bile-duct ligation NASH mice, and Mrp2 deficient TR- rats. Collectively, using a mechanistic model, we conclude that CP-I is a robust and predictable marker for assessing change in the activity of Oatps and Mrps in animal models. Our analysis suggests that efflux transporters (Mrp2 and Mrp3) can play an important role in the disposition of CP-I along with Oatp transporters in rodents.

Breast cancer (BC) is the second leading cause of death in the United States in women. 1 in 8 women in their lifetime has a risk of developing breast cancer. With advances in omics technology, more data is available for diagnosis, treatment, and prognosis. The help of Machine Learning algorithms, a subdomain of Artificial Intelligence, would allow for a better clinical support tool. Machine Learning could be the key to answering a complex problem in BC. The methodology of this research question involves collecting and finding data such as RNA-Seq datasets, selecting and training appropriate machine learning algorithms, and evaluating the performance of the algorithms in predicting BC prognosis. Also, the study explores and tries to identify the most relevant genes and pathways through feature selection extraction and dimensionality reduction techniques. After applying feature extraction, the top 10 genes were extracted using the Univariate Feature Selection (UFS) method, precisely the SelectKBest technique. After employing different machine learning algorithms, such as Networks, Random Forest, Linear SVM, Logistic Regression, and Quadratic Discriminant Analysis (QDA), we found QDA was the best model in classifying the RNA-seq dataset with a 96% accuracy rate and 94% ROC AUC. This study suggests that AK2 and CD68 have a positive correlation with each other, and it could potentially be a biomarker and therapeutic target for BC.

Acute kidney injury (AKI) is a clinical syndrome where a rapid decrease in kidney function and/or urine output is observed, which may result in the imbalance of water, electrolyte and acid base, and is associated with poor prognosis and prolonged hospitalization. Therefore, early diagnosis and treatment to avoid the severe AKI stage is important. While several biomarkers, such as urinary L-FABP and NGAL, can be clinically useful, there is still no gold standard for early detection of AKI and there are limited therapeutic options against AKI. miRNAs are non-coding and single-stranded RNAs that silence their target genes in the post-transcriptional process and are involved in a wide range of biological processes. Recent accumulated evidence has revealed that miRNAs may be potential biomarkers and therapeutic targets for AKI. In this review article, we summarize the current knowledge about miRNAs as promising biomarkers and potential therapeutic targets for AKI, as well as the challenges in their clinical use.

Preferentially expressed Antigen in Melanoma (PRAME) is a cancer testis antigen (CTA) that is selectively expressed in certain somatic tissues, predominantly in the testis and is overexpressed in various cancers. PRAME family proteins are leucine rich repeat proteins, that are localized in the nucleus and cytoplasm, with multifaceted roles in immunity, during gametogenesis and in the overall reproduction process. It is a widely studied CTA and has been associated with the prognosis and therapeutic outcome in patients with epithelial and non-epithelial tumors. PRAME has also been studied extensively as a therapeutic target. Moreover, it has been found to play a role in most of the well-known cancer hallmarks. Interestingly, the role of PRAME in tumorigenesis is paradoxical. Over the last decade, PRAME has garnered substantial interest as a target for immunotherapy. There are multiple clinical trials and pre-clinical studies targeting PRAME alone or in combination with other tumor antigens. This review article is an attempt to update our knowledge and understanding of the context-dependent oncogenic functions of PRAME in various carcinomas, and the current immunotherapeutic strategies, challenges, and perspectives on developing newer strategies to target PRAME for a better outcome.

Immunological aging type definition requires establishing reference intervals from the distribution of immunosenescence biomarkers conditional on age. For 1,605 individuals (18–97 years), we determined the comprehensive IMMmune Age indeX IMMAX from flow cytometry-based blood cell sub-populations, and identified age-specific centiles by fitting generalized additive models for location, scale and shape. The centiles were uncorrelated with age, and facilitated the categorization of individuals as immunologically slow or fast aging types. Using its 50th percentile as reference, we rescaled IMMAX to equivalent years-of-life (EYOL), and computed the immunological age gap as difference between EYOL and chronological age. Applied to preliminary baseline and follow-up measurements from 53 participants of the Dortmund Vital Study (Clinical-Trials.gov Identifier: NCT05155397), the averaged changes in IMMAX and EYOL conformed to the 5-year follow-up period, whereas no significant changes occurred concerning IMMAX centiles and age gap. This suggested that the participants immunologically adapted to aging, and kept their relative positions within the cohort. Sex was non-significant. Methodical comparisons indicated that future confirmatory analyses with the completed follow-up examinations could rely on percentile curves estimated by simple linear quantile regression, while the selection of the immunosenescence biomarker will greatly influence the outcome, with IMMAX representing the preferable choice.

Oncological changes in the prostate are a common cause of death among elderly men. Malignant cells are difficult to identify at early stages, which are asymptomatic. The patient often seeks medical assistance when the disease has already progressed, and the treatment is less effective. Early diagnosis of prostate cancer (PC) is thus one of the priority tasks of modern urology and healthcare in general. The aim of this study is the detection of microRNAs (miRNAs), which are known to be associated with PC. The detection of the target miRNAs in human plasma samples has been performed with a nanoribbon biosensor system, which was based on "silicon-on-insulator" structures (SOI-NR biosensor). In order to provide biospecific detection of the target miRNAs, the surface of individual nanoribbons has been modified with DNA oligonucleotide probes (oDNA probes), whose nucleotide sequences were complementary to those of the target miRNAs. The high detection sensitivity has been demonstrated with the use of model oDNAs, which are complementary to nanoribbon-immobilized oDNA probes, in buffer solutions. The sensitivity threshold was 1.1 × 10^-17 M. The successful detection of target miRNAs, isolated from real plasma samples of PC patients, has also been demonstrated. We believe that the development of highly sensitive nanotechnology-based biosensors for PC markers is a step towards personalized medicine.

Buffalo are silent breeders, therefore detecting estrus is a serious challenge. There is a rising need for sensitive and precise biomarkers in this scenario. Recent research on miRNA has demon-strated the importance of these molecules as biomarkers. Though there have been miRNA studies in saliva during the estrous cycle, there have been few miRNA research in blood samples. The current study was designed to look at blood miRNAs during the oestrous cycle in heifers (n=5) to address the issue of silent estrus. On the day of estrus and diestrus, blood samples from 60 heifers were obtained and pooled into (n=5) separate samples. Ultrasonography and progesterone assay was performed to confirm estrus. Then, employing particular miRNA adapters, small RNA se-quencing of miRNA was performed using the Illumina Miseq 2500. The UEA sRNA bioinfor-matics workbench identified 94 substantially differently expressed miRNAs (p>0.05) from these data. In estrus, 63 miRNA were upregulated and 31 miRNA were downregulated. When fold change was increased to (log2foldchange >1; q value less than 0.05), 25 miRNAs were elevated during estrus. miR-497, miR-582, miR-10174, miR-23, miR-223, miR-1296 were upregulated, whereas miR-10167, 671, 1246,122 were downregulated. miR-497 is unusually elevated (log2 foldchange>5) when compared to another miRNA (log2 foldchange >5) miRNet 2.0, Cytoscape, and MIENTURNET network software found that miR-497 has more degree centrality, above 60; it is associated with more than 60 nodes, followed by miR-93

The fight against suicide is highly challenging as it may be one of the most complex and at the same time most threatening among all psychiatric phenomena. In spite of its huge impact, and despite advances in neurobiology research, understanding and predicting suicide remains a major challenge for both researchers and clinicians. To be able to identify those patients who are likely to engage in suicidal behaviors and identify suicide risk in a reliable and timely manner, we need more specific, novel biological and genetic markers/indicators to develop better screening and diagnostic methods, and in the next step to utilize these molecules as intervention targets. One such potential novel approach is offered by our increasing understanding of the involvement of neuroinflammation based on multiple observations of increased proinflammatory states underlying various psychiatric disorders including suicidal behavior. The present paper overviews our existing understanding of the association between suicide and inflammation including peripheral and central biomarkers, genetic and genomic markers, and our current knowledge of intervention in suicide risk using treatments influencing inflammation, also overviewing the next steps to be taken and obstacles to be overcome before we can utilize cytokines in the treatment of suicidal behavior.

MicroRNAs (miRNAs) are single-stranded, noncoding RNA molecules that regulate gene expression post-transcriptionally by binding to messenger RNAs. miRNAs are important regulators of gene expression, and their dysregulation is implicated in many human and dog diseases. Most cancers tested, to date, have been shown to express altered miRNA levels, which indicates their potential importance in the oncogenic process. Based on this evidence, numerous miRNAs have been suggested as potential cancer biomarkers for both diagnosis and prognosis. miRNA-based therapies have also been tested in different cancers and have provided measurable clinical benefits to patients. In addition, understanding miRNA biogenesis and regulatory mechanisms in cancer can provide important knowledge about resistance to chemotherapies, leading to more personalized cancer treatment. In this review, we have comprehensively summarized the importance of miRNA in human and dog cancer research. We have discussed the current state of development and potential for miRNA as both a diagnostic marker and a therapeutic target.

Immune Checkpoint Inhibitors are monoclonal antibodies that are used to treat over one in three cancer patients. While they have changed the natural history of disease, prolonging life and preserving quality of life, they are highly active in less than 40% of patients, even in the most responsive malignancies such as melanoma, and cause significant autoimmune side effects. Licenced biomarkers include tumour Programmed Death Ligand 1 expression by immunohistochemistry, microsatellite instability, and Tumour Mutational Burden, none of which are particularly sensitive or specific. Emerging tumour and immune tissue biomarkers such as novel immunohistochemistry scores, tumour, stromal and immune cell gene expression profiling, and liquid biomarkers such as systemic inflammatory markers, kynurenine/tryptophan ratio, circulating immune cells, cytokines and DNA are discussed in this review. We also examine the influence of the faecal microbiome on treatment outcome and its use as a biomarker of response and toxicity.

Background: Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 have cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. Methods: In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during pregnancy was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n=749) and 15 (n=793) was measured using the Illumina HumanMethylation 450k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by meta-analysis effect estimates from Gruzieva et al. 2019 and standardizing the sums. Using mixed effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income to needs ratio, nonmartial birth status, and saliva cell type proportions. Results: Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with median income to needs ratio of 1.4. In the third trimester, mean PM2.5 exposure levels were 27.9 ug/m3/day (standard deviation: 7.0, 23.7% of observations exceeded safety standards) and PM10 were 15.0 ug/m3/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 g/m3/day) was associated with -0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: -0.0732, 0.0158, p=0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 g/m3/day) was associated with -0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.3038, 0.0095, p=0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with -0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.043, -0.005, p=0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. Conclusion: In utero PM10 associated DNA methylation differences persist until age 15 and can be detected in saliva. Benchmarking the persistence and cell type generalizability is critical for epigenetic exposure biomarker assessment.

Background: Diabetes is among the most prevalent diseases worldwide, of all the affected individuals a significant proportion of the population remains undiagnosed because of a lack of specific symptoms early in this disorder and inadequate diagnostics. Diabetes and its associated sequela, i.e., comorbidity are associated with microvascular and macrovascular complications. As diabetes is characterized by an altered metabolism of key metabolites and regulatory pathways. Metabolic phenotyping can provide us with a better understanding of the unique set of regulatory perturbations that predispose to diabetes and its associated comorbidities. Methodology: The present study utilizes the analytical platform NMR spectroscopy coupled with Random Forest statistical analysis to identify the discriminatory metabolites of diabetes (DB) and diabetes-related comorbidity (DC) along with the healthy control (HC) subjects. A combined and pairwise analysis was performed, between the serum samples of HC (n=50), and DB (n=38), and DC (n=35) individuals to identify the discriminatory metabolites responsible for class separation. The perturbed metabolites were further rigorously validated using t-test, AUROC analysis to examine the statistical significance of the identified metabolites. Results: The DB and DC patients were well discriminated from HC. However, 15 metabolites were found to be significantly perturbed in DC patients compared to DB, the identified panel of metabolites are TCA cycle (succinate, citrate), methylamine metabolism (trimethylamine, methylamine, betaine), -intermediates; energy metabolites (glucose, lactate, pyruvate); and amino acids (valine, arginine, glutamate, methionine, proline and threonine). The metabolites were further used to identify the perturbed metabolic pathway and correlation of metabolites in DC patients. Conclusion: The 1H NMR metabolomics may prove a promising technique to differentiate and predict diabetes and its comorbidities on their onset or progression by determining the altered levels of the metabolites in serum.

Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibody, CYFRA 21-1, and anti-CYFRA 21-1 autoantibody in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1,132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. The test demonstrated a sensitivity of 78.4% (95% CI: 75.7-81.1) and specificity of 93.1% (95% CI: 90.0-96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. The lung cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.

The stress-inducible heat shock protein 70 (Hsp70), which functions as a molecular chaperone and is frequently overexpressed in different cancer cell types, is presented on the cell surface of tumor cells and is actively released into the circulation in free and extracellular lipid vesicle-associated forms. Since the exact pathomechanism of endometriosis has not yet been elucidated but has been associated with the development of endometrial and ovarian cancer, we asked whether extracellular Hsp70 and circulating endometriotic cells (CECs) reflects the presence and development of endometriosis. Therefore, circulating levels of free and lipid microvesicle-associated Hsp70 were measured using the Hsp70-exo ELISA, and the presence of circulating CECs in the peripheral blood of patients with endometriosis was determined using membrane Hsp70 (mHsp70) and EpCAM monoclonal antibody (mAb)-based bead isolation approaches. Isolated CECs were further characterized by immunofluorescence using reagents directed against cytokeratin (epithelial), CD45 (leukocyte), CD105/CD44 (mesenchymal-stemness) and by comparative RNA analysis. Similar to the situation in patients with cancer, levels of circulating Hsp70 were elevated in the blood of patients with histologically proven endometriosis compared to a healthy control cohort, with the highest Hsp70 level in a patient with lymph node endometriosis. Moreover, CECs could be isolated using the cmHsp70.1 mAb- and to a lesser extent EpCAM mAb-based bead approaches in all patients with endometriosis. The longevity in cell culture and the expression of cytokeratin, CD105 and CD44, together with differentially expressed genes related to EMT reveals similarities of mHsp70 expressing CECs with circulating tumor cells (CTCs) and suggest a mesenchymal-stemness origin. These findings may support the involvement of mHsp70 positive, stem cell-like cells in the development of endometriotic lesions. In summary, elevated levels of Hsp70 in the blood and CECs could serve as liquid biopsy markers for endometriosis and help to elucidate the underlying pathomechanism of the disease.

The blood that remains in the placenta and umbilical cord after the birth of the infant is referred to as umbilical cord blood (UCB), which has the advantages of convenient source and less ethical controversy. MicroRNA (miRNA) is a class of non-coding RNAs that can regulate gene expression after translation and transcription. Alterations in miRNA expression involve changes in a range of gene expression pathways. An increasing body of research indicates that miRNAs are implicated in many human disorders and are involved in almost all biological medium processes. Due to their high stability in UCB, circulating miRNAs are considered promising biomarkers for diagnosis and disease prognosis. Herein, we conduct a comprehensive review to summarize the roles of diverse UCB miRNAs from different perspectives, including UCB miRNA as biomarker for developmental projections and disease diagnosis, the relationship between maternal gestational status and neonatal UCB miRNA expression, the therapeutic function of exosomal UCB miRNA, miRNA expression profiles in UCB cell lineages. Taken together, miRNAs in UCB are very promising biomarkers for indicating physiological states, disease states, drug responses, development states, or health conditions, which can help in diagnosing, classifying, and predicting diseases, prognosis, or providing personalized treatment plans for patients.

This study explores the efficacy of using EEG-based parameters to diagnose bipolar disorder. A synthetic dataset was generated, including both correctly diagnosed and misdiagnosed cases, simulating realistic clinical conditions. EEG features such as theta-alpha mean, beta band mean, and coherence measures were used to train a multi-layer perceptron (MLP) model. The model achieved a validation accuracy of 92%, demonstrating strong potential for EEG-based diagnostics. However, challenges such as standardization of electrode configurations and addressing equipment differences are crucial for broader applicability and validity of the findings in diverse clinical settings.

SerpinB3, a member of the serine-protease inhibitor family, has emerged as a crucial player in various physiological and pathological processes. Initially identified as an oncogenic factor in squamous cell carcinomas, SerpinB3's intricate involvement extends from fibrosis progression and cancer to cell protection in acute oxidative stress conditions. This review explores the multi-faceted roles of SerpinB3, focusing on its implications in fibrosis, metabolic syndrome, carcino-genesis, and immune system impairment. Furthermore, its involvement in tissue protection from oxidative stress and wound healing underscores its potential as diagnostic and therapeutic tool. Recent studies have described the therapeutic potential of targeting SerpinB3 through its upstream regulators, offering novel strategies for cancer treatment development. Overall, this review underscores the importance of further research to fully elucidate the mechanisms of ac-tion of SerpinB3 and to exploit its therapeutic potential across various medical conditions.

This study explores the potential of using a Siamese Network as a biomarker for assessing the effectiveness of Dolphin-Assisted Therapy (DAT) in children with Cerebral Palsy (CP). The problem statement revolves around the need for objective measures to evaluate the impact of DAT on patients with CP, considering the subjective nature of traditional assessment methods. The methodology involves training a Siamese network, a type of neural network designed to compare similarities between inputs, using data collected from CP patients undergoing DAT sessions. The network is trained to learn patterns and similarities between pre- and post-therapy evaluations, in order to identify biomarkers indicative of therapy effectiveness. Notably, the Siamese Network’s architecture ensures that comparisons are made within the same feature space, allowing for more accurate assessments. The results of the study demonstrate promising findings, indicating different patterns in the output of the Siamese Network that correlate with improvements in symptoms of CP post-DAT. These findings suggest the potential utility of the Siamese Network as a biomarker to monitor therapy outcomes in children with CP who undergo DAT, offering a more objective and quantifiable approach to assessing therapeutic interventions. Significant disparities in neuronal voltage perturbations, with a mean of 7.9825 dB in specific samples compared to 6.2838 dB in the data set, indicate a marked difference from resting activity. This suggests that dolphin-assisted therapy selectively activates specific brain regions uniquely during the intervention.

The motor protein Prestin found in the outer hair cells (OHCs) of the inner ear is responsible for producing high sensitivity and sharp frequency selectivity for mammalian hearing. Some studies have suggested that Prestin could serve as a serological biomarker for cochlear damage since OHCs are highly vulnerable to damage from various sources of insults. However, the reported data are inconsistent and lack appropriate negative controls. To investigate this further, we measured Prestin quantities in the bloodstream using ELISA kits from different companies. Wildtype (WT) mice were exposed to different ototoxic treatments, including noise exposure and ototoxic reagents that kill OHCs rapidly. Prestin-knockout (KO) mice were used as a negative control. Our data show that some ELISA kits were not able to detect Prestin specifically. The ELISA kit that could detect Prestin protein from cochlear homogenates failed to detect Prestin in the bloodstream despite significant damage to OHCs in cochleae. Furthermore, the optical densities of samples, which correlate to Prestin quantities, were significantly influenced by hemolysis in the samples. In conclusion, Prestin from OHCs is not a sensitive and reliable serological biomarker for detecting cochlear damage in mice.

Acute coronary syndrome (ACS) is a life-threatening condition that requires a prompt diagnosis and therapeutic intervention. Although serum troponin T and creatinine kinase-MB (CK-MB) are established biomarkers for ACS, it may take several hours to reach diagnostic values for ACS. In this study, we attempted to explore novel biomarkers for ACS with higher sensitivity than that of troponin T and CK-MB. The metabolomic profiles of 18 patients with ACS upon hospital arrival and those of the age-matched control (HC) group consisted of 24 healthy volunteers were analyzed using liquid chromatography-time-of-flight mass spectrometry. Volcano plots showed 24 metabolites whose concentrations differed significantly between the ACS and HC groups. Using these data, we developed a multiple logistic regression model for the ACS diagnosis, in which lysine, isocitrate, and tryptophan were selected as minimum-independent metabolites. The area under the receiver operating characteristic curve value for discriminating ACS from HC was 1.00 (95% confidence interval [CI]: 1.00-1.00). In contrast, those for troponin T and CK-MB were 0.917 (95% confidence interval [CI]: 0.812-1.00) and 0.988 (95% CI: 0.966-1.00), respectively. This study showed the potential of combining three plasma metabolites to discriminate ACS from HC with a higher sensitivity than that of troponin T and CK-MB.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP &gt; 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

The application of bacterial metagenomic analysis as biomarker for cancer detection is emerging. Our aim was to discover gut microbiota signatures with potential utility in the diagnosis of colorectal cancer (CRC) and non-small cell lung cancer (NSCLC). A prospective study was performed on a total of 77 fecal samples from CRC and NSCLC patients and Controls. DNA from stool was analyzed for bacterial genomic sequencing using the Ion Torrent™ technology. Bioinformatic analysis was performed with QIIME2 pipeline. We applied logistic regression for adjusting differences attributable to sex, age and body mass index and compared diagnostic accuracy of our gut signatures with other previously published. The feces of patients affected by different tumor types, such as CRC and NSCLC, showed a differential intestinal microbiota profile. After adjusting for confounders, Parvimonas (OR = 53.3), Gemella (OR = 6.01), Eisenbergiella (OR = 5.35), Peptostreptococcus (OR = 9.42), Lactobacillus (OR = 6.72), Salmonella (OR = 5.44) and Fusobacterium (OR = 78.9) remained significantly associated with the risk of CRC. Two genera from the Ruminoccocaeae family, DTU089 (OR = 20.1) and an uncharacterized genus (OR = 160.1) were associated with the risk of NSCLC. Our two panels had better diagnostic capacity for CRC (AUC = 0.840) and NSLC (AUC = 0.747) compared to the application to our population of two other published panels. Thus, we propose a gut bacteria panel for each cancer type and show its potential application in cancer diagnosis.

This review centers on the pivotal role of the oncoprotein FOSL1, within the dimeric AP-1 transcription factor consisting of FOS-related elements. FOSL1 emerges as a key regulator governing invasion and metastatic dissemination, therefore making it a promising target for therapeutic intervention in cancer patients. The review provides a comprehensive survey of the regulatory mechanisms that exert influence over FOSL1. These encompass a spectrum of transcriptional and post-translational modifications. Notably, we unveiled the intricate involvement of diverse non-coding RNAs, specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in the modulation of FOSL1 expression through targeted interactions with its mRNA transcripts. Furthermore, an exploration into the functional dimensions of FOSL1 unfolds, encompassing apoptosis, proliferation, and migration. This investigation is accompanied by a thorough examination of the elaborate signaling pathways that underpin these multifaced roles. Additionally, emphasis is placed on the role of FOSL1 in orchestrating the stimulation of various cytokines, including TGF-beta, and the initiation of IL-6 and VEGF production in tumor-associated macrophages (TAMs) that transverse into the tumor microenvironment. A distinct focus is dedicated to appraising the prognostic implications associated with FOSL1. Finally, insights emerge into the evolving roles of FOSL1 in the context of mechanisms governing resistance and dependency on targeted therapeutic modalities.

The diagnosis and the pathology of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) remain under debate. However, there is a growing body of evidence for an autoimmune component in ME/CFS caused by the Epstein-Barr virus (EBV) and other viral infections. In this work, we took advantage of a large public dataset on the IgG antibodies to 3,054 EBV peptides to understand whether these immune responses could be used as putative biomarkers for disease diagnosis and triggers of pathological autoimmunity in ME/CFS patients using healthy controls (HCs) as a comparator cohort. We then aimed at predicting disease status of study participants using a Super Learner algorithm targeting an accuracy of 85% when splitting data into train and test datasets. When we compared data of all ME/CFS patients or data of a subgroup of these patients with non-infectious or unknown disease trigger to the dataset of HC, we could not find an antibody-based classifier that would meet the desired accuracy in the test dataset. In contrast, we could identify a 26-antibody classifier that could distinguish ME/CFS patients with an infectious disease trigger from HCs with 100% and 90% accuracies on the train and test sets, respectively. We finally performed a bioinformatic analysis of the EBV peptides associated with these 26 antibodies. We found no correlation between the importance metric of the selected antibodies in the classifier and the maximal sequence homology between human proteins and each EBV peptide recognized by these antibodies. In conclusion, these 26 antibodies against EBV have an effective potential for disease diagnosis of a subset of patients, but they are less likely to trigger pathological autoimmune responses that could explain the pathogenesis of ME/CFS.

Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, we present a novel approach that employs both an LLM-based framework and explainable machine learning to facilitate generalization across single-cell datasets and identify gene signatures to capture disease-driven transcriptional changes. Our approach uses scBERT, which harnesses shared transcriptomic features among cell types to establish consistent cell-type annotations across multiple scRNA-seq datasets. Additionally, we employ a symbolic regression algorithm to pinpoint highly relevant yet minimally redundant models and features for inferring a cell type’s disease state based on its transcriptomic profile. We ascertain the versatility of these cell-specific gene signatures across datasets, showcasing their resilience as molecular markers to pinpoint and characterize disease-associated cell types. Validation is carried out using four publicly available scRNA-seq datasets from both healthy individuals and those suffering from ulcerative colitis (UC). This demonstrates our approach’s efficacy in bridging disparities specific to different datasets, fostering comparative analyses. Notably, the simplicity and symbolic nature of the retrieved gene signatures facilitate their interpretability, allowing us to elucidate underlying molecular disease mechanisms using these models.

Background: The purpose of this study is to carry out bioinformatic analysis of lncRNA data obtained as a result of genomic analysis of kidney tissue samples taken from rats with nephrotoxicity induced by methotrexate (MTX) and from rats without pathology and modeling with tree-based machine learning method. Another aim of the study is to identify potential biomarkers for the diagnosis of nephrotoxicity and to provide a better understanding of the nephrotoxicity formation process by providing the interpretability of the model with explainable artificial intelligence methods as a result of the modeling. Methods: To identify potential indicators of drug-induced nephrotoxicity, 20 female Wistar Albino rats were separated into two groups: nephrotoxicity and control. Kidney tissue samples were collected from the rats, and genomic, histological, and immunohistochemical analyses were performed. The data set obtained as a result of genomic analysis was modeled with Random Forest (RF), one of the tree-based methods. Modeling results were evaluated with sensitivity (Se), specificity (Sp), balanced accuracy (B-Acc), negative predictive value (Npv), accuracy (Acc), positive predictive value (Ppv), and F1-score performance metrics. The Local Interpretable Model-Agnostic Annotations (LIME) method was used to determine the lncRNAs that could be biomarkers for nephrotoxicity by providing the interpretability of the RF model. Results: The outcomes of the histological and immunohistochemical analyses done in the study supported the conclusion that MTX use caused kidney injury. According to the results of the bioinformatics analysis, 52 lncRNAs showed different expression in the groups. As a result of modeling with RF for lncRNAs selected with Boruta variable selection, the B-Acc, Acc, Sp, Se, Npv, Ppv, and F1-score were 88.9%, 90%, 90.9%, 88.9%, 90.9%, 88.9% and 88.9%. respectively. lncRNAs with id rnaXR_591534.3 rnaXR_005503408.1, rnaXR_005495645.1, rnaXR_001839007.2, rnaXR_005492056.1 and rna_XR_005492522.1 the lncRNAs with the highest variable importance values produced from RF modeling can be used as nephroxicity biomarker candidates. Also, according to the LIME results, the high level of lncRNAs with id rnaXR_591534.3 and rnaXR_005503408.1 especially increased the possibility of nephrotoxicity. Conclusions: With the possible biomarkers obtained as a result of the analyses made within the scope of this study, it can be ensured that the procedures for the diagnosis of drug-induced nephrotoxicity can be carried out easily, quickly and effectively.

Aim: This study aimed to investigate the relationship between dental caries, dental anxiety, and salivary cortisol levels in children visiting pediatric dental clinics and their implications on pediatric oral health. Materials and Methods: A cross-sectional study was conducted at a dental university in the UAE. A total of 60 children, aged 4-12 years, were included. Salivary cortisol levels were measured using an Enzyme-Linked Immunosorbent Assay (ELISA) kit. Dental caries status was evaluated, and dental anxiety levels were assessed using the Modified Dental Anxiety Scale (MDAS). Statistical analyses, including Mann-Whitney U test and Pearson's correlation coefficient, were performed to determine significant differences and associations. Results: The study group showed significantly higher salivary cortisol levels compared to the control group (p<0.0001). A strong positive correlation was found between salivary cortisol levels and dental caries status (p<0.001). However, no significant difference in dental anxiety levels was observed between the study and control groups (p=0.85). A strong positive correlation was found between dental anxiety levels and dental caries status (p<0.001). Conclusion: The findings indicate a significant association between salivary cortisol levels and dental caries, suggesting that higher cortisol levels are associated with active caries. Dental anxiety levels were positively correlated with dental caries. Understanding the relationship between these variables can contribute to better oral health strategies and interventions for children, emphasizing the importance of managing dental anxiety and stress in pediatric dental care. Clinical Significance: This study highlights the potential of salivary cortisol as a biomarker for assessing stress and its impact on oral health in children. By addressing dental anxiety and stress, dental professionals can provide child-friendly dental care, enhance preventive measures, and improve oral health outcomes in pediatric patients.