Search Results (6,112)

Background/Objectives: Attention-Deficit/Hyperactivity Disorder (ADHD) is associated with an increased risk of obesity and disordered eating behaviors. This study compared weight status and eating behaviors among drug-naïve ADHD children, those on stimulant monotherapy, those on combined stimulant and antipsychotic treatment, and healthy controls. Methods: This cross-sectional study included 547 children aged 6–12 years from four Turkish provinces: 361 with ADHD (152 drug-naïve, 156 on stimulants, and 53 on combined therapy), and 186 healthy controls. Anthropometric measurements, psychiatric assessments, and eating behavior evaluations were conducted using standardized tools. Results: Drug-naïve ADHD children had the highest obesity rate (13.8%), while those on stimulant monotherapy had the lowest (4.5%) compared to controls. Combined treatment group obesity rates were similar to controls (7.5% vs. 8.6%). The drug-naïve and combined treatment groups showed increased food approach behavior and desire to drink, with the combined treatment group also showing increased emotional overeating. Conclusions: This study reveals a complex relationship between ADHD, its pharmacological management, and the risk of obesity. Stimulant monotherapy may mitigate the risk of obesity, while combined stimulant and antipsychotic treatment may lead to problematic eating behaviors. These findings emphasize the importance of monitoring weight status and eating behaviors in ADHD children, especially those receiving pharmacological interventions. Full article

Background/Objectives: Hormonal alterations during menopause result in substantial physiological changes. Although hormone replacement therapy (HRT) is widely used as a treatment strategy for these changes, its use remains controversial due to its associated risks. Plant isoflavones are phytoestrogens that are considered a potential alternative therapy for postmenopausal syndrome. We aimed to investigate the efficacy of ethanolic extracts from Styphnolobium japonicum fruit (SJF) and germinated soybean embryo (GSE) in alleviating prominent menopausal symptoms. Methods: A cell model (MCF7 human breast cancer cells) was used to investigate estrogen-like activity. A rat ovariectomy model was used to simulate estrogen depletion after menopause and to evaluate the efficacy of the SJF–GSE complex extract at ratios of 1:1, 1:2, and 2:1. Results: Treatment with the SJF–GSE extract elicited estrogen-like effects, raising pS2 and estrogen receptor α expression in MCF7 cells. The extract was found to contain 48–72 mg/g sophoricoside and 8–12 mg/g soyasaponin 1, identified as active compounds. In ovariectomized rats, the extract effectively reduced body weight and fat content, alleviated vasomotor symptoms, improved vaginal mucosal health, and exerted osteoprotective effects by enhancing bone density and structure, reducing bone-resorption markers and positively altering estradiol levels and lipid profiles. Conclusions: The SJF–GSE extract, working synergistically, provides a safe and effective alternative to HRT for managing postmenopausal symptoms and enhancing bone health, without adverse effects. These findings support the inclusion of SJF and GSE in health-functional foods and underscore the importance of further research into plant-based therapies for menopause. Full article

Background/Objectives: Neural decoding methods are often limited by the performance of brain encoders, which map complex brain signals into a latent representation space of perception information. These brain encoders are constrained by the limited amount of paired brain and stimuli data available for training, making it challenging to learn rich neural representations. Methods: To address this limitation, we present a novel multimodal training approach using paired image and functional magnetic resonance imaging (fMRI) data to establish a brain masked autoencoder that learns the interactions between images and brain activities. Subsequently, we employ a diffusion model conditioned on brain data to decode realistic images. Results: Our method achieves high-quality decoding results in semantic contents and low-level visual attributes, outperforming previous methods both qualitatively and quantitatively, while maintaining computational efficiency. Additionally, our method is applied to decode artificial patterns across region of interests (ROIs) to explore their functional properties. We not only validate existing knowledge concerning ROIs but also unveil new insights, such as the synergy between early visual cortex and higher-level scene ROIs, as well as the competition within the higher-level scene ROIs. Conclusions: These findings provide valuable insights for future directions in the field of neural decoding. Full article

Early fire detection is the key to saving lives and limiting property damage. Advanced technology can detect fires in high-risk zones with minimal human presence before they escalate beyond control. This study focuses on providing a more advanced model structure based on the YOLOv8 architecture to enhance early recognition of fire. Although YOLOv8 is excellent at real-time object detection, it can still be better adjusted to the nuances of fire detection. We achieved this advancement by incorporating an additional context-to-flow layer, enabling the YOLOv8 model to more effectively capture both local and global contextual information. The context-to-flow layer enhances the model’s ability to recognize complex patterns like smoke and flames, leading to more effective feature extraction. This extra layer helps the model better detect fires and smoke by improving its ability to focus on fine-grained details and minor variation, which is crucial in challenging environments with low visibility, dynamic fire behavior, and complex backgrounds. Our proposed model achieved a 2.9% greater precision rate, 4.7% more recall rate, and 4% more F1-score in comparison to the YOLOv8 default model. This study discovered that the architecture modification increases information flow and improves fire detection at all fire sizes, from tiny sparks to massive flames. We also included explainable AI strategies to explain the model’s decision-making, thus adding more transparency and improving trust in its predictions. Ultimately, this enhanced system demonstrates remarkable efficacy and accuracy, which allows additional improvements in autonomous fire detection systems. Full article

Background/Objectives: The flexibility deficits of hip flexors have been identified as potential biomechanical risk factors for the lumbo–pelvic–hip complex, with postural repercussions on the trunk and lower limbs. The purpose of this study was to conduct a single gravity stretching experiment and to monitor its acute and prolonged effects. Methods: The sample comprised 14 healthy participants (8 females and 6 males). Data were collected during two-day measurement sessions. These analyzed via Kinovea software. The single intervention (i.e., gravity stretching) was performed on the first day. A modified Thomas test was used at the same time in two ways, both as a measurement and as an intervention tool. Stretching was achieved by relaxing in a position to perform the modified Thomas test where, each participant lies completely relaxed for 3 min, allowing gravity to stretch the hip flexors of the examined limb. Results: After intervention, a significant acute increase in hip extension range of motion and a decrease in knee extension range of motion were found. We did not find any significant prolonged effects; moreover, after 48 h, the hip range of motion almost returned to the initial value. Conclusions: A single 3 min stretch is very effective in terms of achieving immediate changes in the range of motion, but insufficient for long-term improvements in flexibility. Full article

Background: Aneurysmal subarachnoid hemorrhage (SAH) predominantly affects women, accounting for 65% of cases. Women have a 1.3 times higher relative risk than men, with the incidence rising particularly in women aged 55–85 years. Women also have a higher prevalence of unruptured intracranial aneurysms (IAs), especially after the age of 50 years, and are at greater risk of aneurysm growth and rupture. This study aimed to isolate the influence of sex on rupture rate, bleeding severity, functional outcomes, and complications by using a matched cohort, while also examining the impact of sex on aneurysm localization and multiplicity. Methods: We utilized a retrospectively collected database of 300 patients with 511 IAs. Inclusion criteria included the availability of clinical data and 3D angiography for semi-automatic reconstruction of IA morphology. Female patients and their IA were matched with male patients according to clinical parameters and 21 morphological characteristics using an interactive visual exploration tool for multidimensional matching. Results: Contrary to previously published results, our study found no significant sex differences in rupture rates or vasospasm rates between male and female patients. The severity of SAH, functional outcomes, and complications such as hydrocephalus were also similar in women and men. However, women exhibited a higher prevalence of multiple aneurysms and distinct localization patterns. Conclusion: This study underscores the complex role of sex in IA development and rupture. Although sex-specific biological factors influence aneurysm characteristics, they do not necessarily translate into differences in clinical outcomes. Further research is needed to explore these factors and their impact on aneurysm development and management. Full article

Aiming at the problem that insulator image backgrounds are complex and fault types are diverse, which makes it difficult for existing deep learning algorithms to achieve accurate insulator fault diagnosis, an insulator fault diagnosis method based on multi-mechanism optimization YOLOv8-DCP is proposed. Firstly, a feature extraction and fusion module, named CW-DRB, was designed. This module enhances the C2f structure of YOLOv8 by incorporating the dilation-wise residual module and the dilated re-param module. The introduction of this module improves YOLOv8’s capability for multi-scale feature extraction and multi-level feature fusion. Secondly, the CARAFE module, which is feature content-aware, was introduced to replace the up-sampling layer in YOLOv8n, thereby enhancing the model’s feature map reconstruction ability. Finally, an additional small-object detection layer was added to improve the detection accuracy of small defects. Simulation results indicate that YOLOv8-DCP achieves an accuracy of 97.7% and an [email protected] of 93.9%. Compared to YOLOv5, YOLOv7, and YOLOv8n, the accuracy improved by 1.5%, 4.3%, and 4.8%, while the [email protected] increased by 3.0%, 4.3%, and 3.1%. This results in a significant enhancement in the accuracy of insulator fault diagnosis. Full article

Background: Arthritis, a debilitating joint disease, remains a significant global health burden. This study uncovers the therapeutic potential of the medicinal plant Smilax glabra Roxb. (SGR) in attenuating progression of disease by modulating immune responses. Methods: Through computational approaches, key bioactive compounds in SGR were identified by using freely available databases: TCMSP, TCMID, HIT2.0, HERB, and INPUT in order to elucidate their underlying mechanisms of action. Therapeutic targets for the disease have been retrieved by TTD, GeneCard, and OMIM databases. The STRING database was used to analyze the protein–protein interactions (PPI) of intersecting genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to reveal the functional roles of genes. Mcule was used for molecular docking and binding affinity of compounds and targets were evaluated by DeepPurpose model. ALP activity, cell viability assay, TRAP staining were also performed. Results: A total of 14 active SGR compounds with 59 common targets for arthritis have been identified. These targets have a major role in controlling biological processes such as wound healing, oxygen responses, and chemical stimuli. Molecular docking by Mcule platform demonstrated that quercetin and β-sitosterol showed higher binding energy affinities with TNF, TP53, PTGS2, and JUN as compared to other targets. To explore the complex relationship between compounds and targets, pre-trained Davis and KIBA models were used to predict the affinity values of selected compounds. In MC3T3-E1 cells, ALP activity was significantly increased and bone marrow macrophages (BMM) showed a low number of TRAP-positive cells in SGR-treated cells. Conclusions: Our findings demonstrate that SGR effectively inhibits/regulates inflammatory responses, prevents cartilage degradation, promotes bone regeneration, and can be used as a promising candidate for the development of novel arthritis treatment. Full article

Urban vitality, which indicates the development level of a city and the quality of life of its residents, is a complex subject in urban research due to its diverse assessment methods and intricate impact mechanisms. This study uses multisource data to evaluate the urban vitality of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) across social, economic, cultural, and environmental dimensions. It analyzes the spatial distribution characteristics of urban vitality and examines the relationships between urban vitality and land use at both regional and city scales. The results indicate that the urban vitality in the GBA generally exhibits a spatial distribution pattern of a high central density and a low peripheral spread, where built-up areas and cropland emerge as key influencing factors. Cities with different developmental backgrounds have unique relationships between land use and urban vitality. In high-vitality cities, the role of the built-up area diminishes, and natural ecosystems, such as wetlands, enhance vitality. In contrast, in low-vitality cities, built-up areas boost urban vitality, and agriculture-related land types exert a lower negative or even positive effect. This research contributes to the understanding of the spatial structures of urban vitality related to land use at different scales and offers insights for urban planners, builders, and development managers in formulating targeted urban vitality enhancement strategies at the regional collaborative and city levels. Full article

Background/Objectives: For locally applied, locally acting generic drug products, comparison to an originator product based on systemic exposure is usually not feasible due to low plasma concentrations and inadequate reflection of local exposure at the site of action. Where a validated PD model exists, a comparative clinical study can be performed in healthy subjects; where no surrogate endpoint is available, patients with the relevant indication need to be enrolled, with all the associated factors which could result in lack of sensitivity. Even though the need for alternative in vitro approaches has been acknowledged by both industry and regulatory bodies, the complexity of in vivo drug delivery processes makes the development of guidance documents particularly difficult. Our objective was to present in vitro approaches less classically used and to address in vivo relevance of the selected tests. Methods: This article analyses current regulatory approaches in Europe and the U.S., and highlights the key advantages of in vitro tests in terms of their sensitivity, reliability, reproducibility and in vivo relevance using locally applied flurbiprofen in various formulations. Results: The in vitro esophageal retention (IVOR) model demonstrates that the first 6–10 min after application of different flurbiprofen formulations is important for their comparison and also offers the best correlation with in vivo data using the partial area under the concentration-time curves (pAUCs). Rheological evaluations further demonstrated that the mucoadhesive properties of the gel spray formulation are based on interaction with mucin. Conclusions: Designing a relevant in vitro test requires adequate evaluation of the complexity of the drug substance, drug product, dosing conditions and delivery processes. Full article

Background: Chronic Obstructive Pulmonary Disease (COPD) is a major global health challenge, primarily driven by exposures to tobacco smoke and biomass smoke. While Tobacco-Smoke-Induced COPD (TSCOPD) has been extensively studied, the diagnostic challenges and distinct pathogenesis of Biomass-Smoke-Induced COPD (BSCOPD), particularly in low- and middle-income countries, remain underexplored. Objective: To explore the differences in clinical manifestations, pulmonary function, and inflammatory profiles between BSCOPD and TSCOPD and highlight the diagnostic complexities of BSCOPD. Methods: This review analyzes the current literature comparing BSCOPD with TSCOPD, focusing on distinctive pathophysiological mechanisms, inflammatory markers, and oxidative stress processes. Results: BSCOPD presents differences in clinical presentation, with less emphysema, smaller airway damage, and higher rates of pulmonary hypertension compared to TSCOPD. BSCOPD is also characterized by bronchial hyperresponsiveness and significant hypoxemia, unlike TSCOPD, which exhibits severe airflow obstruction and emphysema. Additionally, the inflammatory profile of BSCOPD includes distinct mucous hypersecretion and airway remodeling. Conclusions: The unique genetic, epigenetic, and oxidative stress mechanisms involved in BSCOPD complicate its diagnosis and management. Biomass smoke’s underrecognized impact on accelerated lung aging and exacerbation mechanisms emphasizes the need for targeted research to refine diagnostic criteria and management strategies for BSCOPD. Future directions: Further research should focus on identifying specific biomarkers and molecular pathways to enhance early diagnosis and improve clinical outcomes in populations exposed to biomass smoke. Full article

Background/Objectives: Research suggests that metalinguistic and cognitive/attentional-control processes are key variables in literacy development in young learners. Interactions between these variables are complex, and this complexity is increased in multilingual learners. With data on the interplay between metalinguistic and cognitive awareness, literacy, and multilingualism being scarce, it is far from clear how these variables interact and how they impact the individual child. This article sets out to shine some light on the interconnectedness and interactions between metalinguistic awareness, cognitive/executive functions, and (multilingual) literacy. Conclusions: We argue that the three dimensions are strongly correlated and that this correlation comes with important implications for language learning, language processing, and language development. However, the exact nature of these correlations is yet to be established. Full article

Background: As the population ages, the prevalence of surgical interventions in individuals aged 65+ continues to increase. This poses unique challenges due to the higher incidence of comorbidities, polypharmacy, and frailty in the elderly population, which result in high peri-operative risks. Traditional preoperative risk assessment tools often fail to accurately predict post-operative outcomes in the elderly, overlooking the complex interplay of factors that contribute to risk in the elderly. Methods. A literature review was conducted, focusing on the predictive value of CGA for postoperative prognosis and the implementation of perioperative interventions. Results. Evidence shows that CGA is a superior predictive tool compared to traditional models, as it more accurately identifies elderly patients at higher risk of complications such as postoperative delirium, infections, and prolonged hospital stays. CGA includes assessments of frailty, sarcopenia, nutritional status, cognitive function, mental health, and functional status, which are crucial in predicting post-operative outcomes. Studies demonstrate that CGA can also guide personalized perioperative care, including nutritional support, physical training, and mental health interventions, leading to improved surgical outcomes and reduced functional decline. Conclusions: The CGA provides a more holistic approach to perioperative risk assessment in elderly patients, addressing the limitations of traditional tools. CGA can help guide surgical decisions (e.g., curative or palliative) and select the profiles of patients that will benefit from perioperative interventions to improve their prognosis and prevent functional decline. Full article

This study proposes a novel approach for detecting weak small infrared (IR) targets, called double-image and double-local contrast measurement (DDLCM), designed to overcome challenges of low contrast and complex backgrounds in images. In this approach, the original image is decomposed into odd and even images, and the gray difference contrast is determined using a dual-neighborhood sliding window structure, enhancing target saliency and contrast by increasing the distinction between the target and the local background. A central unit is then constructed to capture relationships between neighboring and non-neighboring units, aiding in clutter suppression and eliminating bright non-target interference. Lastly, the output value is derived by extracting the lowest contrast value of the weak small targets from the saliency map in each direction. Experimental results on two datasets demonstrate that the DDLCM algorithm significantly enhances real-time IR dim target detection, achieving an average performance improvement of 32.83%. The area under the ROC curve (AUC) decline is effectively controlled, with a maximum reduction limited to 3%. Certain algorithms demonstrate a notable AUC improvement of up to 43.96%. To advance infrared dim target detection research, we introduce the IFWS dataset for benchmarking and validating algorithm performance. Full article

Background/Objectives: As a primary source of mortality and disability, bacterial infections continue to develop a severe threat to humanity. Nuclear medicine imaging (NMI) is known for its promising potential to diagnose deep-seated bacterial infections. This work aims to develop a new technetium-99m (^99mTc) labeled tigecycline radiopharmaceutical as an infection imaging agent. Methods: Reduced ^99mTc was used to make a coordinate complex with tigecycline at pH 7.7–7.9 at room temperature. Instantaneous thin-layer chromatography impregnated with silica gel (ITLC-SG) and ray detector equipped high-performance liquid chromatography (ray-HPLC) was performed to access the radiolabeling yield and radiochemical purity (RCP). Results: More than 91% labeling efficiency was achieved after 25 min of mild shaking of the reaction mixture. The radiolabeled complex was found intact up to 4 h in saline. Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) infection-induced rats were used to record the biodistribution of the radiopharmaceutical and its target specificity; 2 h’ post-injection biodistribution revealed a 2.39 ± 0.29 target/non-target (T/NT) ratio in the E. coli infection-induced animal model, while a 2.9 ± 0.31 T/NT value was recorded in the S. aureus bacterial infection-induced animal model. [^99mTc]Tc-tigecycline scintigraphy was performed in healthy rabbits using a single photon emission computed tomography (SPECT) camera. Scintigrams showed normal kidney perfusion and excretion into the bladder. Conclusion: In conclusion, the newly developed [^99mTc]Tc-tigecycline radiopharmaceutical could be considered to diagnose broad-spectrum bacterial infections. Full article