Search Results (205)

Bacillus cereus is a Gram-positive pathogen associated with foodborne illnesses and severe non-gastrointestinal infections. Robust tools for accurate gene transcription analysis are essential for studying toxin gene expression dynamics and deciphering the complex regulatory networks orchestrating the expression of toxin and virulence factors. This study aimed to identify reliable reference genes for normalizing reverse transcription quantitative PCR (RT-qPCR) data in toxigenic B. cereus. An emetic and an enteropathogenic strain were used as model organisms to establish a suitable reference gene set to monitor the dynamics of toxin gene transcription. Ten candidate reference genes were evaluated for their expression stability using geNorm, NormFinder, BestKeeper and the ΔCq method, with the final rankings integrated via RefFinder. Among the tested genes, rho, rpoD and recA were identified as the most stable expressed reference genes across all tested conditions. As shown in this proof-of-principle study, the established reference gene set provides a suitable tool to investigate the influence of extrinsic and intrinsic factors on toxin gene transcription. In conclusion, our newly established reference gene set provides a robust basis for studying toxin gene expression in B. cereus and contributes to a better understanding of its pathogenicity and potential strategies to mitigate its harmful effects. Full article

Background/Objectives: Glioblastoma is the most common and lethal primary brain tumor. Patients often suffer from tumor- and treatment induced vasogenic edema, with devastating neurological consequences. Intracranial edema is effectively treated with dexamethasone. However, systemic dexamethasone requires large doses to surpass the blood brain barrier in therapeutic quantities, which is associated with significant side effects. The aim of this study was to investigate a biodegradable, dextran-hydroxyethyl methacrylate (dex-HEMA) based hydrogel, containing polymeric micelles loaded with dexamethasone and liposomes encapsulating dexamethasone phosphate for localized and prolonged delivery. Methods: Poly(ethylene glycol)-b-poly(N-2-benzoyloxypropyl methacrylamide (mPEG-b-p(HPMA-Bz)) micelles were loaded with dexamethasone and characterized. The dexamethasone micelles, together with dexamethasone phosphate liposomes, were dispersed in an aqueous dex-HEMA solution followed by radical polymerization using a photoinitiator in combination with light. The kinetics and mechanisms of drug release from this hydrogel were determined. Results: The diameter of the nanoparticles was larger than the mesh size of the hydrogel, rendering them immobilized in the polymer network. The micelles immediately released free dexamethasone from the hydrogel for two weeks. The dexamethasone phosphate loaded in the liposomes was not released until the gel degraded and intact liposomes were released, starting after 15 days. The different modes of release result in a biphasic and sequential release profile of dexamethasone followed by dexamethasone phosphate liposomes. Conclusions: The results show that this hydrogel system loaded with both dexamethasone polymeric micelles and dexamethasone phosphate loaded liposomes has potential as a local delivery platform for the sequential release of dexamethasone and dexamethasone phosphate, for the intracranial treatment of glioblastoma associated edema. Full article

This work aims to analyze the effect of pore size on the catalytic reaction of 316L stainless steel electrodes. Porous compacts were fabricated using the space holder technique and sintering at low temperatures. The fabricated porous compacts were characterized using computed tomography and the hydrogen evolution reaction was evaluated under 0.5 M and 1.5 M NaOH. Results indicate that porosity is well controlled by the pore formers, which allows different pore size distributions of pores with similar relative density values to be obtained. The pores are fully interconnected, allowing the passing of fluid throughout the compacts. Permeability is sensitive to the pore size, increasing as the pore size does. The catalytic activity of hydrogen evolution reaction HER is improved as the pore volume and pore size increase concerning the compact fabricated without pore formers. The compact that showed higher C_dl and R_f values was fabricated with S100 pore formers, which means a higher active area that favors the HER. It can be concluded that porosity enhances HER reactivity. However, larger pores are not beneficial due to a more significant permeability value. Full article

2,8-Dithia-5-aza-2,6-pyridinophane (L1) has been used as a receptor unit in the construction of the conjugated redox chemosensor 5-ferrocenylmethyl-2,8-dithia-5-aza-2,6-pyridinophane (L3). In order to further explore the coordination chemistry of L1, and comparatively, that of its structural analogue 2,11-dithia-5,8-diaza-2,6-pyridinophane (L2), featuring two secondary nitrogen atoms in the macrocyclic unit, the crystal structures of the new synthesised complexes [Pb(L1)(ClO₄)₂]·½CH₃CN, [Cu(L2)](ClO₄)₂·CH₃CN and [Cd(L2)(NO₃)]NO₃ were determined by X-ray diffraction analysis. The electrochemical response of L3 towards the metal ions Cu²⁺, Zn²⁺, Cd²⁺, Hg²⁺, and Pb²⁺ was investigated by cyclic voltammetry (CV) in CH₂Cl₂/CH₃CN 0.25:1 (v/v) mixture. Upon addition to L3 of increasing amounts of the aforementioned metal cations, the wave corresponding to the Fc⁺/Fc redox couple of the un-complexed L3 was gradually replaced by a new reversible wave at more positive potentials and corresponding to the Fc⁺/Fc redox couple of the complexed ligand. The maximum anodic shift of the ferrocene oxidation wave is observed in the presence of Pb²⁺ (230 mV), to which corresponds a reaction coupling efficiency (RCE) value as large as 7.9 × 10³. The response selectivity of L3 is discussed in reference to the optical selectivity observed for conjugated chemosensors featuring L1 as receptor unit and different fluorogenic fragments as signalling units. Full article

Background: Non-communicable diseases (NCDs) are the leading cause of global mortality. The WHO projects a rise in NCD-related deaths from 36 million in 2018 to 55 million by 2030, with developing countries being the most affected. Effective community-based primary health care (PHC) can reduce the burden of chronic diseases of lifestyle (CDLs). This study aimed to develop a risk assessment and health promotion framework to strengthen CDL prevention and control in Free State (FS) communities in South Africa. Methods: A convergent mixed-method design was used. Quantitative analysis identified CDL risk factors in rural and urban FS settings, while qualitative focus group discussions explored participants’ knowledge of CDLs and their experiences with program implementation. Results: Key findings highlighted differences in risk profiles, CDL training needs for PHC teams, patient education gaps, and curriculum development. Step 1 of the framework development identified differences and similarities in the CDL risk profiles of the study populations. Step 2 identified CDL training needs for PHC teams, patient educational needs, and CDL curriculum development needs. Step 3 revealed three main barriers: resource constraints, patient non-compliance, and the lack of supporting healthcare services. In Step 4, the six focus areas identified (steps 1–3) were used to develop strategies for implementing a tailored, community-based, patient-centred approach. Conclusions: The results provide valuable insights for improving PHC responses in resource-limited settings. Full article

Automatic geometric problem-solving is an active and challenging subfield at the intersection of AI and mathematics, where geometric problem parsing plays a critical role. It involves converting geometric diagram and text into certain formal language. Due to the complexity of geometric shapes and the diversity of geometric relationships, geometric problem parsing demands that the parser exhibit cross-modal comprehension and reasoning capabilities. In this paper, we propose an enhanced geometric problem parsing method called FGeo-Parser, which converts problem diagrams and text into the formal language of the FormalGeo. It also supports reverse formalization to generate human-like solutions, reflecting the symmetry between parsing and generating. Specifically, diagram parser leverages the BLIP to generate the construction CDL and image CDL, while text parser employs the T5 to produce the text CDL and goal CDL where these neural networks are both based on a symmetric encoder–decoder architecture. With the assistance of a theorem predictor, these CDLs were automatically parsed and step-by-step reasoning was executed within FGPS. Finally, the reasoning process was input into a solution generator, which subsequently produced a human-like solution process. Additionally, we re-annotated problem diagrams and text based on the FormalGeo7K dataset. The formalization experiments on the new dataset achieved a match accuracy of 91.51% and a perfect accuracy of 56.47%, while the combination with the theorem predictor achieved a problem-solving accuracy of 63.45%. Full article

Satellite remote sensing enables monitoring of regenerative agriculture practices, such as crop rotation, cover cropping, and conservation tillage to allow tracking and quantification at unprecedented scales. The Monitor system presented here capitalizes on the scope and scale of these data by integrating crop identification, cover cropping, and tillage intensity estimations annually at field scales across the contiguous United States (CONUS) from 2014 to 2023. The results provide the first ever mapping of these practices at this temporal fidelity and spatial scale, unlocking valuable insights for sustainable agricultural management. Monitor incorporates three datasets: CropID, a deep learning transformer model using Sentinel-2 and USDA Cropland Data Layer (CDL) data from 2018 to 2023 to predict annual crop types; the living root data, which use Normalized Difference Vegetation Index (NDVI) data to determine cover crop presence through regional parameterization; and residue cover (RC) data, which uses the Normalized Difference Tillage Index (NDTI) and crop residue cover (CRC) index to assess tillage intensity. The system calculates field-scale statistics and integrates these components to compile a comprehensive field management history. Results are validated with 35,184 ground-truth data points from 19 U.S. states, showing an overall accuracy of 80% for crop identification, 78% for cover crop detection, and 63% for tillage intensity. Also, comparisons with USDA NASS Ag Census data indicate that cover crop adoption rates were within 20% of estimates for 90% of states in 2017 and 81% in 2022, while for conventional tillage, 52% and 25% of states were within 20% of estimates, increasing to 75% and 67% for conservation tillage. Monitor provides a comprehensive view of regenerative practices by crop season for all of CONUS across a decade, supporting decision-making for sustainable agricultural management including associated outcomes such as reductions in emissions, long term yield resiliency, and supply chain stability. Full article

Cornelia de Lange syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder. Pathogenic variants in genes encoding the structural subunits and regulatory proteins of the cohesin complex (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the primary contributors to the pathogenesis of CdLS. Pathogenic variations in these genes disrupt normal cohesin function, leading to the syndrome’s diverse and complex clinical presentation. In this study, we discovered that cells harboring variants in the NIPBL, SMC1A and HDAC8 genes exhibit spontaneous genome instability, elevated oxidative stress and premature cellular aging. These findings suggest that cohesin plays a critical role in maintaining proper cellular function and highlight its contribution to the pathophysiology seen in the related diagnoses. Full article

Graduate outcomes are a key indicator of university performance, yet the progression of students in career preparation during university is ill-understood. The Career Registration Methodology (CRM) addresses this gap by tracking students’ career planning and participation in employability and professional experiences (EPEs) throughout their university enrolment. This research used CRM to monitor students’ employability development and career readiness, assessing their impact on graduate outcomes. By analysing longitudinal CRM data and Graduate Outcomes Survey (GOS) results from 1653 students, this study examined how EPEs and career readiness influenced full-time employment, job offers, the perceived value of qualifications, and perceptions of overqualification. Correlation and trend analyses revealed positive associations between career readiness over time and employment outcomes, with regression analyses identifying EPEs as the most significant factor. Practical implications of the findings highlight CRM’s value in aiding higher education institutions, especially Work Integrated Learning (WIL) and Career Development Learning (CDL) educators, to identify trends and tailor support whilst students are still in the university. As the first CRM study in Australia based on the first available cohort, the exploratory nature of this research is acknowledged along with recommendations to refine periodic, non-intrusive measurements such as CRM for enhanced validity and reliability. Full article

Cornelia de Lange syndrome (CdLS) is a rare genetic disorder characterized by a distinctive facial appearance, growth/cognitive retardation, developmental delay, skeletal malformation, hypertrichosis, and other abnormalities. Patients with mild CdLS have less severe phenotypes, while retaining representative facial features. Mutations in the genes NIPBL, SMC1A, SMC3, HDAC8, and RAD21 have been associated with CdLS, with mutations in NIPBL accounting for approximately 60% of cases. Herein, we present a case of CdLS accompanied by cholelithiasis and nephrolithiasis. A 9-year-old Korean boy presented with vomiting and abdominal pain. Abdominal ultrasonography revealed several gallstones and renal stones. Extracorporeal shock wave lithotripsy failed; therefore, cholecystectomy and nephrolithotomy were performed. Postoperative stone composition analysis revealed calcium oxalate as the primary component. CdLS was suspected based on the characteristic appearance and physical examination, with genetic testing confirming an NIPBL gene mutation. Simultaneous CdLS, cholelithiasis, and nephrolithiasis requires careful management and treatment tailored to each patient’s specific needs and challenges. Full article

This study investigated the influence of sea–land breezes on nocturnal spatial and temporal distribution of ozone (O₃) and its potential effects on particulate nitrate formation in Qingdao, a coastal city in northern China. Observation campaigns were conducted to measure surface air pollutants and meteorological factors during a typical sea–land breezes event from 22 to 23 July 2022. A coherent Doppler lidar (CDL) system was employed to continuously detect three-dimensional wind fields. The results revealed that nocturnal ozone levels were enhanced by a conversion of sea–land breezes. Initially, the prevailing northerly land breeze transported high concentrations of O₃ and other air pollutants from downtown to the Yellow Sea. As the sea breeze developed in the afternoon, the sea breeze front advanced northward, resulting in a flow of high O₃ concentrations back into inland areas. This penetration of the sea breeze front led to a notable spike in O₃ concentrations between 16:00 on 22 July and 02:00 on 23 July across downtown areas, with an average increase of over 70 μg/m³ within 10 min. Notably, a time lag in peak O₃ concentration was observed with southern downtown areas peaking before northern rural areas. During this period, combined pollution of O₃ and PM_2.5 was also observed. These findings indicated that the nighttime increase in O₃ concentrations, coupled with enhanced atmospheric oxidation, would likely promote the secondary conversion of gaseous precursors into PM_2.5. Full article

Background/Objectives: Limited research had investigated nutritional status in patients with Cornelia de Lange Syndrome (CdLS) (OMIM 122470, 300590, 300882, 610759, 620568 and 614701). Body composition assessed via bioelectric impedance (BIA) is a particularly under-explored issue. In this cross-sectional study, we hypothesize that body composition imbalance is frequent in CdLS and may be associated with dysphagia. We aimed to determine dysphagia prevalence in CdLS. Dysphagia may be a sign or a complication of GERD (gastroesophageal reflux disease), which is the most frequent gastroenterological disorder in CdLS patients; Methods: Fourteen Polish patients with a clinical or genetic diagnosis of CdLS were included in the study. We performed body composition analysis via bioelectric impedance taking into account the phase angle (PhA) and Body Cell Mass (BCM) in patients who cooperated and were able to sit still. The patients’ caregivers completed the pediatric version of the Eating Assessment Tool (PEDI-EAT-10). Based on the questionnaire scoring, we divided the patients into dysphagic and non-dysphagic groups. Body compartments of those two groups were compared. Statistical correlations between PhA and the PEDI-EAT-10 score were calculated; Results: Eleven of the fourteen CdLS patients had abnormalities in the BIA analysis in terms of fat mass (FM), fat free mass (FFM) and skeletal muscle mass (SMM). Six patients had excessive FM and four patients were deficient in FM. Two had deficiency in FFM and two had excessive FFM. We noted prevalence of dysphagia at 28.57%, with four patients having an PEDI-EAT-10 score higher or equal to 3, categorized as dysphagic. The dysphagic and non-dysphagic groups were not significantly different in terms of the proportion of patients with FM, FFM, SMM and BCM in the small cohort presented here. A statistically significant inverse correlation was found between the PhA and PEDI-EAT-10 score (rho = −0.72; p = 0.003); Conclusions: CdLS patients require investigation for dysphagia and nutritional status imbalance, as they are both frequent in this syndrome. The most prevalent are abnormalities in FM, both excess and deficit. PhA deviations observed in the bioimpedance study deepen with the severity of dysphagia. These findings require further investigation in a larger cohort. Full article

This work synthesizes a xerogel from a sol–gel synthesis strategy and supports it on N-doped carbon support from spent coffee biomass (Mn(II)O/N-CC, hereafter MnO) as an efficient oxygen reduction reaction (ORR) catalyst in alkaline electrolytes. The effects of N-CC carbon content on MnO nanoparticle size, dispersion, distribution, morphology, and electrochemistry on ORR are discussed. The SEM and TEM measurements show that increasing the N-CC content during the MnO gelation reaction improved MnO dispersion and particle size during thermal treatment, increasing the ORR’s electrochemical active surface area. Several physiochemical and electrochemical characterizations show a clear relationship between N-CC catalysts and ORR activities. The best catalyst, MnO/N-CC-5, had an even distribution of 27 nm MnO nanoparticles on the N-CC support. The MnO/N-CC-5 catalyst had almost identical ORR kinetics and stability to those of the state-of-the-art Pt/C catalyst in 0.1 M KOH electrolytes, losing only 10 mV in half-wave potential after 5000 potential cycles and retaining 96% of current for over 10 h of continuous chronoamperometric stability. By measuring the electrochemical active surface areas of various catalysts by cyclic voltammetry at different scan rates and measuring the double layer capacitance (C_dl) and ECSA, MnO/N-CC-5 catalysts were shown to have enhanced ORR activity. The XPS analysis explains the ORR activity in terms of the Mn³⁺/Mn⁴⁺ ratio, and a mechanism was proposed. These findings suggest that the MnO/N-CC-5 catalyst could be a cathode catalyst in fuel cells, biofuel cells, metal–air batteries, and other energy conversion devices. Full article

In this paper, we propose a novel approach to the dictionary learning (DL) initialization problem, leveraging the SimCLR framework from deep learning in a self-supervised manner. Dictionary learning seeks to represent signals as sparse combinations of dictionary atoms, but effective initialization remains challenging. By applying contrastive learning, we encourage similar representations for augmented versions of the same sample while distinguishing between different samples. This results in a more diverse and incoherent set of atoms, which enhances the performance of DL applications in classification and anomaly detection tasks. Our experiments across several benchmark datasets demonstrate the effectiveness of our method for improving dictionary learning initialization and its subsequent impact on performance in various applications. Full article

The majority of plant viruses rely on insect vectors for inter-plant transmission. Amid virus transmission, vector-borne viruses such as begomoviruses may significantly modulate host plants in various ways and, in turn, plant palatability to insect vectors. While many case studies on monopartite begomoviruses are available, bipartite begomoviruses are understudied. More importantly, detailed elucidation of the molecular mechanisms involved is limited. Here, we report the mechanisms by which an emerging bipartite begomovirus, the Sri Lankan cassava mosaic virus (SLCMV), modulates plant defenses against whitefly. SLCMV infection of tobacco (Nicotiana tabacum) plants significantly downregulated defenses against whitefly, as whitefly survival and fecundity increased significantly on virus-infected plants when compared to the controls. We then profiled SLCMV-induced transcriptomic changes in plants and identified a repertoire of differentially expressed genes (DEGs). GO enrichment analysis of DEGs demonstrated that the term defense response was significantly enriched. Functional analysis of DEGs associated with defense response revealed that four downregulated DEGs, including putative late blight resistance protein homolog R1B-17 (R1B-17), polygalacturonase inhibitor-like (PGI), serine/threonine protein kinase CDL1-like (CDL1), and Systemin B, directly contributed to plant defenses against whitefly. Taken together, our findings elucidate the role of novel plant factors involved in the modulation of plant defenses against whitefly by a bipartite begomovirus and shed new light on insect vector–virus–host plant tripartite interactions. Full article