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We aimed to assess the epidemiological, clinical, and laboratory characteristics associated with mortality among hospitalized Egyptian patients with COVID-19. A multicenter, retrospective study was conducted on all polymerase chain reaction (PCR)-confirmed COVID-19 cases admitted through the period from April to July 2020. A generalized linear model was reconstructed with covariates based on predictor’s statistical significance and clinically relevance. The odds ratio (OR) was calculated by using stepwise logistic regression modeling. A total of 3712 hospitalized patients were included; of them, 900 deaths were recorded (24.2%). Compared to survived patients, non-survived patients were more likely to be older than 60 years (65.7%), males (53.6%) diabetic (37.6%), hypertensive (37.2%), and had chronic renal insufficiency (9%). Non-survived patients were less likely to receive azithromycin (p 60 years, comorbidities, tachycardia, hypoxemia, and altered consciousness level are independent predictors of mortality among Egyptian hospitalized patients with COVID-19. On the other hand, the use of anticoagulants and azithromycin is associated with reduced mortality.

Introduction The recent publication of a national guideline and quality standards in Canada have provided clinicians with new, evidence-based recommendations on safe, appropriate opioid use. We sought to characterize how well opioid initiation practices aligned with these recommendations before and following their release. Methods We conducted a population-based study among people initiating opioids prior to the release of national guidelines (April 2015—March 2016; fiscal year [FY] 2015) and in the most recent year available (January—December 2019) in Ontario, Canada. We used linked administrative claims data to ascertain the apparent indication for opioid therapy, and characterized the initial daily dose (milligrams morphine or equivalent; MME) and prescription duration for each indication. Results In FY2015, 653,885 individuals commenced opioids, compared to 571,652 in 2019. Over time, there were small overall reductions in the prevalence of initial daily doses exceeding 50MME (23.9% vs. 20.1%) and durations exceeding 7 days (17.4% vs. 14.8%); but the magnitude of the reductions varied widely by indication. The prevalence of high dose (>50MME) initial prescriptions reduced significantly across all indications, with the exception of dentist-prescribed opioids (13.6% vs. 12.1% above 50MME). In contrast, there was little change in initial durations exceeding 7 days across most indications, with the exception of some surgical indications (e.g. common excision; 9.3% vs. 6.2%) and among those in palliative care (35.2% vs. 29.2%). Conclusion Despite some modest reductions in initiation of high dose and long duration prescription opioids between 2015 and 2019, clinical practice is highly variable, with opioid prescribing practices influenced by clinical indication. These findings may help identify medical specialties well-suited to targeted interventions to promote safer opioid prescribing.

Diabetes is a chronic disease commonly managed by family physicians, with the most prevalent complication being cardiovascular disease (CVD). Clinical practice guidelines have been developed to support clinicians in the care of diabetic patients. We conducted a pragmatic cluster randomized controlled trial (RCT) of a printed educational toolkit aimed at improving CVD management in diabetes in primary care, and found no effect, and indeed, the possibility of some harm. We conducted a qualitative evaluation to study the strategy for guideline implementation employed in this trial, and to understand its effects. This paper focuses solely on the qualitative findings, as the RCT's quantitative results have already been reported elsewhere.All family practices in the province of Ontario had been randomized to receive the educational toolkit by mail, in either the summer of 2009 (intervention arm) or the spring of 2010 (control arm).A subset of 80 family physicians (representing approximately 10% of the practices randomized and approached, with records on 1,592 randomly selected patients with diabetes at high risk for CVD) then took part in a chart audit and reflective feedback exercise related to their own practice in comparison to the guideline recommendations. They were asked to complete two forms (one pre- and one post-audit) in order to understand their awareness of the guidelines pre-trial, their expectations regarding their individual performance pre-audit, and their reflections on their audit results. In addition, individual interviews with thirteen other family physicians were conducted. Textual data from interview transcripts and written commentary from the pre- and post-audit forms underwent qualitative descriptive analysis to identify common themes and patterns. Analysis revealed four main themes: impressions of the toolkit, awareness was not the issue, 'it's not me it's my patients', and chart audit as a more effective intervention than the toolkit. Participants saw neither the toolkit content nor its dissemination strategy to be effective, indicating they perceived themselves to be aware of the guidelines pre-trial. However, their accounts also indicated that they may be struggling to prioritize CVD management in the midst of competing demands for their attention. Upon receiving their chart audit results, many participants expressed surprise that they had not performed better. They reported that the audit results would be an important motivator for behaviour change.The qualitative findings outlined in this paper offer important insights into why the intervention was not effective. They also demonstrate that physicians have unperceived needs relative to CVD management and that the chart audit served to identify shortcomings in their practice of which they had been hitherto unaware. The findings also indicate that new methods of intervention development and implementation should be explored. This is important given the high prevalence of diabetes worldwide; appropriate CVD management is critical to addressing the morbidity and mortality associated with the disease.

IMPORTANCE:Without third-party insurance, access to marketed drugs is limited to those who can afford to pay. We examined this phenomenon in the context of anticoagulation for patients with nonvalvular atrial fibrillation (NVAF). OBJECTIVE:To determine whether, among older Ontarians receiving anticoagulation for NVAF, patients of higher socioeconomic status (SES) were more likely to switch from warfarin to dabigatran prior to its addition to the provincial formulary. DESIGN, SETTING AND PARTICIPANTS:Population-based retrospective cohort study of Ontarians aged 66 years and older, between 2008 and 2012. EXPOSURE:Socioeconomic status, as approximated by median neighborhood income. MAIN OUTCOMES AND MEASURE:We identified two groups of older adults with nonvalvular atrial fibrillation: those who appeared to switch from warfarin to dabigatran after its market approval but prior to its inclusion on the provincial formulary ("switchers"), and those with ongoing warfarin use during the same interval ("non-switchers"). RESULTS:We studied 34,797 patients, including 3183 "switchers" and 31,614 "non-switchers". We found that higher SES was associated with switching to dabigatran prior to its coverage on the provincial formulary (p

BACKGROUND:Smoking remains a serious public health concern. Pharmacotherapy for smoking cessation, including bupropion and varenicline, are proven means to increase quit rates. Post-marketing reports describing suicidal behaviours have raised concerns about the safety of varenicline. However, whether varenicline imparts a higher risk of suicide relative to bupropion remains uncertain. METHODS:A population-based nested case-control study in Ontario, Canada, from April 1, 2011 to March 31, 2015 was conducted. Subjects were residents of Ontario aged 18 years and older with publicly funded drug coverage receiving either bupropion or varenicline for smoking cessation. We defined cases were those with a hospitalization or emergency department visit for suicide or non-fatal self-harm within 90 days of treatment. For each case, we identified up to fifty controls from the same cohort matched on age, sex, history of self-harm, use of selected psychotropic medications, alcohol abuse and prior admission to a mental health unit. Adjusted odds ratio were used to compare the risk of suicide/self-harm of varenicline to bupropion. RESULTS:We identified 331 cases and 5,346 matched-controls. Following adjustment for potential confounders, we found that varenicline was not associated with an increased risk of suicide/self-harm relative to bupropion (adjusted odds ratio 1.15; 95% confidence interval 0.71 to 1.87). INTERPRETATION:Treatment with varenicline does not appear to significantly increase the risk of suicide or self-harm relative to bupropion.

The use of opioids for noncancer pain is widespread, and more than 16,000 die of opioid-related causes in the United States annually. The patients at greatest risk of death are those receiving high doses of opioids. Whether sex influences the risk of dose escalation or opioid-related mortality is unknown.We conducted a cohort study using healthcare records of 32,499 individuals aged 15 to 64 who commenced chronic opioid therapy for noncancer pain between April 1, 1997 and December 31, 2010 in Ontario, Canada. Patients were followed from their first opioid prescription until discontinuation of therapy, death from any cause or the end of the study period. Among patients receiving chronic opioid therapy, 589 (1.8%) escalated to high dose therapy and n = 59 (0.2%) died of opioid-related causes while on treatment. After multivariable adjustment, men were more likely than women to escalate to high-dose opioid therapy (adjusted hazard ratio 1.44; 95% confidence interval 1.21 to 1.70) and twice as likely to die of opioid-related causes (adjusted hazard ratio 2.04; 95% confidence interval 1.18 to 3.53). These associations were maintained in a secondary analysis of 285,520 individuals receiving any opioid regardless of the duration of therapy.Men are at higher risk than women for escalation to high-dose opioid therapy and death from opioid-related causes. Both outcomes were more common than anticipated.

Background and objectivesVitamin D deficiency and endothelial dysfunction are non-traditional risk factors for cardiovascular events in chronic kidney disease. Previous studies in chronic kidney disease have failed to demonstrate a beneficial effect of vitamin D on arterial stiffness, left ventricular mass and inflammation but none have assessed the effect of vitamin D on microcirculatory endothelial function.Study designWe conducted a randomised controlled trial of 38 patients with non diabetic chronic kidney disease stage 3-4 and concomitant vitamin D deficiency (ResultsTwenty patients received ergocalciferol and 18 patients received placebo. After 6 months, there was a significant improvement in the ergocalciferol group in both endothelium dependent microcirculatory vasodilatation after iontophoresis of acetylcholine (p = 0.03) and a reduction in tissue advanced glycation end products (p = 0.03). There were no changes in sublingual microcirculatory parameters. Pulse pressure (p = 0.01) but not aortic pulse wave velocity was reduced. There were no significant changes in bone mineral parameters, blood pressure or left ventricular mass index suggesting that ergocalciferol improved endothelial function independently of these parameters. In parallel experiments, expression of endothelial nitric oxide synthase and activity were increased in human endothelial cells in a dose dependent manner.ConclusionsErgocalciferol improved microcirculatory endothelial function in patients with chronic kidney disease and concomitant vitamin D deficiency. This process may be mediated through enhanced expression and activity of endothelial nitric oxide synthase.Trial registrationClinical trials.gov NCT00882401.

Recent evidence suggests that proton pump inhibitors (PPIs) might be linked with adverse cardiac events, but a causal relationship is unproven.We applied the self-matched case series method to two studies using population-based health care data from Ontario, Canada between 1996 and 2008. The first included subjects aged 66 years or older hospitalized for acute myocardial infarction within 12 weeks following initiation of PPI, while the second included subjects hospitalized for heart failure. In both studies we designated the primary risk interval as the initial 4 weeks of therapy and the control interval as the final 4 weeks. To test the specificity of our findings we examined use of histamine H2 receptor antagonists and benzodiazepines, drugs with no plausible causal link to adverse cardiac events.During the 13-year study period, we identified 5550 hospital admissions for acute myocardial infarction and 6003 admissions for heart failure within 12 weeks of commencing PPI therapy. In the main analyses, we found that initiation of a PPI was associated with a higher risk of acute myocardial infarction (odds ratio 1.8; 95% confidence interval 1.7 to 1.9) and heart failure (odds ratio 1.8; 95% confidence interval 1.7 to 1.9). However, secondary analyses revealed similar risk estimates histamine H2 receptor antagonists and benzodiazepines, drugs with no known or suspected association with adverse cardiac events.PPIs are associated with a short-term risk of adverse cardiac events, but similar associations are seen with other drugs exhibiting no known cardiac toxicity. Collectively these observations suggest that the association between PPIs and adverse cardiac events does not represent reflect cause-and-effect.

Strains from a collection of Drosophila GFP protein trap lines express GFP in the normal tissues where the endogenous protein is present. This collection can be used to screen for proteins distributed in the nucleus in a non-uniform pattern.We analyzed four lines that show peripheral or punctate nuclear staining. One of these lines affects an uncharacterized gene named CG11138. The CG11138 protein shows a punctate distribution in the nuclear periphery similar to that of Drosophila insulator proteins but does not co-localize with known insulators. Interestingly, mutations in Lamin proteins result in alterations in CG11138 localization, suggesting that this protein may be a novel component of the nuclear lamina. A second line affects the Decondensation factor 31 (Df31) gene, which encodes a protein with a unique nuclear distribution that appears to segment the nucleus into four different compartments. The X-chromosome of males is confined to one of these compartments. We also find that Drosophila Nucleoplasmin (dNlp) is present in regions of active transcription. Heat shock leads to loss of dNlp from previously transcribed regions of polytene chromosome without redistribution to the heat shock genes. Analysis of Stonewall (Stwl), a protein previously found to be necessary for the maintenance of germline stem cells, shows that Stwl is present in a punctate pattern in the nucleus that partially overlaps with that of known insulator proteins. Finally we show that Stwl, dNlp, and Df31 form part of a highly interactive network. The properties of other components of this network may help understand the role of these proteins in nuclear biology.These results establish screening of GFP protein trap alleles as a strategy to identify factors with novel cellular functions. Information gained from the analysis of CG11138 Stwl, dNlp, and Df31 sets the stage for future studies of these proteins.

Modern dialogue systems rely on emotion recognition in conversation (ERC) as a core element enabling empathetic and human-like interactions. However, the weak correlation between emotions and semantics poses significant challenges to emotion recognition in dialogue. Semantically similar utterances can express different types of emotions, depending on the context or speaker. In order to tackle this challenge, our paper proposes a novel loss called Focal Weighted Loss (FWL) with adversarial training and the compact language model MobileBERT. Our proposed loss function handles the problem of imbalanced emotion classification through Focal Weighted Loss and adversarial training and does not require large batch sizes or more computational resources. Our approach has been employed on four text emotion recognition benchmark datasets, MELD, EmoryNLP, DailyDialog and IEMOCAP demonstrating competitive performance. Extensive experiments on these benchmark datasets validate the effectiveness of our proposed FWL with adversarial training. This enables more human-like interactions on digital platforms. Our approach shows its potential to deliver competitive performance under limited resource constraints, comparable to large language models., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Hussain et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Pomegranate peel powder is used as a functional ingredient in the development of nutritional bars. Pomegranate (Punica granatum) is well known fruit belongs to punicaceae family having multiple health benefits, not only limited to its edible parts but also in its non-edible parts mostly the peel. Fruit wastes are rich source of nutrients, and can be used for the development of functional food products. Pomegranate peel is considered to be beneficial due to its functional and therapeutic properties as it is a source of many biological active components like polyphenols, tannins and flavonoids. Nutrient rich and ready-made foods are the demand of everyone due to their easy availability and cost effectiveness. Among the confectionary products, bars are liked by individuals of different age groups. Hence, nutritional properties of bars can be enhanced by using pomegranate peel powder. The current study was designed to develop bars enriched with pomegranate peel powder as a basic ingredient. Pomegranate peel powder is prepared and analyzed for proximate, mineral, total phenolic content, total flavonoid content and anti-oxidant potential (DPPH). By using pomegranate peel powder, oats and jaggery, bars were prepared. In this research, five treatments T0 (0% pomegranate peel powder and 100% oats). T1 (5% pomegranate peel powder and 95% oats), T2 (10% pomegranate peel powder and 90% oats), T3 (15% pomegranate peel powder and 85% oats) and T4 (20% pomegranate peel powder and 80% oats) were used. The developed product is analyzed for proximate, mineral, total flavonoid contents, total phenolic content and anti-oxidant potential (DPPH). Proximate analysis of bars revealed that moisture, protein, fat, fiber, ash and nitrogen free extract ranges from T0 to T4 (13.38±1.21 to 11.32±1.15, 9.56±0.92 to 8.32±1.14, 9.05±1.21 to 7.93±1.08, 5.23±0.82 to 16.89±0.64, 2.05±0.87 to 2.92±1.25 and 62.51±0.85 to 52.62±0.93 respectively. Phytochemical analysis of bars enriched with pomegranate peel powder revealed that total phenolic content, total flavonoid content and antioxidant potential of bars ranges from T0 to T4 (142.74±0.65 to 211.79±0.63 mg GAE/100g, 129.16±0.64 to 192±0.53 mg QE/100g and 41.35±0.82 to 64.57±0.69%) respectively. Mineral analysis of bars enriched with pomegranate peel powder revealed that calcium, Phosphorus, Potassium, Iron, Magnesium content ranged from T0 to T4 (25.42±0.63 to 31.06±0.58, 51.00±1.01 to 45.05±1.09, 59.46±1.13 to 79.15±0.28, 1.32±1.20 to 1.95±0.83 and 54.17±0.88±0.58 to 57.36±0.68 mg/100g respectively). Sensory evaluation is done for color, aroma, taste, texture overall acceptability. T3 got maximum score. Then, the data obtained were evaluated by CRD design. On the basis of results revealed that treatment T3 with 15% pomegranate peel powder was overall highly acceptable., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Abbas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In human activity-recognition scenarios, including head and entire body pose and orientations, recognizing the pose and direction of a pedestrian is considered a complex problem. A person may be traveling in one sideway while focusing his attention on another side. It is occasionally desirable to analyze such orientation estimates using computer-vision tools for automated analysis of pedestrian behavior and intention. This article uses a deep-learning method to demonstrate the pedestrian full-body pose estimation approach. A deep-learning-based pre-trained supervised model multi-branched deep learning pose net (MBDLP-Net) is proposed for estimation and classification. For full-body pose and orientation estimation, three independent datasets, an extensive dataset for body orientation (BDBO), PKU-Reid, and TUD Multiview Pedestrians, are used. Independently, the proposed technique is trained on dataset CIFAR-100 with 100 classes. The proposed approach is meticulously tested using publicly accessible BDBO, PKU-Reid, and TUD datasets. The results show that the mean accuracy for full-body pose estimation with BDBO and PKU-Reid is 0.95%, and with TUD multiview pedestrians is 0.97%. The performance results show that the proposed technique efficiently distinguishes full-body poses and orientations in various configurations. The efficacy of the provided approach is compared with existing pretrained, robust, and state-of-the-art methodologies, providing a comprehensive understanding of its advantages., Competing Interests: NO authors have competing interests., (Copyright: © 2025 Shahid et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Mushrooms are considered one of the safe and effective medications because they have great economic importance due to countless biological properties. Cordyceps militaris contains bioactive compounds with antioxidant, antimicrobial and anti-cancerous properties. This study was projected to analyze the potentials of biometabolites and to extract antimicrobial peptides and protein from the C. militaris. An in-vitro analysis of biometabolites and antimicrobial peptides was performed to investigate their pharmacological potentials followed by quantification and characterization of extracted protein. Computational analysis on non-small cell lung cancer genes (NSCLC) was performed on quantified compounds to interpret the biometabolites from C. militaris that could be potential drug candidate molecules with high specificity and potency. A total of 34 compounds representing 100% of total detected constituents identified were identified using GCMS analysis and 20 compounds using LC-MS which showed strong biological activities. FT-IR spectroscopy manifest powerful instant peaks to have different bioactive components including carboxylic acid, phenols, amines and alkanes present in methanolic extract of C. militaris. In C. militaris, higher protein concentration was observed in 70% concentration of protein extract (500 μg/ml ± 0.025). The best antioxidant activity (% Radical scavenging activity) of methanolic extracts was 80a ± 0.03, antidiabetic activity was 37 ± 0.057 and anti-inflammatory activity was 40 ± 0.021 at 12 mg/ml. Antibacterial activity for different concentrations of Cordyceps protein and methanolic extracts was significantly (p < 0.05). Indolizine, 2-(4-methylphenyl) has most binding affinity (micromolar) and optimized properties to be selected as the lead inhibitor. It interacts favorably with the active site of RET gene of NSCLC and is neuroprotective and hepatoprotective., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Afzal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Citrus farming is one of the major agricultural sectors of Pakistan and currently represents almost 30% of total fruit production, with its highest concentration in Punjab. Although economically important, citrus crops like sweet orange, grapefruit, lemon, and mandarins face various diseases like canker, scab, and black spot, which lower fruit quality and yield. Traditional manual disease diagnosis is not only slow, less accurate, and expensive but also relies heavily on expert intervention. To address these issues, this research examines the implementation of an automated disease classification system using deep learning and optimal feature selection. The system incorporates data augmentation and transfer learning with pre-trained models such as DenseNet-201 and AlexNet to improve diagnostic accuracy, efficiency, and cost-effectiveness. Experimental results on a citrus leaves dataset show an impressive 99.6% classification accuracy. The proposed framework outperforms existing methods, offering a robust and scalable solution for disease detection in citrus farming, contributing to more sustainable agricultural practices., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Butt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Topological indices are crucial tools for predicting the physicochemical and biological features of different drugs. They are numerical values obtained from the structure of chemical molecules. These indices, particularly the degree-based TIs are a useful tools for evaluating the connection between a compound's structure and its attributes. This study addresses the research problemof how to optimize drug design for HIV treatment using degree-based topological indices. The need for safer and more effective medicines for HIV is further emphasized by the advent of drug resistance and severe negative effects from current therapies. Employing degree-based graph invariants, the study investigates 13 HIV drugs by applying a quantitative structure-property relationship (QSPR) technique to associate their molecular structures with their physical properties. HIV drugs are ranked using the Analytic Hierarchy Process (AHP) according to specific parameters. The findings of the study demonstrate how well these approaches can determine the most effective possible drug combinations and designs, offering insightful information in developing improved HIV treatments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Farooq et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Smallholder farmers produce over 40% of global palm oil, the world's most traded and controversial vegetable oil. Awareness of the effects of palm oil production on ecosystems and human communities has increased drastically in recent years, with ever louder calls for the private and public sector to develop programs to support sustainable cultivation by smallholder farmers. To effectively influence smallholder practices and ensure positive social outcomes, such schemes must consider the variety in perspectives of farmers and align with their priorities. We conducted social surveys on smallholder farmers in Indonesia and Malaysia with varying degrees of participation in programs that offer advice and support with plantation management ("management-assistance programs") led by an industrial palm oil producer in Indonesia and a conservation-focused NGO in Malaysia. We surveyed farmers on their demographics, attitudes, and management decisions. Our analyses act as case studies to investigate the similarities and differences between smallholder palm oil producers involved in different schemes, allowing us to determine the alignment between the intentions of partnership programs and the current realities of smallholder plantations. The relationship between heterogeneity of social factors and management decisions and degree of program involvement differed across different groups and region: Indonesian smallholders most closely partnered with the private sector were the most varied in socio-demographics and attitudes but showed little variation in management inputs, while Malaysian smallholders most closely partnered with an NGO were the most heterogenous across all survey sections. Specifically, Indonesian farmers partnered with the private sector used less herbicide, more fertilizer, and had higher yield and total household income than farmers completely uninvolved with management assistance programs. In Malaysia, farmers partnered with an NGO also had higher yield and fertilizer application than independent farmers, however they used significantly more herbicide and had lower total household income. Our findings demonstrate the wide variety of smallholder farmers in both regions, directly opposing a 'one-size-fits-all' approach to sustainability. The wide variety of existing management practices also provides a potentially valuable natural experiment to identify high-yield, environmentally-friendly management approaches. When taken in context, our findings may inform the interventions of management-assistance programs, ensuring they are approaching the most relevant farmer groups in the most effective way., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Reiss-Woolever et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Extensive research work has been done for the estimation of population mean using bivariate auxiliary information based on conventional measures. Conventional measures of the auxiliary variables provide suspicious results in the presence of outliers/extreme values. However, non-conventional measures of the auxiliary variables include quartile deviation, mid-range, inter-quartile range, quartile average, tri-mean, Hodge-Lehmann estimator etc. give efficient results in case of extreme values. Unfortunately, non-conventional measures are not used by survey practitioners to enhance the estimation of unknown population parameters using bivariate auxiliary information. In this article, difference-cum-exponential-type estimators for population mean utilizing bivariate auxiliary information based on non-conventional measures under simple and stratified random sampling schemes have been suggested. Mathematical properties such as bias and mean squared error are derived. To support theoretical findings, various real-life applications are used to confirm the superiority of the suggested estimators as compared to the competing estimators under study., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Javed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Streptococcus pneumoniae (SPN) is a significant pathogen causing pneumonia and meningitis, particularly in vulnerable populations like children and the elderly. Available pneumonia vaccines have limitations since they only cover particular serotypes and have high production costs. The emergence of antibiotic-resistant SPN strains further underscores the need for a new, cost-effective, broad-spectrum vaccine. Two potential vaccine candidates, CbpA and PspA, were identified, and their B-cell, CTL, and HTL epitopes were predicted and connected with suitable linkers, adjivant and PADRE sequence. The vaccine construct was found to be antigenic, non-toxic, non-allergenic, and soluble. The three-dimensional structure of the vaccine candidate was built and validated. Docking analysis of the vaccine candidate by ClusPro demonstrated robust and stable binding interactions between the MEV and toll-like receptor 4 in both humans and animals. The iMOD server and Amber v.22 tool has verified the stability of the docking complexes. GenScript server confirmed the high efficiency of cloning for the construct and in-silico cloning into the pET28a (+) vector using SnapGene, demonstrating successful translation of the epitope region. Immunological responses were shown to be enhanced by the C-IMMSIM server. This study introduced a strong peptide vaccine candidate that has the potential to contribute to the development of a rapid and cost-effective solution for combating SPN. However, experimental verification is necessary to evaluate the vaccine's effectiveness., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Nahian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the aforementioned diseases can be cured. Consequently, diagnostic identification and management of the patient at this level becomes a rather enormous task. This paper offers a cutting-edge hybrid deep learning approach of better segmentation and classification of skin lesions. The proposed method incorporates three key stages: preprocessing, segmentation of lesions, and classification of lesions. By the stage of preprocessing, a morphology-based technique takes out hair so as to enhance the segmentation precision to use the cleansed images for subsequent analysis. Segmentation cuts off the lesion from the surrounding skin, giving the classification phase a dedicated area of interest and the ability to clear the background noise that may affect classification rates. The isolation enables the model to better analyze anatomical lesion features in order to achieve accurate benign and malignant classifications. Using ResUNet++, the cutting-edge deep learning architecture, we achieved accurate lesion segmentation. Next, we will modify and use an AlexNet-Random Forest (AlexNet-RF) based classifier for robust lesion classification. The proposed hybrid deep learning model is intensively validated on the Ham10000 data set which is one of the most popular datasets for skin lesions analysis. The obtained results show that the utilized approach, compared to the previous ones, is more effective, giving better segmentation and classification results. This method takes advantage of ResUNet++ strong classification skill and modified AlexNet-Random Forest robustness for more accurate segmentation. There is a high probability that ResUNet++, which is highly proficient at medical image segmentation, can produce better segmentation of lesions than the simpler models. The composition of AlexNet's extraction of features with Random Forest ability to reduce overfitting possibly may be more precise in the classification when compared to using only one model., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Mustafa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Nutritional status being the first line of defense for host plants, determines their susceptibility or resistance against invading pathogens. In recent years, the applications of plant nutrient related products have been documented as one of the best performers and considered as alternatives or/and supplements in plant disease management compared to traditional chemicals. However, knowledge about application of plant nutrient related products for the management of destructive fungal pathogen Fusarium oxysporum f.sp. capsici and their impact on the components of the antioxidant defense system, especially in chilli plants, still needs to be discovered. Therefore, in this current study, we aimed to evaluate two nutrient fertilizers viz. Krystafeed and Micro Plus at three different concentrations by soil drenching method for their effects against the Fusarium wilt of chilli and investigate the components of the antioxidant defense system of chilli plants. Correlation and computational analysis on the components of antioxidant defense system in various pathways were performed to predict the suitable binding sites of mineral ions. Results indicated that the combination of Krystafeed and Micro Plus was found the most effective with (27.01, 26.59%) disease incidence, followed by Micro Plus (29.56, 32.35%) and Krystafeed (38.21, 41.15%), both in greenhouse and field conditions, respectively. Moreover, the combination of Krystafeed and Micro Plus significantly increased the concentration of SOD (27.53, 108.96)%, POD (37.29, 45.65)%, CAT (19.33, 95.33)%, H2O2 (22.13, 118.98)%, TPC (27.39, 17.37)%, chlorophyll a (21.80, 35.74)%, chlorophyll b (57.57, 18.25)%, total chlorophyll (30.21, 19.83)%, Tocopherol (13.08, 33.66)%, TrxR (5.03, 36.56)%, MDA (13.84, 54.79)%, ascorbate (4.72, 17.28)%, Proline (5.94, 59.31)%, and phytoalexin (Capsidiol) (11.33, 55.08)% in the treated plants of resistant and susceptible chilli varieties, respectively, as compared to the untreated plants. Pearson's correlation heat-map analysis showed that all the enzymes of antioxidant defense system were found positively correlated with each other. It is concluded that the improvement of crop resistance by the application of plant nutrient related products may be viable alternatives to synthetic chemicals for managing Fusarium wilt disease of chilli and potentially other pathogens., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Usman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In biology and life sciences, fractal theory and fractional calculus have significant applications in simulating and understanding complex problems. In this paper, a compartmental model employing Caputo-type fractional and fractal-fractional operators is presented to analyze Nipah virus (NiV) dynamics and transmission. Initially, the model includes nine nonlinear ordinary differential equations that consider viral concentration, flying fox, and human populations simultaneously. The model is reconstructed using fractional calculus and fractal theory to better understand NiV transmission dynamics. We analyze the model's existence and uniqueness in both contexts and instigate the equilibrium points. The clinical epidemiology of Bangladesh is used to estimate model parameters. The fractional model's stability is examined using Ulam-Hyers and Ulam-Hyers-Rassias stabilities. Moreover, interpolation methods are used to construct computational techniques to simulate the NiV model in fractional and fractal-fractional cases. Simulations are performed to validate the stable behavior of the model for different fractal and fractional orders. The present findings will be beneficial in employing advanced computational approaches in modeling and control of NiV outbreaks., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The adoption of Financial Technology (FinTech), along with the enhancement of Human Resource (HR) competencies, service innovation, and firm growth, plays a crucial role in the development of the banking sector. Despite their importance, obtaining reliable results is often challenging due to the complex, high-dimensional correlations among various features that affect the industry. To address this issue, this research introduces a hybrid Multi-Criteria Decision-Making (MCDM) model that integrates the Entropy-Weighted Method (EWM) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The primary objective of this study is to systematically evaluate and rank multiple alternatives based on key criteria using the EWM-TOPSIS approaches. Specifically, the analysis considers eleven multifaceted characteristics and eight potential alternatives (A1 to A8), revealing the significant influence of the proposed MCDM approaches in assessing FinTech adoption, HR competency, service innovation, and firm growth. The findings underscore the effectiveness of the entropy-TOPSIS approaches in providing a structured analysis for a smarter and well-informed decision-making. Ultimately, this research proposes the best alternative from the evaluated options, contributing valuable insights into the future role of FinTech, HR competencies, service innovation, and firm growth within the banking sector., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Khan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Lumpy skin disease (LSD) is an emerging, highly contagious transboundary disease of bovines caused by the Lumpy skin disease virus (LSDV), responsible for substantial economic losses to the dairy, meat, and leather industries in Pakistan as well as various countries around the world. Epidemiological information on LSD is scarce in Punjab, Pakistan. Therefore, a molecular epidemiological study was conducted in two agro-ecologically diverse districts (Bhakkar and Jhang) of Punjab, Pakistan. A total of 800 blood samples were randomly collected from the jugular vein of clinically suspected cattle with nodular lesions using a multistage cluster sampling technique. The sampling unit was indigenous, crossbred, and exotic breeds of cattle. Four hundred samples were collected from each district. Ten union councils (UC) were selected from each district, and two villages were selected from each union council. From each village, twenty cattle were selected for sample collection. The PCR-based overall prevalence of LSDV in clinically suspected cattle using the P32 gene was 36.25% (36.25%; 290/800). The multivariable logistic regression analysis indicated that animals who were not treated with acaricide (P = 0.014; OR = 1.459; C.I = 1.079-1.972), body condition score (emaciated animals; P = 0.019; OR = 1.573; CI = 1.076-2.301), and gender (female; (P = 0.016; OR = 1.435; CI = 1.072-1.969) were significantly at higher risk for LSDV infection in cattle. The phylogenetic insights revealed that our isolates were linked to Kenya, China, Russia, Egypt, India, Zimbabwe, Iraq, and Iran. It can be concluded that LSD is widely distributed in the study area, with evidence of genetic diversity. Further studies are required on genetic composition using variable genetic markers for effective control and eradication of LSDV in Pakistan., Competing Interests: Authors declare no competing interest., (Copyright: © 2025 Jabbar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The global public health risk posed by Salmonella Kentucky (S. Kentucky) is rising, particularly due to the dissemination of antimicrobial resistance genes in human and animal populations. This serovar, widespread in Africa, has emerged as a notable cause of non-typhoidal gastroenteritis in humans. In this study, we used a bioinformatics approach to develop a peptide-based vaccine targeting epitopes from the outer membrane proteins A, C, and F of S. Kentucky. Additionally, we employed flagellin protein (fliC) from Salmonella Typhimurium (S. Typhimurium) as an adjuvant to enhance the vaccine's effectiveness. Through this approach, we identified 14 CD8+ and 7 CD4+ T-cell epitopes, which are predicted to be restricted by various MHC class I and MHC class II alleles. The predicted epitopes are expected to achieve a population coverage of 94.91% when used in vaccine formulations. Furthermore, we identified seven highly immunogenic linear B-cell epitopes and three conformational B-cell epitopes. These T-cell and B-cell epitopes were then linked using appropriate linkers to create a multi-epitope vaccine (MEV). To boost the immunogenicity of the peptide construct, fliC from S. Typhimurium was included at the N-terminal. The resulting MEV construct demonstrated high structural quality and favorable physicochemical properties. Molecular docking studies with Toll-like receptors 1, 2, 4, and 5, followed by molecular dynamic simulations, suggested that the vaccine-receptor complexes are energetically feasible, stable, and robust. Immune simulation results showed that the MEV elicited significant responses, including IgG, IgM, CD8+ T-cells, CD4+ T-cells, and various cytokines (IFN-γ, TGF-β, IL-2, IL-10, and IL-12), along with a noticeable reduction in antigen levels. Despite these promising in-silico findings, further validation through preclinical and clinical trials is required to confirm the vaccine's efficacy and safety., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Igomu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: JE, CR, PS, PG, and DJP are GSK employees and hold GSK stock. CC is a member of the advisory board of Vivid Genomics and Circular Genomics and owns stocks. MA has nothing to report., (Copyright: © 2025 Euesden et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Controlled-release microparticles offer a promising avenue for enhancing patient compliance and minimizing dosage frequency. In this study, we aimed to design controlled-release microparticles of Glipizide utilizing Eudragit S100 and Methocel K 100 M polymers as controlling agents. The microparticles were fabricated through a simple solvent evaporation method, employing various drug-to-polymer ratios to formulate different controlled-release batches labeled as F1 to F5. Evaluation of the microparticles encompassed a range of parameters including flow properties, particle size, morphology, percentage yield, entrapment efficiencies, percent drug loading, and dissolution studies. Additionally, various kinetic models were employed to elucidate the drug release mechanism. Furthermore, difference and similarity factors were utilized to compare the dissolution profiles of the tested formulations with a reference formulation. The compressibility index and angle of repose indicated favorable flow properties of the prepared microparticles, with values falling within the range of 8 to 10 and 25 to 29, respectively. The particle size distribution of the microparticles ranged from 95.3 to 126 μm. Encouragingly, the microparticles exhibited high percent yield (ranging from 66 to 77%), entrapment efficiency (80 to 96%), and percent drug loading (46 to 54%). All formulated batches demonstrated controlled drug release profiles extending up to 12 hours, with glipizide release following an anomalous non-Fickian diffusion pattern. However, the drug release profiles of the reference formulation and various polymeric microparticles did not meet the acceptable limits of difference and similarity factors. In-vivo studies revealed sustained hypoglycemic effects over a 12-hour period, indicating the efficacy of the controlled-release microparticles. Overall, our findings suggest the successful utilization of polymeric materials in designing controlled-release microparticles, thereby reducing dosage frequency and potentially improving patient compliance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Rasheed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)