Post-discharge spirometry evaluation in patients recovering from moderate-to-critical COVID-19: a cross-sectional study.

Understanding the prevalence of abnormal lung function and its associated factors among patients recovering from COVID-19 is crucial for enhancing post-COVID care strategies. This study primarily aimed to determine the prevalence and types of spirometry abnormalities among post-COVID-19 patients in Malaysia, with a secondary objective of identifying its associated factors. Conducted at the COVID-19 Research Clinic, Faculty of Medicine, University Technology MARA, from March 2021 to December 2022, this study included patients at least three months post-discharge from hospitals following moderate-to-critical COVID-19. Of 408 patients studied, abnormal spirometry was found in 46.8%, with 28.4% exhibiting a restrictive pattern, 17.4% showing preserved ratio impaired spirometry (PRISm), and 1.0% displaying an obstructive pattern. Factors independently associated with abnormal spirometry included consolidation on chest X-ray (OR 8.1, 95% CI 1.75-37.42, p = 0.008), underlying cardiovascular disease (OR 3.5, 95% CI 1.19-10.47, p = 0.023), ground-glass opacity on chest X-ray (OR 2.6, 95% CI 1.52-4.30, p < 0.001), and oxygen desaturation during the 6-min walk test (OR 1.9, 95% CI 1.20-3.06, p = 0.007). This study highlights that patients recovering from moderate-to-critical COVID-19 often exhibit abnormal spirometry, notably a restrictive pattern and PRISm. Routine spirometry screening for high-risk patients is recommended.

In vivo biological screening of extract and bioactive compound from Ficus benghalensis L. and their in silico molecular docking analysis.

BACKGROUND: Ficus benghalensis has been used by local health care practitioners to treat pain, inflammation, rheumatism, and other health issues. OBJECTIVE: In this study, the crude extract and diverse fractions, along with the isolated compound of F. benghalensis were examined for their roles as muscle relaxants, analgesics, and sedatives. METHODS: The extract and isolated compound 1 were screened for muscle-relaxant, analgesic, and sedative actions. The acetic acid-mediated writhing model was utilized for analgesic assessment, the muscle relaxant potential was quantified through traction and inclined plan tests, and the open field test was applied for sedative effects. RESULTS: The extract/fractions (25, 50, and 100 mg/kg) and isolated compounds (2.5, 5, 10, and 20 mg/kg) were tested at various doses. A profound (p< 0.001) reduce in the acetic acid-mediated writhing model was observed against carpachromene (64.44%), followed by ethyl acetate (60.67%) and methanol (58.42%) fractions. A marked (p< 0.001) muscle relaxant activity was noticed against the isolated compound (71.09%), followed by ethyl acetate (66.98%) and methanol (67.10%) fractions. Regarding the sedative effect, a significant action was noted against the isolated compound (71.09%), followed by ethyl acetate (66.98%) and methanol (67.10%) fractions. Furthermore, the binding modes of the isolated compounds were explored using molecular docking. The molecular docking study revealed that the isolated compound possessed good binding affinity for COX2 and GABA. Our isolated compound may possess inhibitory activity against COX2 and GABA receptors. CONCLUSION: The extract and isolated compounds of Ficus benghalensis can be used as analgesics, muscle relaxants, and sedatives. However, detailed molecular and functional analyses are essential to ascertain their function as muscle relaxants, analgesics, and sedatives.

Massive Hemoptysis: An Unusual Complication of Left Atrial Appendage Occlusion Device in Two Patients.

Left atrial appendage occlusion (LAAO) devices have emerged as a promising alternative for stroke prevention in non-valvular atrial fibrillation (NVAF) patients with contraindications to chronic anticoagulation therapy. The most common life-threatening procedural complications described in the literature include pericardial effusion, air embolism, and stroke. We here present a case report of two patients who experienced identical but rare post-procedural complications of pulmonary venous bleed, presenting as hemoptysis.

Evaluation of Antimicrobial and Antioxidant Potential of Oxalis corymbosa Extracts.

This work aimed to assess the antioxidant and antimicrobial properties of Oxalis corymbosa extracts. Biochemical analyses were conducted on various plant parts, utilizing enzymatic and non-enzymatic assays. Parameters such as total soluble protein, chlorophyll, and carotenoid contents were also evaluated to elucidate the role of bioactive chemical compounds. The antimicrobial screening of extracts was performed against the bacterial and fungal strains Escherichia coli, Staphylococcus aureus, and Candida albicans, respectively. Results indicated that chlorophyll a, chlorophyll b, total chlorophyll, carotenoid content, anthocyanin content, catalase, peroxidase, and superoxide dismutase were most abundant in the O. corymbosa leaves. Moreover, total ascorbate peroxidase content, total phenolic content, and total flavonoid content were found to be higher in the roots compared to other parts. High-performance liquid chromatography analysis identified chlorogenic acid as the major component, followed by gallic acid, caffeic acid, quercetin, and salicylic acid. Regarding antibacterial potential, each extract exhibited significant activity, with methanolic and ethyl acetate extracts demonstrating the maximum inhibition zone against S. aureus and E. coli, respectively. These findings highlight the substantial antioxidant and antibacterial potential of different parts of O. corymbosa, suggesting their promising applications as ingredients in various nutraceutical products.

Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective.

The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN-based models in WWTPs, focusing on the latest published research work, by presenting the effectiveness of ANNs in predicting, estimating, and treatment of diverse types of wastewater. Furthermore, this review comprehensively examines the applicability of the ANNs in various processes and methods used for wastewater treatment, including membrane and membrane bioreactors, coagulation/flocculation, UV-disinfection processes, and biological treatment systems. Additionally, it provides a detailed analysis of pollutants viz organic and inorganic substances, nutrients, pharmaceuticals, drugs, pesticides, dyes, etc., from wastewater, utilizing both ANN and ANN-based models. Moreover, it assesses the techno-economic value of ANNs, provides cost estimation and energy analysis, and outlines promising future research directions of ANNs in wastewater treatment. AI-based techniques are used to predict parameters such as chemical oxygen demand (COD) and biological oxygen demand (BOD) in WWTP influent. ANNs have been formed for the estimation of the removal efficiency of pollutants such as total nitrogen (TN), total phosphorus (TP), BOD, and total suspended solids (TSS) in the effluent of WWTPs. The literature also discloses the use of AI techniques in WWT is an economical and energy-effective method. AI enhances the efficiency of the pumping system, leading to energy conservation with an impressive average savings of approximately 10%. The system can achieve a maximum energy savings state of 25%, accompanied by a notable reduction in costs of up to 30%.

Unveiling potent inhibitors for schistosomiasis through ligand-based drug design, molecular docking, molecular dynamics simulations and pharmacokinetics predictions.

Schistosomiasis is a neglected tropical disease which imposes a considerable and enduring impact on affected regions, leading to persistent morbidity, hindering child development, diminishing productivity, and imposing economic burdens. Due to the emergence of drug resistance and limited management options, there is need to develop additional effective inhibitors for schistosomiasis. In view of this, quantitative structure-activity relationship studies, molecular docking, molecular dynamics simulations, drug-likeness and pharmacokinetics predictions were applied to 39 Schistosoma mansoni Thioredoxin Glutathione Reductase (SmTGR) inhibitors. The chosen QSAR model demonstrated robust statistical parameters, including an R2 of 0.798, R2adj of 0.767, Q2cv of 0.681, LOF of 0.930, R2test of 0.776, and cR2p of 0.746, confirming its reliability. The most active derivative (compound 40) was identified as a lead candidate for the development of new potential non-covalent inhibitors through ligand-based design. Subsequently, 12 novel compounds (40a-40l) were designed with enhanced anti-schistosomiasis activity and binding affinity. Molecular docking studies revealed strong and stable interactions, including hydrogen bonding, between the designed compounds and the target receptor. Molecular dynamics simulations over 100 nanoseconds and MM-PBSA free binding energy (ΔGbind) calculations validated the stability of the two best-designed molecules. Furthermore, drug-likeness and pharmacokinetics prediction analyses affirmed the potential of these designed compounds, suggesting their promise as innovative agents for the treatment of schistosomiasis.

Cu-nanoparticles enhance the sustainable growth and yield of drought-subjected wheat through physiological progress.

Drought stress (DS) is a significant abiotic stress that limits agricultural productivity worldwide. In semi-arid climates, one potential solution to alleviate the deleterious effects of drought is the use of soil amendments such as nanoparticles. The current research was conducted out to probe the sway of drought at critical growth stages (CGS) of wheat crop (D0: Control, D1: Drought at tillering stage, and D2: Drought at anthesis stage) and the application of Cu-nanoparticles (T0: 0 mg L-1, T1: 300 mg L-1, T2: 700 mg L-1, and T3: 950 mg L-1) in order to improve drought resilience. Results of the study revealed that DS considerably decreased the wheat growth and yield during CGS. However, Cu-nanoparticles application alleviated the detrimental backlash of DS and led to improvements in various aspects of wheat growth and yield, including plant height, spike length, 1000 grain weight, stomatal conductance, leaf chlorophyll content, water use efficiency, leaf turgor potential, relative water content, and ultimately the grain yield. The use of principal component analysis allowed us to integrate and interpret the diverse findings of our study, elucidating the impact of Cu-nanoparticle treatment on wheat growth and yield under drought. Overall, the study concluded that DS during the anthesis stage had the most significant negative impact on crop yield. However, applying Cu-nanoparticles at the rate of 300 mg L-1 proved to be an effective strategy for improving crop productivity by reducing the harmful effects of drought.

Gender, culture, and migration: A qualitative study of the socioeconomic challenges facing Afghan women refugees in Khyber Pakhtunkhwa, Pakistan.

The research explores Afghan refugee women's challenges in accessing education, employment, and legal rights in Khyber Pakhtunkhwa, Pakistan. It seeks to inform policy changes to improve their socioeconomic circumstances and mitigate these hardships. The study employs qualitative methodologies, utilizing interviews, observation, and document analysis to capture rich, in-depth narratives from three Afghan refugee women. Each narrative provides unique insights into the women's struggles with education, employment, and securing legal rights. The research highlights challenges from forced migration, gender inequality, cultural norms, and socioeconomic marginalization, causing a holistic crisis for Afghan refugee women in Khyber Pakhtunkhwa, Pakistan. These issues hinder access to education, employment, financial vulnerabilities, and legal uncertainties. The study suggests a comprehensive, multi-pronged approach to policy changes, including education reform for refugee girls, gender-responsive recruitment practices, and legal reforms to secure refugees' rights. It emphasizes gender-responsive support services and involves Afghan refugee women in policy development processes, leveraging their experiences for more effective and inclusive policies.

La recherche explore les difficultés rencontrées par les femmes réfugiées afghanes pour accéder à l'éducation, à l'emploi et aux droits légaux à Khyber Pakhtunkhwa, au Pakistan. Il cherche à éclairer les changements politiques pour améliorer leur situation socio-économique et atténuer ces difficultés. L'étude utilise des méthodologies qualitatives, utilisant des entretiens, des observations et des analyses de documents pour recueillir des récits riches et approfondis de trois femmes réfugiées afghanes. Chaque récit fournit un aperçu unique des luttes des femmes en matière d'éducation, d'emploi et d'obtention de leurs droits légaux. La recherche met en évidence les défis liés à la migration forcée, à l'inégalité entre les sexes, aux normes culturelles et à la marginalisation socio-économique, provoquant une crise holistique pour les femmes réfugiées afghanes à Khyber Pakhtunkhwa, au Pakistan. Ces problèmes entravent l'accès à l'éducation, à l'emploi, souffrent de vulnérabilités financières et d'incertitudes juridiques. L'étude suggère une approche globale et multidimensionnelle des changements politiques, y compris une réforme de l'éducation pour les filles réfugiées, des pratiques de recrutement sensibles au genre et des réformes juridiques pour garantir les droits des réfugiés. Il met l'accent sur les services de soutien sensibles au genre et implique les femmes réfugiées afghanes dans les processus d'élaboration des politiques, en tirant parti de leurs expériences pour des politiques plus efficaces et inclusives.

Effective Surgical Site Infection Prevention Strategies for Diabetic Patients Undergoing Surgery: A Systematic Review.

Surgical site infections (SSIs) pose a significant clinical challenge, with heightened risks and severe consequences for diabetic patients undergoing surgical procedures. This systematic review aims to synthesize the current evidence on effective prevention strategies for mitigating SSI risk in this vulnerable population. From inception to March 2024, we comprehensively searched multiple electronic databases (PubMed, Medline, Embase, Cochrane Library, CINAHL) to identify relevant studies evaluating SSI prevention strategies in diabetic surgical patients. Our search strategy followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, utilizing a combination of keywords and Medical Subject Headings (MeSH) terms related to diabetes, surgical site infections, prevention strategies, and surgical procedures. Inclusion criteria focused on peer-reviewed clinical trials, randomized controlled trials, and meta-analyses published in English. The search yielded three studies meeting the eligibility criteria, subject to data extraction and qualitative synthesis. Key findings highlighted the efficacy of interventions such as optimized perioperative glycemic control, timely prophylactic antibiotic administration, and meticulous preoperative skin antisepsis in reducing SSI rates among diabetic surgical patients. The potential for personalized prevention approaches based on individual patient factors, such as diabetes type and surgical complexity, was explored. This systematic review underscores the importance of a multifaceted, evidence-based approach to SSI prevention in diabetic surgical patients, integrating strategies like glycemic control, antibiotic prophylaxis, and preoperative skin antisepsis. Furthermore, our findings suggest the potential benefits of personalized care pathways tailored to individual patient characteristics. Implementing these interventions requires interdisciplinary collaboration, adaptation to diverse healthcare settings, and patient engagement through culturally sensitive education initiatives. This comprehensive analysis informs clinical practice, fosters patient safety, and contributes to the global efforts to enhance surgical outcomes for this high-risk population.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology.

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Modeling different infectious phases of hepatitis B with generalized saturated incidence: An analysis and control.

Hepatitis B is one of the global health issues caused by the hepatitis B virus (HBV), producing 1.1 million deaths yearly. The acute and chronic phases of HBV are significant because worldwide, approximately 250 million people are infected by chronic hepatitis B. The chronic stage is a long-term, persistent infection that can cause liver damage and increase the risk of liver cancer. In the case of multiple phases of infection, a generalized saturated incidence rate model is more reasonable than a simply saturated incidence because it captures the complex dynamics of the different infection phases. In contrast, a simple saturated incidence rate model assumes a fixed shape for the incidence rate curve, which may not accurately reflect the dynamics of multiple infection phases. Considering HBV and its various phases, we constructed a model to present the dynamics and control strategies using the generalized saturated incidence. First, we proved that the model is well-posed. We then found the reproduction quantity and model equilibria to discuss the time dynamics of the model and investigate the conditions for stabilities. We also examined a control mechanism by introducing various controls to the model with the aim to increase the population of those recovered and minimize the infected people. We performed numerical experiments to check the biological significance and control implementation.

Environmental footprints of the data center service sector in Sweden.

The global data center (DC) sector has expanded rapidly during the last decades, due to the rising demand for digital services. In the Nordic region, Sweden has emerged as a global hub, attracting leading technology companies like Amazon, Facebook, Microsoft, and Google. Server halls of DCs are energy intensive buildings, which puts pressure on local water resources and contributes to global greenhouse gas emissions. This study aims to, firstly, quantify the environmental impact of DCs, based on energy usage, water consumption, and greenhouse gas (GHG) emissions. Secondly, it develops a planning tool by employing a multi-criteria approach to optimally locate new DCs and to assess the site suitability of existing ones in Sweden. Data of various performance indicators (geographical data on renewable energy accessibility, free cooling conditions, excess heat receivers, and resilience to water shortages) of DCs was collected through different means, e.g., questionnaire surveys, permit applications, company websites, and other open online data repositories. ArcGIS Pro was employed for spatial analysis, and 68 DCs with a site suitability index (SSI) ≤ 45 % were identified as less ideally located. The principal findings are centered on Sweden, and thereby primarily benefit stakeholders engaged in decision-making for evaluating existing or strategic planning of new DCs by incorporating a comprehensive environmental perspective. Given the rapidly changing climate, strategically siting DCs will become crucial for minimizing the sector's environmental impact.

The Potential of Fecal and Urinary Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer often diagnosed at advanced stages, highlighting the urgent need for early detection strategies. This systematic review explores the potential of fecal and urinary biomarkers for early PDAC detection. A comprehensive search identified eight relevant studies investigating various biomarkers, including proteins, metabolites, microbial profiles, DNA mutations, and non-coding RNAs. Promising findings suggest that urinary biomarkers related to metabolic alterations, inflammatory processes, fecal microbiome profiles, and fecal miRNAs hold diagnostic potential even at early stages of PDAC. Combining biomarkers into panels may enhance diagnostic accuracy. Challenges such as validation in larger cohorts, standardization of protocols, and regulatory approval must be addressed for clinical translation. Despite these hurdles, non-invasive urinary and fecal biomarkers represent a promising avenue for improving PDAC outcomes through early detection.

Anti-Diabetic, Anti-Cholinesterase, and Anti-Inflammatory Potential of Plant Derived Extracts and Column Semi-Purified Fractions of Ficus benghalensis.

BACKGROUND: The present study aimed to investigate the in-vitro anti-diabetic, anti-cholinesterase, and anti-inflammatory potential of extracts from different parts of Ficus benghalensis, including leaves, stem, and roots, as well as isolated column fractions (F-B-1 C, F-B-2 C, F-B-3 C, and F-B-4 C). METHODS: The extracts and subsequent fractions were evaluated for their inhibitory activity against key enzymes involved in diabetes [α-glucosidase and α-amylase], neurodegenerative diseases [acetylcholinesterase and butyrylcholinesterase], and inflammation (cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX)). RESULTS: The results showed that F. benghalensis leaf extract exhibited the highest α-glucosidase inhibitory activity (73.84%) and α-amylase inhibitory activity (76.29%) at 1000 µg/mL. The stem extract (65.50%) and F-B-2 C fraction (69.67%) also demonstrated significant α-glucosidase inhibitory activity. In terms of anti-cholinesterase activity, the extracts of roots, leaves, and stem showed promising inhibition of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), with half maximal inhibitory concentration (IC50) values ranging from 50.50 to 474.83 µg/mL. The derived fractions (F-B-1 C, F-B-2 C, F-B-3 C, and F-B-4 C) also exhibited notable inhibition of AChE and BChE, with IC50 values from 91.85 to 337.94 µg/mL. Moreover, the F-B-3 C fraction demonstrated the highest COX-2 inhibitory potential (85.72%), followed by F-B-1 C (83.13%), the stem extract (80.85%), and the leaves extract (79.00%). The F-B-1 C fraction showed the highest 5-LOX inhibitory activity (87.63%), while the root extract exhibited the lowest inhibition (73.39%). CONCLUSIONS: The results demonstrated promising bioactivity, suggesting the potential of F. benghalensis as a source of natural compounds with therapeutic applications. Further studies are required to identify and isolate the active components responsible for these effects and to evaluate their in-vivo efficacy and safety.

Significance of serum ferritin and De Ritis ratio in non-alcoholic fatty liver disease as diagnostic markers.

Objectives: To ascertain the significance of serum ferritin and De Ritis ratio as diagnostic markers in patients of nonalcoholic fatty liver disease with and without type 2 diabetes mellitus. METHODS: The comparative cross-sectional study was conducted from February to October 2022 at the Radiology Department of Combined Military Hospital, Rawalpindi, Pakistan, and comprised individuals aged 30-65 who were divided into 3 groups. Healthy controls formed group I, non-alcoholic fatty liver disease patients without type 2 diabetes mellitus formed group II and non-alcoholic fatty liver disease patients with type 2 diabetes mellitus were in group III. Blood 5ml was withdrawn and assessed for alkaline phosphatase, aspartate transaminase, alanine transaminase and ferritin. De Ritis ratio was calculated and subjected to intergroup comparison. Data was analysed using SPSS 22. RESULTS: Of the 210 subjects, 110(52.4%) were males and 100(47.6%) were females, with 70(33.3%) in each of the three groups. Group I had 38(54.3%) females and 32(45.7%) males with mean age 37.50±4.513. In group II, there were 27(38.6%) females and 43(61.4%) males with mean age 45.86±9.646, while in group III there were 35(50%) females and 35(50%) males with mean age 54.01±9.243 years. Serum ferritin levels were significantly increased in patient groups II and III compared to control group I (p<0.05). De Ritis ratio was markedly raised in groups II and III compared to group I (p<0.05). Ferritin was significantly correlated to age, weight, height, fasting blood glucose, haemoglobin, alkaline phosphatase, aspartate aminotransferase, alanine transaminase and bilirubin (p<0.05). De Ritis ratio had a significant correlation with body mass index and fasting blood glucose (p<0.05). CONCLUSIONS: Serum ferritin and De Ritis ratio were found to be useful diagnostic indicators for non-alcoholic fatty liver disease, highlighting their importance in improving disease screening.

CAPTURE: Comprehensive anti-cancer peptide predictor with a unique amino acid sequence encoder.

Anticancer peptides (ACPs) key properties including bioactivity, high efficacy, low toxicity, and lack of drug resistance make them ideal candidates for cancer therapies. To deeply explore the potential of ACPs and accelerate development of cancer therapies, although 53 Artificial Intelligence supported computational predictors have been developed for ACPs and non ACPs classification but only one predictor has been developed for ACPs functional types annotations. Moreover, these predictors extract amino acids distribution patterns to transform peptides sequences into statistical vectors that are further fed to classifiers for discriminating peptides sequences and annotating peptides functional classes. Overall, these predictors remain fail in extracting diverse types of amino acids distribution patterns from peptide sequences. The paper in hand presents a unique CARE encoder that transforms peptides sequences into statistical vectors by extracting 4 different types of distribution patterns including correlation, distribution, composition, and transition. Across public benchmark dataset, proposed encoder potential is explored under two different evaluation settings namely; intrinsic and extrinsic. Extrinsic evaluation indicates that 12 different machine learning classifiers achieve superior performance with the proposed encoder as compared to 55 existing encoders. Furthermore, an intrinsic evaluation reveals that, unlike existing encoders, the proposed encoder generates more discriminative clusters for ACPs and non-ACPs classes. Across 8 public benchmark ACPs and non-ACPs classification datasets, proposed encoder and Adaboost classifier based CAPTURE predictor outperforms existing predictors with an average accuracy, recall and MCC score of 1%, 4%, and 2% respectively. In generalizeability evaluation case study, across 7 benchmark anti-microbial peptides classification datasets, CAPTURE surpasses existing predictors by an average AU-ROC of 2%. CAPTURE predictive pipeline along with label powerset method outperforms state-of-the-art ACPs functional types predictor by 5%, 5%, 5%, 6%, and 3% in terms of average accuracy, subset accuracy, precision, recall, and F1 respectively. CAPTURE web application is available at https://sds_genetic_analysis.opendfki.de/CAPTURE.

Hypoglycemic, anti-inflammatory, and neuroprotective potentials of crude methanolic extract from Acacia nilotica L. - results of an in vitro study.

Acacia nilotica L., also known as babul, belonging to the Fabaceae family and the Acacia genus, is typically used for ornamental purposes and also as a medicinal plant found in tropical and subtropical areas. This plant is a rich source of bioactive compounds. The current study aimed to elucidate the hypoglycemic, anti-inflammatory, and neuroprotective potential of A. nilotica's crude methanolic extract. The results of the in vitro antidiabetic assay revealed that methanolic extract of A. nilotica inhibited the enzyme α-glucosidase (IC50: 33 µg mL-1) and α-amylase (IC50: 17 µg mL-1) in a dose-dependent manner. While in the anticholinesterase enzyme inhibitory assay, maximum inhibition was shown by the extract against acetylcholinesterase (AChE) (637.01 µg mL-1) and butyrylcholinesterase (BChE) (491.98 µg mL-1), with the highest percent inhibition of 67.54% and 71.50% at 1000 µg mL-1, respectively. This inhibitory potential was lower as compared to the standard drug Galantamine that exhibited 82.43 and 89.50% inhibition at the same concentration, respectively. Moreover, the methanolic extract of A. nilotica also significantly inhibited the activities of cyclooxygenase 2 (COX-2) and 5-lipoxygenase (5-LOX) in a concentration-dependent manner. The percent inhibitory activity of 5-LOX and COX-2 ranged from 42.47% to 71.53% and 43.48% to 75.22%, respectively. Furthermore, in silico, in vivo, and clinical investigations must be planned to validate the above-stated bioactivities of A. nilotica.

Language-adaptive artificial intelligence: assessing CHATGPT'S answer to frequently asked questions on total hip arthroplasty questions.

ChatGPT is reported to be an acceptable tool to answer a majority of frequently asked patient questions. ChatGPT also converses in other languages including Urdu, which offers immense potential for the education of Pakistani patients. Therefore, this study evaluated ChatGPT's Urdu answers to the ten most frequently asked questions on Total Hip Arthroplasty, which were then rated by an expert. Out of 10 answers in English, 9 (90%) were satisfactory requiring minimal clarification and 1 (10%) was satisfactory requiring moderate clarification. In both Roman and Nastaliq script Urdu, 1 (10%) answer was satisfactory requiring moderate clarification, while 9 (90%) were unsatisfactory requiring substantial clarification. In conclusion, as opposed to ChatGPT English responses, Urdu responses were much less rigorous, generic, and lacked scientific rigor. We have a long way to go before Pakistani patients with limited English language skills could benefit from AI chatbots like ChatGPT.

Long-term Risk of Stroke After New-Onset Atrial Fibrillation in Sepsis Survivors: A 2-Year Follow-Up Study.

BACKGROUND: Cardiovascular complications such as new-onset atrial fibrillation (NOAF) are common in sepsis and are known to increase the risk of in-hospital mortality and stroke. However, only a handful of studies have evaluated the long-term risk of stroke after NOAF in sepsis survivors. As part of our efforts to address this issue, we conducted the first-ever follow-up study in a developing country evaluating the long-term risk of stroke for sepsis survivors following NOAF. Methods: This retrospective study evaluated all adult patients admitted at the Aga Khan University Hospital between July 2019 and December 2019 with the diagnosis of sepsis. Data was collected from medical records of the included patients. Outcome measures included in-hospital mortality and ischemic stroke within 2 years. Results: Seven hundred thirty patients were included in the study; 415 (57%) were males and 315 (43%) females; mean age was 59.4 ± 18 years. 59 (8%) patients developed NOAF. The risk of stroke within 2 years in sepsis survivors was 3.5%. Six out of 30 (20%) patients in the atrial fibrillation (AF) group developed stroke, whereas 11 out of 448 (2%) patients in the non-AF group developed stroke. NOAF was associated with an increased risk of ischemic stroke within 2 years (OR = 6.6; 95% CI, 2.3-12.8; P = <.001). Conclusion: We conclude that AF occurred frequently in sepsis patients and was also associated with a 6-fold increase in the risk of ischemic stroke within 2 years. Reliable interventions for identifying high-risk patients for ischemic stroke are still poorly characterized, and this study may serve as a basis for more extensive multicenter studies to identify patients at high risk for ischemic stroke in the aftermath of septic AF and develop precise interventions for preventing it.

Strengthening neurosurgical training programs in Sub-saharan Africa: a medical student's perspective.

This article provides a nuanced exploration of the state and exigencies of neurosurgical training in sub-Saharan Africa (SSA), viewed through the discerning lens of a medical student. The region has a pronounced scarcity of neurosurgical services, further compounded by sociocultural intricacies and infrastructural inadequacies, resulting in elevated mortality and morbidity rates. The insufficiency of neurosurgeons, facilities, and training centers, particularly in remote areas, exacerbates this predicament. The imperative to fortify neurosurgical training programs is underscored, necessitating a multifaceted approach inclusive of international collaborations and innovative strategies. The challenges impeding neurosurgical training program implementation range from constrained infrastructure to faculty shortages and financial constraints. Recommendations encompass infrastructural investments, faculty development initiatives, and augmented community engagement. An exploration of neurosurgical training programs across diverse African regions reveals commendable strides and imminent deficits, warranting heightened international collaboration. Furthermore, technological innovations, including virtual reality, robotics, and artificial intelligence, are posited as transformative conduits for augmenting neurosurgical training in SSA. The article concludes with a sagacious compendium of recommendations, encompassing standardized curricula, mentorship paradigms, and stringent evaluation mechanisms, all combining efficaciously fortifying neurosurgical insight in SSA and producing transformative improvements in healthcare outcomes.