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Aims: This study identified and determined antibiograms of keratinolytic dermatophytes (DM), non-dermatophytic molds (NDM), and yeasts causing onychomycosis., Methods: Morphological, cultural, and biochemical characteristics were used to identify DM and NDM. The keratinolytic activity (KA) and antibiograms were conducted with keratin azure and the agar diffusion method, respectively. The minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) were determined using the microdilution method., Results: Onychomycosis was more prevalent in males (53%) than females, toenails (57%) than fingernails, and commercial employees (40%) than other employees or unemployed. Fungal growth was observed in 92.5% nail samples. DM, NDM, and yeasts caused 46%, 35%, and 19% onychomycosis, respectively. Trichophyton rubrum and Trichophyton mentagrophytes were the common DM. Five different genus of NDM and three different yeasts were isolated. The KA of DM was 30-45% higher than that of NDM and yeasts. All fungal isolates (FI) were resistant to griseofulvin and fluconazole. However, 71%, 64%, and 36% of FI were sensitive to terbinafine hydrochloride, nystatin, and ketoconazole, respectively, while 84% of DM and 46% of NDM were multidrug-resistant. The MIC and MFC of these antifungals against FI ranged from micrograms to milligrams., Conclusion: Multidrug resistance is growing in keratinolytic DM and NDM.

Exposure to influenza A virus (IAV), respiratory syncytial virus (RSV), and human metapneumovirus (hMPV) is well-known to increase the risk of Streptococcus pneumoniae (SPn) pneumonia in humans. Type I interferon (IFN-I) is a hallmark response to acute viral infections, and alveolar macrophages (AMs) constitute the first line of airway defense against opportunistic bacteria. Our study reveals that virus-induced IFN-I receptor (IFNAR1) signaling directly impairs AM-dependent antibacterial protection. Using Ifnar1 conditional knockout mouse models, in vivo antibodies, bone marrow chimeric mice, and AM reconstitution, we demonstrate that IFN-I intrinsically targets AMs to drive hypersusceptibility to SPn following IAV infection. Importantly, we show that RSV and hMPV infection induces robust IFN-I signaling in AMs, coinciding with lethal susceptibility to secondary SPn pneumonia. In contrast, seasonal human coronavirus neither induces significant IFN-I signaling in AMs nor immune predisposition to SPn . Therefore, we conclude that IFN-I inhibition of AMs represents a crucial mechanism underlying antibacterial complications following otherwise asymptomatic or mild respiratory viral infections.

Reconstructive optoelectronic spectroscopy has generated substantial interest in the miniaturization of traditional spectroscopic tools, such as spectrometers. However, most state-of-the-art demonstrations face fundamental limits of rank deficiency in the photoresponse matrix. In this work, we demonstrate a miniaturized spectral sensing system using an electrically tunable compact optoelectronic interface, which generates distinguishable photoresponses from various input spectra, enabling accurate spectral identification with a device footprint of 5 micrometers by 5 micrometers. We report narrow-band spectral sensing with peak accuracies of ∼0.19 nanometers in free space and ∼2.45 nanometers on-chip. In addition, we implement broadband complex spectral sensing for material identification, applicable to organic dyes, metals, semiconductors, and dielectrics. This work advances high-performance, miniaturized optical spectroscopy for both free-space and on-chip applications, offering cost-effective solutions, broad applicability, and scalable manufacturing.

Background: Logistic regression is a useful statistical technique commonly used in many fields like healthcare, marketing, or finance to generate insights from binary outcomes (e.g., sick vs. not sick). However, when applying logistic regression to complex survey data, which includes complex sampling designs, specific methodological issues are often overlooked., Methods: The systematic review extensively searched the PubMed and ScienceDirect databases from January 2015 to December 2021, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, focusing primarily on the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS). 810 articles met the inclusion criteria and were included in the analysis. When discussing logistic regression, the review considered multiple methodological problems such as the model adequacy assessment, handling dependence of observations, utilization of complex survey design, dealing with missing values, outliers, and more., Results: Among the selected articles, the DHS database was used the most (96%), with MICS accounting for only 3%, and both DHS and MICS accounting for 1%. Of these, it was found that only 19.7% of the studies employed multilevel mixed-effects logistic regression to account for data dependencies. Model validation techniques were not reported in 94.8% of the studies with limited uses of the bootstrap, jackknife, and other resampling methods. Moreover, sample weights, PSUs, and strata variables were used together in 40.4% of the articles, and 41.7% of the studies did not use any of these variables, which could have produced biased results. Goodness-of-fit assessments were not mentioned in 75.3% of the articles, and the Hosmer-Lemeshow and likelihood ratio test were the most common among those reported. Furthermore, 95.8% of studies did not mention outliers, and only 41.0% of studies corrected for missing information, while only 2.7% applied imputation techniques., Conclusions: This systematic review highlights important gaps in the use of logistic regression with complex survey data, such as overlooking data dependencies, survey design, and proper validation techniques, along with neglecting outliers, missing data, and goodness-of-fit assessments, all of which point to the need for clearer methodological standards and more thorough reporting to improve the reliability of results. Future research should focus on consistently following these standards to ensure stronger and more dependable findings., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Diabetes mellitus (DM) can be treated with various medications. However, individuals in underdeveloped countries may face challenges in using these treatments due to side effects and high costs. Anti-diabetic medications can inhibit enzymes, such as α-amylase, which is responsible for breaking down carbohydrates. In this investigation, 16 phytoconstituents were identified from Pterocarpus santalinus leaf extract through GC-MS analysis, and their significant antioxidant activities were noted. Among these, the pure compound lupeol demonstrated α-amylase inhibition activity of 86.13 ± 1.27 % (IC 50  = 58.50 ± 0.83 μg/mL) in vitro. Additionally, lupeol showed the highest binding affinity in silico using PyRx and CB-Dock, with values of -9.5 and -9.3 kcal/mol, respectively. The in silico analysis also indicated that lupeol possesses acceptable ADMET properties, suggesting its potential as an anti-diabetic drug. A molecular dynamics simulation lasting 500 ns was conducted to evaluate hydrogen bonds, RMSF, RMSD, Rg, and SASA, confirming the stability and integrity of the docking scenarios. In STZ-induced diabetic mice, lupeol significantly reduced blood glucose levels by 70.82 % from day 0 to day 28. Furthermore, lupeol markedly decreased total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C), while improving high-density lipoprotein cholesterol (HDL-C) levels in these mice. The antidiabetic effect of lupeol was further validated through histological examinations of the pancreas, heart, kidney, and liver of treated mice, alongside correlation analysis, CAP, and ANOSIM tests. Based on the findings from the in vitro, in silico, and in vivo investigations, this study concludes that lupeol may have potential anti-diabetic effects through the inhibition of the α-amylase enzyme., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier Ltd. All rights reserved.)

Background: Maternal tetanus toxoid (MTT) vaccination during pregnancy remains an important factor for reducing infant mortality globally, especially in developing nations, including Bangladesh. Despite commendable progress in reducing child mortality through widespread MTT vaccination during pregnancy, the issue still exists. This analysis explores the impact of MTT vaccination on neonatal mortality in Bangladesh and identifies associated factors., Methods: This research utilizes data from the 2019 Bangladesh Multiple Indicator Cluster Survey (MICS). The dataset consists of 23,402 cases; among them, 587 cases resulted in infant death. The outcome variable was infant mortality, which was binary. The independent variables identified as potential contributors to the cause of death included tetanus toxoid vaccination status, mode of delivery (cesarean section or not), and mother's education level, among others. The Poisson model was employed to analyze the data., Results: The analyses showed that the neonatal mortality rate was 2.51%. Notably, 45.90% of mothers received the MTT vaccination during pregnancy. Among them, 23.07% received a single dose, and 22.82% took adequate doses (receiving more than two doses) and adhered to WHO guidelines. The adjusted incidence rate ratio (IRR) was 1.36, which indicates that there was a 36% higher risk of neonatal mortality for those children whose mothers did not take TT (IRR = 1.36, p = 0.081). We also found that women from middle-class households (IRR = 1.58, 95% CI = 0.98, 2.54) and women with higher parity (IRR = 1.96, 95% CI = 0.95, 4.03) also had a higher risk of newborn fatalities. A comparable trend has been observed regarding the correlation between the number of tetanus doses administered and neonatal mortality, where it also emphasizes the importance of receiving adequate doses (a minimum of 2 doses of tetanus vaccine) to mitigate neonatal mortality (adjusted IRR = 0.54, 95% CI = 0.29, 1.01) in comparison to no doses received., Conclusion: Administering a minimum of one maternal tetanus dose significantly lowers the risk of neonatal mortality. Other than Maternal Tetanus Toxoid vaccination, the analyses underscore various contributors to neonatal mortality, encompassing maternal healthcare, delivery procedures, socio-economic status, and education. Targeted interventions addressing these factors have the potential to efficiently decrease neonatal mortality rates and improve overall maternal and child health., Competing Interests: No competing interests exist for this manuscript., (Copyright: © 2025 Naha 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.)

Objective: To improve the accuracy and explainability of skin lesion detection and classification, particularly for several types of skin cancers, through a novel approach based on the convolutional neural networks with attention-integrated customized ResNet variants (CRVs) and an optimized ensemble learning (EL) strategy., Methods: Our approach utilizes all ResNet variants combined with three attention mechanisms: channel attention, soft attention, and squeeze-excitation attention. These attention-integrated ResNet variants are aggregated through a unique multi-level EL strategy. We propose an innovative weight optimization method, inverse Gini indexed averaging (IGIA), which is further extended to multi-leveled IGIA (ML-IGIA) to determine the optimal weights for each model within multiple ensemble levels. For interpretability, we employ gradient class activation map to highlight the regions responsible for classification dominance, enhancing the model's transparency., Results: Our method was evaluated on the Human Against Machines 10000 dataset, achieving a superior accuracy of 94.52% with the ML-IGIA approach, outperforming existing methods., Conclusions: The proposed CRV-based ensemble model with ML-IGIA demonstrates robust performance in skin lesion classification, offering both high accuracy and enhanced interpretability. This approach addresses the current research gap in effective weight optimization in EL and supports timely, automated skin disease detection., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2025.)

Perovskite technologies has taken giant steps on its advances in only a decade time, from fundamental science to device engineering. The possibility to exploit this technology on a thin flexible substrate gives an unbeatable power to weight ratio compares to similar photovoltaic systems, opening new possibilities and new integration concepts, going from building integrated and applied photovoltaics (BIPV, BAPV) to internet of things (IoT). In this perspective, the recent progress of perovskite solar technologies on flexible substrates are summarized, focusing on the challenges that researchers face upon using flexible substrates. A dig into material science is necessary to understand what kind of mechanisms are limiting its efficiency compare to rigid substrates, and which physical mechanism limits the upscaling on flexible substrate. Furthermore, an overview of stability test on flexible modules will be described, suggesting common standard procedure and guidelines to follow, showing additional issues that flexible modules face upon bending, and how to prevent device degradation providing an ad-hoc encapsulation. Finally, the recent advances of flexible devices in the perovskite market will be shown, giving an outline of how this technology is exploited on flexible substrates, and what are still missing that need stakeholders' attention., (© 2025 Wiley‐VCH GmbH.)

Precise prediction of adsorption in a multicomponent system is vital for successful design of dye-contaminated industrial wastewater treatment processes. The present work looks for the reason behind the failure of the competitive Langmuir model (CLM) to describe adsorption in such systems, while the Langmuir model (LM) successfully describes the process for a single dye solution. With that end, derivations of LM and CLM have been revisited, and a criterion for the universality of active sites has been defined. Attempts have been made to describe the competitive adsorption based on the LM parameters determined from single dye solutions. Three dyes (safranin, crystal violet, and methylene blue) and two adsorbents [activated carbon (AC) and coconut fiber (CF)] are subjected to adsorption and BET tests. AC complies with the universality criterion, while CF does not. The active site density estimated from dye adsorption is 14-18 folds lower for AC and 18-38 folds higher for CF, than those done from the BET test. The CLM predicts the equilibrium adsorption density of both adsorbents in binary dye systems satisfactorily, but there is a large gap between the predicted and experimental values of equilibrium concentration. It is argued that in liquid systems, adsorption occurs through different types of interactions, and hence the adsorption process even for a single dye should not be presented by a single K L value (as is formulated in LM), rather with multiple K L values corresponding to the interaction types. These K L values will classify the active sites as universal and specific in a multicomponent system, and then the CLM will predict competitive adsorption better, which will make the adsorption process design more precise.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased mortality and malignancy risk, yet the determinants of clonal expansion remain poorly understood. We performed sequencing at >4,000x depth of coverage for CHIP mutations in 6,986 postmenopausal women from the Women's Health Initiative at two timepoints approximately 15 years apart. Among 3,685 mutations detected at baseline (VAF ≥ 0.5%), 50% progressed to CHIP (VAF ≥ 2%) at follow-up. We confirmed that clonal expansion is highly dependent on initial clone size and CHIP driver gene, with SF3B1 and JAK2 mutations exhibiting the fastest growth rate. We identified germline variants in TERT , IL6R , TCL1A , and MSI2 that modulate clonal expansion rate. Measured baseline leukocyte telomere length showed differential effects on incident CHIP risk, with shorter baseline leukocyte telomere length predisposing to incident PPM1D mutations and longer baseline leukocyte telomere length favoring incident DNMT3A mutations. We discovered that the IL6R missense variant p.Asp358Ala specifically impairs TET2 clonal expansion, supported by direct measurements of soluble interleukin-6 receptor and interleukin-6. Faster clonal growth rate was associated with increased risk of cytopenia, leukemia, and all-cause mortality. Notably, CHIP clonal expansion rate mediated 34.4% and 43.7% of the Clonal Hematopoiesis Risk Score's predictive value for leukemia and all-cause mortality, respectively. These findings reveal key biological determinants of CHIP progression and suggest that incorporating growth rate measurements could enhance risk stratification.

Around the world, catastrophes caused by flooding are occurring naturally that cause a great deal of fatalities and financial loss. The loss of life and property can be considerably reduced with precise flood forecasts. The complexity of many flood predicting techniques makes the results difficult to interpret, compromising the process's core goal. This study uses a quick and flexible Gaussian Naïve Bayes (GNB) classifier to categorize eight different years as flooded or non-flooded based on predictor variables obtained via the Mutual Information (MI) technique. During the search, all-sky surface shortwave downward irradiance is identified as the optimum predictor variable out of nineteen stochastic variables, with the highest sensitivity for model accuracy. The model is then validated using four iterations derived from the MAPE of the GNB classification method for Twenty-five percent mean error rates from 4-fold cross-validation indicate that this classification model is suitable for flood forecasting. This high rate of mean error is caused by the short amount of data utilized as training data, as GNB requires huge data records to get effective results. This research could aid in the development and evaluation of hydrological projects in the Sirajganj district., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2025 The Authors.)

Polyethylenimine (PEI) is a widely used cationic polymer for nonviral gene delivery, often modified to enhance transfection efficiency and reduce cytotoxicity. This study investigates how acetylation, succinylation (acPEI and zPEI), and pH influence the internal DNA packaging of polyplexes. Both modifications alter physicochemical properties, leading to complexes that decondense more readily with increasing modification. X-ray scattering reveals that high acetylation produces loosely packed DNA, while succinylation unexpectedly tightens DNA packing at higher modification levels. Polyplexes formed at low pH (pH 4) are more stable and tightly packed than those formed at pH 7.5. Acidifying polyplexes initially formed at pH 7.5 induces structural rearrangement to tighter DNA packing accompanied by significant PEI release, providing direct evidence for models where free PEI aids endosomal escape. These findings challenge conventional assumptions about PEI behavior and offer new insights into DNA packaging, emphasizing tailored polymer modifications and pH conditions to optimize gene delivery.

The increasing demand for sustainable, robust, and cost-efficient arsenic (As) treatment techniques strengthens the implementation of new constructed wetland (CW) designs like aerated CWs in the agricultural sector. The aim was to assess and contrast the influence of various aeration rates on As elimination in subsurface flow CW utilizing Pennisetum purpureum plants for treating As-polluted sand. This study consisted of an experiment with 16 subsurface flow CW, operating at different As concentrations of 0, 5, 22, and 39 mg kg -1 and aeration rates of 0, 0.18, 1, and 2 L min -1 . The highest elimination of As from treatment sand in the subsurface flow CWs was 96.19 ± 3.09%, 93.95 ± 2.17%, and 91.91 ± 1.92% for 5, 22, and 39 mg kg -1 As, respectively, at 0.18 L min -1 aeration. A negative influence of As pollution on growth was detected in the 0, 1, and 2 L min -1 aeration but Pennisetum purpureum grows well in polluted sand with 0.18 L min -1 aeration. Bacterial population and different enzyme activity showed statistically significant differences with 0, 0.18, 1, and 2 L min -1 aerations at all As levels. These results suggest that this treatment can be used for As phytoremediation in anthropogenically polluted environments due to its high capability to uptake As.

Coherent broadband light generation has attracted massive attention due to its numerous applications ranging from metrology, sensing, and imaging to communication. In general, spectral broadening is realized via third-order and higher-order nonlinear optical processes (e.g., self-phase modulation, Raman transition, four-wave mixing, multiwave mixing), which are typically weak and thus require a long interaction length and the phase matching condition to enhance the efficient nonlinear light-matter interaction for broad-spectrum generation. Here, for the first time, we report octave-spanning coherent light generation at the nanometer scale enabled by a phase-matching-free frequency down-conversion process. Up to octave-spanning coherent light generation with a -40dB spectral width covering from ~565 to 1906 nm is demonstrated in discreate manner via difference-frequency generation, a second-order nonlinear process in gallium selenide and niobium oxide diiodide crystals at the 100-nanometer scale. Compared with conventional coherent broadband light sources based on bulk materials, our demonstration is ~5 orders of magnitude thinner and requires ~3 orders of magnitude lower excitation power. Our results open a new way to possibly create compact, versatile and integrated ultra-broadband light sources., Competing Interests: Conflict of interest: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Bangladesh Rural Advancement Committee (BRAC), a leading non-governmental organization (NGO), implemented a large-scale Home Fortification (HF) with Micronutrient Powder (MNP) programme from 2013 to 2018 aimed to reduce undernutrition and iron deficiency anemia among children aged below 5 years old. An adequate and timely supply of MNP was crucial for successful implementation of the programme, but very few studies have documented implementers' MNP supply chain experiences. Therefore, this study aimed to explore the barriers and enablers in the MNP supply chain in Bangladesh., Methods: We conducted this process evaluation in five rural sub-districts and three urban slums from March 2016 to February 2017. We conducted 15 Key Informant Interviews (KIIs) with HF programme personnel, 41 In-depth Interviews (IDIs) with direct HF programme implementers and reviewed relevant documents. We analyzed data using thematic and root-cause analysis approaches., Results: Participants reported the barriers in the MNP supply chain included lack of raw materials for MNP production by local manufacturer, political unrest and insufficient transport facilities, a lack of space for MNP buffer stock at BRAC's central warehouse, and coordination gaps between BRAC's national and sub-national level staff. Enablers to each of the barriers mentioned include ensuring buffer stock at all levels, raising separate transport requisition for MNP supply, and recruiting dedicated supply chain officers., Conclusion: Concurrent course-corrections based on process evaluation findings improved MNP supply chain performance, resulting in higher MNP sales and coverage. The identified barriers and enablers provide useful insights for similar programs, emphasizing the importance of a resilient and well-managed MNP supply chain., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Uddin, Islam, Rahman, Ahmed and Sarma.)

Objective: Breast cancer detection is critical for timely and effective treatment, and automatic detection systems can significantly reduce human error and improve diagnosis speed. This study aims to develop an accurate and robust framework for classifying breast cancer into benign and malignant categories using a novel machine learning architecture., Methods: We propose a dense-ResNet attention integration (DRAI) architecture that combines DenseNet and ResNet models with three attention mechanisms to enhance feature extraction from the BreakHis dataset. The attention mechanisms focus on regionally important features, improving classification accuracy. A triple-level ensemble (TLE) method combines the performance of multiple models, further enhancing prediction accuracy., Results: The proposed DRAI architecture with TLE achieves an accuracy of 99.58% in classifying breast cancer into benign and malignant categories, surpassing existing methodologies. This high accuracy demonstrates the effectiveness of the fusion architecture and its ability to reduce manual errors in breast cancer diagnosis., Conclusion: The DRAI architecture with TLE provides a robust, automated framework for breast cancer classification. Its exceptional accuracy lays a solid foundation for future advancements in automated diagnostics and offers a reliable method for aiding early breast cancer detection., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2025.)

This paper examines the current state of food insecurity in Bangladesh and its socio-economic drivers using data from the latest Household Income and Expenditure Survey (HIES 2022). Unlike previous studies that relied on less precise measures of food insecurity, such as food expenditure, diversity, and calorie intake, this study employs the internationally recognized Food Insecurity Experience Scale (FIES) and Rasch model-based thresholds to classify households as food secure or insecure. Multilevel logistic regression is used to identify significant predictors of moderate and severe food insecurity, considering the hierarchical structure of the data, with households nested within geographical clusters. Key factors found to be significantly associated with food security include the wealth index, land ownership, education of the household head, family size, remittance income and exposure to shocks. A classification tree, a popular machine learning method, is also applied to explore important interactions among these determinants. The tree analysis confirms the importance of several regression-based predictors and identifies households at the highest risk of food insecurity through variable interactions. Factors such as poverty, lack of land ownership, low education levels, and high dependency ratios collectively increase a household's vulnerability to moderate food insecurity to around 51% while the national prevalence is 19%. District-level maps of food insecurity prevalence reveal significant regional disparities, underscoring the need for targeted, district-specific interventions to effectively combat food insecurity. More broadly, policies promoting education and family planning, training in better shock management, and facilitating remittance flows through simplified processes may contribute to addressing the food insecurity challenge., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2025 The Author(s).)

Environmental pollution has been a significant concern for the last few years. The leather industry significantly contributes to the economy but is one of Bangladesh's most prominent polluting industries. It is also responsible for several severe diseases such as cancer, lung diseases, and heart diseases of leather workers because they use bleaching agents and chemicals, and these have numerous adverse effects on human health. The study was aimed at isolating, identifying, and molecularly characterizing bacteria that produce protease enzymes that are highly capable of dehairing goat hide. Several attempts were made to isolate and identify protease-producing bacterial strains from different soil samples of tannery wastes. Initially, a total of four isolates were selected from tannery soil. After the different phenotypic and morphological characterization, one isolate (BS2) showed Gram-positive, rod-shaped, and spore-forming characteristics and could produce novel hair-degrading protease enzymes. The growth profile and protease activity of the bacteria at 37°C were observed; a basal level of extracellular protease increased with time. The enzyme's proteolytic activity was measured, and the unit of enzyme activity of the enzyme sample was 18.1. The ExPASy server (ProtParam) tool was used to estimate the physicochemical characteristics of the proteins and found molecular weight (MW) (7375.94 Da), aliphatic index (71.56), instability index (II, 80.63), Grand Average of Hydropathy (GRAVY) (-0.231), and isoelectric point (11.41). The protein-protein interactions (PPI) networks were generated using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The PSIPRED v.4.0 and SAVES v.6.0 programs were used to determine the secondary and three-dimensional assembly of the selected protein. They found alpha helix (16, 25.00%), extended strand (6, 9.38%), beta-turn (5, 7.81%), and random coil (37, 57.81%). DNA isolation and purification were carried out, and the purity ratio was ~2.17 at 260 and 280 nm. Polymerase chain reaction (PCR) for amplifying the 16S rRNA gene was conducted, and the isolate was authentically recognized as Bacillus cereus (BS2) based on morphological, biochemical, and molecular analyses. The quantitative assessment has shown that 40 mL of culture centrifugation could dehair 2 × 1 cm of goat leather sample in 9 h. This potential bacterial strain can be used in the leather industry as an ecofriendly alternative to chemical dehairing, which can reduce environmental pollution and the risk of severe diseases among leather industry workers., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2025 Md. Ekhlas Uddin et al. BioMed Research International published by John Wiley & Sons Ltd.)

Magnetic resonance imaging (MRI) is considered one of the most valuable diagnostic technologies in the 21st century. To enhance the image contrast of anatomical features, MRI contrast agents have been widely used in clinical MRI diagnosis, especially those based on gadolinium, manganese, and iron oxide. However, these metal-based MRI contrast agents show potential toxicity to patients, which urges researchers to develop novel MRI contrast agents that can replace metal-based MRI contrast agents. Metal-free nitroxide radical contrast agents (NRCAs) effectively overcome the shortcomings of metal-based contrast agents and also have many advantages, including good biocompatibility, prolonged systemic circulation time, and easily functionalized structures. Importantly, since NRCAs acquire MRI signals with standard tissue water 1 H relaxation mechanisms, they have great potential to realize clinical translation among many metal-free MRI contrast agents. At present, NRCAs have been proposed as an effective substitute for metal-based MRI contrast agents. Herein, this review first briefly introduces NRCAs, including their composition, classification, mechanism of action, application performances and advantages. Then, this review highlights the progress of NRCAs, including small molecule-based NRCAs and polymer-based NRCAs. Finally, this review also discusses the challenges and future perspectives of NRCAs.

Importance: Disease characteristics of genetically mediated coronary artery disease (CAD) on coronary angiography and the association of genomic risk with outcomes after coronary angiography are not well understood., Objective: To assess the angiographic characteristics and risk of post-coronary angiography outcomes of patients with genomic drivers of CAD: familial hypercholesterolemia (FH), high polygenic risk score (PRS), and clonal hematopoiesis of indeterminate potential (CHIP)., Design, Setting, and Participants: A retrospective cohort study of 3518 Mass General Brigham Biobank participants with genomic information who underwent coronary angiography was conducted between July 18, 2000, and August 1, 2023., Exposures: The presence of a genomic risk factor of CAD, defined as FH variant, high CAD PRS, or CHIP driver variation., Main Outcomes and Measures: Coronary artery disease presentation (stable or acute), angiographic CAD characteristics (severity and burden), angiographic outcomes (repeat angiogram, revascularization, and in-stent restenosis), and clinical outcomes (heart failure and all-cause mortality)., Results: Among 3518 participants (2467 [70.1%] male; median age, 64.0 [IQR, 55.0-72.0] years), 1509 (42.9%) had at least 1 genomic driver of CAD (26 FH, 1191 high CAD PRS, and 466 CHIP) that was associated with the presentation of acute coronary syndromes (adjusted odds ratio, 2.67; 95% CI, 2.19-3.26) and with the presence, burden, and severity of angiographic CAD. This association was driven by FH and CAD PRS. One SD of CAD PRS was associated with a 12.51-point higher Gensini score. During 9 years of follow-up, there was an increased risk among FH carriers for a repeat angiogram (adjusted hazard ratio [AHR], 1.70; 95% CI, 1.02-2.83), and revascularization (AHR, 1.97; 95% CI, 1.02-3.80), and among people with high CAD PRS (repeat angiogram: AHR, 1.79; 95% CI, 1.45-2.22; revascularization: AHR, 1.85; 95% CI, 1.37-2.50; and in-stent restenosis: AHR, 3.89; 95% CI, 2.16-7.01). CHIP carriers had no significant increase in angiographic outcomes but were at higher risk of heart failure (AHR, 1.58; 95% CI, 1.04-2.40) and all-cause mortality (AHR, 1.78; 95% CI, 1.47-2.16)., Conclusions and Relevance: The findings of this study suggest that germline monogenic and polygenic risk are associated with acute coronary syndromes presentation, severity and burden of atherosclerosis, and risk of repeat angiogram, revascularization, and in-stent restenosis. CHIP variant status is associated with incident heart failure and mortality after coronary angiography.

The antibacterial nanofibrous mat is crucial in biomedicine as it enhances infection control, expedites wound healing, and mitigates health hazards by decreasing antibiotic usage. A novel synergistic antibacterial and hydrophilic nanofibrous mat successfully fabricated by solution electrospinning from polyvinyl alcohol (PVA) incorporated Croton bonplandianum Baill (CBB) leaves extract. Antioxidant-enriched leaf extract of the CBB plant was integrated with PVA in varying proportions of 30% (CBB-30), 40% (CBB-40), and 50% (CBB-50) to manufacture antibacterial nanofibrous mat. The zone of inhibition (ZOI) was recorded at 16, 18, and 21 mm for CBB-30, CBB-40, and CBB-50, respectively. The wetted radius, a key parameter for moisture management properties, reached up to 20 mm for CBB-40 and CBB-50. This demonstrates the rapid absorption and quick-drying characteristics, highlighting the exceptional hydrophilicity of the nanofibrous mat. The increased dozing of CBB extract into the PVA also reduced its fiber diameter. The diameters of pure PVA, CBB-30, CBB-40, and CBB-50 were found as 396, 388, 279, and 241 nm, correspondingly. The developed nanofibrous mat, exhibiting ZOI of up to 21 mm, efficient moisture management properties, and a nanoscale fiber diameter of 241 nm, may possess significant uses in the biomedical domain., (© 2025 Wiley Periodicals LLC.)

Objectives: Dengue emerged as a significant health threat in endemic regions in recent years. However, inconsistent diagnostic accuracy in sequential dengue infections necessitate improved testing methods to ensure effective management of dengue cases. Here, we evaluated a portable, rapid, and sensitive molecular assay-reverse transcriptase recombinase polymerase amplification assay (RT-RAA)-utilizing a mobile suitcase laboratory to detect infections in suspected dengue cases in Bangladesh., Methods: A total of 364 suspected patients with dengue were enrolled in the study. Dengue cases were confirmed by a positive result from any of the four tests: non-structural protein 1 (NS1) rapid diagnostic test (RDT), immunoglobulin (Ig) M RDT, quantitative reverse transcriptive-polymerase chain reaction (RT-PCR), and RT-RAA assay. IgG RDT was performed to differentiate between primary and secondary dengue infections., Results: Of 364 suspected cases, 320 were confirmed dengue cases, with 55.94% classified as primary and 44.06% as secondary infections. Laboratory results showed comparable positivity rates between RT-RAA (78.8%) and NS1 RDT (77.1%) in primary dengue, followed by quantitative RT-PCR (57.5%) and IgM RDT (12.8%). RT-RAA demonstrated superior positivity rates in secondary dengue (76.6%), surpassing RT-PCR (60.3%), NS1 RDT (27%), and IgM RDT (24.8%). Combining RT-RAA with NS1 RDT detected infections in 89.95% primary and 81.56% secondary dengue., Conclusions: The findings suggest that complementing RT-RAA with NS1 RDT could significantly improve dengue detection rate, particularly, for secondary infections., Competing Interests: Declarations of competing interest The authors have no competing interests to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The environmental burden of tannery wastewater, characterized by high levels of total dissolved solids (TDS) and other contaminants, presents a significant challenge for sustainable water management. This study addresses this issue by developing a novel polyvinyl alcohol (PVA) and polyvinyl chloride (PVC) composite membrane optimized for efficient TDS removal from tannery effluent. The membrane was fabricated using a solution casting technique, with glutaraldehyde employed as a crosslinking agent to enhance mechanical properties and stability. Characterization techniques, including Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), zeta potential analysis, and contact angle measurements, were used to evaluate the membrane's surface chemistry, morphology, and hydrophilicity, which are crucial for pollutant separation. Performance testing demonstrated that the membrane achieved a TDS removal efficiency of 91.73% at an optimal pH of 8 and a transmembrane pressure of 3.5 bar, with a permeability of 194 Lm -2  h -1  bar -1 . Additionally, substantial reductions in turbidity (94.51%), chemical oxygen demand (COD, 91.91%), biological oxygen demand (BOD, 89.70%), salinity (80.57%), and total suspended solids (TSS, 96.45%) were observed. The membrane exhibited impressive mechanical properties, with a tensile strength of 44 ± 0.43 MPa, 150 ± 0.67% elongation at break, Young's modulus of 750 ± 0.47 MPa, and flexibility of 23 ± 0.53%, indicating its flexibility and durability. Its partial biodegradability and potential for scalable production contribute to its environmental sustainability. This work establishes the PVA-PVC composite membrane as a promising and cost-effective solution for industrial wastewater treatment, offering a sustainable approach to mitigating water pollution in the leather industry., Competing Interests: Declarations. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: This paper has been approved by all co-authors and is not published in any peer-reviewed literature or under consideration by any other journal. I have not submitted my manuscript to a preprint server before submitting it to Environmental Science and Pollution Research. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Enhancement of dynamic characteristics of sand through bio-cementation is one of the prospective ground improvement techniques for sustainable development considering seismic loading scenarios. Microbially induced calcite precipitation (MICP) has already been established as an efficient and low-cost and sustainable bio-cementation technique. In the present study, engineering characteristics of poorly graded standard Ennore sand of India have been improved through the bio-cementation effects of Sporosarcina pasteurii bacteria using the MICP technique. Microstructure images obtained through scanning electron microscope and crystalline form of minerals present obtained through X-ray diffraction analyses are presented for the bio-cemented sand. Finally, dynamic characteristics of the bio-cemented sand are investigated through strain-controlled unconsolidated undrained cyclic triaxial testing varying the shear strain range from 0.3 to 1.5% with 1.0-Hz frequency. Variations of shear modulus and damping ratio of bio-cemented sand with shear strain are reported considering treatment durations of 7 and 14 days with treatment intervals of 12 and 24 h, respectively. It is observed that the improvement in shear modulus of bio-cemented sand for lesser strain rate approximately ranges from 37% to more than 80% compared to untreated sand. Furthermore, for strain higher than 1.0%, the margin of improvement varies from 50 to 70%. Moreover, the damping of bio-cemented sand was found to be lesser than untreated sand, and the variation is more significant for the higher number of loading cycles. This study is helpful in the assessment of dynamic characteristics of bio-cemented sand specifically applicable to seismic design., Competing Interests: Declarations. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Diabetes mellitus (DM) is a metabolic disease marked by an excessive rise in blood sugar (glucose) levels caused by a partial or total absence of insulin production, combined with alterations in the metabolism of proteins, lipids, and carbohydrates. The International Diabetes Federation estimates that 425 million individuals globally had diabetes in 2017 which will be 629 million by 2045. Several medications are used to treat DM, but they have limitations and side effects including weight gain, nausea, vomiting, and damage to blood vessels and kidneys. Therefore, it is essential to identify anti-diabetic drugs that have less or no side effects. Hence, the current study employed in silico approaches to discover new DPP-IV inhibitors that might be associated with diabetes. Thirty-four (34) co-crystalized DPP-IV enzymes were found from the protein data bank and the co-crystal ligands were docked into the active-site 6B1E protein to find out the hit compounds. From the docking results, we found two hit compounds (5T4E and 4J3J) which were used to find out the analogs from the experimental drug database using the DrugRep software. According to the results, twenty (20) analogs were found from the experimental drug database with the similarity score of ≥ 0.790 and docked once again into the active site of the DPP-IV (PDB ID: 6B1E) enzyme. Interestingly, DB02226 showed the best binding affinity (-10.3 kcal/mol) and prime MM/GBSA (-68.73 kcal/mol) compared to the reference drug (co-crystal ligand; -7.4 kcal/mol and -47.49 kcal/mol, respectively). Additionally, DB02226 has shown excellent reactivity, efficacy, and structural stability in the binding region of target proteins in studies using MD simulation, MM/GBSA, DFT, and MESP analysis. These findings can be utilized to support further in vitro, in vivo, pre-clinical and clinical research rather than definitively confirming anti-diabetic effectiveness., Competing Interests: Conflict of interestsNo., (© King Abdulaziz City for Science and Technology 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Diabetes mellitus (DM) poses a major global healthcare challenge, highlighting the need for new treatments beyond current options. Currently available drugs have side effects including weight gain, nausea, vomiting, diarrhea, insulin resistance etc. Therefore, given the benefits of indole derivatives in diabetes and the lack of computational studies on bis-indole-based triazine derivatives with aldose reductase (AR), this study employs in-silico analysis to explore their potential as type-2 diabetes treatments. Based on the Differential Expression analysis, the human aldose reductase (HAR) encoding gene AKR1B1 showed overexpression in GSE30122 diabetes patients (Log2FC = 0.62, P  < 0.01). Moreover, the compounds 2-((5,6-di(1H-indol-3-yl)-1,2,4-triazin-3-yl)thio)-1-(3-hydroxy-5-methylphenyl)ethan-1-one (4) and 2-((5,6-di(1H-indol-3-yl)-1,2,4-triazin-3-yl)thio)-1-(4-nitrophenyl)ethan-1-one (8) were identified as leading candidates, showing binding energies of - 62.12, - 81.73 kcal/mol and - 57.19, - 85.97 kcal/mol, respectively. Docking, MM/GBSA screening, molecular dynamics (MD) simulations, PCA, and post-MM/GBSA analysis confirmed their stability and favorable binding compared to the apo protein and control. Further in-vitro, in-vivo, and clinical studies are required to validate their therapeutic potential., Competing Interests: Conflict of interestsThe authors declared that they have no conflict of interests., (© King Abdulaziz City for Science and Technology 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Handling venomous snakes poses a significant risk of envenomation. In the case of spitting cobras, additional precautions, like wearing face shields, are necessary to prevent ophthalmic envenomation. Although, the Monocled Cobra (Naja kaouthia) is not a true spitting cobra, however some spitting events has been reported from Northeastern India and Nepal but ocular envenomation is scarce. In this report, a snake researcher experienced eye exposure to spitted venom while measuring a N. kaouthia. The researcher promptly irrigated his eyes and received medical treatment. He experienced intense pain, burning sensations, redness, vision problems, corneal edema, scleral hemorrhage and treated with Paracetamol and Moxifloxacin Hydrochloride. This report underscores the potential risk of ocular injury from Monocled Cobras and emphasizes the importance of using appropriate safety equipment, such as face shields, to minimize the danger of ophthalmic envenomation when working with these snakes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The aerobic electron transfer chain builds a proton gradient by proton coupled electron transfer reactions through a series of proteins. Complex I is the first enzyme in the sequence. Here transfer of two electrons from NADH to quinone yields four protons pumped from the membrane N- (negative, higher pH) side to the P- (positive, lower pH) side. Protons move through three linear antiporter paths, with a few amino acids and waters providing the route; and through the E-channel, a complex of competing paths, with clusters of interconnected protonatable residues. Proton loading sites (PLS) transiently bind protons as they are transported from N- to P-compartments. PLS can be individual residues or extended clusters of residues. The program MCCE uses Monte Carlos sampling to analyze the E-channel proton binding in equilibrium with individual Molecular Dynamics snapshots from trajectories of Thermus thermuphillus Complex I in the apo, quinone and quinol bound states. At pH 7, the five E-channel subunits (Nqo4, Nqo7, Nqo8, Nqo10, and Nqo11) take >25,000 protonation microstates, each with different residues protonated. The microstate explosion is tamed by analyzing interconnected clusters of residues along the proton transfer paths. A proton is bound and released from a cluster of five coupled residues on the protein N-side and to six coupled residues in the protein center. Loaded microstates bind protons to sites closer to the P-side in the forward pumping direction. MCCE microstate analysis identifies strongly coupled proton binding amongst individual residues in the two PLS clusters., Competing Interests: Declaration of competing interest Marilyn Gunner reports financial support was provided by National Science Foundation. Marilyn Gunner reports financial support was provided by DOE. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The disruption of health service delivery during public health emergencies, like Ebola and COVID-19, due to hesitancy among healthcare workers (HCWs) is well-documented. While previous studies have identified motivating factors for HCWs, accommodating all is often unfeasible due to resource limitations. Thus, identifying precise preferences is crucial from a policy standpoint. This study aims to discern HCWs' preferences regarding working conditions and fringe benefits to ensure continued service during emergencies. Additionally, we investigate potential variations in preferences among HCWs who served in dedicated COVID-19 units versus those who did not, considering differences in perceived and realized risks. Conducting a discrete choice experiment (CE) and in-person interviews with 370 HCWs from four tertiary-level hospitals in Bangladesh, our findings reveal HCWs prioritize improving working conditions over fringe benefits. Notably, those in dedicated COVID-19 units exhibit a divergent preference pattern, indicating significant influence of perceived and realized risks. These insights offer valuable guidance for policymakers to address HCWs hesitancy and ensure optimal service delivery during national health crises., Competing Interests: Declaration of competing interest Authors declare no conflict of interest., (Copyright © 2024. Published by Elsevier Ltd.)

A highly conducting polymer electrolyte was developed, where the structure included molecular elements guided by computational modeling results. The electrolyte comprises acidic boron and basic oxygen atoms within the molecular structure. Because of the presence of the boron and oxygen atoms within the structure, it interacts with the anion and cation of the dissolved salt and functions as an ion separator by increasing the bond length between the anion and cation. Increasing the bond length weakens the electrostatic interaction between the anion and cation, resulting in a decreased level of aggregation within the electrolyte matrix and higher ionic conductance. The new electrolytes show ionic conductivity values of 10 -3 S cm -1 at 25 °C, which are suitable for lithium-ion polymer batteries. The approach demonstrates the importance of integrating computational modeling with experimental studies to design and develop promising electrolytes for lithium-ion polymer batteries., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Reducing the harmful chemical use along with obtaining potential yield in field is a worth exploring practice in rice cultivation. To mitigate the prevailing yield gap, the current study was designed to evaluate the effect of chitosan in improving growth, yield contributing characters and yield of rice. The experiment comprised eight different treatments viz. control (no fertilizer and Chitosan) (T 0 ), conventional method (with fertilizers) (T 1 ), conventional method with foliar spray of 100 ppm chitosan solution (T 2 ), conventional method with foliar spray of 300 ppm chitosan solution (T 3 ), conventional method with foliar spray of 500 ppm chitosan solution (T 4 ), only foliar spray of 100 ppm chitosan solution (T 5 ), only foliar spray of 300 ppm chitosan solution (T 6 ), and only foliar spray of 500 ppm chitosan solution (T 7 ). The experiment was laid out in a completely randomized block design containing three replications. Data on different vegetative and yield contributing characters were recorded to evaluate the treatments effectiveness in improving rice yield. Different growth and yield contributing characters showed significant improvement after applying chitosan in addition to the conventional production system. The conventional method with foliar spray of 500 ppm chitosan solution had a greater positive effect on yield contributing characters and yield. In vegetative characters, the highest plant height became (87.3 cm), number of tiller hill -1 (13.7), Total dry matter (12.9), leaf area index (1.35), and chlorophyll content (57.73). On the basis of assessed treatments in yield contributing characters and yield, the highest plant height was (91.8 cm), no. of grains panicle -1 (145.29), grain yield (6.37 t ha -1 ), straw yield (6.47 t ha -1 ). Results showed that the conventional method with foliar spray of different concentration of chitosan solution was able to increase yield up to 26 % in comparison to the conventional method. Overall, our findings suggest that additional foliar spray of chitosan with previously recommended cultivation practice can increase the yield per unit area and offers promising technology to achieve potential yield in farmer's field., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Environmental and human health is severely threatened by wastewater and air pollution, which contain a broad spectrum of organic and inorganic pollutants. Organic contaminants include dyes, volatile organic compounds (VOCs), medical waste, antibiotics, pesticides, and chemical warfare agents. Inorganic gases such as CO 2 , SO 2 , and NO x are commonly found in polluted water and air. Traditional methods for pollutant removal, such as oxidation, physicochemical techniques, biotreatment, and enzymatic decomposition, often prove to be inefficient, costly, or energy-intensive. Contemporary solutions like nanofiber-based filters, activated carbon, and plant biomass also face challenges such as generating secondary contaminants and being time-consuming. In this context, triboelectric nanogenerators (TENGs) are emerging as promising alternatives. These devices harvest ambient mechanical energy and convert it to electrical energy, enabling the self-powered degradation of chemical pollutants. This Review summarizes recent progress and challenges in using TENGs as self-powered electrochemical systems (SPECs) for pollutant degradation via photocatalysis or electrocatalysis. The working principles of TENGs are discussed, focusing on their structural flexibility, operational modes, and ability to capture energy from low-frequency mechanical stimuli. The Review concludes with perspectives and suggestions for future research in this field, hoping to inspire further interest and innovation in developing TENG-based SPECs, which represent sustainable and eco-friendly solutions for pollutant treatment., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Background: Antibiotic exposure for fever/cough has been rising alarmingly, especially among children under five in low- and middle-income countries (LMICs). This excessive use could result in higher healthcare costs, and antibiotic resistance is an alarming trend in developing countries. As a result, it's crucial to look at the variables that affect antibiotic exposure and highlight the subgroups among whom antibiotic abuse is the most prevalent., Methods: We used the most recent standard Demographic and Health Survey (DHS) data for 64 LMICs. Sample weights were employed in studies to ensure exact standard errors and estimate p -values. To analyze antibiotic exposures across countries, continents, economic levels, and the top and bottom ten countries with fever/cough, we conducted descriptive statistics. Additionally, we provided accompanying bar diagrams for each descriptive finding to enhance visual understanding. For geospatial analysis, we utilized ArcGIS, a powerful tool for mapping and spatial analysis., Findings: We used data from 141,018 children under five who were reported to have had fever/cough recently in 64 LMICs. Among them, 30.4 % were exposed to antibiotics for fever/cough. Congo (68.7 %), Egypt (65.5 %), and Tajikistan (61.8 %) had the highest prevalence of antibiotic consumption across LMICs. On the other hand, Cameroon (0.3 %), Armenia (4.0 %), and Mauritania (6.1 %) had the lowest. In the final binary logistic regression, mothers that had any formal education (Primary: OR = 1.28, 95 % CI:1.07-1.53, Secondary: OR = 1.38, 95 % CI:1.14-1.67, Higher Education: OR = 1.69, 95 % CI:1.23-2.33) were more likely to expose their children to antibiotics for fever/cough than illiterate ones. Additionally, children in richer households (Richer: OR = 1.38, 95 % CI:1.15-1.66, Richest: OR = 1.46, 95 % CI:1.19-1.80) were more likely to receive antibiotics than those in poorer households., Conclusions: Antibiotic exposure for fever/cough in children under five was relatively moderate across 64 LMICs. However, the rate was incredibly high in some LMICs and incredibly low in others. The researchers recommend that the countries with high and low percentages of antibiotic exposure investigate either any possibility of antibiotic abuse or proper healthcare service at the national level., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interestsMd. Rashed Babu reports financial support was provided by IAR-10.13039/100019458UIU (Institute for Advanced Research (IAR), 10.13039/100019458United International University). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Drought is a detrimental abiotic stress that severely limits wheat growth and productivity worldwide by altering several physiological processes. Thus, understanding the mechanisms of drought tolerance is essential for the selection of drought-resilient features and drought-tolerant cultivars for wheat breeding programs. This exploratory study evaluated 14 wheat genotypes (13 relatively tolerant, one susceptible) for drought endurance based on flag leaf physiological and biochemical traits during the critical grain-filling stage in the field conditions. Measurements included six physiological, seven gas exchange, six photosystem II, six stomatal, three reactive species, seven metabolomic solutes, and two biomass traits. All parameters were significantly influenced by drought, with varying genotypic responses. Hierarchical cluster analysis (HCA) categorized genotypes into three drought tolerance groups based on trait performance. Seven genotypes in Cluster 2 (BARI Gom 26, BARI Gom 33, BD-631, BD-600, BD-9910, BD-9889, BD-637) exhibited superior drought tolerance, characterized by minimal changes in physiological traits and biomass accumulation, reduced oxidative stress markers, and increased accumulation of osmoprotectants. The innovative multi-trait genotype-ideotype distance index (MGIDI) further ranked wheat genotypes in regard to drought tolerance, identifying BARI Gom 33, BARI Gom 26, BD-9889, and BD-600 as top performers. Notably, all these top-ranking genotypes belonged to Cluster 2, previously identified as the highest-performing group in the HCA. The identified genotypes with superior drought tolerance offer valuable genetic resources for enhancing wheat productivity in water-limiting environments. Traits related to photosynthetic activity, biomass gain, leaf conductance, water stress, and osmoprotection showed high selection differentials and heritability in MGIDI analysis, indicating their potential as selection targets for drought-tolerant wheat. Overall, the strategic approaches have yielded novel insights into genotype screening that can be directly applied to deepen our understanding of drought tolerance mechanisms in wheat.

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have pointed to brain characteristics as predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over 6- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation . Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity., Competing Interests: MM, NL, FZ, KS, KU, ML, MU, AF, GS, ZZ, FN, PG, HF No competing interests declared, (© 2024, Mišić, Lee et al.)

The aim of this research was to evaluate the existing remote sensing (RS) products, various tools and techniques, and their limitations in retrieving the optically active (OA) Chlorophyll-a (CHL) concentration from transitional, coastal and inland waters. In recent decades, satellite RS technique has emerged as a vital tool for assessing surface water quality (WQ) in a cost-effective and timely manner. Initially used in the 1970s to study ocean color (OC), RS techniques have advanced significantly, enabling the retrieval of key WQ indicators like CHL, colored dissolved organic matter (CDOM), total suspended matter (TSM), turbidity (TURB), and more from satellite images. Among these indicators, CHL is particularly important as it directly signifies eutrophication. While RS technique has been reliable in estimating CHL concentrations in open waterbodies (case1 water) such as oceans, it's application in shallow, turbid waters (case2 water) like transitional, coastal and inland areas faces challenges. Interference from other OA-WQ indicators like CDOM and TSM, coupled with environmental factors such as atmospheric components, sun-glint, and adjacency effects (AE), complicate the accurate CHL estimation. To address these challenges, researchers have developed four categories of CHL retrieval algorithms: empirical, semi-empirical, hybrid and data-driven models. Empirical and data-driven methods are straightforward but require regional calibration for accuracy, whereas semi-empirical approaches, rooted in solid theoretical foundations, demand extensive ancillary optical measurements. To harness the potential of RS in WQ assessment fully, it is essential to optimize these algorithms regionally, tailoring them to the specific optical characteristics of diverse waterbodies. This optimization process is vital for integrating RS technique as a complementary data source alongside traditional monitoring approach. By addressing the impact of environmental factors and fine-tuning of CHL retrieval methods according to regional nuances, satellite RS technique can significantly enhance the reliability and effectiveness of surface WQ evaluation, thereby contributing to more informed and efficient water resource management strategies. This review emphasizes the impact of these factors, categorizes CHL retrieval algorithms into empirical, semi-empirical, hybrid and data-driven methods and applicability in terms of tools/models' reliability and challenges for the further advancement of this approaches for monitoring transitional, coastal and inland waters. To optimize the reliability of remotely sensed CHL data, regional configuration(s) of retrieving algorithms is vital. By addressing these challenges and tailoring methods to specific regions, integrating satellite RS into traditional monitoring approaches can significantly enhance surface WQ assessment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) had an adverse effect globally because it caused a global pandemic with several million deaths. This virus possesses spike protein that is cleaved or activated by Furin-like protease enzymes occurring by mammalian lung or respiratory cells to enter the mammalian body. The addition of the Furin cleavage site in SARS-CoV-2 makes it a more infectious and emerging virus than its ancestor's viruses. Phylogenetic relationships of coronavirus spike proteins have analyzed and mapped Furin recognition motif on the tree using bioinformatics tools such as GTEx, KEGG, GO, NCBI, PolyPhen-2, SNAP2, PANTHER, Hidden Markov Models (Fathmm), Phd-single-nucleotide polymorphism (SNP), I-TASSER, Modpred, Phobius, SIFT, iPTREE-STAB, and PROVEAN. During this study, it has been found that in certain regions, Furin SNPs have some relation with the susceptibility to SARS-CoV-2. Whereas in other regions, the effects are very negligible. Finally, our study demonstrates that Furin SNPs have a strong relationship with susceptibility to SARS-CoV-2. As it helps to cleave the spike protein of the virus, thus it can be targeted to inhibit at a particular site to prevent the SARS-CoV-2 from the entrance into the body., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

The integration of behavioral theories in designing antimicrobial stewardship (AMS) interventions aimed at optimizing the antimicrobial prescription in veterinary practice is highly recommended. However, little is known about the factors that influence veterinarians' antimicrobial behavior for food-producing animals in lower- and middle-income settings like Bangladesh. There is a large body of research on the factors that influence veterinarian behavior of prescribing antimicrobials, however, there is a need for more studies that use comprehensive behavior change models to develop and evaluate interventions. Applying the Capability, Opportunity, and Motivation for Behavior (COM-B) model, this qualitative study attempted to address this gap by conducting 32 one-on-one semi-structured interviews with registered veterinarians in Bangladesh. In alignment with COM-B constructs and the theoretical domain framework (TDF), thematic analysis (both inductive and deductive inferences) was performed to analyze the data and identify underlying factors that influence veterinarians' antimicrobial prescription behavior. We found that under "Capability," factors such as knowledge of antimicrobial resistance (AMR); ability to handle complex disease conditions; ability to identify the appropriate antimicrobial type, routes of administration, and potential side effects influence prescription behavior by veterinarians. Under "Opportunity," veterinarians' prescription behavior was influenced by lack of laboratory testing facilities, poor farm biosecurity, farm management and location, farming conditions, impacts of climate change, the clinical history of animals and social influence from different actors including senior figures, peers, farmers, and other informal stakeholders. Under "Motivation," national laws and guidelines serve as catalysts in reducing antimicrobial prescriptions. However, perceived consequences such as fear of treatment failure, losing clients, farmers' reliance on informal service providers, and economic losses demotivate veterinarians from reducing the prescription of antimicrobials. Additionally, veterinarians feel that reducing the burden of AMR is a shared responsibility since many informal stakeholders are involved in the administration and purchase of these medicines. Based on our results, this study recommends incorporating the factors we identified into existing or novel AMS interventions. The behavior change wheel can be used as the guiding principle while designing AMS interventions to increase capability, opportunity and motivation to reduce antimicrobial over-prescription., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Shano 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.)

Magnetic resonance imaging (MRI) is a popular imaging tool that is valuable for the early detection and monitoring of malignancies because it does not involve radiation and is noninvasive. Metal-based contrast agents (CAs) are commonly used in clinical settings despite concerns about the toxicity of free metals. Therefore, finding alternative nontoxic imaging probes is vital. In this work, we have synthesized and effectively utilized sustainable biomass lignin-based all-organic nanoconjugates linked with nitroxide radicals as MRI CAs. Lignin grafted with poly(4-glycidyloxy-2,2,6,6-tetramethylpiperidine-1-oxyl) (LPGT) exhibits a longitudinal relaxivity of 0.54 mM -1 s -1 . LPGT shows exceptional characteristics, including resistance to reduction and nontoxicity toward living organisms. LPGT displays enhanced MRI contrast in the BALB/c mouse model for a duration exceeding 4.35 h. Our primary goal is to design MRI agents that are exceptionally effective sustainable biomass-derived materials and do not require the use of metals. Nicely, LPGT offers adequate contrast enhancement at 5-fold lower (0.020 mmol/kg) than the standard dose (0.1 mmol/kg), easing worries about toxic metal buildup. Consequently, LPGT shows promise as a feasible CA for metal-free MRI.

Respiratory viral infections have a considerable detrimental impact on animal health as well as significant financial consequences in the poultry industry. The primary aim of this study is to investigate the major pathogens involved in respiratory diseases of poultry, the co-infection rate, and their epidemiological distribution in commercial chicken farms in Bangladesh. From June 2022 to December 2023, 300 pooled samples (swabs from live birds, and respiratory tissues from dead birds) were collected from the selected poultry farms where respiratory outbreaks were noticed. Samples were screened for five important respiratory pathogens circulating in Bangladesh including H9N2 low pathogenic avian influenza virus (LPAIV), H5N1 highly pathogenic avian influenza virus (HPAIV), infectious bronchitis virus (IBV), Newcastle disease virus (NDV), and infectious laryngotracheitis virus (ILTV). One-step qPCR was performed using either TaqMan probe-based or SYBR Green chemistry. A total of 140 flocks (46.67 %) were found infected with these respiratory pathogens including 18.57 % H5N1(n = 26), 20 % H9N2 (n = 28), 50 % IBV (n = 70), 37.15 % NDV (n = 52), 0.71 % ILTV (n = 1) and 26.40 % (n = 37) mixed infections were present. The present study also revealed that co-infection of several respiratory pathogens (26.40 %) caused more serious synergistic pathogenic effects and complicating factors in poultry infections. In Bangladesh, for this study, the most common season for infections in layer, broiler, broiler breeder, and Sonali is spring where these infections exhibited a consistent pattern. Nevertheless, the investigation revealed the continuous co-circulations of various respiratory viruses, resulting in a complex environment in the poultry industry. This information also helps raise farmer-level disease awareness to prevent and control the spread of viruses., Competing Interests: Disclosures The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Investigating the potential of novel data mining algorithms (DMAs) for modeling groundwater quality in coastal areas is an important requirement for groundwater resource management, especially in the coastal region of Bangladesh where groundwater is highly contaminated. In this work, the applicability of DMA, including Gaussian Process Regression (GPR), Bayesian Ridge Regression (BRR) and Artificial Neural Network (ANN), for predicting groundwater quality in coastal areas was investigated. The optuna-based optimized hyperparameter is proposed to improve the accuracy of the models, including optuna-GPR and optuna-BRR as benchmark models. Combined cross-validation (CV) and bootstrapping (B) methods were used to build six predictive models. The entropy-based coastal groundwater quality index (ECWQI) was converted into a normalized index (ECWQIn), which was divided into five classes from very poor to excellent. The self-organizing map (SOM), spatial autocorrelation and fuzzy logic model were used to identify spatial groundwater quality patterns based on 12 physicochemical variables collected from 67 groundwater wells. The SOM analysis identified four distinct spatial patterns, including EC-TDS-Cl - , MgpH, Ca 2+ K + NO₃ - , and HCO₃ - SO₄ 2- Na + F - . The results showed that both the ANN (CV) and ANN (B) models performed better than other optuna-based models during the test phase (RMSE = 0.041, MAE = 0.026, R2 = 0.971, RAE = 0.15 = 21 and CC = 0.986) and (RMSE = 0.041, MAE = 0.025, R2 = 0.969, RAE = 0.119 and CC = 0.975), respectively. SO 4 2- , Cl - and F - played an important role in the prediction accuracy. F- and SO 4 2- showed higher spatial autocorrelation, which affected groundwater quality degradation. In addition, the ANN (CV) and ANN (B) models showed a Gaussian distribution of model errors (small standard error, <1 %), indicating the stability of the model. These results indicate the efficiency of the ANN model in predicting groundwater quality in coastal areas, which would help regional water managers in real-time monitoring and management of sustainable groundwater resources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Growth and yield reduction of crops due to salt stress have become a serious issue worldwide. Trichoderma is very well known as a plant growth-promoting fungi under abiotic stress conditions. Therefore, this study was designed to investigate the effect of Trichoderma harzianum on the growth, yield, nutrient uptake, and antioxidant activity of three Indian mustard genotypes under saline condition (EC 9.28 dS m -1 ). A two-factorial ( Trichoderma and Indian mustard genotypes) pot experiment was conducted following a completely randomized design (CRD) with four replicates. Trichoderma was applied to soil as compost and suspension. The BD-7104 genotype showed better performance than Tori-7 under saline conditions. Compared to control, application of T. harzianum showed better performance in enhancing growth and yield of all the genotypes by increasing plants' tolerance to salt stress. Again, Trichoderma application increased the chlorophyll, proline, and oil content of Indian mustard. The generation of antioxidant enzymes viz., SOD, CAT, APX, and POD was significantly increased and, synthesis of H 2 O 2 and MDA was decreased to a variable degree under different Trichoderma treatments. On average, application of Trichoderma as compost enhanced seed yield by 23 % than control. The better growth and yield in Trichoderma treated plants were the results of better uptake and assimilation of N, P, S, Ca, Mg, and K and reduced uptake of Na with a lower Na/K. Overall, BD-7104 genotype can be grown in soil treated with Trichoderma as compost at a rate of TdC 12.5 for obtaining better yield and nutritional quality under salinity stress condition., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

In infectious disease outbreak modeling, there remains a gap in addressing spatiotemporal challenges present in established models. This study addresses this gap by evaluating four established hybrid neural network models for predicting influenza outbreaks. These models were analyzed by employing time series data from eight different countries to challenge the models with imposed spatial difficulties, in a month-on-month structure. The models' predictions were compared using MAPE, and RMSE, as well as graphical representations generated by employed models. The SARIMA-LSTM model excelled in achieving the lowest average RMSE score of 66.93 as well as reporting the lowest RMSE score for three out of eight countries studied. In this case also, GA-ConvLSTM-CNN model comes in second place with an average RMSE score of 68.46. Considering these results and the ability to follow the seasonal trends of the actual values, this study suggests the SARIMA-LSTM model to be more robust to spatiotemporal challenges compared with the other models under examination. This study•Evaluated established methods with unique imposed difficulty.•Addressed spatiotemporal characteristics of the data.•Proposed the SARIMA-LSTM model based on evaluation metrics., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

A high recombination rate is a major limiting factor in photocatalysis. Mitigating recombination through material engineering and photocatalyst optimization is key to enhancing photocatalytic performance. In this study, a heterostructure MoS 2 /CdS nanocomposite was synthesized through a hydrothermal method in a Teflon-lined autoclave subjected to a temperature of 200 °C for 16 hours. The resulting photocatalysts were characterized using a variety of techniques to understand their structural, surface, and optical properties. The photocatalytic activity of the as-synthesized photocatalysts was investigated by degrading methyl orange dye under both sunlight and visible light irradiation. Regardless of its MoS 2 content, the heterostructure MoS 2 /CdS NC exhibited enhanced degradation efficiency relative to that of pure CdS, MoS 2 , and commercial TiO 2 P25, with 5 wt% MoS 2 /CdS NCs exhibiting the highest degradation performance among all the evaluated photocatalysts. This behavior was justified by improved charge separation and reduced charge recombination, which were attributed to the valence band and conduction band offsets at the MoS 2 /CdS interface, as evidenced by band alignment study. The enhanced charge separation and reduced charge recombination were further validated by photoluminescence (PL), electrochemical impedance spectroscopy (EIS) and linear sweep voltammetry (LSV) measurements. Furthermore, an active species trapping experiment confirmed that electron transfer to oxygen and the subsequent formation of superoxide anions (O 2 - ) radical play the most significant roles in photocatalytic degradation under visible light illumination. Finally, the ability to reuse the MoS 2 /CdS NCs multiple times without substantial loss of activity evidenced their stability, thus paving the way for advancements in large-scale environmental remediation and other industrial applications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (This journal is © The Royal Society of Chemistry.)

Background: Rice is subjected to various environmental stresses, resulting in significant production losses. Abiotic stresses, particularly drought and salinity, are the leading causes of plant damage worldwide. The High-affinity Potassium Transporter (HKT) gene family plays an important role in enhancing crop stress tolerance by regulating physiological and enzymatic functions., Methods and Results: This study investigates the effect of overexpressing the rice HKT1;5 gene in Arabidopsis thaliana on its tolerance to salinity and drought. The OsHKT1;5 gene was introduced into Arabidopsis under the control of 35 S promoter of CaMV via floral dip transformation method. PCR confirmed the integration of the transgene into the Arabidopsis genome, while qPCR analysis showed its expression. Three transgenic lines of OsHKT1;5 were used for stress treatment and phenotypic studies. The overexpressed lines showed considerably higher germination rates, increased leaf counts, greater fresh and dry weights of the roots and shoots, higher chlorophyll contents, longer root lengths, and reduced Na + levels together with increased K + ions levels after salt and drought treatments, in comparison to wild-type plants. Furthermore, overexpressed lines exhibited higher antioxidant levels than wild-type plants under salinity and drought conditions. In addition, transgenic lines showed higher expression levels of the OsHKT1;5 gene in both roots and shoots compared to wild-type plants., Conclusions: In conclusion, this study revealed OsHKT1;5 as a promising candidate for enhancing tolerance to salinity and drought stresses in rice, marking a significant step toward developing a new rice variety with improved abiotic stress tolerance., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: All authors have read and agreed to the publication of the manuscript. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Background/Objectives : Cuminum cyminum L. has been utilized as a medicinal plant for centuries. This research sought to examine the effects of cumin methanolic extract (CMT) on the chondrogenic differentiation of human bone marrow-derived mesenchymal stem cells. Methods : Spheroids were generated using human stem cells and cultured with CMT at concentrations between 0 and 1 µg/mL. Morphological assessments and cell viability tests were conducted on days 1 and 3. Chondrogenic differentiation expression was evaluated through quantitative polymerase chain reaction, Western blot, and RNA sequencing. SOX9, FAM20B, COL2A1, and COL1A1 mRNA expression levels were determined using real-time polymerase chain reaction. Protein expression was analyzed via Western blot. Results : Throughout this study, the spheroids maintained their integrity and shape. No significant variations in spheroid diameter were observed among the groups. CMT treatment enhanced the expression of SOX9 and FAM20B. Conclusions : The methanolic extract of Cuminum cyminum facilitated chondrogenic differentiation in human bone marrow-derived mesenchymal stem cells by modulating SOX9 and FAM20B expression. This indicates its potential application in cartilage tissue engineering.

Biochar is gaining importance due to its potential to enhance soil health, crop yield, and quality. It may also promote more sustainable farming methods. This study evaluated the combined effects of biochar, vermicompost, and inorganic fertilizers on soil characteristics, growth, and yield in wheat. Ten different treatments were applied to wheat (cultivar BARI Gom-33). The tallest plants, highest total dry weight, and largest leaf area index were observed in plots where chemical fertilizers, rice husk biochar, poultry manure, and vermicompost were applied together. At harvest, the treatment containing 1/4 recommended fertilizer dose (RFD) + 1/4 poultry manure biochar + 1/4 rice husk biochar + 1/4 vermicompost produced the best yield and yield-contributing factors. The combination of biochar, vermicompost, and inorganic fertilizers increased grain production by 43.23%-79.48% compared with the control. These treatments also improved soil health by increasing available phosphorus, organic matter, carbon-to-nitrogen ratio, and organic carbon. In conclusion, the combined application of 1/4 RFD, 1/4 poultry manure biochar, 1/4 rice husk biochar, and 1/4 vermicompost can replace the sole use of chemical fertilizers and serve as a key component for sustainable crop production., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Ahmed Khairul Hasan et al.)