ABSTRACT The tannery industry faces a serious challenge in managing solid waste sustainably. The most hazardous form of solid waste is chromium-tanned solid waste, mainly consisting of leather shavings (LS) with elevated chromium levels. This study explored anaerobic co-digestion of LS with cow dung (CD), sawdust (SD), and food waste (FW) to enhance biogas production and waste stabilization. LS exhibited a low carbon-to-nitrogen ratio (3.01) and acidic pH (4.51 ± 0.42), necessitating co-substrate blending to optimize digestion conditions. Laboratory-scale batch reactors operated at 28 ± 3°C for 40 days revealed that the LS:CD:FW (1:1:1) mixture achieved the highest cumulative biogas yield (5895.2 mL kg−1 solid feed), methane content (53.63%), volatile solids reduction (51.99%), total organic carbon reduction (47.55%), and chemical oxygen demand removal (53.8%). In contrast, the LS:CD:SD (1:1:1) mixture yielded the lowest biogas output (3910.3 mL kg−1) due to high lignocellulosic content in SD. Notably, the digestate from LS:CD:FW contained 88.13 ppm of chromium, remaining below the 100 ppm soil safety threshold, indicating its potential for safe disposal. Results demonstrate that co-digestion with nutrient-rich substrates (CD, FW) significantly improves methane recovery and organic matter degradation from LS, while ensuring digestate safety. This approach offers a viable pathway for renewable energy generation and environmentally safer disposal of chromium-laden tannery waste.

BackgroundBangladesh’s diabetes burden is accelerating alongside rapid urbanisation and population ageing. Contemporary, population-representative risk estimates are needed to guide prevention.MethodsWe analysed 13,835 adults in the 2022 Bangladesh Demographic and Health Survey. Diabetes was defined as fasting plasma glucose :ge: 7 mmol/L or current use of diabetes medication. Associations with demographic, socioeconomic and clinical covariates were modelled using a Bayesian survey-weighted logistic mixed model with primary sampling unit random intercepts; design-unadjusted GLMM and survey-weighted GLM served as comparators. Posterior medians and 95% credible intervals (CrI) are reported.ResultsAge, adiposity and hypertension dominated the risk profile. Relative to 18–24 years, the odds of diabetes rose to 5.13 (4.22–6.24) for adults :ge: 65 years; overweight and obesity increased odds to 1.37 (1.22–1.53) and 1.78 (1.50–2.10), whereas underweight had lower odds at 0.80 (0.69–0.92). Hypertension conferred an odds ratio of 1.52 (1.35–1.70). Rural residence 0.75 (0.65–0.87) and residence in Rajshahi, Mymensingh or Khulna divisions (:approx: 0.55–0.66) were lower, while the richest wealth quintile carried higher risk at 1.77 (1.51–2.10). Model diagnostics were favourable: AUC = 0.79 indicates good discrimination; WAIC = 10,501 improved by :> 600 points versus the unweighted GLMM and survey-weighted GLM; and residual spatial autocorrelation was negligible (Moran’s I = 0.06, p = 0.14).ConclusionsDiabetes in Bangladesh clusters among older adults, overweight/obese individuals, those with hypertension, and the socio-economically affluent, while remaining lower in rural and several northern divisions. Priority actions include age- and BMI-targeted screening, integrated hypertension–diabetes services, and urban lifestyle interventions, particularly in Dhaka and other high-prevalence regions. The Bayesian survey-weighted mixed-model framework yields policy-relevant, nationally generalisable estimates and offers a robust platform for tracking Sustainable Development Goal 3.4 indicators.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12889-025-23762-5.

This work reviews percolation-related phenomena in porous organosilica glass (OSG) low-k dielectrics and their critical impact on mass transport, electrical conductivity, mechanical integrity, and dielectric breakdown. We discuss how leakage current arises from the formation of minimal percolating conductive paths along pores and defect chains, while dielectric breakdown requires system-spanning pore connectivity, resulting in a higher effective percolation threshold. Mechanical properties similarly degrade when pores coalesce into a connected network, exhibiting multiple percolation thresholds due to both chemical network modifications and porosity. Experimental trends demonstrate that leakage current increases sharply at low porosity, whereas breakdown voltage and mechanical stiffness collapse at higher porosity levels (~20%–30%). We highlight that distinct percolation classes govern transport, mechanical, and nonlinear phenomena, with correlation length and diffusion timescales providing a unified framework for understanding these effects. The analysis underscores the fundamental role of network connectivity in determining the performance of organosilicate glass-based ultra-low-k dielectrics and offers guidance for material design strategies aimed at simultaneously improving electrical, mechanical, and chemical robustness.

As prevalence of obesity is emerging in urban settings of Bangladesh, the study aims to investigate the effects of calorie-restriction (CR) diet in weight reduction by applying the local South Asian dietary pattern. An 8-weeks randomized controlled trial among 120 young adults aged 18-35 year with overweight and obesity from Dhaka city were randomized where 60 participants were in a calorie-restriction diet group with South Asian food pattern, and the rest in a control group followed an ad libitum diet without any dietary counselling for 8 weeks. Participants underwent weight measurement at two weeks' intervals to determine the change in body weight with continuous weight loss motivation and rearranged meal plans to avoid repetition. Mean 2.47kg (95% CI: 1.94, 3.01; p < 0.001) weight reduction in CR group (n = 58; 2 dropouts) group and mean 0.313kg (95% CI: -0.36,0.053; p < 0.142) weight gain in control (n = 60) group was observed. The Body Mass Index dropped from mean 26.68kg/m2 (95% CI: 26.02,27.34; p < 0.001) to 25.65kg/m2 (95% CI: 24.99,26.32; p < 0.001) in the CR group. The results of this study of weight reduction intervention provide primary evidence of successful weight loss by following local food patterns. It is an attempt to evaluate the feasibility of South Asian diet in established dietary regime. Further studies on different biochemical parameters (e.g., lipid profile, glucose) and long-term trials in the South Asian region are recommended. This trial is retrospectively registered at anzctr.org.au as ACTRN12625000219482 at 27th March, 2025.

Acute myeloid leukemia (AML) is an aggressive hematological malignancy with a poor prognosis. While the medicinal plant Eclipta prostrata has shown promising anticancer properties against AML, its underlying mechanisms against AML remain largely unexplored. Hence, this study aimed to unveil the molecular mechanisms of E. prostrata, identify therapeutic targets, detect regulatory elements, and discover potential biomarkers for AML using comprehensive in-silico analyses. We implemented an integrated computational approach combining network pharmacology, molecular docking, molecular dynamics simulations, 3D-QSAR modeling, gene regulatory network, gene expression, patient survival, and cancer hallmarks analysis to investigate the mechanism of action of E. prostrata against AML. Our computational approaches identified 12 potential anti-cancer compounds from E. prostrata. Molecular docking revealed strong binding affinities of Kaempferol (-8.931 kcal/mol) and Apigenin (-8.752 kcal/mol) to FLT3, compared to control Pacritinib (-5.403 kcal/mol). Tricetin (-8.634 kcal/mol) and Diosmetin (-7.780 kcal/mol) showed strong binding to PIM1 compared to control SEL24 (-6.385 kcal/mol). Post-molecular dynamics simulation MM-GBSA analysis further confirmed these interactions, with binding free energies for FLT3: Kaempferol (-73.75 kcal/mol), Apigenin (-68.76 kcal/mol), Pacritinib (-51.27 kcal/mol); and for PIM1: Tricetin (-64.28 kcal/mol), Diosmetin (-52.2 kcal/mol), SEL24 (-53.38 kcal/mol). Predicted IC50 values showed promising results for PIM1 inhibition by Tricetin (406.44 nM) and Diosmetin (523.60 nM), and for FLT3 inhibition by Kaempferol (493.17 nM) and Apigenin (588.84 nM). The developed 3D-QSAR models showed robust predictive power (PIM1: R2 = 0.96, Q2 = 0.93; FLT3: R2 = 0.95, Q2 = 0.85). Key regulatory elements were identified, including microRNAs (hsa-mir-335-5p, hsa-mir-150-5p, has-mir-1324) and transcription factors (ABL1, RUNX1, SP1, PML) regulating the target genes. FLT3 and MPO were identified as specific diagnostic and prognostic biomarkers for AML. This comprehensive in-silico analysis revealed promising therapeutic compounds from E. prostrata targeting FLT3 and PIM1, along with novel biomarker potentials of FLT3 and MPO for improved AML diagnosis and prognosis, subject to further experimental validation.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-18547-0.

ABSTRACTBackground and AimsGetting married young is a common system in developing nations, and it has detrimental effects on the health of the women involved as well as the unborn children. This study aims to identify the key factors affecting early marriage among Bangladeshi women using BDHS‐2022 data, focusing on region, education, residence type, employment status, and religion by considering the best‐fit model among Cox proportional hazard (Cox‐PH) and various accelerated failure time (AFT) survival models.MethodsThis study used survival analysis techniques, such as Cox proportional hazard model and accelerated failure time (AFT) models, using data from the Bangladesh Demographic and Health Survey 2022 (BDHS‐2022). The Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) were used to choose the models, and based on these criteria, the log logistic AFT model was identified as the best‐fitting model.ResultsThe women who had an early marriage have a much higher frequency (65.9%) than those who did not have early marriage (34.1%). The log logistic AFT model identified several significant factors influencing early marriage. The hazard ratio of getting early marriage of respondents with primary (HR: 1.017, p < 0.05) and secondary education (HR: 1.024, p < 0.01) had a higher risk compared to those with no education, while the same results are shown in the respondent's husband's education. Respondent's currently working had a lower risk of getting married young (HR: 0.988, p < 0.01). Additionally, rural residence was associated with a higher risk (HR: 1.019, p < 0.001) than urban residence. These results emphasize that the educational level of both male and female, living area, and employment status are influencing factors that affect early marriage.ConclusionEarly marriage in Bangladesh is influenced by socioeconomic and demographic factors, emphasizing the need for targeted interventions focusing on education, employment, and regional disparities to delay marriage and improve women's social outcomes.

One of the most crucial respiratory pathogens in the world, namely human metapneumovirus (HMPV), causes acute upper and lower respiratory tract infection. The HMPV Fusion (F) protein is a vital element for viral entry and is the sole target of neutralizing antibodies, making it a prime target for drug and vaccine development. Targeting the Fusion (F) protein of HMPV for inhibition has emerged as a potential therapeutic strategy, particularly in respiratory infection treatment. We aimed to identify potential inhibitors against HMPV F protein by molecular docking and molecular dynamics study. Through molecular docking, we were able to identify 16 lead compounds derived from Dolichos lablab (DL). These compounds exhibited robust binding affinities with the HMPV F protein, with better docking scores compared to the ribavirin inhibitor as a control with a −6.7 kcal/mol docking score. Among these top-ranked compounds, Brassinolide (CID_115196), Quercetin (CID_5280343), and 2’-Hydroxygenistein (CID_5282074) demonstrated favorable molecular, pharmacokinetics, and drug-like properties, promising biological activities, and acceptable toxicity profiles. Furthermore, Brassinolide, Quercetin, and 2’-Hydroxygenistein were found to be promising drug inhibitors with the greatest binding stability against the HMPV F protein compared to the ribavirin inhibitor, which is validated by the highest protein-ligand interactions and lowest Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (Rg) values using 100 ns molecular dynamic simulation. Our study provides valuable insights into the therapeutic potential of DL compounds as potential or hypothetical inhibitors for HMPV F protein having three promising candidates- Brassinolide, Quercetin, and 2’-Hydroxygenistein. These results warrant further validation through detailed in vitro and in vivo investigations.

Student dropout is a significant challenge in Bangladesh, with serious impacts on both educational and socio-economic outcomes. This study investigates the factors influencing school dropout among students aged 6–24 years, employing data from the 2019 Multiple Indicator Cluster Survey (MICS). The research integrates statistical analysis with machine learning (ML) techniques and explainable AI (XAI) to identify key predictors and enhance model interpretability. Initially, descriptive and inferential statistical analyses were applied to identify significant predictors and guide feature selection. The hybrid feature selection strategy, combining statistical significance and model-based importance measures, revealed key features. Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. Model performance was evaluated using accuracy, precision, recall, and an F1 score. The XGB model achieved the best performance with an accuracy of 94.4%, followed by the RF model. To interpret model predictions and ensure transparency, SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-Agnostic Explanations) were employed in tandem with the statistical analyses. Key factors influencing student dropout included age, sex, completed grade, last education grade, division, wealth index, father’s and mother’s education. These insights offer a data-driven foundation for policymakers to develop targeted intervention strategies aimed at reducing student dropout rates and improving educational outcomes in Bangladesh.

ABSTRACT This study explored the effects of eucalyptus boundary plantation on the physicochemical properties of agricultural soils. Two strategies were applied : (Strategy 1) comparing soil properties of rice fields surrounded or not by eucalyptus trees, and (Strategy 2) comparing soil properties as a function of distance (0, 10, and 20 m) from eucalyptus boundary. Both surface and sub-surface soil samples were collected and analyzedfor pH, electrical conductivity (EC), organic matter (OM), moisture, and the contents of macro-nutrients (N, P, K, S, Ca, and Mg) and micro-nutrients (Na, Cu, Zn, Mn, and Fe). The results from strategy 1 revealed that eucalyptus boundary significantly (p < 0.05) decreased soil pH, moisture, and Fe, while increases EC, OM, macro-nutrients compared to non-eucalyptus fields. Strategy 2 (ANOVA) exhibited significant (p < 0.05) effects on Ca and major micro-nutrients. Total Ca decreased with distance from eucalyptus boundaries, while Cu, Zn, and Fe increased. No significant distance-related differences were found for pH, EC, OM, moisture, or other macro-nutrients. Correlation analysis highlighted significant interrelationships among soil parameters and their associations with boundary proximity. The findings unveil that eucalyptus boundary plantations enhance OM and macro-nutrients in surface soils but can reduce moisture and alter micro-nutrient contents.