Background: Abnormal uterine bleeding (AUB) in perimenopausal women may indicate a spectrum of endometrial pathology ranging from atrophic change to carcinoma, and transvaginal sonographic measurement of endometrial thickness (ET) has been proposed as a non-invasive tool to triage women who require histopathological sampling. This study aimed to determine the distribution of ET and histopathological diagnoses among perimenopausal women with AUB and to evaluate the diagnostic performance of ET cut-off values in predicting endometrial pathology. Materials & Methods: This cross-sectional study was conducted in the Department of Radiology and Imaging, Sylhet MAG Osmani Medical College Hospital, Bangladesh, in collaboration with the Departments of Obstetrics and Gynaecology and Pathology, from July 2021 to June 2023. Ninety-seven perimenopausal women aged 39 years and above presenting with AUB underwent transvaginal sonography followed by histopathological evaluation of endometrial samples. ET was correlated with histopathological findings using the chi-square test. Results: The mean age was 43.04±2.54 years; menorrhagia was the commonest symptom (51.5%). The overall mean ET was 7.98±3.32 mm, ranging from 5.83±1.06 mm in atrophic endometrium to 12.15±2.36 mm in endometrial polyps. ET was significantly associated with histopathological diagnosis (χ²=21.74, p<0.001). An ET cut-off of >4.9 mm gave 100% sensitivity and negative predictive value but 24.0% specificity; >7.9 mm gave the best balance (66.0% sensitivity, 76.0% specificity, 71.1% accuracy); >11.9 mm gave 100% specificity and positive predictive value but 29.8% sensitivity. Conclusion: Endometrial thickness correlates significantly with histopathological diagnosis in perimenopausal women with AUB. No single cut-off simultaneously optimises both rule-in and rule-out performance; a graded diagnostic approach combining ET with clinical judgement is recommended before proceeding to invasive sampling.

Chemotherapy remains a cornerstone in cancer management; however, its non-selective cytotoxic effects frequently result in significant oral mucosal complications that adversely affect patient wellbeing and treatment outcomes. The oral mucosa is particularly susceptible to injury because of its rapid epithelial turnover, rich vascularity, and constant exposure to mechanical and microbial insults. Chemotherapy-induced oral changes commonly include oral mucositis, xerostomia, opportunistic infections, dysgeusia, ulcerative lesions, mucosal pigmentation, and bleeding manifestations. Among these, oral mucositis is the most common and debilitating complication, often leading to pain, dysphagia, impaired nutrition, reduced quality of life, and interruption of cancer therapy. The pathogenesis involves direct epithelial toxicity, oxidative stress, inflammatory cytokine activation, and breakdown of the mucosal barrier, predisposing patients to secondary infections and delayed healing. Early diagnosis, preventive oral care, and multidisciplinary management are essential for minimizing morbidity and improving therapeutic outcomes. This review summarizes the pathogenesis, clinical manifestations, diagnosis, prevention, and management of chemotherapy-induced oral mucosal changes.

This study compares the impact of migration on rural employment in Nigeria and India from 2005 to 2023, exploring its impact on the global economy. Using a dynamic panel Generalized Method of Moments (GMM) model with the Arellano-Bond estimator, the analysis covers 34 observations across two countries, sourced from the World Bank, Nigeria’s National Bureau of Statistics, and India’s Periodic Labour Force Survey. Rural employment rate is the dependent variable, with migration rate as the key independent variable, alongside controls for rural population, foreign direct investment (FDI), and agricultural output. Findings indicate that, a 1% increase in migration reduces rural employment by 1.5% (p < 0.05), driven by labor supply declines in Nigeria (1.2% to 1.6%) and India (0.4% to 0.55%). Rural population and agricultural output positively influence employment, while FDI shows a negative effect due to urban bias. Globally, Nigeria’s remittances (6% of GDP) and India’s urban productivity enhance international labor markets and supply chains, contributing to a $2 trillion economy. Policy recommendations include rural job creation through agricultural technology, economic zones in India, remittance-funded entrepreneurship in Nigeria, and FDI targeting rural development.

Advanced multifunctional nanomaterials are emerging as versatile platforms for addressing interconnected energy and environmental challenges through tunable composition, high surface area, engineered interfaces, and nanoscale reactivity. This review critically examines the design, synthesis, functionalization, and application of metal, metal oxide, carbon-based, polymeric, porous, two-dimensional, and hybrid nanomaterials. Particular emphasis is placed on green synthesis, renewable precursors, low-impact fabrication, waste-derived feedstocks, scalability, and life-cycle sustainability. The role of surface functionalization, heteroatom doping, defect engineering, heterostructure formation, and interfacial charge transfer in controlling catalytic, optical, electrochemical, and adsorption properties is systematically discussed. Applications in heterogeneous catalysis, photocatalytic hydrogen production, carbon dioxide conversion, pollutant degradation, rechargeable batteries, supercapacitors, and emerging flexible storage devices are evaluated using structure–property–performance relationships. The review also explores nanomaterial-enabled water purification, membrane separation, antimicrobial treatment, and chemical, electrochemical, optical, and gas sensing, including integrated remediation–sensing platforms for real-time monitoring. Current barriers involving toxicity, agglomeration, instability, poor selectivity, recovery, reproducibility, standardization, and industrial scale-up are identified. Finally, future directions highlight artificial-intelligence-guided discovery, operando characterization, circular material design, self-healing systems, and safe, economical deployment, establishing a unified roadmap for sustainable multifunctional nanotechnology across energy conversion, storage, environmental remediation, and chemical detection under realistic operating conditions and across diverse environmental matrices worldwide.

The transition toward carbon-neutral chemical manufacturing requires catalytic systems that can convert abundant waste molecules into value-added chemicals under mild, renewable-energy-driven conditions. Single-atom electrocatalysts (SAECs), featuring isolated metal centers anchored on tailored supports, offer maximum atom utilization, tunable coordination environments, and well-defined active sites for complex multielectron reactions. This review critically examines the emerging role of artificial intelligence in accelerating the discovery, optimization, and mechanistic understanding of SAECs for carbon dioxide electroreduction and green ammonia synthesis through nitrate conversion. First, fundamental design principles are discussed, including metal–support interactions, coordination engineering, electronic-structure modulation, and stability limitations. Next, machine learning, density functional theory integration, high-throughput screening, explainable descriptors, and self-driving laboratory concepts are evaluated as tools for rational catalyst development. Particular emphasis is placed on CO₂ valorization pathways toward CO, formate, hydrocarbons, and alcohols, together with nitrate-to-ammonia conversion as a sustainable nitrogen-recycling strategy. Advanced in situ/operando characterization, performance benchmarking, selectivity control, and degradation mechanisms are also assessed. Finally, this review highlights current barriers related to data quality, catalyst durability, reactor design, product separation, techno-economic feasibility, and industrial scale-up. The article provides a forward-looking framework for integrating AI, atomically precise catalysis, and renewable electrosynthesis in future sustainable chemical manufacturing.

Micro- and nanoplastics have emerged as biologically active contaminants that connect environmental pollution with ecosystem dysfunction, microbial imbalance, animal toxicity, and human health uncertainty. This One Health review critically synthesizes current evidence on the sources, physicochemical characteristics, environmental fate, biological toxicity, microbial interactions, and medical relevance of micro- and nanoplastics in biological systems. These particles originate from primary manufactured materials and secondary fragmentation of plastic waste, synthetic textiles, agricultural plastics, tyre wear, packaging, wastewater, and atmospheric deposition. Their toxicity is strongly influenced by particle size, shape, polymer type, surface chemistry, aging, biofilm formation, and contaminant adsorption. In plants and ecosystems, micro- and nanoplastics can impair seed germination, root architecture, photosynthesis, nutrient cycling, soil microbial activity, crop productivity, and ecological stability. Animal studies further demonstrate oxidative stress, inflammation, neurotoxicity, reproductive injury, developmental disruption, gut damage, and metabolic disturbance, although many experiments still rely on high doses and pristine laboratory particles. Microplastics also create plastisphere biofilms that alter soil, aquatic, and gut microbiomes and may facilitate pathogen survival and antimicrobial resistance gene dissemination. Human exposure occurs through food, drinking water, air, dust, and consumer products, with increasing detection in blood, lung, placenta, breast milk, vascular tissues, and other biological samples. However, causal links with chronic disease remain uncertain due to limitations in detection, dose standardization, contamination control, and long-term epidemiological evidence. Overall, micro- and nanoplastics represent an emerging cross-sectoral biological threat requiring standardized monitoring, realistic toxicology, biosensor development, biotechnology-based remediation, safer material design, and integrated One Health risk assessment.

Background: Preterm neonates with perinatal asphyxia are at high risk of seizures, yet optimal first-line anticonvulsant therapy remains uncertain. Phenobarbitone has traditionally been used but carries significant adverse effects, while levetiracetam offers a potentially safer alternative. This study compared the efficacy and safety of levetiracetam versus phenobarbitone in preterm neonates with post-asphyxial seizures. Methods: This open-label randomized controlled trial enrolled 72 preterm neonates (31 to <37 weeks gestation) with convulsions due to perinatal asphyxia (HIE stage II/III). Neonates were randomized to receive either intravenous levetiracetam (20 mg/kg loading, 10 mg/kg/dose 12 hourly maintenance) or phenobarbitone (20-40 mg/kg loading, 5 mg/kg/day maintenance). Primary outcomes included seizure control, time to seizure cessation and adverse effects. Results: Seizure control with monotherapy was significantly higher in the levetiracetam group (72.22%) compared to phenobarbitone (44.44%) (p=0.004). The need for additional anticonvulsants was substantially lower in the levetiracetam group (27.78% vs. 55.6%, p=0.004). Seizure control within 12 hours was achieved in 83.33% of levetiracetam-treated neonates versus 50.0% in the phenobarbitone group (p=0.039). Adverse effects occurred significantly less frequently with levetiracetam (5.56% vs. 27.78%, p=0.024), with somnolence being the most common adverse effect in both groups. Conclusion: Levetiracetam demonstrated superior efficacy with more rapid seizure control and a significantly better safety profile compared to phenobarbitone in preterm neonates with post-asphyxial seizures. These findings support levetiracetam as a favorable first-line agent in this vulnerable population.