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This study examined university students’ perceptions and practices of using ChatGPT through a qualitative approach, employing semi-structured, in-depth interviews with 20 Khulna University students. Using thematic analysis, the research identified key themes, including both academic and non-academic motivations, with applications ranging from assignments and research to entertainment. Despite limitations such as false references and predetermined feedback, students found ChatGPT efficient and useful both inside and outside the classroom. However, concerns about academic integrity arose, as some students devised creative ways to bypass existing plagiarism detection systems. Ethical considerations emerged regarding responsible AI use, underscoring the need for clear guidelines and training to ensure proper referencing and the development of critical thinking skills. Future research should focus on continuous evaluation and the implementation of support services to encourage the responsible integration of ChatGPT in university settings.

Dengue, the mosquito borne disease has become a growing public health threat in Bangladesh due to its gradual increasing morbidity and mortality since 2000. In 2019, the country witnessed the worst ever dengue outbreak. The present study was conducted to characterize the socio-economic factors and knowledge, attitude and practice (KAP) status towards dengue among the people of Bangladesh. A cross-sectional study was conducted with 1,010 randomly selected respondents from nine different administrative regions of Bangladesh between July and November 2019. Although majority (93.8%) of the respondents had heard about dengue, however, they had still misconceptions about Aedes breeding habitat. Around half of the study population (45.7%) had mistaken belief that Aedes can breed in dirty water and 43.1% knew that Aedes mosquito usually bites around sunrise and sunset. Fever indication was found in 36.6% of people which is the most common symptom of dengue. Among the socio-demographic variables, the level of education of the respondents was identified as an independent predictor for both knowledge (p<0.05) and awareness (p<0.05) of dengue. The preventive practice level was moderately less than the knowledge level though there was a significant association (p<0.05) existed between knowledge and preventive practices. Our study noted that TV/Radio is an effective predominant source of information about dengue fever. As dengue is emerging in Bangladesh, there is an urgent need to increase health promotion activities through campaigns for eliminating the misconception and considerable knowledge gaps about dengue.

High blood pressure is a major risk factor for premature death. Leisure-time physical activities have been recommended to control hypertension. Studies examining how leisure-time physical activity affects blood pressure have found mixed results. We aimed to conduct a systematic review examining the effect of leisure-time physical activity (LTPA) on lowering blood pressure among adults living with hypertension. We searched studies in Embase, Medline/PubMed, Web of Science, Physical Education Index, Scopus and CENTRAL (the Cochrane Library). The primary outcome variables were systolic blood pressure (SBP) and diastolic blood pressure (DBP). This systematic review is registered on PROSPERO (CRD42021260751). We included 17 studies out of 12,046 screened articles in this review. Moderate-intensity LTPA (all types) reduced SBP compared to the non-intervention control group (MD −5.35 mm Hg, 95% CI −8.06 to −2.65, nine trials, n = 531, low certainty of the evidence). Mean DBP was reduced by −4.76 mm Hg (95% CI −8.35 to −1.17, nine trials, n = 531, low certainty of the evidence) in all types of LTPA (moderate intensity) group compared to the non-intervention control group. Leisure-time walking reduced mean SBP by −8.36 mmHg, 95% CI −13.39 to −3.32, three trials, n = 128, low certainty of the evidence). Walking during leisure time reduced −5.03 mmHg mean DBP, 95% CI −8.23 to −1.84, three trials, n = 128, low certainty of the evidence). Performing physical activity during free time probably reduces SBP and DBP (low certainty of the evidence) among adults with hypertension.

The importance of bio-robotics has been increasing day by day. Researchers are trying to mimic nature in a more creative way so that the system can easily adapt to the complex nature and its environment. Hence, bio-robotic grippers play a role in the physical connection between the environment and the bio-robotics system. While handling the physical world using a bio-robotic gripper, complexity occurs in the feedback system, where the sensor plays a vital role. Therefore, a human-centered gripper sensor can have a good impact on the bio-robotics field. But categorical classification and the selection process are not very systematic. This review paper follows the PRISMA methodology to summarize the previous works on bio-robotic gripper sensors and their selection process. This paper discusses challenges in soft robotic systems, the importance of sensing systems in facilitating critical control mechanisms, along with their selection considerations. Furthermore, a classification of soft actuation based on grippers has been introduced. Moreover, some unique characteristics of soft robotic sensors are explored, namely compliance, flexibility, multifunctionality, sensor nature, surface properties, and material requirements. In addition, a categorization of sensors for soft robotic grippers in terms of modalities has been established, ranging from the tactile and force sensor to the slippage sensor. Various tactile sensors, ranging from piezoelectric sensing to optical sensing, are explored as they are of the utmost importance in soft grippers to effectively address the increasing requirements for intelligence and automation. Finally, taking everything into consideration, a flow diagram has been suggested for selecting sensors specific to soft robotic applications.

Antibiotic-free broiler meat production is becoming increasingly popular worldwide due to consumer perception that it is superior to conventional broiler meat. Globally, broiler farming impacts the income generation of low-income households, helping to alleviate poverty and secure food in the countryside and in semi-municipal societies. For decades, antibiotics have been utilized in the poultry industry to prevent and treat diseases and promote growth. This practice contributes to the development of drug-resistant bacteria in livestock, including poultry, and humans through the food chain, posing a global public health threat. Additionally, consumer demand for antibiotic-free broiler meat is increasing. However, there are many challenges that need to be overcome by adopting suitable strategies to produce antibiotic-free broiler meat with regards to food safety and chicken welfare issues. Herein, we focus on the importance and current scenario of antibiotic use, prospects, and challenges in the production of sustainable antibiotic-free broiler meat, emphasizing broiler farming in the context of Bangladesh. Moreover, we also discuss the need for and challenges of antibiotic alternatives and provide a future outlook for antibiotic-free broiler meat production.

Dengue fever (DF), a potentially fatal mosquito-transmitted viral disease caused by dengue virus (DENV) infections (DENVI), stands as the predominant arthropod-borne viral illness worldwide, presenting a significant global health challenge. DENV-mediated proteins/proteases interact with host proteins to develop the infection. Despite the severity of DENVI, the infection-causing host key-genes (hKGs), their pathogenetic processes, and inhibitors/activators are not yet rigorously investigated. This study aimed to disclose DENVI-causing hKGs, highlighting their pathogenetic mechanisms and therapeutic agents. At first, 115 host differentially expressed genes (hDEGs) between DENVI and control samples were identified by employing the LIMMA statistical approach. Through protein-protein interaction (PPI) network analysis, the top nine hDEGs (CDK1, BIRC5, TYMS, KIF20A, CCNB2, CDC20, AURKB, TK1, and PTEN) were detected as the infection-causing hGBs or host key-genes (hKGs). Among these hKGs, six genes (CDK1, BIRC5, TYMS, KIF20A, CCNB2, and TK1) have been emphasized as the DENVI-causing genes by the literature review. Functional enrichment analysis showed how hKGs orchestrate viral infection processes by disrupting cell cycles and immune responses. CDK1 and AURKB divert mitotic machinery to support viral replication, while PTEN and BIRC5 inhibit MAVS-MDA5 pathways to suppress interferon responses. In the nucleus, CDK1 and TYMS manipulate host transcription to favor viral processes. Key pathways identified through KEGG analysis include cell cycle and p53 signaling, explaining DENV-induced thrombocytopenia and dysregulated apoptosis. The regulatory network analysis identified five transcription factors (FOXC1, GATA2, RELA, TP53, PPARG) as the transcriptomic regulators of hKGs. The regulators FOXC1 and RELA influence EMT and inflammatory responses, and PPARG’s involvement in lipid metabolism correlates with Dengue Shock Syndrome severity, while miR-103a-3p enhances viral replication by targeting the OTUD4/p38 MAPK pathway. Finally, hKGs-guided three drug candidates (ENTRECTINIB, IMATINIB, and QL47) were selected by molecular docking analysis. These findings provide valuable insights that could significantly impact dengue fever diagnosis and treatment strategies.

Background In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress. Results For functioning factors and subfactors, several machine learning models like Logistics Regression, Random Forest, AdaBoost, Naïve Bayes, Neural Network, kNN, CN2 rule Inducer, Decision Tree, Quadratic Classifier were compared with standard metrics e.g., F1, AUC, CA. For certainty info gain, gain ratio, gini index were revealed for both cervical and ovarian cancer. Attributes were ranked using different feature selection evaluators. Then the most significant analysis was made with the significant factors. Factors like children, age of first intercourse, age of husband, Pap test, age are the most significant factors of cervical cancer. On the other hand, genital area infection, pregnancy problems, use of drugs, abortion, and the number of children are important factors of ovarian cancer. Conclusion Resulting factors were merged, categorized, weighted according to their significance level. The categorized factors were indexed using ranker algorithm which provides them a weightage value. An algorithm has been formulated afterward which can be used to predict the risk level of cervical and ovarian cancer in relation to women's mental health. The research will have a great impact on the low incoming country like Bangladesh as most women in low incoming nations were unaware of it. As these two can be described as the most sensitive cancers to women, the development of the application from algorithm will also help to reduce women’s mental stress. More data and parameters will be added in future for research in this perspective.

Pediatric acute-myeloid-leukemia (pAML) is an aggressive malignancy and the second most common blood cancer in children. In spite of significant advances in the frontline therapeutic approaches, approximately 50% of pAML patients show poor prognosis and relapse. Though drugs show positive response against the cancer cells initially, however, it becomes resistant in the long run of treatment, requiring the use of alternative drugs. Therefore, this study aimed to discover pAML-causing druggable molecular signatures highlighting their pathogenetic processes and alternative therapeutic agents. To address these issues, at first, we performed an integrated single-cell RNA sequencing (scRNA-seq) profile analysis of two datasets with accession IDs GSE154109 and GSE235923, which revealed 6 pAML-related key cell types (Erythroid cells, GdT-cells, Naive B-cells, Naive CD4 T-cells, Non-Classical Monocytes, and T-regs) and 198 common differentially expressed genes (cDEGs) between pAML and healthy groups. The protein-protein interaction (PPI) analysis yielded top-ranked eight cDEGs (JUN, MDM2, FOS, SOD2, FBXW7, CHD3, MCL1, and MAP2K1) as common key genes (cKGs) across the key cell types. Disease-cKGs enrichment analysis further confirmed the relevance of these genes to pAML and other leukemic diseases. Regulatory network analysis identified top four transcription factors (FOXC1, GATA2, RELA, and TP53) and three microRNAs (hsa-let-7a-5p, hsa-let-7e-5p, hsa-miR-15a-5p) that regulate these cKGs. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis results reflected their potential roles in pAML pathogenesis. Pathway perturbation analysis through gene-set enrichment analysis (GSEA) tool identified significantly perturbed pathways, highlighting how they are altered in pAML environment and how the cKGs are linked in the process. Subsequently, three potential therapeutic candidates (IRINOTECAN HYDROCHLORIDE, IMATINIB and IBRUTINIB) were disclosed through an integrative strategy combining molecular docking, drug-likeness, ADME/T, and DFT analyses. Molecular dynamics (MD) simulation studies for the top three drug-target complexes indicated the stability of complexes. Thus, the findings potentially offer valuable insights for pAML pathogenesis and effective therapeutic candidates for pAML patients.

The empowerment of women is a global concern with significant implications both for individual well-being and societal progress. This study assessed the status of women's empowerment and its relationship with dietary diversity among Tripura ethnic women in Khagrachari district, Bangladesh. A cross-sectional survey was conducted with 230 randomly selected reproductive-aged women with a predesigned questionnaire. Significant relationships between socio-economic characteristics, women's empowerment, women's role in household food management, and Dietary Diversity Score (DDS) were examined by performing binary logistic regression analysis with the aid of Stata/MP 16.0 software. The study findings revealed that only 13.9% (32) of the Tripura tribal women are empowered, with a mean aggregated empowerment score of 0.51 ± 0.24. Dietary assessment showed that 25% of the respondents consumed fewer than five food groups, while 15% reported no intake of Animal Source Foods (ASFs). Furthermore, several factors appear to be associated with dietary diversity and ASFs consumption of women including education, (AOR = 3.80, 95% CI: 1.66-8.69; AOR = 3.04, 95% CI: 1.23-7.48), household structure, (AOR = 4.93, 95% CI: 2.24-10.87; AOR = 3.16, 95% CI: 1.32-7.57) and meal preparation roles (ASFs; AOR = 3.30, 95% CI: 1.12-9.75). Notably, empowered women had 10.53 times higher odds (AOR = 10.53, 95% CI: 1.40-79.10) of achieving greater DDS compared to their disempowered counterparts. These findings highlight the importance of enhancing women's empowerment, improving female education, and addressing household decision-making roles when designing nutrition interventions for tribal women.

Accurate detection of insertions and deletions (indels) is critical for applications in disease genomics, population genetics, and personalized healthcare. Despite advancements in sequencing technologies, indel detection remains challenging, particularly in difficult-to-map genomic regions. In this study, we present a universal machine learning-based filtering workflow that significantly improves indel detection accuracy for both long-read and short-read sequencing data, utilizing only publicly available genomic annotation datasets, eliminating the need for sequencing workflow-specific information, such as read depth. Our method (a gradient-boosting classifier powered by XGBoost) enhances precision by ~ 26% for long-read and ~ 24% for short-read data while maintaining high recall rates (~ 90%). We validate our approach using the Genome in a Bottle (GIAB) dataset and 62 indel call sets from the precisionFDA Truth Challenge V2, demonstrating its effectiveness in handling complex genomic regions and diverse sequencing workflows. Our tool is open-access and workflow-agnostic, making it a valuable resource for improving indel calling accuracy across various applications.