Age and sex-specific disability-free life expectancy in urban and rural settings of Bangladesh.

BACKGROUND: Disability-free life expectancy (DFLE) has been used to gain a better understanding of the population's quality of life. OBJECTIVES: The authors aimed to estimate age and sex-specific disability-free life expectancy (DFLE) for urban and rural areas of Bangladesh, as well as to investigate the differences in DFLE between males and females of urban and rural areas. METHODS: Data from the Bangladesh Sample Vital Statistics-2016 and the Bangladesh Household Income and Expenditure Survey (HIES)-2016 were used to calculate the disability-free life expectancy (DFLE) of urban and rural males and females in Bangladesh in 2016. The DFLE was calculated using the Sullivan method. RESULTS: With only a few exceptions, rural areas have higher mortality and disability rates than urban areas. For both males and females, statistically significant differences in DFLE were reported between urban and rural areas between the ages of birth and 39 years. In comparison to rural males and females, urban males and females had a longer life expectancy (LE), a longer disability-free life expectancy, and a higher share of life without disability. CONCLUSION: This study illuminates stark urban-rural disparities in LE and DFLE, especially among individuals aged < 1-39 years. Gender dynamics reveal longer life expectancy but shorter disability-free life expectancy for Bangladeshi women compared to men, emphasizing the need for targeted interventions to address these pronounced health inequalities.

Machine learning to analyse omic-data for COVID-19 diagnosis and prognosis.

BACKGROUND: With the global spread of COVID-19, the world has seen many patients, including many severe cases. The rapid development of machine learning (ML) has made significant disease diagnosis and prediction achievements. Current studies have confirmed that omics data at the host level can reflect the development process and prognosis of the disease. Since early diagnosis and effective treatment of severe COVID-19 patients remains challenging, this research aims to use omics data in different ML models for COVID-19 diagnosis and prognosis. We used several ML models on omics data of a large number of individuals to first predict whether patients are COVID-19 positive or negative, followed by the severity of the disease. RESULTS: On the COVID-19 diagnosis task, we got the best AUC of 0.99 with our multilayer perceptron model and the highest F1-score of 0.95 with our logistic regression (LR) model. For the severity prediction task, we achieved the highest accuracy of 0.76 with an LR model. Beyond classification and predictive modeling, our study founds ML models performed better on integrated multi-omics data, rather than single omics. By comparing top features from different omics dataset, we also found the robustness of our model, with a wider range of applicability in diverse dataset related to COVID-19. Additionally, we have found that omics-based models performed better than image or physiological feature-based models, proving the importance of the omics-based dataset for future model development. CONCLUSIONS: This study diagnoses COVID-19 positive cases and predicts accurate severity levels. It lowers the dependence on clinical data and professional judgment, by leveraging the utilization of state-of-the-art models. our model showed wider applicability across different omics dataset, which is highly transferable in other respiratory or similar diseases. Hospital and public health care mechanisms can optimize the distribution of medical resources and improve the robustness of the medical system.

Trends and long-term variation explaining nutritional determinants of child linear growth: analysis of Bangladesh Demographic and Health Surveys 1996-2018.

OBJECTIVE: To examine the height-for-age z-score (HAZ) of 0-35 months' children along with stunting prevalence to identify trends, changes and available nutrition-sensitive and specific determinants that could help explain the long-term variation in child linear growth using successive Bangladesh Demographic and Health Surveys (BDHS) data from 1996 to 2018. DESIGN: The BDHS pooled data are used for determining the key outcome variables HAZ, stunting and severe stunting. Trends, kernel-weighted local polynomial smoothing illustrations, pooled multivariable linear probability model (LPM), ordinary least squares method (OLS) and regression decomposition were used. PARTICIPANTS: Mothers having 0-35 months' children, the most critical age range for growth faltering. RESULTS: The mean HAZ increased by 0·91(±1·53) with 0·041 annual average change, while the percentages of stunting (-26·63 ± 0·54) and severe stunting (-21·12 ± 0·48) showed a reduction with 1·21 and 0·96 average annual changes, respectively. The average HAZ improvement (0·42 ± 1·56) in urban areas was less than the rural areas (1·16 ± 1·44). Similar patterns followed for stunting and severe stunting. The prenatal doctor visits (3064·65 %), birth in a medical facility (1054·32 %), breastfeeding initiation (153·18 %) and asset index (144·73 %) demonstrated a huge change. The findings of OLS, LPM and regression decomposition identified asset index, birth order, paternal and maternal education, bottle-fed, prenatal doctor visit, birth in a medical facility, vaccination, maternal BMI and ever-breastfed as influencing factors to predict the long-term changes of stunting and severe stunting. CONCLUSION: The nutrition-sensitive and specific factors identified through regression decomposition describing long-term variation in child linear growth should be focused further to attain the sustainable development goals.

Environmental quality and its impact on total fertility rate: an econometric analysis from a new perspective.

BACKGROUND: Environmental quality significantly affects various aspects of human existence. This study employs ecological footprint as a proxy to assess the impact of environmental quality on the TFR, measured as births per woman. This study investigates the extent to which ecological footprint indicators impact on the TFR in across 31 countries between from 1990 to 2017. METHODS: We gathered data on ecological footprints, specifically carbon, agricultural land, grazing land, forest products, and fisheries, from the Global Footprint Network. Information on the TFR, Human Development Index (HDI), and per capita Gross National Income (GNI) were sourced from the World Bank and the United Nations. We applied static panel and quantile regression models to scrutinize the connection between the ecological footprint and TFR, showing how the former influences the latter. RESULTS: The outcomes reveal that, in both fixed and random effects models, factors including HDI, carbon, and fishing grounds exert a negative influence on TFR, all at a significance level of p < 0.01. Conversely, cropland and forest product footprints exhibited a favorable impact on the TFR (p < 0.01). Furthermore, GNI per capita positively affected the TFR in both models, with a p-value of 0.01. Quantiles regression analysis demonstrated that HDI and carbon footprint had a negative impact on TFR across all quantiles. This statistical significance is maintained for all quantiles, although it is only significant for the carbon footprint up to the 60th quantile, at p < 0.01. CONCLUSIONS: This study establishes a negative correlation between specific ecological footprint indicators, such as carbon and fishing grounds, and TFR. Conversely, there was a positive correlation between the footprint of forest products and the TFR. The primary conclusion drawn is that there is heterogeneity in the results regarding the relationship between ecological footprint and TFR. Moreover, the ecological footprint indicators considered in this study did not uniformly influence TFR. Each ecological footprint indicator exhibited distinct effects on the TFR, displaying either positive or negative correlation coefficients. Future research endeavors may delve into how ecological footprints impact other population dynamics, such as mortality and migration.

Supplemental nitrite increases choroidal neovascularization in mice.

Low doses of nitrite, close to physiological levels, increase blood flow in normal and ischemic tissues through a nitric oxide (NO) dependent mechanism. Given that nitrite therapy and dietary supplementation with vegetables high in nitrate (e.g. beets) are gaining popularity we decided to determine if low doses of nitrite impact the development of choroidal neovascularization (CNV), a key feature of wet age related macular degeneration (AMD). Sodium nitrite (at 50 mg/L, 150 mg/L, and 300 mg/L), nitrate (1 g/L) or water alone were provided in the drinking water of C57BL/6 J mice aged 2 or 12 months. Mice were allowed to drink ad libitum for 1 week at which time laser-induced choroidal neovascularization (L-CNV) was induced. The mice continued to drink the supplemented water ad libitum for a further 14 days at which point optical coherence tomography (OCT) was performed to determine the volume of the CNV lesion. Blood was drawn to determine nitrite and nitrate levels and eyes taken for histology. CNV volume was 2.86 × 107 µm3 (±0.4 × 107) in young mice on water alone but CNV volume more than doubled to >6.9 × 107 µm3 (±0.8 × 107) in mice receiving 300 mg/L nitrite or 7.34 × 107 µm3 (±1.4 × 107) in 1 g/L nitrate (p < 0.01). A similar trend was observed in older mice. CNV volume was 5.3 × 107 µm3 (±0.5 × 107) in older mice on water alone but CNV volume almost doubled to approximately 9.3 × 107 µm3 (±1.1 × 107) in mice receiving 300 mg/L nitrite or 8.7 × 107 µm3 (±0.9 × 107) 1 g/L nitrate (p < 0.01). Plasma nitrite levels were highest in young mice receiving 150 mg/L in the drinking water with no changes in plasma nitrate observed. In older mice, drinking water nitrite did not significantly change plasma nitrite, but plasma nitrate was increased. Plasma nitrate was elevated in both young and old mice provided with nitrate supplemented drinking water. Our data demonstrate that the CNV lesion is larger in older mice compared to young and that therapeutic levels of oral nitrite increase the volume of CNV lesions in both young and older mice. Therapeutic nitrite or nitrate supplementation should be used with caution in the elderly population prone to CNV.

Potential role for age as a modulator of oral nitrate reductase activity.

Reduction of salivary nitrate to nitrite by oral nitrate reductase (NR) expressing bacteria has emerged as an integral pathway in regulating nitric oxide (NO) homeostasis and signaling. The oral microbiome is critical for this pathway. Variations in this pathway may underlie variable responses in the magnitude by which dietary or therapeutic nitrate modulates NO-signaling. The relationships between oral microbes and NR activity, and the factors that affect this relationship remain unclear however. Using a cross-sectional study design, the objective of this study was to determine the relationships between oral microbes and oral NR activity using a protocol that directly measures initial NR activity. Tongue swabs were collected from 28 subjects ranging in age from 21 to 73y. Initial NR activity showed a bell-shaped dependence with age, with activity peaking at ~40-50y and being lower but similar between younger (20-30y) and older (51-73) individuals. Microbiome relative abundance and diversity analyses, using 16s sequencing, demonstrated differences across age and identified both NR expressing and non-expressing bacteria in modulating initial NR activity. Finally, initial NR activity was measured in 3mo and 13mo old C57BL/6J mice. No differences in bacterial number were observed. However initial NR activity was significantly (80%) lower in 13mo old mice. Collectively, these data suggest that age is a variable in NR activity and may modulate responsiveness to dietary nitrate.

Association of Uncoupling Protein 1 (UCP1) gene polymorphism with obesity: a case-control study.

BACKGROUND: Obesity is one of the main causes of morbidity and mortality worldwide. More than 120 genes have been shown to be associated with obesity related phenotypes. The aim of this study was to determine the effect of selected genetic polymorphisms in Uncoupling protein 1 (UCP1) and Niemann-Pick C1 (NPC1) genes in an obese population in Saudi Arabia. METHODS: The genotypes of rs1800592, rs10011540 and rs3811791 (UCP1 gene) and rs1805081 and rs1805082 (NPC1 gene) were determined in a total of 492 subjects using TaqMan chemistry by Real-time PCR. In addition, capillary sequencing assay was performed to identify two specific polymorphisms viz., rs45539933 (exon 2) and rs2270565 (exon 5) of UCP1 gene. RESULTS: A significant association of UCP1 polymorphisms rs1800592 [OR, 1.52 (1.10-2.08); p = 0.009] was observed in the obese cohort after adjusting with age, sex and type 2 diabetes. Further BMI based stratification revealed that this association was inconsistent with both moderate and extreme obese cohort. A significant association of UCP1 polymorphisms rs3811791 was observed only in the moderate-obese cohort [OR = 2.89 (1.33-6.25); p = 0.007] but not in the extreme-obese cohort indicating an overlying genetic complexity between moderate-obesity and extreme-obesity. The risk allele frequencies, which were higher in moderate-obese cohort, had abnormal HDL, LDL and triglyceride levels. CONCLUSION: The rs1800592 and rs3811791 of UCP1 gene are associated with obesity in general and in the moderate-obese group in particular. The associated UCP1 polymorphisms in the moderate-obese group may regulate the impaired energy metabolism which plays a significant role in the initial stages of obesity.

Measuring nitrate reductase activity from human and rodent tongues.

Reduction of salivary nitrate to nitrite by oral microbes expressing nitrate-reductase has emerged as a crucial pathway in systemic NO homeostasis in humans and other mammals. Selective depletion of oral microbes prevents dietary nitrate-dependent lowering of blood pressure, inhibition of platelet aggregation and ischemic injury. To date, most studies interrogate enterosalivary nitrate reduction by following changes in saliva or plasma nitrite and NO-signaling (functional) end points. Little is known about whether, and if so how, nitrate-reductase enzymatic activity per se (i.e. independent of nitrate levels) is a variable and may account for any individual to individual variation. Here, we describe a minimally invasive protocol that allows for NR activity determination from human, rat and mouse tongue scrapes/swabs. We validate this method using selective application of antiseptic agents to the distal tongue surface which decreased NR activity by >80% and show that bacterial number is a significant variable in measured NR activities between males and females. Also, we show that NR activity is >80% lower in smokers (humans) and after bromine gas exposure (mice), suggesting that exposure to inhaled reactive substances inhibit NR activity identifying a potentially new mechanism by which environmental toxicants promote dysfunction in NO-bioavailability. The described method will facilitate studies testing whether NR specific activity is a variable in different pathophysiologic settings, and in turn how this activity modulates enterosalivary nitrate-reduction.

Synthesis and Characterization of 8-Nitroguanosine 3',5'-Cyclic Monophosphorothioate Rp-Isomer as a Potent Inhibitor of Protein Kinase G1α.

Guanosine 3',5'-cyclic monophosphate (cGMP)-dependent protein kinases (PKG) are kinases regulating diverse physiological functions including vascular smooth muscle relaxation, neuronal synaptic plasticity, and platelet activities. Certain PKG inhibitors, such as Rp-diastereomers of derivatives of guanosine 3',5'-cyclic monophosphorothioate (Rp-cGMPS), have been designed and used to study PKG-regulated cell signaling. 8-Nitroguanosine 3',5'-cyclic monophosphate (8-nitro-cGMP) is an endogenous cGMP derivative formed as a result of excess production of reactive oxygen species and nitric oxide. 8-Nitro-cGMP causes persistent activation of PKG1α through covalent attachment of cGMP moieties to cysteine residues of the enzyme (i.e., the process called protein S-guanylation). In this study, we synthesized a nitrated analogue of Rp-cGMPS, 8-nitroguanosine 3',5'-cyclic monophosphorothioate Rp-isomer (Rp-8-nitro-cGMPS), and investigated its effects on PKG1α activity. We synthesized Rp-8-nitro-cGMPS by reacting Rp-8-bromoguanosine 3',5'-cyclic monophosphorothioate (Rp-8-bromo-cGMPS) with sodium nitrite. Rp-8-Nitro-cGMPS reacted with the thiol compounds cysteine and glutathione to form Rp-8-thioalkoxy-cGMPS adducts to a similar extent as did 8-nitro-cGMP. As an important finding, a protein S-guanylation-like modification was clearly observed, by using Western blotting, in the reaction between recombinant PKG1α and Rp-8-nitro-cGMPS. Rp-8-Nitro-cGMPS inhibited PKG1α activity with an inhibitory constant of 22 µM in a competitive manner. An organ bath assay with mouse aorta demonstrated that Rp-8-nitro-cGMPS inhibited vascular relaxation induced by acetylcholine or 8-bromo-cGMP more than Rp-8-bromo-cGMPS did. These findings suggest that Rp-8-nitro-cGMPS inhibits PKG through induction of an S-guanylation-like modification by attaching the Rp-cGMPS moiety to the enzyme. Additional study is warranted to explore the potential application of Rp-8-nitro-cGMPS to biochemical and therapeutic research involving PKG1α activation.

Persistent Activation of cGMP-Dependent Protein Kinase by a Nitrated Cyclic Nucleotide via Site Specific Protein S-Guanylation.

8-Nitroguanosine 3',5'-cyclic monophosphate (8-nitro-cGMP) is a nitrated derivative of guanosine 3',5'-cyclic monophosphate (cGMP) formed endogenously under conditions associated with production of both reactive oxygen species and nitric oxide. It acts as an electrophilic second messenger in the regulation of cellular signaling by inducing a post-translational modification of redox-sensitive protein thiols via covalent adduction of cGMP moieties to protein thiols (protein S-guanylation). Here, we demonstrate that 8-nitro-cGMP potentially S-guanylates thiol groups of cGMP-dependent protein kinase (PKG), the enzyme that serves as one of the major receptor proteins for intracellular cGMP and controls a variety of cellular responses. S-Guanylation of PKG was found to occur in a site specific manner; Cys42 and Cys195 were the susceptible residues among 11 Cys residues. Importantly, S-guanylation at Cys195, which is located in the high-affinity cGMP binding domain of PKG, causes persistent enzyme activation as determined by in vitro kinase assay as well as by an organ bath assay. In vivo, S-guanylation of PKG was demonstrated to occur in mice without any specific treatment and was significantly enhanced by lipopolysaccharide administration. These findings warrant further investigation in terms of the physiological and pathophysiological roles of S-guanylation-dependent persistent PKG activation.

An open set model for pest identification.

Agricultural pest identification is a prerequisite for increasing crop production and meeting global food demands. Generally, numerous phenotypic and genotypic features are widely utilized for species-level pest identification. However, the approaches are time-consuming and require expert knowledge in relevant fields. Numerous image-based machine learning (ML) models also exist to identify insect pests in agricultural fields. The models are significantly rely on a large, manually curated dataset and are close-set in nature. Our study aims to develop an open set pest identification approach by adding the capability of rejecting any irrelevant inputs. Tephritid fruit flies (Diptera:Tephritidae) are considered as an example since they are the most economically important agricultural pests worldwide. Images of the fruit flies were collected from a publicly available database and filtered to exclude uninformative images using a deep learning model (Inception-V3) and an unsupervised k-means clustering method. For the closed-set identification task, our EfficientNet-B2 model classified four major genera of notorious tephritid flies, namely, Anastrepha, Ceratitis, Rhagoletis, and Bactrocera with an accuracy of 89.65%. We further improvise our proposed model for open-set recognition tasks to leverage the identification beyond the trained datasets. The open set model achieved an overall accuracy of 86.48% and a macro F1-score of 94.44% on the four genera and an unknown class. Our proposed model can be a practical and effective pest identification tool for harmful fruit flies. In addition, the model is easy to implement with existing agricultural pest control systems in an open-world scenario.

Complete mitogenome and intra-family comparative mitogenomics showed distinct position of Pama Croaker Otolithoides pama.

The Pama Croaker, Otolithoides pama, is an economically important fish species in Bangladesh. Intra-family similarities in morphology and typical barcode sequences of cox1 create ambiguities in its identification. Therefore, morphology and the complete mitochondrial genome of O. pama, and comparative mitogenomics within the family Sciaenidae have been studied. Extracted genomic DNA was subjected to Illumina-based short read sequencing for De-Novo mitogenome assembly. The complete mitogenome of O. pama (Accession: OQ784575.1) was 16,513 bp, with strong AC biasness and strand asymmetry. Relative synonymous codon usage (RSCU) among 13 protein-coding genes (PCGs) of O. pama was also analyzed. The studied mitogenomes including O. pama exhibited consistent sizes and gene orders, except for the genus Johnius which possessed notably longer mitogenomes with unique gene rearrangements. Different genetic distance metrics across 30 species of Sciaenidae family demonstrated 12S rRNA and the control region (CR) as the most conserved and variable regions, respectively, while most of the PCGs undergone a purifying selection. Different phylogenetic trees were congruent with one another, where O. pama was distinctly placed. This study would contribute to distinguishing closely related fish species of Sciaenidae family and can be instrumental in conserving the genetic diversity of O. pama.

Improved reference quality genome sequence of the plastic-degrading greater wax moth, Galleria mellonella.

Galleria mellonella is a pest of honeybees in many countries because its larvae feed on beeswax. However, G. mellonella larvae can also eat various plastics, including polyethylene, polystyrene, and polypropylene, and therefore, the species is garnering increasing interest as a tool for plastic biodegradation research. This paper presents an improved genome (99.3% completed lepidoptera_odb10 BUSCO; genome mode) for G. mellonella. This 472 Mb genome is in 221 contigs with an N50 of 6.4 Mb and contains 13,604 protein-coding genes. Genes that code for known and putative polyethylene-degrading enzymes and their similarity to proteins found in other Lepidoptera are highlighted. An analysis of secretory proteins more likely to be involved in the plastic catabolic process has also been carried out.

Knowledge, attitudes, and practices regarding antibiotic use in Bangladesh: Findings from a cross-sectional study.

BACKGROUND: Escalating antibiotic resistance presents a notable worldwide dilemma, pointing a large involvement of general population. The objective of this study was to assess knowledge, attitudes, and practices regarding the utilization of antibiotics among Bangladeshi residents. METHODS: A cross-sectional study, conducted from January 01 to April 25, 2022, included 1,947 Bangladeshi adults with a history of antibiotic use, via online surveys and face-to-face interviews using a pretested semi-structured questionnaire. Descriptive statistics, Chi-square tests, and multivariate linear regression models were employed. RESULTS: Mean scores for knowledge, attitudes, and practices were 6.59±1.20, 8.34±1.19, and 12.74±2.59, with correct rates of 73.22%, 92.67%, and 57.91%. Positive predictors for knowledge included being unmarried (ß = 0.10, p = 0.001), higher education (College: ß = 0.09, p = 0.025; Bachelor: ß = 0.22, p<0.001; Master or above: ß = 0.14, p<0.001), various professions (student: ß = 0.57, p<0.001; housewife: ß = 0.33, p<0.001; employee: ß = 0.53, p<0.001; businessman: ß = 0.31, p<0.001; unemployed: ß = 0.15, p<0.001), and residing in semi-urban (ß = 0.32, p<0.001) or urban areas (ß = 0.15, p<0.001). Positive predictors for attitudes included being married (ß = 0.18, p<0.001), specific professions (student: ß = 1.06, p<0.001; housewife: ß = 0.33, p<0.001; employee: ß = 0.86, p<0.001; businessman: ß = 0.37, p<0.001; unemployed: ß = 0.47, p<0.001), higher SES (Lower-middle: ß = 0.22, p<0.001; Middle: ß = 0.26, p<0.001), and residing in semi-urban areas (ß = 0.18, p<0.001); negative predictors included higher education (College: ß = -0.12, p = 0.001; Master or above: ß = -0.09, p = 0.008) and being rich (ß = -0.13, p<0.001). Positive predictors for practices included being married (ß = 0.18, p<0.001), specific professions (student: ß = 0.32, p<0.001; employee: ß = 0.43, p<0.001; businessman: ß = 10, p = 0.034; unemployed: ß = 0.11, p = 0.009), and higher SES (Lower-middle: ß = 0.14, p = 0.009; Middle: ß = 0.38, p<0.001; Higher-middle: ß = 0.15, p = 0.008); negative predictors included higher education (College: ß = -0.21, p<0.001), being rich (ß = -0.12, p<0.001), residing in semi-urban (ß = -0.14, p<0.001) or urban areas (ß = -0.16, p<0.001). CONCLUSIONS: Participants exhibited adequate knowledge and positive attitudes but lagged behind in proper practice of antibiotic use. Proper initiatives should be tailored to enhance prudent antibiotic use and mitigate the risk of antimicrobial resistance.

Regulation by mitochondrial superoxide and NADPH oxidase of cellular formation of nitrated cyclic GMP: potential implications for ROS signalling.

8-Nitro-cGMP (8-nitroguanosine 3',5'-cyclic monophosphate) is a nitrated derivative of cGMP, which can function as a unique electrophilic second messenger involved in regulation of an antioxidant adaptive response in cells. In the present study, we investigated chemical and biochemical regulatory mechanisms involved in 8-nitro-cGMP formation, with particular focus on the roles of ROS (reactive oxygen species). Chemical analyses demonstrated that peroxynitrite-dependent oxidation and myeloperoxidase-dependent oxidation of nitrite in the presence of H2O2 were two major pathways for guanine nucleotide nitration. Among the guanine nucleotides examined, GTP was the most sensitive to peroxynitrite-mediated nitration. Immunocytochemical and tandem mass spectrometric analyses revealed that formation of 8-nitro-cGMP in rat C6 glioma cells stimulated with lipopolysaccharide plus pro-inflammatory cytokines depended on production of both superoxide and H2O2. Using the mitochondria-targeted chemical probe MitoSOX Red, we found that mitochondria-derived superoxide can act as a direct determinant of 8-nitro-cGMP formation. Furthermore, we demonstrated that Nox2 (NADPH oxidase 2)-generated H2O2 regulated mitochondria-derived superoxide production, which suggests the importance of cross-talk between Nox2-dependent H2O2 production and mitochondrial superoxide production. The results of the present study suggest that 8-nitro-cGMP can serve as a unique second messenger that may be implicated in regulating ROS signalling in the presence of NO.

Machine learning for detecting DNA attachment on SPR biosensor.

Optoelectric biosensors measure the conformational changes of biomolecules and their molecular interactions, allowing researchers to use them in different biomedical diagnostics and analysis activities. Among different biosensors, surface plasmon resonance (SPR)-based biosensors utilize label-free and gold-based plasmonic principles with high precision and accuracy, allowing these gold-based biosensors as one of the preferred methods. The dataset generated from these biosensors are being used in different machine learning (ML) models for disease diagnosis and prognosis, but there is a scarcity of models to develop or assess the accuracy of SPR-based biosensors and ensure a reliable dataset for downstream model development. Current study proposed innovative ML-based DNA detection and classification models from the reflective light angles on different gold surfaces of biosensors and associated properties. We have conducted several statistical analyses and different visualization techniques to evaluate the SPR-based dataset and applied t-SNE feature extraction and min-max normalization to differentiate classifiers of low-variances. We experimented with several ML classifiers, namely support vector machine (SVM), decision tree (DT), multi-layer perceptron (MLP), k-nearest neighbors (KNN), logistic regression (LR) and random forest (RF) and evaluated our findings in terms of different evaluation metrics. Our analysis showed the best accuracy of 0.94 by RF, DT and KNN for DNA classification and 0.96 by RF and KNN for DNA detection tasks. Considering area under the receiver operating characteristic curve (AUC) (0.97), precision (0.96) and F1-score (0.97), we found RF performed best for both tasks. Our research shows the potentiality of ML models in the field of biosensor development, which can be expanded to develop novel disease diagnosis and prognosis tools in the future.

Influencing factors associated with maternal delivery at home in urban areas: a cross-sectional analysis of the Bangladesh Demographic and Health Survey 2017-2018 data.

BACKGROUND: The associated factors and patterns of giving birth in home settings of rural areas have been extensively studied in Bangladeshi literature. However, urban areas still need to be explored, particularly with recent data. Therefore, the authors aimed to investigate the influential determinants of delivery at home in urban areas of Bangladesh. MATERIALS AND METHODS: In this study, 1699 urban-dwelling women who had given birth within the previous 60 months of the survey and lived in urban areas were used. The secondary data were extracted from the latest Bangladesh Demographic and Health Survey 2017-2018. Descriptive statistics and logistic regression were applied along with the association among selected variables were examined by the Chi-square test. RESULTS: Findings depict that 36.49% of women who lived in urban areas of Bangladesh delivered at home, whereas, 63.51% delivered at different govt. and private health care facilities. Women who lived in Chittagong [adjusted odds ratio (AOR) = 2.11, 95% CI 1.24-3.60], Barisal [AOR = 2.05, 95% CI 1.16-3.64] and Sylhet [AOR = 1.92, 95% CI 1.08-3.43] divisions have more likelihood to deliver at home (36.85%). Urban women following Christian religion [AOR = 10.71, 95% CI 1.32-86.68] have higher odds of delivering child at home (0.47%). Urban women having three or more children before her latest delivery (22.37%) and who are employed (29.37%) have more likelihood to deliver at home. However, women aged between 25 and 34 years (43.50%), who have higher education (25.90%), play the role of household head (9.06%), have parity of more than two births (2.24%), and read daily newspapers (68.69%) had a lower chance of delivery at home. Furthermore, women from wealthier families (89.12%) and more antenatal care (ANC) visits (94.93%) were less likely to have a delivery at home. CONCLUSION: Despite significant progress in women and reproductive health in Bangladesh, the proportion of delivery in the home in urban areas is alarming and should be emphasized more. The authors believe the identified factors will help design interventions and policy development on this issue.

Association of dietary diversity of 6-23 months aged children with prenatal and postnatal obstetric care: evidence from a nationwide cross-sectional study.

BACKGROUND: Dietary diversity is a key determinant of infant and young child eating patterns for a variety of food groups taken by children between the ages of 6-23 months. The study aimed to examine the association between prenatal and postnatal obstetric care factors of mother and child's dietary diversity, and specific food practices in Bangladesh. METHODS: This study analyzed the data of 2497 children between the age of 6-23 extracted from the latest countrywide Bangladesh Demographic Health Survey 2017-2018 and explored relationships between prenatal and postnatal obstetric care received by mother and dietary diversity score (DDS), minimum dietary diversity (MDD), and introduction of solid, semi-solid, and soft foods (ISSSF) of their children. RESULTS: Findings revealed that ≥ 4 antenatal care (ANC) visits care visits increased the DDS (adjusted [Formula: see text]: 0.32, 95% CI [0.21, 0.43]), increased the likelihood of MDD (AOR 1.54, 95% CI [1.23, 1.93]), and ISSSF (AOR 1.24, 95% CI [1.08, 1.48]), consuming eggs (AOR 1.47, 95% CI [1.23, 1.76]), and vitamin A vegetables and fruits (AOR 1.38, 95% CI [1.15, 1.66]). Moreover, DDS (adjusted ß: 0.05, 95% CI [0.00, 0.11]) and MDD (AOR 1.66, 95% CI [1.31, 2.11]) are linked to childbirth in a medical facility. The C-section delivery influences the DDS (adjusted [Formula: see text]: 0.05, 95% CI [0.00, 0.10]), MDD (AOR 1.39, 95% CI [1.10, 1.75]), and ISSSF (AOR 1.22, 95% CI [1.02, 1.48]). Besides, postnatal visits within 48 h of delivery linked to MDD (AOR 0.66, 95% CI [0.49, 0.89]) and ISSSF (AOR 0.76, 95% CI [0.59, 0.97]), and physicians or professionals providing postnatal checkups were significantly associated with DDS (adjusted [Formula: see text]: 0.09, 95% CI [0.02, 0.16]), MDD (AOR 1.69, 95% CI [1.26, 2.26]), and ISSSF (AOR 1.30, 95% CI [1.04, 1.62]). CONCLUSION: Knowledge of child nutritional feeding should emphasize during prenatal and postnatal obstetric care of mother, particularly during antenatal and postnatal visits, C-section delivery, and birth in a healthcare facility to eradicate malnutrition and establish healthy child feeding practices.

Positive impacts of COVID-19 Lock down in Bangladesh: An online investigation.

Background: This research focuses on the positive impacts of the COVID-19 lockdown on society and the environment, despite acknowledging the widespread negative effects of the pandemic and lockdown measures. The research was aimed at pinpointing and evaluating the beneficial results stemming from these measures. Method: Data for the study was collected through an online survey distributed via Google forms to adults over the age of 18 across the country. A total of 1230 participants completed the survey, mostly from rural areas (61.7%), providing valuable insights for analysis. The questionnaire encompassed personal, family, and cohesive social data, along with information on the environment and biodiversity. The study utilized structural equation modeling (SEM) and confirmatory factor analysis (CFA) to analyze the data and examine correlations between variables. Results: The findings indicated that the COVID-19 lockdown had positive implications for individuals and society, leading to increased health consciousness, improved family relationships, and constructive social attitudes. Moreover, restrictions on access to natural tourist destinations and parks during the lockdown contributed to positive changes in biodiversity. These results highlight the importance of adopting appropriate measures during pandemics to foster personal and social well-being, as well as the preservation of natural environments and biodiversity. Conclusion: This study emphasizes the need for further research to promote sustainable living in similar situations. By understanding the data appropriately, individuals can play a constructive role in future pandemics, leading to positive outcomes for both society and the environment.