Pivotal relationship between heavy metal, PM2.5 exposures and tuberculosis in Bangladeshi children: protocol paper of a case-control study.

INTRODUCTION: Air pollution is a global issue that poses a significant threat to public health. Children, due to their developing physiology, are particularly susceptible to the inhalation of environmental pollutants. Exposure can trigger immune modulation and organ damage, increasing susceptibility to respiratory diseases. Therefore, we aim to examine the association between heavy metal and particulate matter exposure with tuberculosis in children. METHODS AND ANALYSIS: As a case-control study, we will include children diagnosed with pulmonary tuberculosis (n=60) and matched healthy controls (n=80) recruited from the same communities in Dhaka, Bangladesh. Exposure data for both cases and controls will be collected by a trained field team conducting home visits. They will administer an exposure questionnaire, measure child anthropometry, collect blood and household dust samples and instal 48-hour air quality monitors. The blood samples will be analysed by inductively coupled plasma mass spectrometry for serum heavy metal concentrations (lead, cadmium, arsenic, mercury and chromium), as a representative marker of exposure, and the presence of inflammatory biomarkers. Descriptive and inferential statistics, including independent samples t-tests, analysis of variance and conditional regression analysis, will be used to quantify heavy metal and particulate matter exposure status in tuberculosis cases compared with healthy controls, while accounting for potential confounders. Dust samples and air quality results will be analysed to understand household sources of heavy metal and particulate matter exposure. To test the study hypothesis, there is a positive association between exposure and tuberculosis diseases, we will also measure the accumulated effect of simultaneous exposures using Bayesian statistical modelling. ETHICS AND DISSEMINATION: This study has been approved by International Centre for Diarrhoeal Disease Research, Bangladesh's Institutional Review Board (PR-22030). The study findings will be disseminated at conferences and published in peer-reviewed journals.

Synthesis, characterization and thermoluminescence properties of LiCaPO4 phosphor for ionizing radiation dosimetry.

Many minerals and compounds show thermoluminescence (TL) properties but only a few of them can meet the requirements of an ideal dosimeter. Several phosphate materials have been studied for low-dose dosimetryin recent times. Among the various phosphates, ABPO4-type material shows interesting TL properties. In this study, an ABPO4-type (A = Lithium, B=Calcium) phosphor is synthesized using a modified solid-state diffusion method. Temperature is maintained below 800 °C in every step of phosphor preparation to obtain the pure phase of Lithium calcium phosphate (LiCaPO4). The purpose of this work is to synthesize LiCaPO4 using a simple method, examine its structural and luminescence properties in order to gain a deeper understanding of its TL characteristics. The general TL properties, such as TL glow curve, dose linearity, sensitivity, and fading, are investigated. Additionally, this study aims to determine various kinetic parameters through Glow Curve Deconvolution (GCD) method using the Origin Lab software together with the Chen model. XRD analysis confirmed the phase purity of the phosphor with a rhombohedral structure. Lattice parameters, unit cell volume, grain size, dislocated density, and microstrain were also calculated from XRD data. Raman analysis and Fourier Transform Infrared analysis were used to collect information about molecular bonds, vibrations, identity, and structure of the phosphor. To investigate TL properties and associated kinetic parameters, the phosphor was irradiated with 6.0 MV (photon energy) and 6.0 MeV (electron energy) from a linear accelerator for doses ranging from 0.5 Gy to 6.0 Gy. For both photon and electron energy, TL glow curves have two identical peaks near 200 °C and 240 °C.The TL glow curves for 0.5 Gy-6 Gy are deconvoluted, then fitted with the appropriate model and then calculated the kinetic parameters. Kinetic parameters such as geometric factor (µg), order of kinetics, activation energy (E), and frequency factor (s) are obtained from Chen's peak shape method. The dose against the TL intensity curve shows that the response is almost linear in the investigated dose range. For photon and electron energy, the phosphor is found to be the most sensitive at 2.0 Gy and 4.0 Gy, respectively. The phosphor shows a low fading and after 28 days of exposure, it shows a signal loss of better than 3%. The studied TL properties suggest the suitability of LiCaPO4 in radiation dosimetry and associated fields.

Anthropometry in predicting Semitendinosus and Gracilis graft diameter for arthroscopic ACL reconstruction among the Bengali population.

Semitendinosus and Gracilis autografts are commonly used for anterior cruciate ligament (ACL) reconstruction. However, its main drawback is individual variation in the tendon diameter. This study aimed to evaluate the usefulness of the anthropometric measurements for the prediction of Semitendinosus and Gracilis combined (quadrupled) strands graft diameter in arthroscopic ACL reconstruction among the Bengali population. Sixty consecutive patients who underwent ACL reconstruction between July 2019 to June 2020 were observed in this cross-sectional study. In all cases, the doubled (2 strands) Gracilis and Semitendinosus tendons were combined to get the final quadrupled (combined 4 strands) graft for use. Anthropometries such as body mass index (BMI), body weight, and height were recorded preoperatively and quadrupled combined tendon diameter was measured at the operating theater. The relationship between these parameters was statistically determined using the Pearson correlation coefficient, and scatter diagrams were plotted. Among the study subjects, most (54) were male, and the mean age of all subjects was 24 ±â€…6.92 years. The average graft diameter was 7.20 ±â€…0.76 mm. Correlations between the mean graft diameter with BMI (r = 0.018, and P = .891), body height (r = 0.011 and P = .933), and weight (r = 0.028 and P = .832) were not significant. Scatter diagrams also showed that the variables were not correlated. Anthropometries like BMI, body weight, or body height cannot be used in predicting Semitendinosus and Gracilis tendon graft diameter for arthroscopic ACL reconstruction among the Bengali population.

Flash flooding considerations aside: Knowledge brokering by the extension and advisory services to adapt a farming system to flash flooding.

The development of agriculture sector and livelihood in Bangladesh are threatened by various climatic stressors, including flash flooding. Therefore, Extension and advisory services (EAS) need to navigate the knowledge landscape effectively to connect various farm actors and help secure the optimum benefits of knowledge and information for making rational decisions. However, little is known how EAS can perform this task to combat various effects of climate change. This study investigates the means of brokering knowledge by the EAS to help the farming sector adapt to flash flooding. The research was conducted in the north-eastern part of Bangladesh with 73 staff of the Department of Agricultural Extension (DAE), the largest public EAS in Bangladesh. The results showed that DAE primarily dealt with crop production-related information. However, EAS did not navigate knowledge and information about flash flooding, such as weather forecasting and crop-saving-embankments updates, among the farming actors. Moreover, they missed the broad utilization of internet-based-communication channels to rapidly navigate information and knowledge about possible flash flooding and its adaptation strategies. This article provides some policy implications to effectively support the adaptation of farming system to flash flooding through EAS.

Influence of Sn doping on the optoelectronic properties of ZnO nanoparticles.

Zinc Oxide (ZnO) nanoparticles (NPs) obtained a lot of attention from researchers and industries because of their superior properties as an optoelectronic material. Doping, especially tin (Sn), can further fine-tune their optoelectronic properties. In this manuscript, we have reported the optoelectronic properties of Sn-doped ZnO NPs, which were synthesized by a simple chemical solution method. A wide range of dopant (Sn) concentrations were used in the ratios of 0, 1, 3, 5, 7, and 10 weight percent. The effects of dopant (Sn) concentration on the structural, morphological, elemental composition, and optical properties of ZnO NPs were investigated by using an X-ray diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), X-ray photoelectron spectrometer (XPS) and UV-Vis-NIR respectively. XRD analysis revealed the shifting of diffraction patterns towards a higher angle along with decreasing intensity. The calculated crystallite size using the XRD varied from 40.12 nm to 28.15 nm with an increasing doping percentage. Sn doping notably influences the size of ZnO NPs, along with crystal quality, strain, and dislocation density. The X-ray photoelectron spectroscopy (XPS) study showed the presence of zinc (Zn), oxygen (O), and tin (Sn) with their preferred oxidation states in the synthesized NPs. UV-Visible spectroscopy (UV-Vis) showed that the bandgap changed from 3.55 to 3.85 eV with the increasing concentration of Sn. FE-SEM revealed that the structures and surfaces were irregular and not homogeneous. The above findings for ZnO nanostructures show their potential application in optoelectronic devices.

General and abdominal obesity and dietary nutrient intake among university students in Bangladesh: A cross-sectional study targeting potential risk factors.

BACKGROUND & AIMS: The overall national increase in the prevalence of overweight and obesity has emerged among university students in Bangladesh. Though, poor dietary habits and lifestyle is quite common among university students, their dietary nutrient intake level, obesity prevalence and potential risk factors has hitherto given little priority. This study aimed to understand the prevalence and factors associated with general and abdominal obesity and level of dietary nutrient intake among university students in Bangladesh. METHODS: Data from 320 unselected tertiary level students (81.6% males, 18.4% females; average age 22.7±3.0, BMI 22.4±3.1 and waist-hip ratio (WHR) 0.88 ± 0.1) was collected randomly, in a single visit, from Islamic University, Kushtia, Bangladesh. Basic demographic and anthropometric information were collected. Twenty-four hour (24H) dietary recall and food frequency questionnaire (FFQ) was used to collect dietary nutrient level retrospectively. Descriptive statistics, chi-square test, t-test, ANOVA, and binomial logistic regression analysis were done. RESULTS: Around 3% and 42% student were reported to be obese and overweight respectively. Whereas abdominal obesity was prevalent among ∼52% and more than 67% of student were reportedly obese/overweight by either BMI or WHR or WHtR category. Energy and carbohydrate (CHO) intake were reported to be significantly higher (P < 0.05) among overweight who born by C-section delivery and were fed formula milk than those were normal weight and born by vaginal-birth and were breastfed. The overweight individual with a history of preterm birth was reported to intake significantly higher (P < 0.05) carbohydrates compared to normal-weight individuals with a history of term birth. While total fat intake was significantly higher (P < 0.05) among overweight individuals with their mother had gestational diabetes than those with normal weight individuals with mother without gestational diabetes. CONCLUSIONS: General and abdominal obesity is common among university students and possibly associated with mode of birth, gestational duration, gestational diabetes, and breastfeeding practice.

Prevalence of antibiotic use for diarrhea among 1.3 million under-five years children: A multicounty retrospective analysis from 2006-2018.

BACKGROUND: This paper aims to estimate the prevalence of antibiotic use for diarrhea among under-five children (u5c) in low- and middle-income countries (LMICs) using data from 112 Demographic Health Surveys (DHS) conducted between 2006 and 2018. The focus is on understanding the extent of antibiotic usage for managing diarrhea, a condition characterized by frequent loose or watery bowel movements that can lead to severe dehydration. METHODS AND FINDINGS: A cross-sectional study design was employed in the DHS. The prevalence of antibiotic use for diarrhea among under-five children was estimated by analyzing DHS data from 2006 to 2018 and using the R statistical programming language. Out of a total of 12,69,944 children under five included in this study, 1,80,067 children had diarrhea and 19,502 children had bloody diarrhea. The overall prevalence of diarrhea estimated at ~14% (prevalence = 0.142; 95% CI = 0.141, 0.142). Among the children with diarrhea, 47,755 child received antibiotic treatment, resulting a prevalence of ~27% (prevalence = 0.27, 95% CI = 0.26, 0.27) globally. Central Asia had the highest prevalence of antibiotic use at ~55% (prevalence = (967/1748) = 0.55, 95% CI = 0.52, 0.59), followed by the Europe region with a prevalence of ~44% (prevalence = (5483/12502) = 0.44, 95% CI = 0.43, 0.45). In the South East and Central Asia region, DHS conducted between 2006 and 2018, showed the highest prevalence of antibiotic use in DHS 2007 (~44%), DHS 2012 (~49%), DHS 2016 (~40%) and DHS 2017 (~65%). The linear trend analysis showed an upward trend for using antibiotic of diarrhea in the South East and Central Asia region. CONCLUSIONS: The Central Asia region had the highest proportion of antibiotic use, with an estimated prevalence of ~55% (95% CI = 0.52, 0.59). The Europe region followed closely with a prevalence of ~44% (95% CI = 0.43, 0.45). The South East Asia region had the lowest prevalence of antibiotic use estimated at ~23% (95% CI = 0.22, 0.24), with a gradual increasing trend.

Application of TOPSIS method for flood susceptibility mapping using Excel and GIS.

This study elaborately manifests a simplified Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multicriteria decision-making (MCDM) approach that goals to determine the disparity among the distances between the positive and negative ideal solutions. MCDM methods evaluate options based on a variety of criteria by using mathematical and analytical methodologies. This promotes a more transparent and objective decision-making process by removing human biases and subjective judgements. By considering the comparative proximity to the optimal situation, TOPSIS considers the distances between the ideal and the negative-ideal alternatives. This study has concentrated on the normalization process, the appropriate determination of the ideal and the anti-ideal solution, and the metric utilized to compute the euclidean distances from the ideal best and the ideal worst.•This study expresses the simplified TOPSIS methodology as stated by Hwang and Yoon (1981). The categorization and weight assignments of the criteria have been executed from the expert's opinion and based on existing literatures.•Integration of the TOPSIS technique with GIS has been properly performed for the production of a flood susceptibility map of a highly vulnerable region and visual interpretation of the TOPSIS algorithm.•This kind of investigation saved time by sufficiently skilled specialized personnel in this field.

GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India.

Predicting landslides is becoming a crucial global challenge for sustainable development in mountainous areas. This research compares the landslide susceptibility maps (LSMs) prepared from five GIS-based data-driven bivariate statistical models, namely, (a) Frequency Ratio (FR), (b) Index of Entropy (IOE), (c) Statistical Index (SI), (d) Modified Information Value Model (MIV) and (e) Evidential Belief Function (EBF). These five models were tested in the high landslides-prone humid sub-tropical type Upper Tista basin of the Darjeeling-Sikkim Himalaya by integrating the GIS and remote sensing. The landslide inventory map consisting of 477 landslide locations was prepared, and about 70% of all landslide data was utilized for training the model, and 30% was used to validate it after training. A total of fourteen landslide triggering parameters (elevation, slope, aspect, curvature, roughness, stream power index, TWI, distance to stream, distance to road, NDVI, LULC, rainfall, modified fournier index, and lithology) were taken into consideration for preparing the LSMs. The multicollinearity statistics revealed no collinearity problem among the fourteen causative factors used in this study. Based on the FR, MIV, IOE, SI, and EBF approaches, 12.00%, 21.46%, 28.53%, 31.42%, and 14.17% areas, respectively, identified in the high and very high landslide-prone zones. The research also revealed that the IOE model has the highest training accuracy of 95.80%, followed by SI (92.60%), MIV (92.20%), FR (91.50%), and EBF (89.90%) models. Consistent with the actual distribution of landslides, the very high, high, and medium hazardous zones stretch along the Tista River and major roads. The suggested landslide susceptibility models have enough accuracy for usage in landslide mitigation and long-term land use planning in the study area. Decision-makers and local planners may utilise the study's findings. The techniques for determining landslide susceptibility can also be employed in other Himalayan regions to manage and evaluate landslide hazards.

How biotic, abiotic, and functional variables drive belowground soil carbon stocks along stress gradient in the Sundarbans Mangrove Forest?

Mangrove forests, some of the most carbon-dense ecosystems on Earth, play an important role in climate change mitigation through storing carbon in the soil. However, increasing anthropogenic pressures and sea level rise are likely to alter mangrove forest structure and functions, including the major source of carbon in mangrove ecosystems - below-ground soil carbon stocks (BSCS). Although estimating soil carbon stocks has been a popular practice in the mangroves, but poorly understood the (I) the linkage between BSCS and key ecosystem drivers (i.e., biotic, abiotic, and functional) and in (II) determining the pathways of how BSCS and multiple forest variables interact along stress gradients. This lack of understanding limits our ability to predict ecosystem carbon dynamics under future changes in climate. Here, we aimed to understand how abiotic factors (such as salinity, canopy gap fraction, nutrients, and soil pH), biotic factors (e.g., structural parameters, canopy packing, and leaf area index, LAI), and forest functional variables (e.g., growth and aboveground biomass stocks, AGB) affect BSCS (i.e., soil organic carbon, SOC, and root carbon, RC) using spatiotemporal data collected from the Sundarbans Mangrove Forest (SMF) in Bangladesh. We observed that BSCS decreased significantly with increasing salinity (e.g., from 70.6 Mg C ha-1 in the low-saline zone to 44.6 Mg C ha-1 in the high-saline zone). In contrast, the availability of several macronutrients (such as nitrogen, phosphorous, and potassium), LAI, species diversity, AGB, and growth showed a significant positive effect on SOC and RC. Stand properties, including tree height, basal area, density, canopy packing, and structural diversity, had a non-significant but positive impact on RC, while tree height and basal area significantly influenced SOC. Pathway analysis showed that salinity affects BSCS variability directly and indirectly by regulating stand structure and restricting nutrients and forest functions, although basal area, nutrients, and LAI directly enhance RC stocks. Our results indicate that an increase in nutrient content, canopy density, species diversity, and leaf area index can enhance BSCS, as they improve forest functions and contribute to a better understanding of the underlying mechanisms.

Overcoming barriers to adapt rice farming to recurring flash floods in haor wetlands of Bangladesh.

Climate change resultant hazards have become a major threat to farming, food production systems and agricultural sustainability globally. Like many other countries, Bangladesh is also the prey of climate change extremities. Haor wetlands of this country, a major rice growing area, are subjected to extreme climate tremors where millions of inhabitants lose their boro rice production due to recurring flash flood events. This study examined the barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh. The ways of overcoming barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh were also explored during the research work. The research was conducted in the Sunamganj district of Bangladesh and data was collected through a mixed-method approach. A survey was conducted with 115 haor farmers and FGD and key informant interviews were conducted with 32 and 4 respondents respectively. The results showed that the lack of availability of submergence tolerant variety (a rice variety that can survive and continue growing after being completely submerged in water for several days) is the major barrier to farmers' adaptation to flooding events followed by limited market access and lack of access to inputs. A total of 85% of respondents reported encountering moderate to severe barriers to adapt to flash flooding. Besides, some socio-economic traits, including annual family income, extension media exposure, and perception on climate change have been identified to be influencing farmers' adaptation behaviour to adapt their rice farming system to recurring flash flood events. This study elaborated pathways and suggested policy recommendations to adapt to flash flooding and to ensure sustainability in the agricultural system in the haor wetlands of Bangladesh.

Salinity reduces site quality and mangrove forest functions. From monitoring to understanding.

Mangroves continue to be threatened across their range by a mix of anthropogenic and climate change-related stress. Climate change-induced salinity is likely to alter the structure and functions of highly productive mangrove systems. However, we still lack a comprehensive understanding of how rising salinity affects forest structure and functions because of the limited availability of mangrove field data. Therefore, based on extensive spatiotemporal mangrove data covering a large-scale salinity gradient, collected from the world's largest single tract mangrove ecosystem - the Bangladesh Sundarbans, we, aimed to examine (QI) how rising salinity influences forest structure (e.g., stand density, diversity, leaf area index (LAI), etc.), functions (e.g., carbon stocks, forest growth), nutrients availability, and functional traits (e.g., specific leaf area, wood density). We also wanted to know (QII) how forest functions interact (direct vs. indirect) with biotic (i.e., stand structure, species richness, etc.) and abiotic factors (salinity, nutrients, light availability, etc.). We also asked (QIII) whether the functional variable decreases disproportionately with salinity and applied the power-law (i.e., Y = a Xb) to the salinity and functional variable relationships. In this study, we found that rises in salinity significantly impede forest growth and produce less productive ecosystems dominated by dwarf species while reducing stand structural properties (i.e., tree height, basal area, dominant tree height, LAI), soil carbon (organic and root carbon), and macronutrient availability in the soil (e.g., NH4+, P, and K). Besides, species-specific leaf area (related to resource acquisition) also decreased with salinity, whereas wood density (related to resource conservation) increased. We observed a declining abundance of the salt-intolerant climax species (Heritiera fomes) and dominance of the salt-tolerant species (Excoecaria agallocha, Ceriops decandra) in the high saline areas. In the case of biotic and abiotic factors, salinity and salinity-driven gap fraction (high transmission of light) had a strong negative impact on functional variables, while nutrients and LAI had a positive impact. In addition, the power-law explained the consistent decline of functional variables with salinity. Our study disentangles the negative effects of salinity on site quality in the Sundarbans mangrove ecosystem, and we recognize that nutrient availability and LAI are likely to buffer the less salt-tolerant species to maintain the ability to sequester carbon with sea-level rise. These novel findings advance our understanding of how a single stressor-salinity-can shape mangrove structure, functions, and productivity and offer decision makers a much-needed scientific basis for developing pragmatic ecosystem management and conservation plans in highly stressed coastal ecosystems across the globe.

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh.

Intended pregnancy is one of the significant indicators of women's well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married women in Bangladesh. From BDHS 2017-18, only 1129 pregnant women aged 15-49 were eligible for this study. An independent χ 2 test had performed before we considered six popular ML algorithms, such as logistic regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), naïve Bayes (NB), and elastic net regression (ENR) to predict the unintended pregnancy. Accuracy, sensitivity, specificity, Cohen's Kappa statistic, and area under curve (AUC) value were used as model evaluation. The bivariate analysis result showed that women aged 30-49 years, poor, not educated, and living in male-headed households had a higher percentage of unintended pregnancy. We found various performance parameters for the classification of unintended pregnancy: LR accuracy = 79.29%, LR AUC = 72.12%; RF accuracy = 77.81%, RF AUC = 72.17%; SVM accuracy = 76.92%, SVM AUC = 70.90%; KNN accuracy = 77.22%, KNN AUC = 70.27%; NB accuracy = 78%, NB AUC = 73.06%; and ENR accuracy = 77.51%, ENR AUC = 74.67%. Based on the AUC value, we can conclude that of all the ML algorithms we investigated, the ENR algorithm provides the most accurate classification for predicting unwanted pregnancy among Bangladeshi women. Our findings contribute to a better understanding of how to categorize pregnancy intentions among Bangladeshi women. As a result, the government can initiate an effective campaign to raise contraception awareness.

Green logistics and environment, economic growth in the context of the Belt and Road Initiative.

Infrastructure development has been a priority area since the Belt and Road Initiative (BRI) was proposed. This paper uses the generalized method of moments (GMM) to analyze the relationship between the green logistics, environment and economic growth based on panel data of countries along the BRI from 2007 to 2018. It is found that fossil fuels are the core of logistics operation activities, and the more fossil fuels are used, the more detrimental to the sustainable development of the environment. "The green logistics is negatively correlated with fossil fuel energy consumption and carbon emissions per capita in countries along the Belt and Road. At the same time, the green logistics can also bring more export opportunities for these countries and increase the national income per capita. The development of the green logistics is of great significance to the countries' environment and sustainable economic development along the Belt and Road.

Effects of hydrocarbon chain on the vesicle size distribution, kinetics of average size, bending modulus, and elastic modulus of lipid membranes.

The effects of the hydrocarbon chain of lipids on the size distribution of giant unilamellar vesicles (GUVs), kinetics of average size, bending modulus, and elastic modulus of membranes have been investigated. 1,2-dioleoyl-sn-glycero-3-phosphocholine (18:1 (Δ9-Cis) PC (DOPC)), 1,2-dipalmitoleoyl-sn-glycero-3-phosphocholine (16:1 (Δ9-Cis) PC), and 1,2-ditridecanoyl-sn-glycerol-3-phosphocholine (13:0 PC (DTPC)) lipids were considered. The number of hydrocarbons in a chain of the corresponding lipid was 18, 16, and 13. GUVs were prepared using the natural swelling method under incubation times of 20, 40, 60, 90, 120, and 180 min. The size distribution of vesicles was fitted using the lognormal distribution. The average sizes of DOPC, 16:1 (Δ9-Cis) PC, and DTPC-GUVs increased with the incubation time until 120 min, and then remained steady at 16.7 ± 0.2, 15.2 ± 0.4 and 12.0 ± 0.3 µm for the corresponding lipids. The average size at equilibrium state increased with the number of hydrocarbons. The incubation time-dependent average size was fitted with an exponential growth equation, and then the kinetic constants of 0.028 ± 0.004, 0.036 ± 0.007, and 0.083 ± 0.009 min-1 for DOPC, 16:1 (Δ9-Cis) PC, and DTPC-GUVs, respectively, were obtained. The equilibrium size distribution was fitted by the theoretical equation, and the bending modulus for DOPC, 16:1 (Δ9-Cis) PC, and DTPC membranes were 19.5 ± 0.2, 18.5 ± 0.1 and 14.3 ± 0.1 kBT, respectively. The bending modulus increased with the number of hydrocarbons. The elastic modulus of these membranes was 261 mN/m with a 4% fluctuation. The correlation between the average size and the square root of the bending modulus was supported by theoretical analysis.

Meta-Analysis of Randomized Clinical Trials Evaluating Effectiveness of a Multivitamin Supplementation against Oxidative Stress in Healthy Subjects.

A meta-analysis has been widely applied to draw general conclusions using a set of studies with similar purposes and designs. This study aimed to perform a meta-analysis of six randomized placebo-controlled trials, independently conducted for the relationship between a plant-based multivitamin/mineral supplementation (PMS) and oxidative stress for 6 to 8 weeks, to provide overall estimates of those effects. In detail, linear mixed model analysis was first conducted on each study to obtain individual estimates; then, two types of meta-analysis were applied to combine the individual estimates from all available studies (overall meta-analysis) and region-specific studies (subgroup meta-analysis). In the meta-analysis, we selected 19 biomarker variables that overlapped in at least two studies and found 6 variables significant in at least one meta-analysis. The overall estimates of beta coefficients were 0.17 for vitamin C, 0.80 for vitamin B6, 0.46 for vitamin B12, 0.81 for folate, 0.36 for ß-carotene, and -0.17 for oxidized LDL (ox-LDL). Subsequent association analysis revealed significant negative correlations between plasma free radical scavenging nutrients and plasma ox-LDL levels, indicating a general benefit of PMS in alleviating oxidative stress by providing exogenous oxidant scavengers.

A Dynamic Algorithm for Interference Management in D2D-Enabled Heterogeneous Cellular Networks: Modeling and Analysis.

To supporting a wider and diverse range of applications, device-to-device (D2D) communication is a key enabler in heterogeneous cellular networks (HetCNets). It plays an important role in fulfilling the performance and quality of service (QoS) requirements for 5G networks and beyond. D2D-enabled cellular networks enable user equipment (UE) to communicate directly, without any or with a partial association with base stations (eNBs). Interference management is one of the critical and complex issues in D2D-enabled HetCNets. Despite the wide adoption of D2D communications, there are very few researchers addressing the problems of mode selection (MS), as well as resource allocation for mutual interference in three-tier cellular networks. In this paper, we first identify and analyze three key factors, namely outage probability, signal-to-interference and noise ratio (SINR), and cell density that influence the performance of D2D-enabled HetCNets. We then propose a dynamic algorithm based on a distance-based approach to minimize the interference and to guarantee QoS for both cellular and D2D communication links. Results obtained show that outage probability is improved by 35% and 49% in eNB and SCeNB links, respectively, when compared with traditional neighbor-based methods. The findings reported in this paper provide some insights into interference management in D2D communications that can help network researchers and engineers contribute to further developing next-generation cellular networks.

Smoker's characteristics, general health and their perception of smoking in the social environment: a study of smokers in Rajshahi City, Bangladesh.

Background: Smoking is one of the bad habits in social environment and is one of the main causes of immature death in Bangladesh. Rajshahi is one of the cleanest, most peaceful cities in Bangladesh, but the inhabitants often feel uncomfortable about smokers who smoke in public places and often on transport. Smoking frequency is very high among males compared to females, and a large number of smokers are building or road construction laborers and people involved in offering different services such as transportation, vending from vans, etc. The practice of smoking in this area is destructive for mental and physical health especially for students compared to other professionals because the city is known as the City of Education. Methods: The study analyzes smokers' characteristics, general health, and their (smokers) perception of smoking in public places. Cross-sectional data were collected randomly from 160 smokers through face-to-face questionnaire survey. The determinants of complexities with regard to social environment and human health were studied using frequency distribution, chi-square test, and binary and multinomial logistic regression analysis using IBM SPSS version 24. Results: Frequency distributions reveal that 93.8% of smokers believe that smoking creates public health hazards, 51.3% of smokers think it causes breathing complexities for non-smokers, 48.8% of smokers feel smoking causes air pollution, 68.8% of smokers think smoking causes gastric problems, 24.4% of smokers had headache problems due to smoking and cigarette fumes, 86.3% of smokers learnt smoking from friends, 48.8% of smokers smoke due to their addiction and 25.6% for depression, and 80.6% usually smoke after having a meal. The chi-square test reveals that class of smokers was significantly associated with frequency of heartbeat rate, starting smoking at specific age level was significantly associated with suffering from diseases, category of smoking articles was significantly associated with suffering from disease, class of smokers was significantly associated with causes for smoking, and starting smoking at specific age level was significantly associated with profession of the smokers at 1% level of significance respectively. A significant odds ratio was found (OR = 6.363, 95% CI 1.918-21.104, p < 0.01) for the profession group of students/labour at 1% level; their outcomes for suffering from diseases such as gastric problem and fever/headache/others were 6.363 times those for the profession group of service/other smokers. Conclusion: Smoking in public places should be restricted because non-smokers cannot breathe freely and it is not healthy for them to inhale smoke indirectly, which has many adverse effects on public health. The study also reveals that the majority of the smokers have gastric problems, abnormal heartbeat rates, frequent headaches, depression and addiction problems, etc., and that they believe that smoking causes significant health hazard on human health and social environment. Therefore, necessary interventions should be taken immediately by policy-makers to prevent smoking in public places. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-020-01413-w.

Is BMI associated with anemia and hemoglobin level of women and children in Bangladesh: A study with multiple statistical approaches.

BACKGROUND: The coexistence of undernutrition and obesity is an emerging problem for developing countries like Bangladesh. Anemia is another critical public health threat, prevalent predominantly among women and children. Undernutrition is linked with a higher risk of anemia, and lower dietary iron intake might be the possible reason. However, the risk of anemia among obese/overweight individuals is controversial. The study explores the relation of BMI with anemia and blood hemoglobin level among women and children in Bangladesh. METHODS: Multiple statistical approaches were employed to nationally representative secondary data (BDHS 2011) on women (n = 5680) age 15-49 years and children (n = 2373) age 6-59 months to illuminate the relation between BMI and anemia. BMI was categorized according to the WHO recommended BMI category for Asian people. Descriptive statistics were used to measure mean hemoglobin level. Chi-square test, Pearson correlation, Two-way ANOVA, binary, ordinal, and restricted cubic splines (RCS) regression were used to study the association of BMI with anemia and hemoglobin level. RESULTS: Chi-square test reveals significant association, though not intense, among BMI and anemia categories of women (15-49 years) (χ2 ≥99, p<2.2e-16 and Cramér's V = 0.0799-0.1357). From ANOVA analysis, a significant difference in blood hemoglobin level was found among women (total sample and nonpregnant) with different BMI categories (p≤0.05). Binary (Severely Underweight: OR 1.2680, 95% CI 0.755-2.161; Obese: OR 0.4038, 95% CI 0.120-1.177), Ordinal logistic regression (Severely Underweight: OR 1.337, 95% CI 0.842-2.115; Obese: OR 0.504, 95% CI 0.153-1.411) and restricted cubic spline regression (Severely Underweight: OR >1.5; Obese: OR ~0.5) reveal that the risk of anemia was higher among underweight and lower among obese/overweight women compared to normal women. Lower anemia risk among richest women indicates probable higher dietary iron intake among obese/overweight women. CONCLUSION: In the current study, women with overweight/obesity from Bangladesh were shown to have lower likelihood of being anemic, while underweight women more likely to be anemic. However, no relation between BMI and anemia was found among children.

The anthropometric assessment of body composition and nutritional status in children aged 2-15 years: A cross-sectional study from three districts in Bangladesh.

BACKGROUND: Early life nutrition plays a critical role in the development of better health and nutrition in adulthood. However, assessing the nutritional status of Bangladeshi children and adolescents through measurement of body composition using skinfold thickness is barely studied. The current study aims to determine children's body composition and nutritional status, and contributing factors among children aged 2 to 15 years in the northern part of Bangladesh. METHODS: This is a descriptive cross-sectional study done in Bangladesh. Anthropometric methods, including multiple skinfold thickness and basic anthropometric and socio-demographic characteristics, were used. Body composition was calculated from multiple skinfold thicknesses using the standard regression equation. Nutritional status was measured using Z score according to WHO 2007 reference standard. A total of 330 children from Naogaon, Bogra and Kurigram districts in Bangladesh were examined from April 2019 to September 2019. RESULTS: The Nutritional status of 2-15 years old child is exceedingly poor in the northern part of Bangladesh. Fat mass and fat-free mass were higher among children from Kurigram district than from Bogra and Naogaon district. Body fat percentages and arm fat area were greater among female children than males. The overall prevalence of stunting, underweight and wasting was around 25%, 32% and 29%, respectively, and the rate was higher among girls and children aged 2-5 years. The average SD score for weight-for-age, height-for-age, and BMI-for-age was -1.295, -0.937 and -1.009. The median weight-for-age and height-for-age Z scores of boys and girls were below the WHO reference percentile rank. Girls were twice (OR:1.951, CI:1.150-3.331) as likely to suffer from being underweight than boys. Children who don't practice handwashing are three times (OR:3.531, CI:1.657-7.525) more likely to be underweight. Children become underweight and stunted when their family income is not sufficient to maintain their nutritional requirements. CONCLUSIONS: The children of the three northern districts had a poor nutritional status, and family income was the potential contributing factor. Therefore, interventions like the promotion of income-generating activities and integrated approaches to ensuring food diversification could be an option to address the nutritional problem of children of the three northern districts of Bangladesh.