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

by Md. Abu Raihan, Md. Saiful Islam, Shariful Islam, A. F. M. Mahmudul Islam, Khandaker Tanveer Ahmed, Tania Ahmed, Md. Nahidul Islam, Shamsunnahar Ahmed, Mysha Samiha Chowdhury, Dipto Kumar Sarker, Anika Bushra Lamisa

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 (β = 0.10, p = 0.001), higher education (College: β = 0.09, p = 0.025; Bachelor: β = 0.22, p 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.

Nutrient density of Bangladeshi foods and its application in planning diet for pregnant women

by Nazma Shaheen, Abira Nowar, Saiful Islam, Md. Hafizul Islam, Md. Ruhul Amin

Nutrient profiling is a method that classifies foods based on their nutrient content and identifies foods that are high in micronutrients both across and within food groups. This study aimed to identify foods that are rich sources of the seven micronutrients (iron, zinc, calcium, thiamine, riboflavin, vitamin A, and vitamin B₁₂) of public health concern for the Bangladeshi population._. This study developed a metric termed “naturally nutrient-rich score 7 (NNR₇)” specifically for third-trimester pregnant women to identify nutrient-dense foods. Further, it computed the nutrient adequacy score (NAS) of the top NNR₇-scored foods for seven micronutrients to assess the extent (percent) to which foods can meet pregnant women’s recommended dietary allowances (RDA). A linear programming technique was then used to construct a nutrient-adequate model diet for third-trimester pregnant women using the top ten NNR₇-scored foods. According to the NNR₇, food groups such as leafy vegetables, fish, meat, poultry and eggs, and vegetables are the richest sources of the problem micronutrients. Mutton liver (916.7%), soybean (39.3%), lamb liver (2160%) and duck liver (50.0%) were found to fulfill the highest percentage of the RDA of vitamin A, zinc, vitamin B_12, and iron, respectively. In the formulated nutrient-adequate diets for pregnant women, rice, potato, brown wheat flour, and soya oil were universal to all three diets and Bengal gram, orange, Ganges River sprat, and duck liver were the most common ones. The study findings highlight the need for the consumption of foods such as leafy vegetables, fish, meat, poultry, eggs, pulses and vegetables to increase the intake of problematic micronutrients. Planning a nutrient-adequate diet for pregnant women using linear programming can be an alternative approach to optimize and shape food choices to meet their nutritional requirements.

An agent-based nested model integrating within-host and between-host mechanisms to predict an epidemic

by Yuichi Tatsukawa, Md. Rajib Arefin, Kazuki Kuga, Jun Tanimoto

The COVID-19 pandemic has remarkably heightened concerns regarding the prediction of communicable disease spread. This study introduces an innovative agent-based modeling approach. In this model, the quantification of human-to-human transmission aligns with the dynamic variations in the viral load within an individual, termed “within-host” and adheres to the susceptible–infected–recovered (SIR) process, referred to as “between-host.” Variations in the viral load over time affect the infectivity between individual agents. This model diverges from the traditional SIR model, which employs a constant transmission probability, by incorporating a dynamic, time-dependent transmission probability influenced by the viral load in a host agent. The proposed model retains the time-integrated transmission probability characteristic of the conventional SIR model. As observed in this model, the overall epidemic size remains consistent with the predictions of the standard SIR model. Nonetheless, compared to predictions based on the classical SIR process, notable differences existed in the peak number of the infected individuals and the timing of this peak. These nontrivial differences are induced by the direct correlation between the time-evolving transmission probability and the viral load within a host agent. The developed model can inform targeted intervention strategies and public health policies by providing detailed insights into disease spread dynamics, crucial for effectively managing epidemics.

Development of an enhanced analytical method utilizing pepper matrix as an analyte protectant for sensitive GC‒MS/MS detection of dimethipin in animal-based food products

by Jae-Han Shim, Md. Musfiqur Rahman, Tuba Esatbeyoglu, Fatih Oz, A. M. Abd El-Aty

Herein, an analytical method using gas chromatography-tandem mass spectrometry (GC‒MS/MS) was devised to detect the presence of the troublesome pesticide dimethipin in various animal-based food products, including chicken, pork, beef, eggs, and milk. The injection port was primed with a matrix derived from pepper leaves that acts as an analyte protectant (AP) to safeguard the target compound from thermal degradation during gas chromatography. The presence of AP resulted in a remarkable limit of quantification of 0.005 mg/kg for dimethipin in five matrices. Three different versions (original, EN, and AOAC) of the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method were compared for dimethipin extraction, with a double-layer solid-phase extraction (SPE) cartridge utilized for matrix purification. A seven-point external calibration curve was established for dimethipin in the five matrices, demonstrating excellent linearity with determination coefficients (R²) ≥ 0.998. The developed quantitative method was validated by fortifying each matrix with three different concentrations of standard dimethipin, and the average recovery fell within the acceptable range outlined in the CODEX guidelines (ranging from 88.8% to 110.0%), with a relative standard deviation (RSD) of ≤ 11.97%. This method effectively addresses the challenge of analyzing dimethipin and can therefore be used as a routine monitoring tool for dimethipin across various matrices.

Downscaling epidemiological time series data for improving forecasting accuracy: An algorithmic approach

by Mahadee Al Mobin, Md. Kamrujjaman

Data scarcity and discontinuity are common occurrences in the healthcare and epidemiological dataset and often is needed to form an educative decision and forecast the upcoming scenario. Often to avoid these problems, these data are processed as monthly/yearly aggregate where the prevalent forecasting tools like Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and TBATS often fail to provide satisfactory results. Artificial data synthesis methods have been proven to be a powerful tool for tackling these challenges. The paper aims to propose a novel algorithm named Stochastic Bayesian Downscaling (SBD) algorithm based on the Bayesian approach that can regenerate downscaled time series of varying time lengths from aggregated data, preserving most of the statistical characteristics and the aggregated sum of the original data. The paper presents two epidemiological time series case studies of Bangladesh (Dengue, Covid-19) to showcase the workflow of the algorithm. The case studies illustrate that the synthesized data agrees with the original data regarding its statistical properties, trend, seasonality, and residuals. In the case of forecasting performance, using the last 12 years data of Dengue infection data in Bangladesh, we were able to decrease error terms up to 72.76% using synthetic data over actual aggregated data.

The burden of non-disabled frailty and its associated factors among older adults in Bangladesh

by Sabuj Kanti Mistry, A. R. M. Mehrab Ali, Uday Narayan Yadav, Saruna Ghimire, Afsana Anwar, Md. Nazmul Huda, Fouzia Khanam, Rashidul Alam Mahumud, Ateeb Ahmad Parray, Shovon Bhattacharjee, David Lim, Mark Fort Harris

Objective

The present study aims to measure the prevalence of non-disabled frailty and its associated factors among Bangladeshi older adults.

Methods

This cross-sectional study was conducted during September and October 2021 among 1,045 Bangladeshi older adults (≥60 years). Telephone interviews, using a semi-structured questionnaire, were undertaken to collect data on participants’ characteristics and level of frailty. The non-disabled frailty was measured using the ‘Frail Non-Disabled (FiND)’ questionnaire. A multinomial logistic regression model assessed the factors associated with frailty among the participants.

Results

Around a quarter of the participants (24.8%) were frail. The multinomial regression analysis showed that older participants aged ≥80 years (RRR = 3.23, 95% CI: 1.41–7.37) were more likely to be frail compared to participants aged 60–69 years. Likewise, the participants living in a large family with ≥4 members (RRR = 1.39, 95% CI: 1.01–1.92) were more likely to be frail compared to those living in smaller families. Also, participants having memory or concentration problems (RRR = 1.56, 95% CI: 1.12–2.17) were more likely to be frail compared to those who were not suffering from these problems. Moreover, participants whose family members were non-responsive to their day-to-day assistance (RRR = 1.47, 95% CI: 1.06–2.03) were more likely to be frail compared to those whose family members were responsive. Furthermore, participants who were feeling lonely (RRR = 1.45, 95% CI: 1.07–1.98) were more likely to be frail than their counterparts who were not feeling lonely.

Conclusions

The findings of the present study suggest developing tailored interventions to address the burden of frailty among the older populations in Bangladesh. In particular, providing long-term care and health promotion activities can be of value in preventing frailty and reducing adverse health outcomes among this vulnerable population group.

In silico exploration of <i>Serratia</i> sp. BRL41 genome for detecting prodigiosin Biosynthetic Gene Cluster (BGC) and in vitro antimicrobial activity assessment of secreted prodigiosin

by Farhana Boby, Md. Nurul Huda Bhuiyan, Barun Kanti Saha, Subarna Sandhani Dey, Anik Kumar Saha, Md Jahidul Islam, Mahci Al Bashera, Shyama Prosad Moulick, Farhana Jahan, Md. Asad Uz Zaman, Sanjana Fatema Chowdhury, Showti Raheel Naser, Md. Salim Khan, Md. Murshed Hasan Sarkar

The raising concern of drug resistance, having substantial impacts on public health, has instigated the search of new natural compounds with substantial medicinal activity. In order to find out a natural solution, the current study has utilized prodigiosin, a linear tripyrrole red pigment, as an active ingredient to control bacterial proliferation and prevent cellular oxidation caused by ROS (Reactive Oxygen Species). A prodigiosin-producing bacterium BRL41 was isolated from the ancient Barhind soil of BCSIR Rajshahi Laboratories, Bangladesh, and its morphological and biochemical characteristics were investigated. Whole genome sequencing data of the isolate revealed its identity as Serratia sp. and conferred the presence of prodigiosin gene cluster in the bacterial genome. “Prodigiosin NRPS”, among the 10 analyzed gene clusters, showed 100% similarity with query sequences where pigC, pigH, pigI, and pigJ were identified as fundamental genes for prodigiosin biosynthesis. Some other prominent clusters for synthesis of ririwpeptides, yersinopine, trichrysobactin were also found in the chromosome of BRL41, whilst the rest displayed less similarity with query sequences. Except some first-generation beta-lactam resistance genes, no virulence and resistance genes were found in the genome of BRL41. Structural illumination of the extracted red pigment by spectrophotometric scanning, Thin-Layer Chromatography (TLC), Fourier Transform Infrared Spectroscopy (FTIR), and change of color at different pH solutions verified the identity of the isolated compound as prodigiosin. Serratia sp. BRL41 attained its maximum productivity 564.74 units/cell at temperature 30˚C and pH 7.5 in two-fold diluted nutrient broth medium. The compound exhibited promising antibacterial activity against Gram-positive and Gram-negative bacteria with MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration) values ranged from 3.9 to15.62 μg/mL and 7.81 to 31.25 μg/mL respectively. At concentration 500 μg/mL, except in Salmonella enterica ATCC-10708, prodigiosin significantly diminished biofilm formed by Listeria monocytogens ATCC-3193, Pseudomonas aeruginosa ATCC-9027, Escherichia coli (environmental isolate), Staphylococcus aureus (environmental isolate). Cellular glutathione level (GSH) was elevated upon application of 250 and 500 μg/mL pigment where 125 μg/mL failed to show any free radical scavenging activity. Additionally, release of cellular components in growth media of both Gram-positive and Gram-negative bacteria were facilitated by the extract that might be associated with cell membrane destabilization. Therefore, the overall findings of antimicrobial, antibiofilm and antioxidant activities suggest that in time to come prodigiosin might be a potential natural source to treat various diseases and infections.

Altered serum TNF-α and MCP-4 levels are associated with the pathophysiology of major depressive disorder: A case-control study results

by Jannatul Nayem, Rapty Sarker, A. S. M. Roknuzzaman, M. M. A. Shalahuddin Qusar, Sheikh Zahir Raihan, Md. Rabiul Islam, Zobaer Al Mahmud

Background

Major Depressive Disorder (MDD) is a debilitating mental health condition with complex etiology, and recent research has focused on pro-inflammatory cytokines and chemokines as potential contributors to its pathogenesis. However, studies investigating the roles of TNF-α and MCP-4 in MDD within the Bangladeshi population are scarce. This study aimed to assess the association between serum TNF-α and MCP-4 levels and the severity of MDD, exploring their potential as risk indicators for MDD development.

Methods

This case-control study enrolled 58 MDD patients from Bangabandhu Sheikh Mujib Medical University (BSMMU) Hospital, Dhaka, Bangladesh, alongside 30 age, sex, and BMI-matched healthy controls. MDD diagnosis followed DSM-5 criteria and disease severity using the 17-item Hamilton Depression Rating Scale (Ham-D). We measured serum TNF-α and MCP-4 levels using ELISA assays according to the supplied protocols.

Results

The study revealed significantly elevated serum TNF-α levels in MDD patients (47±6.6 pg/ml, mean±SEM) compared to controls (28.06±1.07 pg/ml). These increased TNF-α levels positively correlated with Ham-D scores (Pearson’s r = 0.300, p = 0.038), suggesting a potential association between peripheral TNF-α levels and MDD pathology. Additionally, MDD patients exhibited significantly higher serum MCP-4 levels (70.49±6.45 pg/ml) than controls (40.21±4.08 pg/ml). However, serum MCP-4 levels showed a significant negative correlation (r = -0.270, P = 0.048) with Ham-D scores in MDD patients, indicating a more complex role for MCP-4 in MDD pathogenesis.

Conclusion

This study highlights that Bangladeshi MDD patients exhibit heightened inflammatory and immune responses compared to controls, supporting the cytokine hypothesis in MDD pathogenesis. Serum TNF-α, but not MCP-4, shows promise as a potential biomarker for assessing the risk of MDD development, which could aid in early detection. Future investigations involving larger populations and longitudinal studies are essential to confirm the utility of these cytokines as biomarkers for MDD.