Evaluating an ICD-10 Based Proxy for Date of Birth in Electronic Health Record Data.

Purpose: To comply with the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule, many real-world data providers mask a patient's date of birth by supplying only year of birth to data users. The lack of granularity around patient age is a challenge when using RWD, especially for pediatric research studies. In this study, a proxy for patient date of birth is evaluated using electronic health record (EHR) data.

Pathogenic single nucleotide polymorphisms in RhoA gene: Insights into structural and functional impacts on RhoA-PLD1 interaction through molecular dynamics simulation.

Molecular switches serve as key regulators of biological systems by acting as one of the crucial driving forces in the initiation of signal transduction pathway cascades. The Ras homolog gene family member A (RhoA) is one of the molecular switches that binds with GTP in order to cycle between an active GTP-bound state and an inactive GDP-bound state. Any aberrance in control over this circuit, particularly due to any perturbation in switching, leads to the development of different pathogenicity.

Segmentation for mammography classification utilizing deep convolutional neural network.

Background: Mammography for the diagnosis of early breast cancer (BC) relies heavily on the identification of breast masses. However, in the early stages, it might be challenging to ascertain whether a breast mass is benign or malignant. Consequently, many deep learning (DL)-based computer-aided diagnosis (CAD) approaches for BC classification have been developed.

Evaluation of Efficacy and Safety of Empagliflozin in Bangladeshi Patients with Type 2 Diabetes Mellitus (EFFISAEM Study).

Background: Empagliflozin is a relatively newer glucose-lowering drug (GLD) with many extra-glycemic benefits. To date, no study has evaluated the efficacy and safety of empagliflozin in Bangladeshi patients with type 2 diabetes mellitus (T2DM).

Objectives: To assess the efficacy and safety of empagliflozin as an add-on to ongoing GLDs in Bangladeshi adults with uncontrolled T2DM.

Prodigiosin Demonstrates Promising Antiviral Activity Against Dengue Virus and Zika Virus in In-silico Study.

Dengue (DENV) and Zika virus (ZIKV), transmitted by Aedes mosquitoes, pose significant public health challenges. Effective treatments for these viruses remain elusive, highlighting the urgent need for new efficient antiviral therapies. This study explores prodigiosin, a microbial tripyrrole pigment, as an antiviral agent against both DENV and ZIKV employing advanced analytical approaches which integrate molecular docking, CASTp 3.

Efficacy and tolerability of single-fraction radiotherapy for spinal bone metastases in a low-middle-income country setting: a prospective study.

Aims: This study aimed to evaluate the symptomatic efficacy and tolerability of three different radiotherapy (RT) regimens for patients with vertebral metastases in a low-middle-income country setting, focusing specifically on the effectiveness of single-fraction radiotherapy.

Methods: Conducted at the National Institute of Cancer Research and Hospital, Bangladesh, from July 1, 2020, to June 30, 2021, this prospective, non-randomized study enrolled 90 patients aged 18 to 75 years with histologically confirmed primary malignancies and vertebral metastases. Patients were allocated to one of three treatment arms: 8 Gy in a single fraction (Arm A), 20 Gy in 5 fractions (Arm B), or 30 Gy in 10 fractions (Arm C).

Rethinking dormancy: Antibiotic persisters are metabolically active, non-growing cells.

Objectives: Bacterial persisters are a subpopulation of multidrug-tolerant cells capable of surviving and resuming activity after exposure to bactericidal antibiotic concentrations, contributing to relapsing infections and the development of antibiotic resistance. In this study, we challenge the conventional view that persisters are metabolically dormant by providing compelling evidence that an isogenic population of Escherichia coli remains metabolically active in persistence.

Methods: Using transcriptomic analysis, we examined E.

Ensemble of hybrid model based technique for early detecting of depression based on SVM and neural networks.

The prevalence of depression has increased dramatically over the last several decades: it is frequently overlooked and can have a significant impact on both physical and mental health. Therefore, it is crucial to develop an automated detection system that can instantly identify whether a person is depressed. Currently, machine learning (ML) and artificial neural networks (ANNs) are among the most promising approaches for developing automated computer-based systems to predict several mental health issues, such as depression.

Feasibility of Employing mHealth in Delivering Preventive Nutrition Interventions Targeting the First 1000 Days of Life: Experiences from a Community-Based Cluster Randomised Trial in Rural Bangladesh.

Background/objectives: An Android platform-based customised app and web-linked system was developed to aid in implementing selected nutrition interventions by community health workers (CHWs) in a community-based cluster randomised trial (c-RCT) in rural Bangladesh.

Methods: Here, we describe the architecture of the intervention delivery system, and explore feasibility of employing mHealth as CHWs' job aid, employing a mixed-method study design covering 17 visits per mother-child dyad. We analysed CHWs' real-time visit information from monitoring and documentation data, and CHWs' qualitative interviews to explore the advantages and barriers of using mHealth as a job aid.

Hyperbaric oxygen rapidly produces intracellular bioenergetics dysfunction in human pulmonary cells.

Hyperoxic exposure lasting days alters mitochondrial bioenergetic and dynamic functions in pulmonary cells as indices of oxygen toxicity. The aim of this study was to examine effects of short duration hyperbaric and hyperoxic exposures to induce oxygen toxicity similarly. Cultured human lung microvascular endothelial cells, human pulmonary artery endothelial cells and A549 cells were exposed to hyperoxia (∼5 % CO equivalent, balance O) under hyperbaric conditions (4.

The cost of COVID-19 vaccine delivery in Bangladesh.

COVID-19 vaccination has been instrumental in fighting the pandemic, but evidence on the actual costs associated with delivering these vaccines in resource-constrained settings has been limited. We estimated the cost of delivering COVID-19 vaccines in Bangladesh through five delivery strategies in 2021 and 2022, including Ministry of Health (MOH) hospitals, non-MOH government hospitals, outreach at Expanded Program on Immunization (EPI) centers, mass campaigns, and schools. This was a bottom-up costing study, estimating costs from a payer and beneficiary perspective.

Enhancing Thermal Stability of Perovskite Solar Cells through Thermal Transition and Thin Film Crystallization Engineering of Polymeric Hole Transport Layers.

Organic hole transport layers (HTLs) have been known to be susceptible to thermal stress, leading to poor long-term stability in perovskite solar cells (PSCs). We synthesized three 2,5-dialkoxy-substituted, 1,4-bis(2-thienyl)phenylene (TPT)-based conjugated polymers (CPs) linked with thiophene-based (thiophene (T) and thienothiophene (TT)) comonomers and evaluated them as HTLs in n-i-p PSCs. TPT-T (MB/C6), which has branched 2-methylbutyl and linear hexyl (MB/C6) side chains, emerged as a promising HTL candidate, enabling power conversion efficiencies (PCEs) greater than 15%.

Two-year epidemiology of post-COVID-19 conditions in Bangladesh: a cohort study of post-COVID-19 from 12,925 SARS-CoV-2 cases between July and December 2021-2023 in Bangladesh.

Background: Post-COVID-19 conditions (PCCs), also known as long COVID, is persistently debilitating disorders that need investigation on their incidence, morbidity, and case-fatality rate.

Purpose: The objectives of this cohort study were to determine the incidence, characteristics, case-fatality, morbidity, and recovery of post-COVID-19 symptoms throughout a two-year period of observation.

Methods: This was a population-based cohort study of post-COVID-19 cases among 12,925 SARS-CoV-2 positive individuals in eight administrative districts of Bangladesh between July and December 2021-2023.

Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentime.

Background: Mood and anxiety disorders are highly prevalent and comorbid worldwide, with variability in symptom severity that fluctuates over time. Digital phenotyping, a growing field that aims to characterize clinical, cognitive and behavioral features via personal digital devices, enables continuous quantification of symptom severity in the real world, and in real-time.

Methods: In this study, N=114 individuals with a mood or anxiety disorder (MA) or healthy controls (HC) were enrolled and completed 30-days of ecological momentary assessments (EMA) of symptom severity.

Early Postoperative Outcome Following Laparoscopic Surgeries in Rectal Malignancies.

Rectal malignancies that require abdominoperineal resection (APR) and Anterior resection (AR) is very common. Laparoscopic APR or AR can be a better option. This study observed the feasibility of this newer technique for alternative to conventional open method.

An Alarming Rise of Candidemia Caused by Non-Albicans Candida Species in Intensive Care Unit in Mymensingh, Bangladesh.

In Intensive Care Units (ICUs) infection represents the most frequent complication leading to high mortality. Particularly the incidence of fungal infections, especially due to Candida spp., has been increasing during the last years.

Symptom response and episodic disability of long COVID in people with spinal cord injury: A case-control study.

Background: Spinal cord injury (SCI) is a consequence of significant disability and health issues globally, and long COVID represents the symptoms of neuro-musculoskeletal, cardiovascular and respiratory complications.

Purpose: This study aimed to identify the symptom responses and disease burden of long COVID in individuals with spinal cord injury.

Methods: This case-control study was conducted on patients with SCI residing at a specialised rehabilitation centre in Bangladesh.

Specific quantification of inducible HIV-1 reservoir by RT-LAMP.

Background: Strategies toward HIV-1 cure aim to clear, inactivate, reduce, or immunologically control the virus from a pool of latently infected cells such that combination antiretroviral therapy (cART) can be safely interrupted. In order to assess the impact of any putative curative interventions on the size and inducibility of the latent HIV-1 reservoir, robust and scalable assays are needed to precisely quantify the frequency of infected cells containing inducible HIV-1.

Methods: We developed Specific Quantification of Inducible HIV-1 by RT-LAMP (SQuHIVLa), leveraging the high sensitivity and specificity of RT-LAMP, performed in a single reaction, to detect and quantify cells expressing tat/rev HIV-1 multiply spliced RNA (msRNA) upon activation.

Comparing effectiveness of physiotherapy versus drug management on fatigue, physical functioning, and episodic disability for myalgic encephalomyelitis in post-COVID-19 condition: a study protocol of randomized control trial.

Background: Physiotherapy interventions effectively improved fatigue and physical functioning in non-COVID patients with myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS). There is a research gap on the effectiveness of physiotherapy interventions versus drug management on ME/CFS in post-COVID-19 conditions (PCC).

Methods: We planned a three-arm prospective randomized control trial on 135 PCC cases with ME/CFS who are diagnosed between 20 November 2023 and 20 May 2024 from a population-based cohort.

Development of a multi-fusion convolutional neural network (MF-CNN) for enhanced gastrointestinal disease diagnosis in endoscopy image analysis.

Gastrointestinal (GI) diseases are prevalent medical conditions that require accurate and timely diagnosis for effective treatment. To address this, we developed the Multi-Fusion Convolutional Neural Network (MF-CNN), a deep learning framework that strategically integrates and adapts elements from six deep learning models, enhancing feature extraction and classification of GI diseases from endoscopic images. The MF-CNN architecture leverages truncated and partially frozen layers from existing models, augmented with novel components such as Auxiliary Fusing Layers (AuxFL), Fusion Residual Block (FuRB), and Alpha Dropouts (αDO) to improve precision and robustness.