Recent Publications

J Glob Health. 2025 Feb 28;15:04050. doi: 10.7189/jogh.15.04050.

ABSTRACT

BACKGROUND: The COVID-19 pandemic significantly impacted global mortality, underscoring the need for reliable data to guide public health policy. In low- and middle-income countries, graveyard-based death records can offer valuable insights into COVID-19-related mortality, yet they remain limited. Additionally, data on mortality beyond the pandemic remains scarce as we approach the 2030 Sustainable Development Goals. We addressed this gap by using graveyard-based data to assess excess mortality during the pandemic (2020-23) and predict mortality trends through 2030.

METHODS: We analysed 70 585 deaths from six graveyards in Dhaka, Bangladesh, from January 2001 to December 2023. The data was divided into pre-COVID-19 (2001-19), peak-COVID-19 (2020-21), and end-of-COVID-19 (2022-23) phases. We assessed the excess mortality using the P-score and Bayesian approach. We estimated excess mortality with a log-linear Bayesian model and predicted death trends for 2024-30, reporting incidence rate ratio (IRR) with 95% credible intervals (CrI).

RESULTS: Overall, excess mortality was 69% greater in 2020 and 31% in 2023 compared to the 2018-19 average. The IRR for deaths during peak-COVID-19 was 1.66 times higher than pre-COVID-19 (95% CrI = 1.35-2.04). Neonates had significantly higher IRRs during both the peak (IRR = 1.45; 95% CrI = 1.02-2.05) and end-of-COVID-19 (IRR = 1.67; 95% CrI = 1.02-2.71). Individuals aged >40 years showed a significantly higher IRR during peak-COVID-19 (IRR = 1.79; 95% CrI = 1.46-2.18). Predictions using data between 2001-23 indicate rising mortality, with the number of adult deaths increasing from 3318 in 2023 to 5089 (95% CrI = 3871-6267) by 2030.

CONCLUSIONS: We revealed a significant rise in mortality during the pandemic, with elevated death rates persisting at the end of the pandemic. Predictions indicate continued mortality increases through 2030, underscoring the pandemic's long-term health impacts. While further research is needed, these findings highlight the value of graveyard-based death registration data for tracking mortality trends and informing public health strategies.

PMID:40019156 | DOI:10.7189/jogh.15.04050

J Glob Health. 2025 Feb 28;15:04086. doi: 10.7189/jogh.15.04086.

ABSTRACT

BACKGROUND: Digitalisation of death documentation in Bangladesh's graveyards is crucial for accurate mortality data and public health planning. Additionally, studying the usability, technology acceptance, and implementation aspects of the digital death record-keeping system, an innovative intervention that has not been previously explored, ensures the effectiveness, user adoption, and long-term sustainability. We designed, implemented, and evaluated a digital mortality surveillance system in graveyards in Dhaka city of Bangladesh.

METHODS: The study was conducted in six graveyards of the Dhaka North City Corporation (DNCC). First, we conducted formative research to understand the documentation process of the graveyard record-keeping and inform architecture for a digital record-keeping system. We then developed a digital record-keeping system for graveyard. A cross-sectional quantitative and qualitative study was conducted among web and app users, and graveyard managers and death records keepers.

RESULTS: A total of 200 app and web users and 14 record-keepers and managers participated. App and web users had high levels of system usability (88%) and found them easy to use (100%) and well-integrated (100%), with disagreement on complexity (100%), inconsistency (100%), and technical support needs (100%). These users had high technology acceptance and agreed the tools help accomplish tasks quickly (100%), improve performance (100%), and were easy to learn (100%). Digital death record-keepers reported using the system frequently (71%) but found it somewhat complex (14%) and not consistently easy to use (28%), with some reported that the systems were well integration (50%) and easy to learn (43%). While technology acceptance varied, death record keepers generally agreed that the system helps with quick task completion (50%) and performance improvement (57%), increase productivity (43%), enhance effectiveness (57%), and easy to use (50%). The digital death record-keeping system received mixed reactions, with younger, tech-savvy operators being optimistic, while older supervisors were sceptical and uncomfortable with technology. Additionally, the system was found to be feasible to an extent, particularly by data entry operators and graveyard managers.

CONCLUSIONS: The digital death record-keeping system was generally well-received by app and web users for its usability and integration, though graveyard supervisor found it somewhat complex, with mixed reactions based on tech-savviness; overall, the system was deemed feasible and sustainable.

PMID:40017452 | DOI:10.7189/jogh.15.04086

Nat Commun. 2025 Feb 27;16(1):2020. doi: 10.1038/s41467-025-57034-y.

ABSTRACT

G protein-coupled receptors (GPCRs) constitute a functionally diverse protein family and are targets for a broad spectrum of pharmaceuticals. Technological progress in X-ray crystallography and cryogenic electron microscopy has enabled extensive, high-resolution structural characterisation of GPCRs in different conformational states. However, as highly dynamic events underlie GPCR signalling, a complete understanding of GPCR functionality requires insights into their conformational dynamics. Here, we present a large dataset of molecular dynamics simulations covering 60% of currently available GPCR structures. Our analysis reveals extensive local "breathing" motions of the receptor on a nano- to microsecond timescale and provides access to numerous previously unexplored receptor conformational states. Furthermore, we reveal that receptor flexibility impacts the shape of allosteric drug binding sites, which frequently adopt partially or completely closed states in the absence of a molecular modulator. We demonstrate that exploring membrane lipid dynamics and their interaction with GPCRs is an efficient approach to expose such hidden allosteric sites and even lateral ligand entrance gateways. The obtained insights and generated dataset on conformations, allosteric sites and lateral entrance gates in GPCRs allows us to better understand the functionality of these receptors and opens new therapeutic avenues for drug-targeting strategies.

PMID:40016203 | DOI:10.1038/s41467-025-57034-y

Chemistry. 2025 Feb 26:e202404152. doi: 10.1002/chem.202404152. Online ahead of print.

ABSTRACT

Methods to prepare vicinal amino alcohols are important because of their presence in biologically active compounds. Despite the development of various methods for vicinal amino alcohol synthesis, C(sp3)-rich oxygen-containing β-amine compounds continue to pose great challenge. While ring-opening reaction of epoxides with amine nucleophile is the prime method for vicinal amino alcohol preparation, epoxides are highly reactive and sometimes difficult to make, resulting in drawbacks regarding selectivity of this approach. Here, we report a catalytic enantio-convergent amination of α-tertiary 1,2-diols for the efficient access to vicinal amino α-tertiary alcohols. The racemic α-tertiary 1,2-diol substrates of different alkyl/aryl or alkyl/alkyl backbone, can be converted to chiral vicinal amino a-tertiary alcohols through diphenyl phosphate-mediated RuCl3 catalysed asymmetric borrowing hydrogen (ABH) pathway. This simple ABH reaction can be scaled up to the synthesis of chiral ligands, synthetic intermediates, and other medicinally-relevant compounds. Overall, this catalytic redox-neutral procedure broadens the scope of Ru-catalysed amination of alcohols and discloses an underexplored step- and atom-economical synthetic strategy for the synthesis of vicinal amino α-tertiary alcohols and provides a practicable alternative to the present benchmark procedures.

PMID:40011211 | DOI:10.1002/chem.202404152

Heliyon. 2025 Feb 5;11(3):e42478. doi: 10.1016/j.heliyon.2025.e42478. eCollection 2025 Feb 15.

ABSTRACT

Cystatin A (CSTA) functions as a cysteine protease inhibitor by forming tight complexes with the cathepsins. Pathogenic mutations in the CSTA gene can disrupt this interaction, potentially leading to physiological ailments. In this study, eight bioinformatics tools (SIFT, PolyPhen-2, PROVEAN, P-Mut, MutPred2, SNAP2, SNPs & GO, and PHD-SNP) were implemented to analyze non-synonymous SNPs from the dbSNP database. Five mutations (Y43C, Y43N, V48F, Y53H, and E94K) located in the conserved region were found to be highly deleterious and less stabilizing. The protein-protein interaction network found that Cathepsin B (CTSB) interacts highly with CSTA. Mutated CSTAs were created by homology modeling, and their altered binding with CTSB was examined through molecular docking and dynamics simulations. Among these, the Y53H (rs1448459675) and E94K (rs200394711) mutants were recognized as weaker inhibitors because they had 2.5 % and an 8 % lower binding affinity, respectively. Moreover, the E94K-CTSB complex, with a root mean square deviation (RMSD) above 5 Å, was found to be highly unstable during molecular dynamics. The root mean square fluctuation (RMSF) of the E94K mutant showed insufficient flexibility, indicating a reduced capacity to suppress CTSB. These findings suggest that the E94K mutation could affect the protein structure and cathepsin B interaction, potentially leading to pathological consequences as evidenced by colorectal adenocarcinoma patients in the COSMIC (Catalogue of Somatic Mutations in Cancer) database.

PMID:40007784 | PMC:PMC11850136 | DOI:10.1016/j.heliyon.2025.e42478

BMC Public Health. 2025 Feb 25;25(1):775. doi: 10.1186/s12889-025-21990-3.

ABSTRACT

BACKGROUND: This study explores the impact of HIV/AIDS on urban slum dwellers in Dhaka, Bangladesh, addressing unique socio-economic challenges and limited health resources. Despite low overall prevalence, gender inequalities, economic disparities, and awareness gaps persist. The aim is to assess HIV/AIDS-related knowledge, attitudes, and practices among this population, informing targeted interventions.

METHODS: A cross-sectional survey was conducted using face-to-face interviews in Dhaka's slum areas between October and November 2023. The sample size was calculated as 453 participants through non-probability (convenient sampling) sampling. A structured questionnaire in Bengali assessed socio-demographic factors, HIV/AIDS-related knowledge, attitudes, and prevention practices. Data were analysed using descriptive statistics, bivariate, and multivariable linear regression by SPSS (version 26) and STATA (version 14).

RESULTS: Urban slum dwellers exhibited limited average HIV/AIDS knowledge of 33.00%, favouring males. Positive association was found between daily physical exercise and knowledge, while insufficient sleep and lack of social media access were negative predictors. Average attitudes were generally positive (81.06%), influenced by factors such as gender, employment status, family history of STDs, and daily physical exercise. The average score of prevention practices was 60.6%, with positive predictors including male gender, cooperative family members, STD history, family history of STDs, acquaintance with HIV patients, and social media usage over 2 h. Younger age was negatively associated with prevention practices.

CONCLUSION: This study pinpoints factors influencing HIV/AIDS knowledge and behaviours in Bangladeshi urban slum dwellers. Tailored interventions focusing on gender, and social media can enhance preventive measures. Acknowledging limitations, the study urges cautious interpretation due to potential biases in convenience sampling and self-reporting.

PMID:40001071 | DOI:10.1186/s12889-025-21990-3

Data Brief. 2025 Jan 27;59:111331. doi: 10.1016/j.dib.2025.111331. eCollection 2025 Apr.

ABSTRACT

In contemporary industrial, robotics, and technical education settings, the efficient detection and sorting of electronic components play a pivotal role in advancing automation and increasing efficiency in these sectors. To address this need, we present "ElectroCom61," a comprehensive multi-class object detection dataset encompassing 61 commonly used electronic components. Our dataset, sourced from the electronic components collection at United International University (UIU) in Dhaka, Bangladesh, comprises 2121 meticulously annotated images. We ensured that these images reflect real-world conditions, incorporating varied lighting, backgrounds, distances, and camera angles to bolster the potential machine learning model's robustness. We also divided the dataset into training, validation, and test sets to facilitate deep learning model development. Additionally, we conducted minimal pre-processing to optimise model training and performance. "ElectroCom61" stands as a valuable asset for developing cutting-edge electronic component detection systems, with far-reaching applications in both education and industry. Its potential applications span from interactive educational tools to e-waste management systems and streamlined inventory management processes in electronic manufacturing and automation. The code for technical validation of this dataset is available on GitHub: https://github.com/faiyazabdullah/ElectroCom61.

PMID:39990128 | PMC:PMC11847280 | DOI:10.1016/j.dib.2025.111331

Brain Spine. 2025 Jan 25;5:104197. doi: 10.1016/j.bas.2025.104197. eCollection 2025.

ABSTRACT

Over the past two decades, genomics has transformed our understanding of various clinical conditions, with Chromosomal Microarray Analysis (CMA) standing out as a key technique. Offering unparalleled sensitivity, CMA detects submicroscopic chromosomal imbalances, enabling the examination of DNA for copy number variations, deletions, duplications, and other structural differences. In neurology, CMA has revolutionised diagnoses, personalised treatment plans, and patient outcomes. By identifying genetic anomalies linked to neurological conditions, CMA allows clinicians to tailor treatments based on individual genetic profiles, enhancing precision medicine. CMA's clinical utility spans numerous neurological conditions, providing crucial insights into neurodevelopmental disorders, CNS tumours, neurodegenerative diseases, cerebrovascular diseases, and epilepsy. In neurodevelopmental disorders, CMA aids in diagnosing autism and intellectual disabilities, facilitating early interventions that improve long-term outcomes. In epilepsy, CMA helps identify genetic causes of drug-resistant seizures, enabling more targeted therapies and reducing adverse reactions. CMA also aids in stratifying risk for cerebrovascular diseases, enabling preventive interventions that improve patient prognosis. Despite its potential, challenges remain, such as interpreting variants of uncertain significance (VOUS), the lack of standardised testing guidelines, and issues of cost and accessibility. Addressing these challenges will optimise CMA's impact, advancing personalised medicine and reshaping neurology. This review discusses CMA's pivotal role in bridging the gap between genomics and clinical practice, underscoring its potential to transform neurogenetics and ultimately improve patient care.

PMID:39990116 | PMC:PMC11847126 | DOI:10.1016/j.bas.2025.104197

J Genet Genomics. 2025 Feb 20:S1673-8527(25)00040-2. doi: 10.1016/j.jgg.2025.02.003. Online ahead of print.

ABSTRACT

Evidence has shown that differential transcriptomic profiles among human populations from diverse ancestries, supporting the role of genetic architecture in regulating gene expression alongside environmental stimuli. Genetic variants that regulate gene expression, known as expression quantitative trait loci (eQTL), are primarily shaped by human migration history and evolutionary forces, likewise, regulation of gene expression in principle could have been influenced by these events. Therefore, a comprehensive understanding of how human evolution impacts eQTL offers important insights into how phenotypic diversity is shaped. Recent studies, however, suggest that eQTL is enriched in genes that are selectively constrained. Whether eQTL is minimally affected by selective pressures remains an open question and requires comprehensive investigations. In addition, such studies are primarily dominated by the major populations of European ancestry, leaving many marginalized populations underrepresented. These observations indicate there exists a fundamental knowledge gap in the role of genomics variation on phenotypic diversity, which potentially hinders precision medicine. This article aims to revisit the abundance of eQTL across diverse populations and provide an overview of their impact from the population and evolutionary genetics perspective, subsequently discuss their influence on phenomics, as well as challenges and opportunities in the applications to precision medicine.

PMID:39986349 | DOI:10.1016/j.jgg.2025.02.003

J Biomed Phys Eng. 2025 Feb 1;15(1):77-92. doi: 10.31661/jbpe.v0i0.2307-1636. eCollection 2025 Feb.

ABSTRACT

BACKGROUND: Cardiovascular Diseases (CVD) requires precise and efficient diagnostic tools. The manual analysis of Electrocardiograms (ECGs) is labor-intensive, necessitating the development of automated methods to enhance diagnostic accuracy and efficiency.

OBJECTIVE: This research aimed to develop an automated ECG classification using Continuous Wavelet Transform (CWT) and Deep Convolutional Neural Network (DCNN), and transform 1D ECG signals into 2D spectrograms using CWT and train a DCNN to accurately detect abnormalities associated with CVD. The DCNN is trained on datasets from PhysioNet and the MIT-BIH and the MIT-BIH arrhythmia dataset. The integrated CWT and DCNN enable simultaneous classification of multiple ECG abnormalities alongside normal signals.

MATERIAL AND METHODS: This analytical observational research employed CWT to generate spectrograms from 1D ECG signals, as input to a DCNN trained on diverse datasets. The model is evaluated using performance metrics, such as precision, specificity, recall, overall accuracy, and F1-score.

RESULTS: The proposed algorithm demonstrates remarkable performance metrics with a precision of 100% for normal signals, an average specificity of 100%, an average recall of 97.65%, an average overall accuracy of 98.67%, and an average F1-score of 98.81%. This model achieves an approximate average overall accuracy of 98.67%, highlighting its effectiveness in detecting CVD.

CONCLUSION: The integration of CWT and DCNN in ECG classification improves accuracy and classification capabilities, addressing the challenges with manual analysis. This algorithm can reduce misdiagnoses in primary care and enhance efficiency in larger medical institutions. By contributing to automated diagnostic tools for cardiovascular disorders, it can significantly improve healthcare practices in the field of CVD detection.

PMID:39975522 | PMC:PMC11833154 | DOI:10.31661/jbpe.v0i0.2307-1636

Am J Kidney Dis. 2025 Feb 6:S0272-6386(25)00047-2. doi: 10.1053/j.ajkd.2024.11.015. Online ahead of print.

NO ABSTRACT

PMID:39969461 | DOI:10.1053/j.ajkd.2024.11.015

Nat Commun. 2025 Feb 16;16(1):1681. doi: 10.1038/s41467-025-56916-5.

ABSTRACT

Progeria syndromes are very rare, incurable premature aging conditions recapitulating most aging features. Here, we report a whole genome, multiparametric CRISPR screen, identifying 43 genes that can rescue multiple cellular phenotypes associated with progeria. We implement the screen in fibroblasts from Néstor-Guillermo Progeria Syndrome male patients, carrying a homozygous A12T mutation in BAF. The hits are enriched for genes involved in protein synthesis, protein and RNA transport and osteoclast formation and are validated in a whole-organism Caenorhabditis elegans model. We further confirm that BAF A12T can disrupt protein synthesis rate and fidelity, which could contribute to premature aging in patients. This work highlights the power of multiparametric genome-wide suppressor screens to identify genes enhancing cellular resilience in premature aging and provide insights into the biology underlying progeria-associated cellular dysfunction.

PMID:39956852 | DOI:10.1038/s41467-025-56916-5

J Phys Condens Matter. 2025 Feb 11;37(13). doi: 10.1088/1361-648X/adad2b.

ABSTRACT

We present a density functional theory-based mechanistic understanding of CO2hydrogenation to value-added products on a nitrogen-vacancy (VN) defect in hexagonal boron nitride (dh-BN). Activation occurs through back-donation to theπ* orbitals of CO2from the frontier orbitals (defect state) of theh-BN sheet that are localized near a nitrogen-vacancy. Subsequent hydrogenation to methanol (CH3OH) and formic acid (HCOOH) proceed through vacancy-facilitated co-adsorption of hydrogen and CO2. More importantly, our reaction pathway analyses complimented by microkinetic modeling indicate thatdh-BN is potentially a low-temperature, selective catalyst for CO2reduction to methanol. Our findings are in agreement with experiments conducted in a mechanical reactor that show high selectivity towards methanol formation for CO2hydrogenation on defect inducedh-BN.

PMID:39932171 | DOI:10.1088/1361-648X/adad2b

Expert Opin Drug Saf. 2025 Feb 7. doi: 10.1080/14740338.2025.2462652. Online ahead of print.

ABSTRACT

Coronary Artery Disease (CAD) and Peripheral Artery Disease (PAD) are leading causes of death and illness worldwide. These conditions greatly impact the quality of life and increase the risk of serious cardiovascular and limb events (MACE and MALE). Even with advances in medical treatments, patients with chronic CAD and PAD still face a high risk of thrombotic events. Traditional anticoagulant therapies, such as warfarin combined with aspirin, have not effectively reduced cardiovascular events and often lead to major bleeding. Therefore, rivaroxaban, an oral factor Xa inhibitor, has emerged as a promising therapeutic agent. The COMPASS trial found that combining low-dose rivaroxaban with aspirin significantly reduces MACE and MALE in chronic CAD and PAD patients, though it also increases the risk of major bleeding. Additional studies, including COMPASS, LTOLE and VOYAGER PAD, have confirmed these results, demonstrating rivaroxaban's effectiveness and safety across different patient groups. It is important to note that the populations studied in these trials differ significantly, particularly regarding the heart failure population. Some patients, such as those with recent worsening chronic heart failure, do not benefit from rivaroxaban. Specifically, the COMMANDER HF trial found that in patients with chronic heart failure, reduced ejection fraction, and coronary artery disease who were not in atrial fibrillation, low-dose rivaroxaban did not significantly reduce the risk of death, myocardial infarction, or stroke compared to placebo. These distinct population characteristics highlight the importance of considering specific patient factors when interpreting the efficacy of rivaroxaban. Cost-effectiveness analyses from various healthcare systems show that rivaroxaban, especially when used with aspirin, is a cost-effective treatment for CAD and PAD patients. This review explores rivaroxaban's role in reducing MACE and MALE in CAD and PAD patients, discussing its pharmacology, uses, effectiveness, safety, and cost-efficiency. It also reviews recent research and recommendations for specific patient characteristics, offering a comprehensive overview and future perspectives on its role in managing cardiovascular diseasess.

PMID:39919210 | DOI:10.1080/14740338.2025.2462652

PLoS One. 2025 Feb 7;20(2):e0319100. doi: 10.1371/journal.pone.0319100. eCollection 2025.

ABSTRACT

Chronic kidney disease (CKD) has a significant impact on the health-related quality of life (HRQoL) of affected individuals due to its progressive and disabling nature. The aim of this study was to evaluate the HRQoL and its predictors among CKD patients. A cross-sectional study was carried out at kidney foundation Hospital and research Institute at Dhaka, Bangladesh. Kidney Disease Quality of Life (KDQoL™ -36) questionnaire were used to measure the HRQoL of CKD patients. The study also used kidney-targeted KDQoL-36 Summary Score (KSS). Socio-demographic and medical records were also collected. Descriptive statistics, and multiple linear regression were performed. Out of 430 patients, 77.9% were in moderate to advanced stage of CKD. Patients aged, occupation, income, co-morbidities such as diabetes or hypertension, medication used, and serum hemoglobin were found significantly (p <0.05) associated at different stages of CKD. The mean domain scores of physical component summary (PCS), mental component summary (MCS), burden of kidney disease (BKD), effect of kidney disease (EKD), symptoms and problems of kidney disease (SPKD) subscales were 37.19, 45.94, 31.49, 63.95, and 73.35, respectively. The KSS was 63.24. The stage of CKD has been documented as an important predictor of HRQoL of all subscales of KDQoL-36 as well as KSS. The older age group also showed a clear link with a lower HRQoL in all subscales of KDQoL-36, except SPKD. In multiple linear regression analysis, stage of CKD, patients age, employment status and use of medication were found significant predictors of KSS. Further, higher levels of education, being married, absence of diabetes and heart disease were all independent predictors of a higher MCS. Whereas retirement, low duration of CKD and the use of three or more drugs strongly linked to worse scores of PCS. By addressing the determinants of poor HRQoL, healthcare providers can tailor treatment plans to better meet the needs of these individuals and ultimately enhance their overall well-being.

PMID:39919056 | DOI:10.1371/journal.pone.0319100

J Craniomaxillofac Surg. 2025 Feb 5:S1010-5182(25)00038-1. doi: 10.1016/j.jcms.2025.01.027. Online ahead of print.

ABSTRACT

Mandibular fractures are common maxillofacial injuries among children and adolescents, but treatment remains controversial. The aim of this study was to analyse the methods and outcomes of open reduction and internal fixation (ORIF) for non-condylar mandibular fractures in paediatric patients among 14 maxillofacial centres. Patients ≤16 years of age undergoing ORIF for non-condylar mandibular fractures between 2011 and 2022 were included. Age, gender, dentition stage, site and type of fracture, surgical approach, material, thickness, and number of plates, and outcome were recorded. 179 patients (mean age, 11.1 years) reported 120 single and 59 double fractures, 79% involving at least one displaced or comminuted site. Single fractures were preferentially treated with rigid osteosynthesis in all dentition groups (64%), while double fractures with non-rigid osteosynthesis in mixed and permanent dentition patients (59% and 43%) and mixed osteosynthesis in deciduous dentition patients (50%). Mean follow-up was 21 months. Surgical would infection was the most common complication (8.9%), followed by minor malocclusion (1.7%) and osteitis (1.7%). In conclusion, the centres opted for fixation patterns like those recommended for adults, favoring non-rigid or mixed osteosynthesis for double fractures. The low complication rate shows ORIF is effective and safe for non-condylar mandibular fractures in paediatric patients.

PMID:39915154 | DOI:10.1016/j.jcms.2025.01.027

Curr Opin Biotechnol. 2025 Feb 5;92:103267. doi: 10.1016/j.copbio.2025.103267. Online ahead of print.

ABSTRACT

Intermolecular relationships at the cell surface dictate the behavior and regulatory network of cells. Such interactions often require precise spatial control for optimal response. By binding simultaneously to two different target sites, bispecific binders can bridge molecules of interest. Despite decades of bispecific development, only recently have bispecifics been engineered with programmable, tuneable geometries to replicate natural interaction geometries or achieve new responses from unnatural arrangements. This review highlights emerging methods of protein engineering and modular bioconjugation to control pairing and orientation of binders in bispecific scaffolds. We also describe novel biophysical and phenotypic assays, which reveal how bispecific geometries change cell fate. These approaches are informing design of next-generation precision therapeutics, as well as uncovering fundamental features of signal integration.

PMID:39914134 | DOI:10.1016/j.copbio.2025.103267

Health Promot J Austr. 2025 Apr;36(2):e951. doi: 10.1002/hpja.951.

ABSTRACT

ISSUE ADDRESSED: Adolescent e-cigarette use is increasing and is associated with subsequent smoking. This study examines potential protective factors associated with not vaping among First Nations adolescents in Australia to inform community programs.

METHODS: The 'Next Generation: Youth Wellbeing Study' is a cohort study of First Nations adolescents aged 10-24 years from urban, rural and remote communities in Central Australia, Western Australia and New South Wales. Analysis of self-reported vaping from 16 to 24-year-olds, collected 2018-2020, using multi-level mixed-effects Poisson regression to estimate age-site-adjusted prevalence ratios (PRs) for never-vaping in relation to various factors.

RESULTS: Among 419 participants, 65% were female, 75% had never vaped, 49% had never smoked and 82% lived in smoke-free homes. Never vaping was more common among those who had: never-smoked (PR = 1.78, 95%CI: 1.56-2.04); never used cannabis (1.89, 1.60-2.24); non-smoking friends (1.38, 1.26-1.51); good mental health (1.15, 1.01-1.30), never diagnosed with depression (1.21, 1.01-1.46) or anxiety (1.31, 1.08-1.57); and no experiences of racism (1.21, 1.08-1.36), no negative criminal justice system experiences (1.25, 1.11-1.41), or vicarious racism through negative media (1.24, 1.10-1.39).

CONCLUSIONS: Most First Nations adolescents have never vaped, with potential protective factors being better mental health, no other substance use and fewer experiences of racism and justice system interactions. Comprehensive community adolescent prevention programs are needed to prevent vaping and protect future health, including preventing nicotine addiction and future smoking. SO WHAT?: Policies and programs must address e-cigarettes directly as well as structural factors, promoting broader adolescent wellbeing, centring culture and family in a strengths-based approach.

PMID:39912122 | DOI:10.1002/hpja.951

Eur J Med Res. 2025 Jan 31;30(1):61. doi: 10.1186/s40001-025-02339-3.

ABSTRACT

Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, characterised by rapid progression and a poor prognosis. Survival analysis is an essential aspect of glioma management and research, as most studies use time-to-event outcomes to assess overall survival (OS) and progression-free survival (PFS) as key measures to evaluate patients. However, predicting survival using traditional methods such as the Kaplan-Meier estimator and the Cox Proportional Hazards (CPH) model has faced many challenges and inaccuracies. Recently, advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), have enabled significant improvements in survival prediction for glioma patients by integrating multimodal data such as imaging, clinical parameters and molecular biomarkers. This study highlights the comparative effectiveness of imaging-based, non-imaging and combined AI models. Imaging models excel at identifying tumour-specific features through radiomics, achieving high predictive accuracy. Non-imaging approaches also excel in utilising clinical and genetic data to provide complementary insights, whilst combined methods integrate multiple data modalities and have the greatest potential for accurate survival prediction. Limitations include data heterogeneity, interpretability challenges and computational demands, particularly in resource-limited settings. Solutions such as federated learning, lightweight AI models and explainable AI frameworks are proposed to overcome these barriers. Ultimately, the integration of advanced AI techniques promises to transform glioma management by enabling personalised treatment strategies and improved prognostic accuracy.

PMID:39891313 | DOI:10.1186/s40001-025-02339-3

Crit Care Nurse. 2025 Feb 1;45(1):52-60. doi: 10.4037/ccn2025452.

ABSTRACT

BACKGROUND: For patients receiving extracorporeal membrane oxygenation, early mobility decreases mechanical ventilation time, delirium incidence, and length of intensive care unit stay and improves physical functioning. Individual centers use institutional guidelines to develop ambulation protocols. Local Problem A quality improvement initiative was used to evaluate an ambulation protocol for adult intensive care unit patients receiving extracorporeal membrane oxygenation.

METHODS: Adult patients receiving extracorporeal membrane oxygenation who walked according to the protocol were compared with a historical control group of patients who walked without the protocol. Data analysis included descriptive statistics and independent t tests. Outcomes included adverse safety events, number of patients and ambulation sessions, standing and ambulation time, and distance.

RESULTS: From January to March 2021, 13 of 46 patients receiving extracorporeal membrane oxygenation (28%) walked according to the protocol. In the control group, 14 of 147 patients (10%) walked in 2019; 21 of 144 patients (15%) walked in 2020. Some characteristics of the control group (hospitalized before the COVID-19 pandemic) differed from those of the protocol group (hospitalized during the pandemic). Mean number of ambulation sessions was not significantly different between groups (protocol group, 10; control group, 9). Differences in mean standing time (protocol group, 121.23 minutes; control group, 210.80 minutes), ambulation time (protocol group, 11.77 minutes; control group, 198.70 minutes), and ambulation distance were not significant.

CONCLUSIONS: Standing time, ambulation time, and distance were not significantly different between the groups. The extracorporeal membrane oxygenation ambulation protocol demonstrated clinical significance by increasing the number of patients walking.

PMID:39889799 | DOI:10.4037/ccn2025452