Tag: nevin manimala

Bioinformatics. 2026 Mar 1:btag090. doi: 10.1093/bioinformatics/btag090. Online ahead of print.

ABSTRACT

MOTIVATION: Understanding the functional roles of lipids is essential for interpreting metabolic phenotypes in health, disease, and dietary interventions. However, lipidomic analyses typically focus on individual lipid species, making it difficult to extract mechanistic and systems-level insights. We therefore asked how quantitative lipidomic data can be translated into biologically structured and function-oriented interpretations.

RESULTS: Here, we present a major update to LipidOne (lipidone.eu), introducing the novel analytical module: Functional Lipid Analysis (FLA). FLA computes 42 indices describing lipid functions related to membrane structure, energy storage, and signaling. Indices are derived from lipid classes and fatty acyl-, alkyl-, and alkenyl-chain composition, statistically compared across experimental groups, and explored using multivariate and visualization tools. Each index is semantically annotated and linked to predicted protein mediators, enabling pathway- and network-based interpretation. Application to published datasets confirmed previous conclusions while uncovering additional biologically coherent functional insights.

AVAILABILITY AND IMPLEMENTATION: New FLA module is freely available through LipidOne.eu web platform. The LipidOne FLA core R script (v1.0.0) is archived on Zenodo (DOI: 10.5281/zenodo.18468230). The LipidOne web platform is available at https://lipidone.eu.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:41764409 | DOI:10.1093/bioinformatics/btag090

J Water Health. 2026 Feb;24(2):128-147. doi: 10.2166/wh.2026.145. Epub 2026 Feb 6.

ABSTRACT

This study assessed the health risks associated with groundwater contamination by metals and metalloids in the Tabalaopa-Aldama aquifer, located in the arid region of northern Mexico. A total of 40 drinking water wells were sampled and analyzed for elements including arsenic, aluminum, uranium, iron, nickel, and zinc. The results revealed that a significant proportion of the wells exceeded national and international permissible limits for these contaminants. To evaluate the potential impact on public health, three complementary indices were applied: the health risk index, the hazard quotient, and the water quality index. The integrated analysis demonstrated high consistency among the indices, particularly highlighting arsenic, iron, and nickel as critical contaminants. Multivariate statistical techniques further identified key patterns and groupings, revealing that contaminant levels are influenced by geological and hydrological factors such as well depth and flow rate. The integration of the results from these indices through multivariate statistical methods – specifically Principal Component Analysis (PCA) and cluster analysis – provided a valuable assessment of the concordance and divergences between the indices. This allowed for more robust identification of high-risk areas and contributed to better-informed decision-making for targeted water quality management and public health protection.

PMID:41764387 | DOI:10.2166/wh.2026.145

Clin Gerontol. 2026 Mar 1:1-20. doi: 10.1080/07317115.2026.2629563. Online ahead of print.

ABSTRACT

OBJECTIVES: To examine the association between work beyond the traditional retirement age and mental health outcomes among older Canadians (65+ years) and to assess whether these associations vary by sex.

METHODS: A subsample of (N = 65,033) older adults was drawn from repeated national Canadian Community Health Surveys between 2013 to 2018. Firth’s logistic regression model was applied to identify factors associated with self-reported mood and anxiety disorders. Prevalence estimates and adjusted odds ratios with 95% confidence intervals are reported.

RESULTS: The prevalence of self-reported mood and anxiety disorders were 6.9% and 5.3% respectively. We found that paid full-time work was positively associated with self-reported mood disorder (OR = 0.61, 95% CI: 0.50-0.73) and self-reported anxiety disorder (OR = 0.65, 95% CI: 0.52-0.81). Older age (75+) was positively associated with self-reported mood disorder (OR = 0.56, 95% CI: 0.51-0.62) and self-reported anxiety disorder (OR = 0.62, 95% CI: 0.55-0.69). High work-related stress was a significant negative associated factor for both mental disorders [(OR = 1.46, 95% CI: 1.16-1.82), and (OR = 1.38, 95% CI: 1.07-1.77, respectively)]. Being female, single, a current smoker, and multimorbidity were statistically significant negative associated factors for both self-reported mood and anxiety disorders. Although females reported higher prevalence of self-reported mood and anxiety disorders, the significant factors associated with these conditions were largely similar across both sexes.

CONCLUSIONS: Our findings emphasize the positive mental health benefits of paid work past age 65+ and its obvious financial benefit.

CLINICAL IMPLICATIONS: This research supports the idea of “active aging” and emphasize the need for further research to explore the motivations behind continued employment and their differential impact on mental health.

PMID:41764384 | DOI:10.1080/07317115.2026.2629563

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-42144-4. Online ahead of print.

ABSTRACT

Afghan refugees face persistent poverty, social marginalization, and restricted access to healthcare in Pakistan, making them one of the world’s largest and longest-displaced groups. Health disparities have been made worse by decades of instability, especially among marginalized groups living in informal urban settlements and refugee camps. With an emphasis on how income, education, and legal status affect health outcomes and healthcare access, this study explores the socioeconomic determinants and health burdens among Afghan refugees residing in Pakistan. Between January and June 2025, 250 Afghan refugee families (n = 1460 people) in the provinces of Balochistan and Khyber Pakhtunkhwa were surveyed. To guarantee proportionate representation from camp-based and urban populations, stratified random sampling was employed. Data were gathered via structured questionnaires using a cross-sectional methodology, and SPSS v.27 was used for analysis. Multiple logistic regression, chi-square tests, and descriptive statistics were used to find predictors of poor health outcomes. Undocumented status (OR = 3.11, p < 0.001) and low income (OR = 2.34, p < 0.001) were found to be significant risk variables. Results show that poor health outcomes are strongly correlated with socioeconomic deprivation. Reducing health disparities among Afghan refugees in Pakistan requires bolstering social protection systems, livelihood initiatives, and inclusive healthcare access.

PMID:41764346 | DOI:10.1038/s41598-026-42144-4

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-41837-0. Online ahead of print.

NO ABSTRACT

PMID:41764340 | DOI:10.1038/s41598-026-41837-0

Int J Obes (Lond). 2026 Feb 28. doi: 10.1038/s41366-026-02038-x. Online ahead of print.

ABSTRACT

BACKGROUND: Obesity is a known cardiovascular risk factor, but the “obesity paradox” has been observed in patients with acute myocardial infarction (AMI), where obesity may be linked to better survival outcomes. The relationship between body mass index (BMI) and recurrent myocardial infarction, particularly with age-specific effects, remains unclear.

METHODS: This retrospective cohort study included 4023 AMI patients from a tertiary medical center (2015-2023). Patients were stratified by age: ≤60 years (n = 1277) and >60 years (n = 2746). Multivariable-adjusted Cox proportional hazards models were used to assess the association between BMI and recurrent myocardial infarction, adjusting for demographics, biomarkers [N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT)], imaging parameters [left ventricular ejection fraction (LVEF)], comorbidities, and treatment regimens. Curve-fitting models were also applied. The median follow-up time was 35 months (Q1-Q3 25-58).

RESULTS: In the ≤60 years group, higher BMI was associated with a significantly lower risk of recurrent myocardial infarction [adjusted hazard ratio (HR) = 0.965, 95% confidence interval (CI) 0.936-0.994, P = 0.018]. In contrast, the >60 years group showed a trend toward higher risk (unadjusted HR = 1.032, 95% CI 1.012-1.053, P = 0.001), which lost statistical significance after adjustment (adjusted HR = 1.015, 95% CI 0.994-1.037, P = 0.151). Curve fitting revealed a negative linear correlation in the ≤60 years group and a positive relationship in the >60 years group.

CONCLUSIONS: This study presents the first evidence of an age-dependent obesity paradox in AMI. In patients aged ≤60 years, higher BMI reduced recurrent myocardial infarction risk, whereas in those aged >60 years, the protective effect disappeared and reversed, indicating potential harm. These findings highlight the need for age-stratified secondary prevention strategies for AMI. Summary of Principal Study Outcomes.

PMID:41764327 | DOI:10.1038/s41366-026-02038-x

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-42346-w. Online ahead of print.

ABSTRACT

Socioeconomic status (SES) has been linked to brain-based markers, but most studies rely on conventional statistical methods that overlook the complexity and inherent multicollinearity of the brain. We trained elastic net models to predict SES from multimodal neuroimaging data: diffusion tensor imaging (DTI), structural MRI (sMRI), and resting-state functional connectivity (RSFC) data. Neural features independently predicted SES, and demographic information only minimally enhanced performance. The income and multimodal models performed best; accordingly, the best-performing primary model predicted income using multimodal data, achieving AUCs of 0.75 (test) and 0.811 (train) without demographic information and 0.779 (test) and 0.836 (train) with demographic information. The performance of the secondary multimodal models for predicting income had a positive relationship with income disparity; expectedly, the best performing model distinguished between children from the top and bottom ~ 10-20% of income brackets, reaching AUCs of 0.81 (test) and 0.969 (train) without demographic information and 0.863 (test) and 0.986 (train) with demographic information. Among the modalities, DTI was the most discriminative, followed by sMRI. Globally distributed along with executive functioning (EF) and language features were the most discriminative. Multimodal neuroimaging can predict SES, especially income, even without demographic data, and the most discriminative features tended to be measurements of white matter integrity and organization; more globally distributed than isolated to specific regions; and linked to cognitive control and language.

PMID:41764315 | DOI:10.1038/s41598-026-42346-w

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-40388-8. Online ahead of print.

NO ABSTRACT

PMID:41764310 | DOI:10.1038/s41598-026-40388-8

NPJ Digit Med. 2026 Feb 28. doi: 10.1038/s41746-026-02486-9. Online ahead of print.

ABSTRACT

Objective, scalable biomarkers are needed for continuous monitoring of major depressive disorder. Smartphone-collected speech is promising, yet clinically useful signals remain elusive. We analyzed 3151 weekly voice diaries from 284 German-speaking adults (128 MDD, 156 controls) to predict Beck Depression Inventory (BDI) scores. Sentence-embedding models outperformed lexical and acoustic baselines: Qwen3-8B achieved MAE 4.65 and R² 0.34, and stacked generalization of multilingual-E5 with Qwen3-8B further improved performance (MAE 4.37, R² 0.41). Audio embeddings added little incremental value. In an MDD-only analysis, multilingual-E5 was the top single modality (MAE 6.74, R² 0.20). To aid interpretation, BERTopic uncovered six coherent themes; BDI scores were highest for “Distress & care”, supporting clinical face validity. Together, LLM embeddings paired with lightweight topic analysis capture the dominant signal of depression severity in everyday speech and offer a scalable route to ecologically valid digital phenotyping.

PMID:41764298 | DOI:10.1038/s41746-026-02486-9

Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-40367-z. Online ahead of print.

ABSTRACT

Heterozygous familial hypercholesterolemia (FH), a monogenic cause for premature coronary artery disease (CAD) is often underdiagnosed. In individuals who meet the FH diagnostic criteria and lack pathogenic variants, polygenic factors are recognized as potential contributors. This study aimed to characterize the spectrum of genetic variants and determine the low-density lipoprotein polygenic risk score (LDL-PRS) among clinically diagnosed FH participants from South India. We recruited 116 unrelated participants with a pretreatment LDL- C concentration ≥ 190 mg/dl and a DLCN (Dutch Lipid Clinic Network) score ≥ 3. Targeted next-generation sequencing (NGS) of 23 lipid related genes and 12-SNP (Single nucleotide polymorphism) genotyping were performed. NGS identified 39 variants including 13 pathogenic and 26 variants of unknown significance (VUS) some of which were in non-classical genes: ABCG5, ABCG8, APOE, PPP1R17, SREBF2. Pathogenic variants were detected in 66.7% of those with definite FH,19.7% in probable FH and 2.7% in possible FH. Overall,66% were variant negative. Among variant negative (FH/V-) participants, 64% demonstrated high LDL-PRS, whereas 70% of variant positive participants also exhibited elevated scores; suggesting a contributory role of polygenic factors across both groups. Additionally, the observation that variant positive individuals with high LDL-PRS have an increased risk of coronary artery disease (CAD) adds important nuance to risk stratification within genetically confirmed FH patients. Confirmation of diagnosis by genetic testing is essential for the diagnosis of FH. Although LDL-PRS may offer little benefit in variant negative cases and improve CAD risk prediction in variant positive individuals, large scale studies are essential to validate its clinical utility and assess whether inclusion of additional LDL- raising SNPs could enhance the detection of polygenic FH in the Indian population.

PMID:41764281 | DOI:10.1038/s41598-026-40367-z