Nevin Manimala

Health Sci Rep. 2026 Apr 2;9(4):e72268. doi: 10.1002/hsr2.72268. eCollection 2026 Apr.

ABSTRACT

BACKGROUND AND AIMS: Computer vision syndrome (CVS) is a recognised health concern characterized by eye and vision-related symptoms resulting from prolonged use of digital devices. Approximately 60 million people worldwide are affected by CVS, with almost one million new cases reported annually.

METHODS: This cross-sectional study was conducted from September 1 to October 15, 2024, among medical students. A paper questionnaire was distributed to students across all academic years at both public and private universities in Syria. The data were analyzed using descriptive statistics, with categorical variables shown as frequencies and percentages. A Chi-square test was used to explore the association between CVS incidence among medical students in Syrian universities and other relevant factors.

RESULTS: The study included 2,636 medical students from Syrian universities, with a majority (74.54%) enrolled in public institutions. The prevalence of CVS among these students was 47%. The most used electronic devices were smartphones (96%), followed by laptops (32%). The primary reasons for computer use included social media (90%), studying (83%), and watching movies (44%). The most frequently employed preventive measure was taking breaks during usage (60%), while adherence to the 20-20-20 rule was minimal (7%).

CONCLUSION: The prevalence of CVS among medical students is 47%, with 90% of the sample using digital devices for social media and 83% for studying. A significant association exists between the occurrence of CVS and factors such as gender, daily computer usage time, the distance from the screen, sitting posture, and whether the individual wears corrective lenses or glasses. This study underscores the need to educate computer and smartphone users about proper ergonomics, posture, and eye exercises.

PMID:41948655 | PMC:PMC13051820 | DOI:10.1002/hsr2.72268

BMC Womens Health. 2026 Apr 7. doi: 10.1186/s12905-026-04425-y. Online ahead of print.

NO ABSTRACT

PMID:41947129 | DOI:10.1186/s12905-026-04425-y

BMC Public Health. 2026 Apr 7. doi: 10.1186/s12889-026-27266-8. Online ahead of print.

NO ABSTRACT

PMID:41947126 | DOI:10.1186/s12889-026-27266-8

BMC Public Health. 2026 Apr 7. doi: 10.1186/s12889-026-27235-1. Online ahead of print.

NO ABSTRACT

PMID:41947107 | DOI:10.1186/s12889-026-27235-1

BMC Infect Dis. 2026 Apr 7. doi: 10.1186/s12879-026-13273-y. Online ahead of print.

ABSTRACT

BACKGROUND: Data describing HIV prevalence, ART use and virological suppression, in older adults in urban or rural South Africa, are limited. We aimed to address this evidence gap.

METHODS: In a population-based cross-sectional study, using age- and sex-stratified random sampling of adults aged ≥ 40 years, a researcher-administered questionnaire collected socio-demographic, and clinical data (03/2022-04/2024). HIV was confirmed using two point-of-care tests (discrepancies resolved by ELISA). The age- and sex-specific study prevalence was applied to the KwaZulu Natal (KZN) province population structure to provide an illustrative projection of HIV prevalence in KZN. Achievement of UNAIDS 95-95-95 targets was calculated in 10-year age bands. People living with HIV (PLHIV) were categorised as virologically suppressed (< 50copies/mL) vs. unsuppressed, and younger (40-49years) vs. older (≥ 50years). Logistic regression determined associations with HIV and virological suppression.

RESULTS: 1,916 adults were recruited; 713 (37.2%) living with HIV, 36.7% men and 37.7% women. HIV prevalence was 68.1% among 40-49-year-olds, 49.4% among 50-59-year-olds, 26.0% among 60-69-year-olds and 9.8% age ≥ 70 years. In older adults (≥ 50 years), the prevalence was 27.9%. The overall projected standardised HIV prevalence in adults ≥ 40 years in KZN was 47.4% (44.8% men; 49.3% women). In our sample, 98% of PLHIV were aware of their status, 97.6% on ART, and 77.7% virologically suppressed. Men ≥ 70 years achieved highest virological suppression (88.2%). Overall, being female vs. male (57.8% vs. 42.2%; OR 1.6 [95%CI 1.1, 2.4]; p = 0.008), having HIV ≥ 3 years vs. < 3 years (62.2% vs. 55.1%; OR 3.0 [95%CI 1.6, 5.7]; p = 0.001), rural vs. urban living (50.9% vs. 49.1%; OR 1.5 [95%CI 1.0, 2.1]; p = 0.044) were associated with virological suppression. Older PLHIV (≥ 50years) vs. younger (40-49years) reported hypertension (51.0% vs. 30.0%), diabetes (10.0% vs. 5.0%), and polypharmacy (≥ 5 drugs) (13.2% vs. 6.3%).

CONCLUSION: In KZN, the overall study prevalence of HIV in adults age ≥ 50 years was 27.9% in both urban and rural populations, the UNAIDS 95-95-95 targets were met for known status and being on treatment, but not virological suppression.

PMID:41947066 | DOI:10.1186/s12879-026-13273-y

BMC Emerg Med. 2026 Apr 7. doi: 10.1186/s12873-026-01574-z. Online ahead of print.

NO ABSTRACT

PMID:41947057 | DOI:10.1186/s12873-026-01574-z

G3 (Bethesda). 2026 Apr 6:jkag092. doi: 10.1093/g3journal/jkag092. Online ahead of print.

ABSTRACT

Mutation is the fundamental source of genetic variation, yet growing evidence shows that mutations are not uniformly distributed across genomes but are shaped by genomic architecture, DNA-repair dynamics, and environmental conditions. Here, we investigate fine-scale determinants of mutation distribution in the non-biting midge Chironomus riparius, an ecologically important freshwater insect widely used in ecotoxicology. We integrated mutation data from five independent studies, including spontaneous mutation-accumulation experiments and multigenerational exposure assays involving cadmium, benzo[a]pyrene, tyre and road wear particles, and varying generational time. In total, we analysed 420 single-nucleotide mutations mapped to the chromosome-scale C. riparius reference genome. Using a Bayesian modelling framework, we tested whether mutation density is (i) uniformly distributed, (ii) non-uniformly distributed, or predicted by (iii) distance to telomeres and centromeres, (iv) proximity to genes, or (v) distance to repetitive elements. Models were compared using a cross-validation method. We also quantified the proportion of mutations in exons and evaluated the synonymous vs. non-synonymous spectrum using BayesFactor in R. The best-supported model incorporated non-linear effects of genomic position and distance to genes, identifying proximity to coding regions as the dominant predictor of mutation rate. Mutation density increased with distance from genes, indicating strong protection of genic regions. A model including repetitive elements showed nearly equivalent support, suggesting that functional and structural features jointly shape mutational landscapes. Only 9.8% of mutations occurred in exons despite exons representing 22.85% of callable sites, demonstrating marked depletion of exonic mutations. Among exonic mutations, 70.7% were non-synonymous-statistically indistinguishable from the neutral expectation (75%). These findings show that mutation processes in C. riparius are strongly structured by genome architecture, with implications for evolutionary genomics, ecotoxicology, and population-genetic inference.

PMID:41947018 | DOI:10.1093/g3journal/jkag092

Nat Neurosci. 2026 Apr 7. doi: 10.1038/s41593-026-02255-7. Online ahead of print.

ABSTRACT

The brain must infer the state of the external world despite the inherent uncertainty of its sensory inputs and internal processes. Under conditions of heightened uncertainty, it increasingly relies on prior knowledge, derived from accumulated experience with the regularities and statistical structures of the environment. This principle has been formalized by Bayesian inference theories, which are supported by substantial evidence from both behavioral and neuroscience studies. However, direct evidence for the existence of prior knowledge in the brain, and for the encoding of environmental statistics by neural circuits, remains limited. Here we show that cerebellar circuits learn the prior probability distribution of temporal variables during eyeblink conditioning in mice and encode these representations in Purkinje cell simple and complex spike signaling. We further demonstrate that Purkinje cells are involved in eliciting predictive motor behaviors, such as the conditioned eyeblink response, that also reflect the statistics of the experimentally imposed prior distribution of the stimulus. Computational modeling of these results indicates the juxtaposition of counteracting long-term plasticity mechanisms by which cerebellar Purkinje cells could acquire prior knowledge that is shaped by the statistics of different probability distributions. Our results suggest that the cerebellar circuitry may be uniquely poised to learn the probability of events in the world and internalize these as prior knowledge. These findings advance understanding of how neural computations could implement Bayesian inference.

PMID:41946969 | DOI:10.1038/s41593-026-02255-7

NPJ Digit Med. 2026 Apr 7;9(1):289. doi: 10.1038/s41746-026-02470-3.

ABSTRACT

Atrial fibrillation (AF) is the most common sustained arrhythmia and a leading cause of ischemic stroke. Existing risk scores, such as CHA₂DS₂-VASc, offer limited predictive accuracy and fail to capture complex clinical patterns. To improve generalizability and clinical utility, we developed and externally validated clinically interpretable machine learning models using only age, comorbidities, and medication use to predict 1-year stroke risk in patients with newly diagnosed AF. Both logistic regression (LR) and Platt-calibrated extreme gradient boosting (XGB) models achieved high discrimination in internal (AUCs = 0.915 and 0.914) and external validation cohorts (AUCs = 0.877-0.886), significantly outperforming CHA₂DS₂-VASc (AUCs = 0.614-0.621; p < 0.001). Calibration curves and decision curve analysis confirmed strong clinical utility. Long-term follow-up demonstrated superior risk stratification and treatment responsiveness in LR-defined high-risk groups. These models provide accurate, individualized stroke risk estimates to guide direct oral anticoagulant (DOAC) initiation in real-world hospital settings.

PMID:41946928 | DOI:10.1038/s41746-026-02470-3

Sci Rep. 2026 Apr 7. doi: 10.1038/s41598-026-47471-0. Online ahead of print.

ABSTRACT

Almost half of under-five children in health facilities are febrile in sub-Saharan Africa. The non-specific clinical symptoms coupled with; limited diagnostics capacities, overlapping endemicity and the surveillance gaps complicates accurate cause identification of an acute febrile illnesses in resource limited settings. This challenge leads to misdiagnosis, overtreatment, and delays in appropriate management, increasing morbidity and mortality. Health systems are often overloaded, with providers attributing fevers to the most common pathogen, while other emerging infections are the cause. This study unpacked the febrile illness by testing for dengue fever in parallel to malaria. Febrile ill children below 5 years seeking health services public health facilities in Busia and Kisumu Counties were screened using an approved malaria and dengue fever rapid test kits at the outpatient department. Those who screened positive were recruited into the study. A total of 1004 children were screened, 380 met the recruitment criteria. 215 (21.4%) tested positive for P. falciparum alone, 90 (8.9%) tested positive for dengue fever alone while 75 (7.5%) had co-infections. Busia had the highest P. falciparum-only infection (23.4%) while Kisumu had the highest dengue-only infections (12.6%). Dengue fever is a re-emerging neglected tropical, climate change driven disease in malaria endemic regions. Other than creating awareness to build capacity for diagnosis, this study unmasked and confirmed dengue as a major contributor to the non malarial febrile illnesses among children. There is need to revise the screening algorithm for febrile patients to improve arboviral surveillance.

PMID:41946915 | DOI:10.1038/s41598-026-47471-0