Category: Nevin Manimala

J Hazard Mater. 2026 May 27;513:142544. doi: 10.1016/j.jhazmat.2026.142544. Online ahead of print.

ABSTRACT

Microbial mercury (Hg) methylation and methylmercury (MeHg) demethylation critically govern MeHg production in paddy soils and its accumulation in rice. However, how the decline in microbial diversity under climate change affects these processes remains unclear. Here, we combined stable isotope tracing with a dilution-to-extinction approach to manipulate microbial diversity across paddy soils with Hg contamination gradient (HX: 165 ng/g, GX: 20,707 ng/g and SK: 659,303 ng/g), investigating its effects on Hg methylation and demethylation. Results showed that diversity loss suppressed methylation (to 0.31-0.82 times the original soil) while enhanced demethylation (to 1.33-7.00 times the original soil) in HX and GX soils, reducing net MeHg production. Conversely, in SK soil, it promoted methylation (to 0.31-0.71 times the original soil) and inhibited demethylation (0.14-0.48 times the original soil), increasing MeHg accumulation. Marginal density curves and linear regression analyses indicate that the regulatory effect of microbial diversity on MeHg production depends strongly on Hg levels, with a significant shift in MeHg concentration across a critical threshold of 30,000 ng/g. Nationwide expanded data further confirmed that diversity loss deceases MeHg production below this threshold but elevates it above. This divergence is attributed to Hg-induced shifts in microbial community structure induced. Our findings highlight the crucial role of microbial diversity in regulating net MeHg production in paddy soils, offering important insights for predicting Hg risks under climate change and ensuring food security.

PMID:42218839 | DOI:10.1016/j.jhazmat.2026.142544

J ECT. 2026 May 28. doi: 10.1097/YCT.0000000000001282. Online ahead of print.

ABSTRACT

OBJECTIVE: Evidence about nonvoluntary electroconvulsive therapy (ECT) is limited. Observational studies have suggested that nonvoluntary ECT is equally effective as voluntary ECT in treating psychotic and mood disorders. However, prior studies with short follow-up periods of ∼6 months have been inconclusive regarding long-term clinical outcomes following nonvoluntary ECT, particularly in patients with schizophrenia-spectrum disorders.

METHODS: We conducted a retrospective chart review and included patients who received ECT treatment between 2016 and 2023 at our hospital. The patients were assigned to the nonvoluntary and voluntary groups. We compared the short-term and long-term outcomes between the 2 groups over a 1-year period.

RESULTS: In total, 227 patients were included in this study: 58 in the nonvoluntary group and 169 in the voluntary group. No significant intergroup differences were observed in short-term outcomes, such as the clinical global impressions-improvement scale score, number of discharged patients, and duration of admission. Furthermore, the Cox proportional hazard model found that the nonvoluntary group was not significantly associated with treatment failure 1 year after discharge (hazard ratio: 0.94, 95% CI: 0.55-1.61). However, 6 patients in the nonvoluntary ECT group underwent the procedure again, representing a statistically significant difference.

CONCLUSIONS: Nonvoluntary ECT may be an effective treatment option for patients with life-threatening conditions when no alternative is available. However, further investigation is needed to explore ways to improve patient acceptance of future treatments.

PMID:42218831 | DOI:10.1097/YCT.0000000000001282

Pharmacogenet Genomics. 2026 Mar 26. doi: 10.1097/FPC.0000000000000599. Online ahead of print.

ABSTRACT

OBJECTIVES: Gastroesophageal reflux disease is primarily treated with proton pump inhibitors (PPIs), which are metabolized by cytochrome P450 2C19 (CYP2C19) in the liver. CYP2C19 polymorphisms affect PPI plasma levels, with rapid (2-27%) and ultra-rapid (<1-5%) metabolizers needing higher doses, while poor (3-15%) and intermediate (27-47%) metabolizers require lower doses for therapeutic effectiveness. Antireflux surgery is recommended for patients refractory to medical therapy or with symptomatic hiatal hernias.

METHODS: This is a multisite retrospective review of adult patients from 2012 to 2023 diagnosed with gastroesophageal reflux disease who underwent hiatal hernia operations and completed CYP2C19 testing. CYP2C19 phenotypes were grouped as poor metabolizer/intermediate metabolizer, normal metabolizers, or rapid metabolizer/ultra-rapid metabolizer. Hiatal hernia size was classified as small, medium, or large based on preoperative and intra-operative findings. Descriptive statistics were used.

RESULTS: Eighty patients [female: 66%, median age: 60.5 (interquartile range 53.3-67.0) years, 90% White, 6% Hispanic] had CYP2C19 testing and underwent a hiatal hernia repair. CYP2C19 phenotypes were poor metabolizer (4%), intermediate metabolizer (24%), normal metabolizers (30%), rapid metabolizer (31%), and ultra-rapid metabolizer (11%). About 28% were grouped as poor metabolizer/intermediate metabolizer and 43% as rapid metabolizer/ultra-rapid metabolizer. Among patients with small (n = 41) and medium (n = 23) hernias, 39% and 57%, respectively, were classified as rapid metabolizer/ultra-rapid metabolizer, suggesting they were resistant to PPIs.

CONCLUSION: The prevalence of rapid metabolizer/ultra-rapid metabolizer CYP2C19 phenotypes in patients undergoing antireflux surgery is higher than generally reported in the general population. These patients could potentially benefit from higher PPI doses or surgical intervention if ineffective. Prospective multisite studies with diverse, representative samples are needed to confirm these findings.

PMID:42218813 | DOI:10.1097/FPC.0000000000000599

Disabil Rehabil Assist Technol. 2026 May 31:1-18. doi: 10.1080/17483107.2026.2680552. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to clarify the selection trends of ATDs by occupational therapists for children with developmental disabilities or developmental concerns in childcare facilities, based on the challenges of inclusive childcare in Japan. We explored variability in ATD selection across cases, the reasoning behind these selections, and alternative devices or strategies considered.

METHODS: An online questionnaire survey was conducted targeting occupational therapists in Japan. Descriptive statistics were used to calculate the selection frequency of ATDs for each case. Correspondence analysis and characteristic word extraction were used to analyse the reasons for ATD selection, and thematic analysis was used to categorise alternative devices and strategies.

RESULTS: Responses were received from 75 occupational therapists, with 72 valid responses. The results showed that ATD selection tended to be relatively consistent for some cases, while it was more varied for others. The reasons for selection were categorised into six categories. Regarding alternatives other than ATDs, various support methods were considered, including adjustments to the human environment and modifications of activities.

CONCLUSION: The results suggest that the variety of support methods available to occupational therapists may influence the variability in ATD selection. The selection of ATDs was based primarily on four factors: support for sensory characteristics, visual support, calming down, and physical function. The findings suggest that occupational therapists comprehensively consider a diverse range of support methods, including ATDs, to achieve inclusion.

PMID:42218785 | DOI:10.1080/17483107.2026.2680552

Breast J. 2026;2026(1):e6589301. doi: 10.1155/tbj/6589301.

ABSTRACT

BACKGROUND: Neoadjuvant chemotherapy (NACT) is an important component in preparing breast cancer patients for surgery. Its impact on postoperative complications, such as wound infections and bleeding, remains unclear. While most studies show no increase in complication rates, factors such as smoking may elevate risk. Understanding surgeons’ perspectives on bleeding and related influences is therefore essential.

METHODS: This study used a questionnaire on bleeding and wound healing. After ethical approval in Vienna and Burgenland, 33 surgeons were recruited. Data were collected between July and December 2022 through interviews or self-administered questionnaires and analyzed descriptively.

RESULTS: Overall, 63.6% of surgeons reported recognizing NACT-treated patients intraoperatively. Perceptions of blood loss varied, with some noting no difference and others reporting increased bleeding. The influence of tumor size and smoking was debated, with no clear consensus. Most surgeons did not observe prolonged operative times. Challenges in axillary dissection and sentinel lymph node identification were reported, particularly after NACT.

CONCLUSION: Surgeons’ views on the impact of NACT in breast surgery vary considerably. These findings highlight the complexity of integrating NACT into surgical practice and the need for further research to improve training, patient counseling, and evidence-based guidelines.

PMID:42218781 | DOI:10.1155/tbj/6589301

Scand J Clin Lab Invest. 2026 May 31:1-14. doi: 10.1080/00365513.2026.2681040. Online ahead of print.

ABSTRACT

In large datasets, conventional t-tests may identify statistically significant but practically trivial differences because statistical significance increases with sample size. A log-adjusted t-statistic, defined as an empirical sample-size-aware modification of the classical t-statistic, was evaluated to reduce this oversensitivity. Performance was assessed by Monte Carlo simulations of two-sample comparisons across sample sizes from 10 to 50,000 and effect sizes from δ = 0 to 1.0, and by application to a real clinical laboratory dataset comprising 464,145 participants. In simulations, the ${\text{log}}_{10}\left(\text{Df}\right)$-adjusted statistic showed null rejection rates close to 0.05 across sample sizes, whereas the classical t-test became increasingly oversized at very large n. The adjustment was more conservative for small effects (δ = 0.2-0.4) while high rejection rates were retained for larger effects (δ = 0.6-1.0). In the real-data analysis, several sex differences that were highly significant by the classical t-test had small effect sizes and yielded reference p-values above the conventional 0.05 threshold after adjustment; platelet count (Cohen’s d = 0.13) changed from p < 10^-300 to reference p = 0.052, and potassium (d = 0.05) from p = 10-51 to reference p = 0.104. In contrast, larger effects such as hematocrit (d = 0.83) and HDL cholesterol (d = 0.77) continued to yield reference p-values below that threshold. These reference p-values were compared with the conventional α = 0.05 threshold for illustrative purposes only and were not intended to imply formal Type I error control. These findings suggest that the log-adjusted t-statistic may serve as a useful empirical decision aid for interpreting large clinical laboratory datasets by attenuating sample-size-driven significance while preserving detection of substantively meaningful effects.

PMID:42218778 | DOI:10.1080/00365513.2026.2681040

J Sports Sci. 2026 May 31:1-12. doi: 10.1080/02640414.2026.2673237. Online ahead of print.

ABSTRACT

The shared genetic architecture linking physical activity, sedentary behavior, and osteoporosis risk remains unclear. We investigated the genetic basis, pleiotropic effects, and causal relationships between moderate-to-vigorous physical activity (MVPA), leisure screen time (LST), and heel estimated bone mineral density (eBMD). Leveraging summary statistics from genome-wide association studies of European individuals (MVPA: N = 606,820; LST: N = 526,725; eBMD: N = 426,824), we conducted a genome-wide cross-trait analysis. A significant global genetic correlation was observed for MVPA and eBMD ($r_g$ = 0.13, P = 7.97 × 10^-11), but not for LST and eBMD ($r_g$ = $–$ 0.02, P = 0.34). Two specific genomic regions showed evidence of local genetic correlation. Cross-trait meta-analysis identified 90 pleiotropic loci, of which 20 were novel. Transcriptome-wide association studies revealed 42 shared genes. Mendelian randomization suggested a causal relationship between genetically predicted MVPA and eBMD (beta = 0.07, 95%CIs = 0.01-0.14, P = 0.03), but not for LST (beta = 0.01, 95%CIs = $–$ 0.04-0.05, P = 0.81). Our findings demonstrate a shared genetic basis and pleiotropic effects between MVPA and eBMD, highlighting their intrinsic link and supporting MVPA’s role in osteoporosis prevention.

PMID:42218761 | DOI:10.1080/02640414.2026.2673237

JAMA Health Forum. 2026 May 1;7(5):e261649. doi: 10.1001/jamahealthforum.2026.1649.

ABSTRACT

IMPORTANCE: Nursing home residents with dementia are often unnecessarily hospitalized at the end of life. Institutional Special Needs Plans (I-SNPs) are a type of Medicare Advantage plan for long-term nursing home residents that use advanced practice clinicians to manage care. Studies have demonstrated the effectiveness of the original and largest I-SNP operated by UnitedHealthcare (UHC), but there has been minimal evaluation of non-UHC I-SNPs, which have driven recent growth, nor specific focus on end-of-life outcomes.

OBJECTIVE: To examine the association of I-SNP enrollment with end-of-life outcomes for nursing home residents with dementia, separately for UHC and non-UHC I-SNPs.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used 2010 to 2022 Medicare data on 1.4 million long-stay nursing home residents with dementia who died between 2013 and 2022. Facility-level and patient-level selection bias were addressed with cross-temporal propensity score matching and difference-in-differences models. Both the direct effects of I-SNP enrollment, as well as the indirect (ie, spillover) effects on nonenrollees residing in nursing homes offering I-SNPs were assessed. Variation in these relationships by I-SNP maturity was also examined. Data were analyzed from November 2024 to April 2026.

EXPOSURE: Four I-SNP exposure categories: UHC I-SNP enrollment and spillover; non-UHC I-SNP enrollment and spillover.

MAIN OUTCOMES AND MEASURES: Hospitalization and hospice use in the last month of life.

RESULTS: The study cohort included 1 415 265 long-stay nursing home residents with dementia who died between 2013 and 2022. The unadjusted hospitalization rate in the last 30 days of life was 27.7%. UHC I-SNP enrollment was associated with a 9.0-percentage point (pp) reduction in hospitalization (95% CI, -10.3 pp to -7.7 pp) while non-UHC I-SNP enrollment was associated with a 5.9-pp reduction (95% CI, -8.4 pp to -3.5 pp). The spillover effect on nonenrollees in nursing homes offering a UHC I-SNP was a 1.7-pp (95% CI, -2.4 pp to -1.1 pp) decline in hospitalizations; the spillover effect in non-UHC nursing homes was not statistically significant. Similar trends appeared with hospitalization in the last 3 days of life, intensive care unit admission, and mechanical ventilation, but there was no association with hospice use. The reduction in hospitalizations increased in the 3 years after nursing home I-SNP adoption, then plateaued.

CONCLUSIONS AND RELEVANCE: In this retrospective cohort study, I-SNP enrollment was associated with significantly fewer hospitalizations for nursing home residents with dementia at the end of life, with effect sizes larger for UHC vs non-UHC I-SNPs. Plan maturity and volume are likely important factors impacting success.

PMID:42218737 | DOI:10.1001/jamahealthforum.2026.1649

Brief Bioinform. 2026 May 4;27(3):bbag270. doi: 10.1093/bib/bbag270.

ABSTRACT

Genomic selection leverages genome-wide markers and phenotypes to predict breeding values, with its effectiveness largely dependent on the accuracy of genomic prediction (GP) models. However, GP methods often struggle to capture inter-individual variability and are limited by the curse of dimensionality, where the number of single-nucleotide polymorphisms (SNPs) far exceeds the sample size. To address these challenges, we present CLCNet (Contrastive Learning and Chromosome-aware Network), a novel deep learning framework that integrates contrastive learning and chromosome-aware feature modeling. CLCNet comprises two key components: (i) a contrastive learning module that enhances the model’s ability to capture fine-grained, genotype-dependent phenotypic differences among individuals, and (ii) a chromosome-aware module that captures structured feature selection at both chromosome and genome levels, thereby distilling the most informative SNPs. We evaluated CLCNet across 4 crop species, covering 10 agronomically important traits, and compared it with a diverse set of classical linear, machine learning, and deep learning models. CLCNet achieved superior prediction performance, with statistically significant improvements in Pearson correlation coefficient, ranging from 0.34% to 12.19% over baseline, together with reduced mean squared error. Performance gains were more pronounced for traits with moderate linkage disequilibrium (LD; r2 = 0.21-0.36) and high heritability (h2 > 0.66), such as those in maize, rapeseed, and soybean. For cotton traits characterized by high LD (r2 = 0.74) and lower heritability (h2 < 0.50), CLCNet maintained robust performance without degradation. Overall, these results demonstrate that CLCNet is an effective framework for improving genomic prediction accuracy and holds strong potential for practical applications in plant breeding.

PMID:42218721 | DOI:10.1093/bib/bbag270

Brief Bioinform. 2026 May 4;27(3):bbag262. doi: 10.1093/bib/bbag262.

ABSTRACT

Gene set analysis evaluates the collective impact of groups of genes on an outcome of interest, such as disease occurrence. By incorporating biological knowledge through predefined gene sets, this approach enhances the interpretability of results and improves statistical power compared with gene-wise analyses. In the context of time-to-event data, existing methods are limited and fail to account for potentially strong correlations within gene sets. Given the strong performance of the Generalized Berk-Jones (GBJ) statistic, which effectively incorporates correlation within the test statistic, we adapted this method to the time-to-event framework using a Cox model. We then compared its performance with established methods, including the Cauchy, Harmonic Mean, Wald test, global test, and global boost test. We further benchmarked these methods in two different real-world datasets: gliomas and breast cancer. Our proposed method, sGBJ, shows an overcontrol of Type I error, leading to reduced statistical power compared with other methods in numerical studies particularly when the number of genes is greater than or equal to the number of observations. The Wald test and global boost test generally exhibited the highest power, except in very high-correlation settings for the global boost test, while the Wald test could not adjust for confounders in current implementations.

PMID:42218714 | DOI:10.1093/bib/bbag262