Tag: pubmed

Cancer Causes Control. 2026 Jul 8;37(8):124. doi: 10.1007/s10552-026-02193-6.

ABSTRACT

BACKGROUND: Epidemiological and clinical characteristics of primary pancreatic lymphoma (PPL) have been rarely reported in the literature. This study aimed to characterize the epidemiological features of PPL and develop robust nomograms for predicting patient survival outcomes.

METHODS: Patients diagnosed with PPL were extracted from the Surveillance, Epidemiology, and End Results (SEER) database for the period 1983-2015. Incidence rates of PPL were calculated for 1975-2018, and temporal trends were assessed using Joinpoint regression analysis. Cox proportional hazards regression models were applied to identify independent prognostic factors for overall survival (OS) and disease-specific survival (DSS). Nomograms were constructed based on independent clinicopathological factors to predict the probability of survival in PPL patients.

RESULTS: A total of 867 PPL patients were identified between 1983 and 2015, with a mean age at diagnosis of 65.7 years and a male-to-female ratio of 1.5:1. The overall age-adjusted incidence of PPL from 1975 to 2018 was 0.44 per 1,000,000 population, exhibiting a statistically significant increasing trend with an annual percentage change (APC) of 2.33 (95% confidence interval [CI]: 0.88-3.80, P < 0.05). Multivariate Cox regression analysis revealed that age, sex, marital status, pathological subtype, Ann Arbor stage, surgical intervention, and chemotherapy were independent prognostic factors for both OS and DSS (all P < 0.05). Nomograms were developed to predict 1-, 5-, and 10-year OS and DSS, and the predictive performance and calibration of these models were validated using the concordance index (C-index) and calibration curves, respectively.

CONCLUSION: PPL is an extremely rare malignancy, yet its incidence has increased steadily over the past four decades. The constructed nomograms can accurately predict 1-, 5-, and 10-year OS and DSS in PPL patients and effectively stratify patients into high-risk and low-risk groups, thus facilitating clinical decision-making.

PMID:42420569 | DOI:10.1007/s10552-026-02193-6

Sci Rep. 2026 Jul 8. doi: 10.1038/s41598-026-60392-2. Online ahead of print.

ABSTRACT

Emotion detection from social media is crucial for understanding human emotions across languages. However, for low-resourced languages such as Amharic, the lack of annotated data makes this task challenging. Additionally, most current models use black-box methods that obscure whether predictions rely on linguistically meaningful cues. To address these gaps, this study proposes a multi-label emotion classification model for Amharic by fine-tuning AfroXLMR. To enhance transparency, we integrate explainable artificial intelligence (XAI) into the framework. We compiled and annotated a new dataset of 22,000 unique social media comments across eight emotion categories for training, validation, and testing. The data was split into 80% for training, 10% for validation, and 10% for testing. The proposed model achieved a recall of 87% and a Hamming loss of 0.08. To interpret its predictions, we applied Local Interpretable Model-agnostic Explanations (LIME). We also evaluated the model against several state-of-the-art baselines, including XLM-R base, mBART, BiLSTM, LSTM, CNN, and AfriBERTa. The results show that our approach outperformed each baseline, achieving F1-score improvements of 5% over XLM-R base, 3% over mBART, 5% over BiLSTM, 7% over LSTM, 9% over CNN, and 2% over AfriBERTa. Bootstrapped statistical significance testing confirms that these improvements are robust and not attributable to random variation. In conclusion, the fine-tuned AfroXLMR model demonstrates promising performance in Amharic multi-label emotion classification. Building on this success, next steps could involve exploring more advanced fine-tuning strategies and expanding our datasets to strengthen both performance and the model’s ability to generalize across diverse Amharic contexts.

PMID:42420540 | DOI:10.1038/s41598-026-60392-2

Neurol Sci. 2026 Jul 9;47(8):614. doi: 10.1007/s10072-026-09217-8.

ABSTRACT

BACKGROUND: Muscular dystrophy (MD) is a progressive neuromuscular disorder characterized by muscle degeneration, leading to fatigue, reduced endurance, and impaired functional capacity. Evidence regarding the role of therapeutic exercises in late-onset muscular dystrophies (LOMD) remains limited and inconclusive.

METHODS: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted in accordance with PRISMA guidelines. Electronic databases including MEDLINE, Scopus, and Web of Science were searched from inception to September 2025. Eligible studies evaluated the effects of therapeutic exercises on fatigue, exercise tolerance, and aerobic capacity in individuals with LOMD. Data extraction and risk of bias assessment were performed independently by two reviewers. Meta-analysis was conducted using a random-effects model.

RESULTS: Eight RCTs involving 501 participants were included. Meta-analysis demonstrated small, statistically non-significant effects of therapeutic exercises on fatigue (SMD = -0.20; 95% CI: -0.72 to 0.33; p = 0.46), exercise tolerance (SMD = 0.16, 95% CI: -0.06 to 0.38; p = 0.15), and aerobic power (SMD = 0.12; 95% CI: -0.24 to 0.48; p = 0.51). Heterogeneity ranged from low to high across outcomes.

CONCLUSION: Therapeutic exercises appears to be a safe adjunct intervention and may provide small, although statistically non-significant, improvements in fatigue, exercise tolerance, and aerobic capacity in individuals with LOMD. While the findings suggest potential clinical benefits, the limited number of high-quality trials and heterogeneity warrant cautious interpretation. Further large-scale, well-designed RCTs are required to establish definitive evidence.

PMID:42420535 | DOI:10.1007/s10072-026-09217-8

Sci Rep. 2026 Jul 8. doi: 10.1038/s41598-026-61582-8. Online ahead of print.

ABSTRACT

The objective of this systematic review and meta-analysis was to assess the risk of any and major congenital malformations and other adverse pregnancy outcomes following maternal exposure to glucagon-like peptide-1 receptor agonists during the periconceptional period and pregnancy. We conducted a systematic literature search of the PubMed, MEDLINE, Embase, Web of Science, and Reprotox electronic databases from inception through January 2026. Seven cohort studies encompassing over 40,000 exposed pregnancies were included. Maternal exposure to glucagon-like peptide-1 receptor agonists at any time during pregnancy was not associated with a statistically significant increase in any congenital malformations (OR, 1.11; 95% CI 0.82-1.51). First-trimester exposure did not significantly increase the risk of major congenital malformations (OR, 1.39; 95% CI 0.73-2.65). Furthermore, no significant risk increase was observed for stillbirth, spontaneous abortion, small for gestational age, or preterm birth. A significant association for urinary malformations was noted (OR, 1.24; 95% CI 1.05-1.47) based exclusively on unadjusted data. Maternal exposure to glucagon-like peptide-1 receptor agonists does not demonstrate a statistically significant association with major congenital malformations, stillbirth, spontaneous abortion, small for gestational age, or preterm birth. The urinary malformation signal relies on unadjusted estimates, likely reflecting residual confounding. These findings provide cautiously reassuring evidence regarding reproductive safety, though the certainty of evidence remains low.

PMID:42420519 | DOI:10.1038/s41598-026-61582-8

Sci Rep. 2026 Jul 8. doi: 10.1038/s41598-026-61057-w. Online ahead of print.

ABSTRACT

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern, ranging from simple steatosis to advanced fibrosis. SMAD3 promotes liver injury, while Farnesoid X Receptor (FXR) regulates lipid metabolism and may have protective effects. This study evaluated the preventive and therapeutic effects of hesperidin, nanohesperidin and obeticholic acid (OCA) in an HFD/fructose-fed mice, focusing on FXR and SMAD3 levels. Forty-eight female C57BL/6J mice were utilized in prevention (10 weeks) and recovery (20 weeks) protocols. Hepatic and serum SMAD3 and FXR protein levels were measured by ELISA, gene expression by qPCR, and liver injury markers (ALT, AST) were also evaluated. No significant differences in body weight were observed between the experimental groups (p > 0.05). In the recovery protocol, nanohesperidin treatment exhibited the highest hepatic FXR protein levels (p > 0.05). Serum SMAD3 levels were significantly lower in hesperidin, nanohesperidin and OCA study groups than in the control group. Although there were significant reductions in AST levels in the treatment groups, no statistically significant differences were detected in hepatic mRNA expression levels for FXR or SMAD3 (p > 0.05). These findings suggest that hesperidin, nanohesperidin, and OCA may influence fibrosis-related pathways in experimental MASLD, possibly through modulation of FXR and SMAD3 signaling. The more pronounced FXR response observed with nanohesperidin indicates that formulation strategies may affect the biological activity of hesperidin.

PMID:42420514 | DOI:10.1038/s41598-026-61057-w

Psychiatry Res. 2026 Jul 1;364:117317. doi: 10.1016/j.psychres.2026.117317. Online ahead of print.

ABSTRACT

The contribution of gut microbiota to outcomes of autism spectrum disorders (ASD) has been increasingly appreciated in recent years. With the accumulating evidence on ASD-driven alterations of the gut microbiota, heterogeneities arise across different reports. To account for variabilities in gut microbiota, clinical representations of ASD and data processing approaches, as well as limitations in sample sizes among the existing gut microbiota studies for ASD, the present multi-cohort analysis applied a standard bioinformatic and statistical pipeline on the publicly available gut metagenomic sequencing data for 674 samples, including 326 TD and 348 ASD individuals, collected from eight studies across three main geographical regions. Throughout the analysis, we identified taxonomic profiles of the gut microbiota exhibited more pronounced dysbiosis associated with ASD and between-study variations compared to functional profiles. Differentially abundant taxonomic and pathway markers were identified and validated for their consistent response to ASD across different studies. Co-occurring deficits in microbial pathways for salvaging adenosylcobalamin and S-adenosyl-L-methionine and biosynthesis of methionine in children with ASD point to a reduced microbial support for the host methionine cycle. Species from Faecalibacterium, Bacteroides, Blautia and Bifidobacterium were identified as microbial contributors to ASD-deficient microbial pathways, particularly those related to the methionine cycle. Therefore, the generalisable ASD-deficient contributors to the methionine cycle, such as Blautia wexlerae, Bacteroides stercoris and Streptococcus thermophilus, could be further investigated for their role in therapeutic applications for ASD.

PMID:42418904 | DOI:10.1016/j.psychres.2026.117317

Int J Gynecol Cancer. 2026 Jun 4;36(8):104789. doi: 10.1016/j.ijgc.2026.104789. Online ahead of print.

ABSTRACT

OBJECTIVE: Homologous recombination deficiency predicts response to platinum-based chemotherapy and poly(adenosine diphosphate-ribose) polymerase inhibitors in advanced high-grade serous ovarian carcinoma. However, the optimal timing of homologous recombination deficiency testing remains unclear for patients receiving neoadjuvant chemotherapy, as it may affect test informativity and results. We evaluated the concordance of genomic and functional homologous recombination deficiency testing before and after neoadjuvant chemotherapy in patients with high-grade serous ovarian carcinoma.

METHODS: Matched tumor samples collected before and after neoadjuvant chemotherapy from patients with high-grade serous ovarian carcinoma treated at the European Institute of Oncology (Milan, Italy, July 2018-December 2021) were analyzed. Genomic homologous recombination deficiency assessment included the Genomic Instability Score and tumor BRCA1/2 mutation testing using SOPHiA DDM Homologous Recombination Deficiency Solution. Functional homologous recombination deficiency assessment was performed through RAD51 foci formation immunofluorescence. Cohen’s kappa coefficients (κ) assessed genomic and functional homologous recombination deficiency testing concordance for matched pre- versus post-neoadjuvant chemotherapy results, and functional versus genomic homologous recombination deficiency testing concordance at all time points.

RESULTS: Samples collected before and after neoadjuvant chemotherapy from 23 patients with high-grade serous ovarian carcinoma were analyzed. Homologous recombination deficiency informativity was higher before neoadjuvant chemotherapy (87%, 20/23) than in samples collected afterward (65%, 15/23), whereas Genomic Instability Score informativity was 91% (21/23) and 78% (18/23), respectively. Concordance of the Genomic Instability Score was moderate (κ = 0.52), while homologous recombination deficiency concordance was substantial (κ = 0.67) in matched samples collected before and after neoadjuvant chemotherapy. Two of 15 matched informative samples (13%) lost Genomic Instability Score positivity after chemotherapy, but their homologous recombination deficiency test remained positive due to BRCA mutations. Functional homologous recombination deficiency assessment showed poor concordance between time points and with homologous recombination deficiency testing at each time point.

CONCLUSIONS: Genomic homologous recombination deficiency tests were concordant in matched tumor samples collected before and after neoadjuvant chemotherapy for high-grade serous ovarian carcinoma, but tissue collection before chemotherapy should be prioritized due to higher informativity. Loss of informativity may result in missed opportunities for poly(adenosine diphosphate-ribose) polymerase inhibitor therapy.

PMID:42418892 | DOI:10.1016/j.ijgc.2026.104789

Nurse Educ Today. 2026 Jul 8;167:107261. doi: 10.1016/j.nedt.2026.107261. Online ahead of print.

ABSTRACT

BACKGROUND: The growing global population of older adults necessitates more nurses with positive attitudes, competence, and willingness to provide gerontological and long-term care. However, research indicates that many nursing students lack these attributes. Simulation-based learning (SBL) is proposed as a promising teaching method to address this issue. Aim This study aimed to evaluate the effectiveness of SBL in improving nursing students’ attitudes, willingness, and performance in gerontological nursing and long-term care-related competencies.

METHODS: This study is a meta-analysis of randomized controlled trials (RCTs). Embase, CNAHL, ERIC, and PubMed were the four databases that were searched. Studies that examined how SBL affects students’ attitudes, willingness, and performance with respect to gerontological-related skills were included. The Cochrane RoB 2 risk of bias assessment tools were used to evaluate the quality of the included studies.

RESULTS: The study examined eight randomized controlled trials (RCTs) involving a total of 692 participants. The results show that SBL had no significant effect on improving nursing students’ attitudes toward older adults (SMD = 0.22, 95% CI [-0.4048], P = 0.10) or their willingness to work with this population group (SMD = 0.31, 95% CI [-0.15, 0.78], P = 0.19). However, SBL had a statistically significant effect on improving students’ performance in gerontological and long-term care-related competencies (SMD = 1.48, 95% CI [0.67, 2.28], P < 0.001).

CONCLUSION: SBL effectively enhances gerontological and long-term care competency among nursing students, but its effects on attitudes and willingness remain inconclusive. Further research is needed to integrate SBL comprehensively into gerontological nursing education.

PMID:42418856 | DOI:10.1016/j.nedt.2026.107261

JMIR Form Res. 2026 Jul 8;10:e87163. doi: 10.2196/87163.

ABSTRACT

BACKGROUND: Symptom-based localization of brainstem ischemia is challenging because of the anatomical complexity of the brainstem and the nonspecific overlap of clinical syndromes. Whether large language models (LLMs) can meaningfully assist in this task remains uncertain.

OBJECTIVE: This study aimed to compare the performance of several OpenAI LLMs and neurologists in localizing diffusion-weighted imaging (DWI)-confirmed brainstem ischemic lesions based on symptom descriptions alone.

METHODS: In this retrospective single-center study, 109 patients with DWI-confirmed acute brainstem ischemia were included. Three neurologists and 6 LLMs (GPT-5, GPT-4, GPT-4.1, GPT-4o, o3, and o3-pro) predicted lesion localization using a combined anatomical-lateral end point (left or right midbrain, pons, and medulla) based on symptom descriptions alone. Overall and regional accuracy, the Cohen κ, 6-class confusion matrices, and point-biserial correlations between symptom count and correct prediction were assessed. Because all raters evaluated the same cases, paired McNemar tests with Benjamini-Hochberg correction were used for pairwise performance comparisons.

RESULTS: GPT-4 and GPT-4o achieved the highest overall accuracy (61/109, 56%; 95% CI 46.1%-65.5%). Agreement with the DWI reference standard remained limited across all raters, with the Cohen κ reaching a maximum of 0.291 for GPT-4o. Confusion matrices showed that higher performance was driven mainly by pontine cases, whereas misclassification remained frequent in mesencephalic and medullary lesions. Regional analyses outside the pons were imprecise because mesencephalic and medullary subgroups each contained only 16 cases. A higher number of documented symptoms was associated with correct prediction for GPT-4, GPT-5, GPT-o3, and 1 neurologist.

CONCLUSIONS: Although some LLMs showed higher relative accuracy than the participating neurologists, absolute performance remained limited and clinically insufficient. These findings are best interpreted as an exploratory benchmark under constrained conditions: absolute performance remained modest, agreement beyond chance was limited, and performance outside pontine lesions was inconclusive.

PMID:42418842 | DOI:10.2196/87163

J Vet Intern Med. 2026 Jul 1;40(4):aalag135. doi: 10.1093/jvimsj/aalag135.

ABSTRACT

BACKGROUND: Cerebrospinal fluid (CSF) analysis is a critical component in the diagnosis of equine protozoal myeloencephalitis (EPM). Test results obtained may differ based on different collection sites.

HYPOTHESIS/OBJECTIVES: Compare results of EPM-specific diagnostic tests obtained from different collections sites in EPM-affected and non-EPM affected horses.

ANIMALS: Twenty control and 7 EPM-affected horses.

METHODS: Prospective observational study. CSF was collected from the lumbosacral (LS) and cranial sites (atlantooccipital or C1-2) in 27 horses and EPM-specific diagnostic tests were performed. Data were summarized by collection site and disease status. Results were compared by Wilcoxon signed rank test in the non-EPM and EPM-affected cohorts.

RESULTS: The EPM-specific diagnostic test results (anti-Sarcocystis neurona CSF antibody titer, serum/CSF titer ratios, and S. neurona antibody index [AI]) in non-EPM affected horses did not differ based on collection site. In EPM-affected horses the median [interquartile range] CSF anti-S. neurona antibody titers were higher in samples from the LS site compared with fluid collected from the cranial sites (160 [1240] vs. 80 [600]; Wald test statistic, 21.0; P = .03) and the median serum/CSF titer ratio was also lower in fluid collected from the LS site (25 [46.8] vs 50 [93.7]; Wald test statistic, 0; P = .03). Median AI values did not differ based on CSF collection site.

CONCLUSIONS AND CLINICAL IMPORTANCE: Results of EPM diagnostic tests on CSF may differ based on collection site and lead to misdiagnosis. The AI appears to be less affected by collection site than antibody titers or the serum/CSF titer ratio.

PMID:42418837 | DOI:10.1093/jvimsj/aalag135