Nevin Manimala

Surg Endosc. 2025 Aug 19. doi: 10.1007/s00464-025-12100-w. Online ahead of print.

ABSTRACT

INTRODUCTION: Complex gastroschisis requires timely intervention to protect the fetal intestine from inflammation and strangulation and avoid viscero-abdominal disproportion (VAD). Earlier results in ovine models for the fetoscopic management of gastroschisis highlight the benefits of minimally invasive coverage; yet specialized instruments appear to be needed for better procedural execution. The aim of this study was to create and validate a first prototype instrument for the prenatal covering of the protruded intestines in gastroschisis.

METHODS: A 7-mm diameter fetoscopic instrument was designed to hold and deploy a protective bag over the gastroschisis defect after suture fixation to the fetus. An inanimate model was used to evaluate the instrument’s usability and effectiveness: Eleven participants performed bag placement and suturing both with and without the prototype, enabling a comparative assessment of procedural performance. Statistical analysis was conducted to evaluate the duration of the procedure, while product deficiencies were qualitatively assessed using a Likert-scale questionnaire. The overall usability of the prototype was further evaluated using the system usability scale (SUS).

RESULTS: The prototype consistently enhanced bag handling and positioning. Median procedural time slightly increased from 118.5 to 120.5 s with the prototype (p = 0.98), without affecting the overall procedural efficiency. Usability assessments using the SUS (median score: 67.95) and the Likert scale indicated a generally favorable response. Importantly, usability ratings were consistent regardless of participants’ prior experience in minimally invasive surgery (p = 0.43), underscoring the intuitive design and ease of adoption of the prototype.

CONCLUSION: Despite a minor increase in procedural time, the prototype enabled secure bag placement and demonstrated moderate usability across all participants. This is particularly relevant for fetal procedures requiring amnioinfusion, as opposed to partial amniotic carbon dioxide insufflation (PACI) used in the inanimate model. However, further mechanical refinement is warranted to enhance performance and address usability concerns.

PMID:40830539 | DOI:10.1007/s00464-025-12100-w

BMC Psychol. 2025 Aug 19;13(1):942. doi: 10.1186/s40359-025-03258-y.

NO ABSTRACT

PMID:40830533 | DOI:10.1186/s40359-025-03258-y

Genome Biol. 2025 Aug 20;26(1):246. doi: 10.1186/s13059-025-03718-z.

ABSTRACT

Tandem repeat copy number variations (TR-CNVs), structural variations (SVs), and short indels have been responsible for many diseases and traits, but no tools exist to distinguish and detect these variants. In this study, we developed a computational tool, TRsv, to distinguish and detect TR-CNVs, SVs, and short indels using long reads. In evaluation with simulated and real datasets, TRsv outperformed existing tools for detection of TR-CNVs and indels and performed equally well for detection of SVs. We demonstrated genome-wide detection of TR-CNVs, including variants associated with gene expression, disease, and quantitative traits, using 160 long-read whole genome sequencing data and TRsv.

PMID:40830527 | DOI:10.1186/s13059-025-03718-z

Infect Dis Poverty. 2025 Aug 19;14(1):87. doi: 10.1186/s40249-025-01358-w.

ABSTRACT

BACKGROUND: Toxoplasma gondii is a globally widespread zoonotic parasite, infecting nearly one-third of the human population, often leading to chronic, latent infections. Among the emerging layers of gene regulation, 5-methylcytosine (m⁵C) has emerged as a pivotal post-transcriptional modification in eukaryotes. Despite its growing recognition in various species, the epitranscriptomic landscape of m⁵C in the tachyzoite stage of T. gondii remains largely unexplored. To address this gap, we performed the first comprehensive m⁵C methylation profiling across three major T. gondii genotypes-RH (type I), ME49 (type II), and VEG (type III).

METHODS: The comparative m⁵C methylation analysis was carried out using methylated RNA immunoprecipitation sequencing (MeRIP-Seq) combined with RNA sequencing (RNA-Seq). Differentially m⁵C-methylated genes (DMMGs) were functionally annotated via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. By combining methylation and transcriptomic data, we uncovered strain-specific correlations between m⁵C modifications and gene expression. Additionally, expression and methylation patterns of potential regulators identified via BLASTP searches were examined. Statistical analyses were determined by one-way ANOVA.

RESULTS: Our analysis revealed a total of 5129, 4968, and 4577 m⁵C-methylated genes in RH, ME49, and VEG tachyzoites, respectively, with methylation predominantly enriched in the coding sequences. Comparative analysis across different strains uncovered 1710, 1131, and 784 DMMGs in RH versus ME49, RH versus VEG, and ME49 versus VEG, respectively. Functional enrichment analysis highlighted key biological processes, including catalytic activity, transport, phospholipid metabolism and transcription regulation. Furthermore, KEGG pathway analysis identified critical m⁵C-regulated processes such as nucleocytoplasmic transport, DNA replication, and ATP-dependent chromatin remodeling. Virulence-associated secretory effectors exhibited hypermethylation in more virulent strains, such as GRA39 and ROP35. Additionally, several putative m⁵C regulators displayed genotype-specific or conserved expression and methylation patterns.

CONCLUSIONS: This study presents the first m⁵C epitranscriptomic atlas of T. gondii tachyzoites, revealing both conserved and genotype-specific mRNA modification networks. These insights significantly increased the understanding of the regulatory role of m⁵C in T. gondii pathogenesis and open promising avenues for the development of vaccines and therapeutics aimed at combating zoonotic toxoplasmosis.

PMID:40830525 | DOI:10.1186/s40249-025-01358-w

Alzheimers Res Ther. 2025 Aug 20;17(1):194. doi: 10.1186/s13195-025-01851-2.

ABSTRACT

BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer’s disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a potential alternative. This study evaluates the diagnostic accuracy of a combined-panel approach using machine learning models and evaluated the biomarker significance.

METHODS: We enrolled 371 participants, including AD (n = 143), non-AD (n = 159), and cognitively unimpaired (CU, n = 69) controls. Combined panels of pTau217, pTau181, glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), Aβ42/40, and total tau were measured prior to the amyloid PET scan. The multiclass logistic (LR) regression, support vector machines, decision trees, and random forests (RF)-were applied to classify amyloid positivity (A+) at all stages or at early clinical stages (1-3). In AD, we tested whether the biomarker may define the clinical stagings.

RESULTS: When benchmarked against amyloid PET, plasma biomarker-based stratification achieves an optimal balance between diagnostic accuracy and cost-effectiveness. The multi-class LR performed equivalently with RF model in identifying A+. The combined plasma panel reached an > 92% accuracy in identifying A+, with performance increasing to 93.4% at early clinical stages. We ranked the importance of individual biomarkers and pTau217 alone achieved comparable accuracy (> 90%) and was the top-ranked biomarker in the LR or RF model. NFL and GFAP correlated significantly with Mini-Mental State Examination; however, these plasma biomarkers did not enhance clinical staging stratification.

DISCUSSION: The use of multiclass LR model enhances amyloid classification, particularly at earlier clinical stages. While the combined-panel approach is most accurate, pTau217 alone provides a cost-effective alternative for screening. These findings support the integration of plasma biomarkers and ML into clinical workflows for early detection and patient stratification.

PMID:40830505 | DOI:10.1186/s13195-025-01851-2

Acta Psychol (Amst). 2025 Aug 18;259:105415. doi: 10.1016/j.actpsy.2025.105415. Online ahead of print.

ABSTRACT

BACKGROUND: Eating disorder symptoms are a major global mental health concern and are often associated with body image concerns. This study explores the relationship between body image and eating disorder symptoms in Chinese female university students, highlighting the parallel mediating roles of core self-evaluations and negative emotions.

METHODS: A random sample of 668 female university students completed an online survey using the Body Image State Scale (BISS), Eating Disorder Examination Questionnaire (EDE-QS), Core Self-Evaluations Scale (CSES), and Depression Anxiety Stress Scales (DASS-21). SPSS Statistics 26 was used for reliability, validity, descriptive statistics, and correlation analysis, while mediation analysis was conducted using Model 4 in PROCESS 4.0.

RESULTS: The study found that body image was significantly associated with eating disorder symptoms both directly (β = -0.108, p < 0.01) and indirectly through the parallel mediating roles of core self-evaluations (β = -0.092, 95 % CI [-0.137, -0.052]) and negative emotions (β = -0.058, 95 % CI [-0.091, -0.028]). Core self-evaluations accounted for 35.7 % and negative emotions for 22.5 % of the total effect (β = -0.258, 95 % CI [-0.332, -0.185]).

CONCLUSION: Core self-evaluations and negative emotions play essential roles in the associations between body image and eating disorder symptoms. These findings provide theoretical insights for psychological interventions and practical recommendations for mental health education programs in universities. However, the results should be interpreted cautiously, as they are generalizable only to female participants within the Chinese context. Future research could extend this work to female populations from different cultural backgrounds to examine the cross-cultural applicability of the findings.

PMID:40829192 | DOI:10.1016/j.actpsy.2025.105415

J Clin Invest. 2025 Aug 15;135(16):e184597. doi: 10.1172/JCI184597. eCollection 2025 Aug 15.

ABSTRACT

Platelet hyperreactivity increases the risk of cardiovascular thrombosis in diabetes and failure of antiplatelet drug therapies. Elevated basal and agonist-induced calcium flux is a fundamental cause of platelet hyperreactivity in diabetes; however, the mechanisms responsible for this remain largely unknown. Using a high-sensitivity, unbiased proteomic platform, we consistently detected over 2,400 intracellular proteins and identified proteins that were differentially released by platelets in type 2 diabetes. We identified that SEC61 translocon subunit β (SEC61B) was increased in platelets from humans and mice with hyperglycemia and in megakaryocytes from mice with hyperglycemia. SEC61 is known to act as an endoplasmic reticulum (ER) calcium leak channel in nucleated cells. Using HEK293 cells, we showed that SEC61B overexpression increased calcium flux into the cytosol and decreased protein synthesis. Concordantly, platelets in hyperglycemic mice mobilized more calcium and had decreased protein synthesis. Platelets in both humans and mice with hyperglycemia had increased ER stress. ER stress induced the expression of platelet SEC61B and increased cytosolic calcium. Inhibition of SEC61 with anisomycin decreased platelet calcium flux and inhibited platelet aggregation in vitro and in vivo. These studies demonstrate the existence of a mechanism whereby ER stress-induced upregulation of platelet SEC61B leads to increased cytosolic calcium, potentially contributing to platelet hyperreactivity in diabetes.

PMID:40829182 | DOI:10.1172/JCI184597

JMIR Med Educ. 2025 Aug 19;11:e76574. doi: 10.2196/76574.

ABSTRACT

BACKGROUND: Artificial intelligence-powered chatbots (AI-PCs) are increasingly integrated into educational settings, including health care disciplines. Despite their potential to enhance learning, limited research has investigated physiotherapy (PT) students’ acceptance of this technology.

OBJECTIVE: This study aims to assess undergraduate PT students’ acceptance of AI-PCs and to identify personal, academic, and technological factors influencing their acceptance.

METHODS: Over a 4-month period, a cross-sectional survey was conducted across 7 PT programs in 5 countries. Eligible participants were national undergraduate PT students. The technology acceptance model (TAM)-based questionnaire was used for capturing perceived usefulness, perceived ease of use, attitude, behavioral intention, and actual behavioral use of AI-PCs. The influence of personal, academic, and technological factors was examined. Descriptive and inferential statistics were conducted.

RESULTS: The mean total TAM score was 3.59 (SD 0.82), indicating moderate acceptance. Of the 1066 participants, 375 (35.2%) showed high acceptance, 650 (60.9%) moderate, and 41 (3.9%) low. Prior experience with artificial intelligence (AI) tools emerged as the strongest predictor of acceptance (β=.43; P<.001), followed by university affiliation (ANOVA P<.001). Cumulative grade point average percentage was positively correlated with TAM score (r=0.135; P<.001) but was not a significant predictor in regression (P=.23). Age (P=.54), sex (P=.56), academic level (P=.26), and current use of AI-PCs (P=.10) were not significant predictors.

CONCLUSIONS: PT students demonstrated moderate acceptance of AI-PCs. Prior technological experience was the strongest predictor, underscoring the importance of early exposure to AI tools. Educational institutions should consider integrating AI technologies to enhance students’ familiarity and foster positive attitudes toward their use.

PMID:40829169 | DOI:10.2196/76574

Ultrasound Obstet Gynecol. 2025 Aug 19. doi: 10.1002/uog.29314. Online ahead of print.

ABSTRACT

OBJECTIVE: We previously proposed two cell-free (cf) DNA-based scores (genome-wide Z-score and nucleosome score) as candidate non-invasive biomarkers to further improve the presurgical diagnosis of ovarian malignancy. We aimed to investigate the added value of these cfDNA-based scores in combination with the clinical and ultrasound predictors of the Assessment of Different NEoplasias in the adneXa (ADNEX) model to estimate the risk of ovarian malignancy.

METHODS: In this prospective cohort study, 526 patients with an adnexal mass scheduled for surgery were recruited consecutively in three oncology referral centers. All patients underwent a transvaginal ultrasound examination, and adnexal masses were described according to the International Ovarian Tumor Analysis terms and definitions. cfDNA was extracted from preoperative plasma samples and genome-wide Z-scores and nucleosome scores were calculated. Logistic regression models were fitted for ADNEX predictors alone and after inclusion of the cfDNA-based scores. We report likelihood ratios, area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity and net benefit for thresholds between 5% and 40%, to assess the diagnostic performance of the models in discriminating between benign and malignant ovarian masses.

RESULTS: The study included 272 benign, 86 borderline, 36 Stage-I invasive, 113 Stage-II-IV invasive, and 19 secondary metastatic tumors. The likelihood ratios for adding the cfDNA-based scores to the ADNEX model were statistically significant (P < 0.001 for ADNEX without CA 125; P = 0.001 for ADNEX including CA 125). The accompanying increases in AUC were 0.013 when the cfDNA biomarkers were added to the ADNEX model without CA 125, and 0.003 when added to the ADNEX model including CA 125. Net benefit, sensitivity and specificity were similar for all models. The increase in net benefit at the recommended 10% threshold estimated risk of malignancy when adding the cfDNA-based scores was 0.0017 and 0.0020, respectively, for the ADNEX model without CA 125 and the ADNEX model with CA 125. According to these results, adding cfDNA markers would require at least 453 patients per additional true-positive test result at the 10% risk threshold.

CONCLUSION: Although statistically significant, cfDNA-based biomarker scores have limited clinical utility in addition to established clinical and ultrasound-based ADNEX predictors for discriminating between benign and malignant ovarian masses. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

PMID:40829165 | DOI:10.1002/uog.29314

Clin Nucl Med. 2025 Jul 29. doi: 10.1097/RLU.0000000000006061. Online ahead of print.

ABSTRACT

BACKGROUND: Prostate-specific membrane antigen (PSMA), expressed in neovascular endothelial cells of various malignancies including lung cancer (LC), highlights its potential as a biomarker for neovascularization. This study aimed to investigate the diagnostic efficacy of PSMA PET/CT in primary lung cancer (PLC), as well as to explore its role in staging and neovascularization detection in PLC.

PATIENTS AND METHODS: This retrospective study included 39 patients (27 with PLC, 12 with benign lesions) who underwent PSMA PET/CT, with or without FDG PET/CT, between April 2021 and July 2024. Lesion characteristics and immunohistochemistry for PSMA, VEGFA, and CD31 were assessed in 11 surgical cases. Statistical analyses included the Mann-Whitney U test and Spearman correlation (p<0.05).

RESULTS: Our study demonstrated that PSMA PET/CT effectively differentiates PLC from benign lesions, achieving a high SUVmax AUC of 0.89 (cutoff: 2.3 g/mL) and a mediastinal lymph node (LN) identification AUC of 0.86 (cutoff: 2.5 g/mL). Compared with FDG PET/CT, PSMA PET/CT exhibited a lower false-positive LN detection rate, resulting in N-stage reclassification in 60% (12/20) of cases. PSMA PET uptake in intrapulmonary lesions correlated significantly with the PSMA H-score (R=0.63, p<0.05), CD31-assessed microvessel density (R=0.77, p<0.01), and VEGFA H-score (R=0.65, p<0.05), while FDG uptake showed no correlation.

CONCLUSIONS: PSMA PET shows higher uptake in PLC than in benign lesions, improves LN staging, and reveals its potential as a biomarker for neovascularization and treatment optimization in LC.

PMID:40829160 | DOI:10.1097/RLU.0000000000006061