Category: Nevin Manimala

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

Eye Contact Lens. 2025 Aug 15. doi: 10.1097/ICL.0000000000001216. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aimed to estimate direct and indirect economic costs associated with Acanthamoeba keratitis and explore variations in individual and healthcare characteristics.

METHODS: Patients treated at Moorfields Eye Hospital, UK, between January 2011 and August 2014 were surveyed. Patients were included if they had a confirmed diagnosis and wore contact lenses. Direct costs included healthcare expenses, whereas indirect costs encompassed lost wages for patients and caregivers. The Mann-Whitney U test and generalized linear models were used to analyze cost data and their associated factors, with P<0.05 being considered statistically significant.

RESULTS: A total of 73 patients were included, with a mean age of 39.3 years (19-81); 40 patients (54.8%) were female, and 41 (56.2%) had good outcomes. Median direct, indirect, and total costs were £2,966.5 (IQR £5,553.2), £1,776.0 (IQR £3,223.3), and £6,678.6 (IQR £17,268.4), respectively. Higher direct costs were independently associated with multiple medical visits (P<0.001), steroids before antiamoeba therapy (P=0.042), and keratoplasty (P<0.001).

CONCLUSIONS: The cost of managing Acanthamoeba keratitis is substantial. Future research should focus on optimizing treatment strategies and improving patient outcomes to help alleviate the financial burden on patients and healthcare systems.

PMID:40829159 | DOI:10.1097/ICL.0000000000001216

JMIR Form Res. 2025 Aug 19;9:e73193. doi: 10.2196/73193.

ABSTRACT

BACKGROUND: Social media is an important source of e-cigarette-related information for adolescents and young adults. However, misinformation is being shared across platforms, which may encourage e-cigarette use.

OBJECTIVE: This study aims to examine adolescent and young adult perceptions of a novel pop-up on social media that provides links to vaping-related health information from credible sources (eg, CDC).

METHODS: Between December 2023 and March 2024, participants aged 13-24 years (N=5326) completed a web-based cross-sectional survey. Participants were asked to select from 4 positive (eg, useful to share, helpful to check health-related information) and 4 negative or neutral sentiments (eg, usually ignore such notifications, would not trust it) to reflect their perceptions about a mock pop-up that provided a link to e-cigarette-related information on social media.

RESULTS: More participants endorsed positive sentiments than negative or neutral sentiments in relation to the pop-up. Specifically, 1078 (20.8%) endorsed two or more positive sentiments, and 690 (13.3%) endorsed two or more negative or neutral sentiments when searching for “vaping” on social media; similarly 913 (17.6%) participants endorsed two or more positive sentiments and 690 (13.3%) endorsed two or more negative or neutral sentiments when viewing e-cigarette-related posts in their feed (all P<.001). Among those who were searching for e-cigarette-related information, participants aged 13-18 years were more likely to endorse at least two positive sentiments compared to those aged 19-24 years (ie, 646, 22.0% vs 423, 19.2%, respectively), those who had never used e-cigarettes compared with those who had ever used them (ie, 674, 23.6% vs 404, 17.3%, respectively), and those who last used e-cigarettes more than 30 days ago compared with those who had used them in the past 30 days (ie, 187, 19.8% vs 217, 15.6%, respectively). Similarly, among participants who viewed e-cigarette-related posts in their feed, those who had never used e-cigarettes were more likely to endorse two or more positive perceptions compared to those who had ever used e-cigarettes (ie, 563, 19.7% vs 350, 15.0%), and those who had last used e-cigarettes more than 30 days ago (ie, 159, 16.9% vs 191, 13.7%) were more likely to endorse two or more positive perceptions compared to those who had used them in the past 30 days (all Ps<.001). Participants who had never used e-cigarettes were also less likely to trust pop-ups, compared to those who had ever used them, whether while searching for e-cigarette-related information on social media or while seeing e-cigarette-related posts in their feed (approximately, 19%vs 24%). There were no significant differences in the endorsement of negative or neutral sentiments. However, participants aged 13-18 years were more likely to ignore such notifications while viewing e-cigarette-related posts in their social media feed compared to those aged 19-24 years (ie, 850, 28.9% vs 563 25%); further, participants who had never used e-cigarettes were less trusting of e-cigarette-related information while searching for vaping or in their feed.

CONCLUSIONS: Positive perception of a social media pop-up indicates its potential to prevent e-cigarette-related misinformation. Further development of a pop-up requires strategies to better engage and inform adolescents and young adults, specifically younger individuals, as they may be more likely to disregard pop-ups, and older individuals and those who used e-cigarettes in the past 30 days, as they are potentially more dismissive of such information.

PMID:40829154 | DOI:10.2196/73193

JMIR Form Res. 2025 Aug 19;9:e70863. doi: 10.2196/70863.

ABSTRACT

BACKGROUND: Thyroid nodules are common, with ultrasound imaging as the primary modality for their assessment. Risk stratification systems like the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) have been developed but suffer from interobserver variability and low specificity. Artificial intelligence, particularly large language models (LLMs) with multimodal capabilities, presents opportunities for efficient end-to-end diagnostic processes. However, their clinical utility remains uncertain.

OBJECTIVE: This study evaluates the accuracy and consistency of multimodal LLMs for thyroid nodule risk stratification using the ACR TI-RADS system, examining the effects of model fine-tuning, image annotation, prompt engineering, and comparing open-source versus commercial models.

METHODS: In total, 3 multimodal vision-language models were evaluated: Microsoft’s open-source Large Language and Visual Assistant (LLaVA) model, its medically fine-tuned variant (Large Language and Vision Assistant for bioMedicine [LLaVA-Med]), and OpenAI’s commercial o3 model. A total of 192 thyroid nodules from publicly available ultrasound image datasets were assessed. Each model was evaluated using 2 prompts (basic and modified) and 2 image scenarios (unlabeled vs radiologist-annotated), yielding 6912 responses. Model outputs were compared with expert ratings for accuracy and consistency. Statistical comparisons included Chi-square tests, Mann-Whitney U tests, and Fleiss’ kappa for interrater reliability.

RESULTS: Overall, 88.4% (6110/6912) of responses were valid, with the o3 model producing the highest validity rate (2273/2304, 98.6%), followed by LLaVA (2108/2304, 91.5%) and LLaVA-Med (1729/2304, 75%; P<.001). The o3 model demonstrated the highest accuracy overall, achieving up to 57.3% accuracy in Thyroid Imaging Reporting and Data System (TI-RADS) classification, although still remaining suboptimal. Labeled images improved accuracy marginally in nodule margin assessment only when evaluating LLaVA models (407/768, 53% to 447/768, 58.2%; P=.04). Prompt engineering improved accuracy for composition (649/1,152, 56.3% vs 483/1152, 41.9%; P<.001), but significantly reduced accuracy for shape, margins, and overall classification. Consistency was the highest with the o3 model (up to 85.4%), but was comparable for LLaVA and significantly improved with image labeling and modified prompts across multiple TI-RADS categories (P<.001). Subgroup analysis for o3 alone showed prompt engineering did not affect accuracy significantly but markedly improved consistency across all TI-RADS categories (up to 97.1% for shape, P<.001). Interrater reliability was consistently poor across all combinations (Fleiss’ kappa<0.60).

CONCLUSIONS: The study demonstrates the comparative advantages and limitations of multimodal LLMs for thyroid nodule risk stratification. While the commercial model (o3) consistently outperformed open-source models in accuracy and consistency, even the best-performing model outputs remained suboptimal for direct clinical deployment. Prompt engineering significantly enhanced output consistency, particularly in the commercial model. These findings underline the importance of strategic model optimization techniques and highlight areas requiring further development before multimodal LLMs can be reliably used in clinical thyroid imaging workflows.

PMID:40829145 | DOI:10.2196/70863

J Med Internet Res. 2025 Aug 19;27:e69031. doi: 10.2196/69031.

ABSTRACT

BACKGROUND: University students frequently face mental health challenges due to academic pressures, lifestyle changes, and developmental factors. Digital interventions, such as Doing What Matters in Times of Stress (DWM), a psychosocial e-mental health intervention developed by the World Health Organization (WHO), offer scalable approaches to address these issues. These data emerging from the literature provide the framework for the CAMPUS (Characterize and Address Mental health Problems in University Students) study aimed at supporting the mental health of students attending the University of Verona.

OBJECTIVE: This study aimed to assess the effectiveness and implementability of DWM as a psychological strategy for effective mental health prevention and promotion, as well as for reducing psychological symptoms and distress and improving well-being in university students.

METHODS: During the study period (October 2023-June 2024), we conducted a prospective hybrid type-1 nonrandomized follow-up study, with a pretest-posttest design. The study population consisted of students attending the University of Verona, who were recruited through university communication channels and participated via web-based platforms. Data were collected at baseline (T1) and after the intervention (T2) using an ad hoc sociodemographic information page and self-reported tools assessing psychological distress with the Kessler-10 (K-10), depressive symptoms with the Patient Health Questionnaire-9 (PHQ-9) depression scale, anxiety symptoms with the Generalized Anxiety Disorder-7 (GAD-7) scale, and psychological well-being with the WHO-5 Well-Being Index (WHO-5). In addition, at postintervention, the implementability was assessed. Statistical analyses included Wilcoxon matched pairs signed rank tests and logistic regression models to identify associated factors.

RESULTS: Out of 2296 interested students, 1498 (65.24%) completed all DWM sessions and assessments. At T1, students exhibited mild psychological distress, anxiety, and depressive symptoms with moderate well-being. Significant improvements were observed postintervention: the K-10 scores decreased from 22.41 (SD 6.54) to 19.86 (SD 5.96), the GAD-7 scale scores decreased from 8.27 (SD 4.31) to 6.57 (SD 3.76), and the PHQ-9 scores decreased from 8.28 (SD 7.73) to 6.75 (SD 4.37; all P<.001). The WHO-5 well-being scores increased from 11.73 (SD 4.65) to 13.26 (SD 4.68; P<.001). Satisfaction was high, with 90.72% (1359/1498) of participants agreeing or strongly agreeing on satisfaction, 77.37% (1159/1498) agreeing or strongly agreeing on appropriateness, and 94.99% (1423/1498) finding the program easy to use. No significant differences in clinical outcomes were associated with sociodemographic or baseline mental health variables.

CONCLUSIONS: The DWM intervention demonstrated positive effects on students’ mental health, showing reductions in distress, anxiety, and depressive symptoms, alongside improved well-being. The program’s high levels of acceptability, appropriateness, and feasibility highlight its potential for broader application as a digital mental health strategy for university students.

PMID:40829124 | DOI:10.2196/69031

JMIR Form Res. 2025 Aug 19;9:e73078. doi: 10.2196/73078.

ABSTRACT

BACKGROUND: Disaster telehealth can be used to provide rapid access to remote specialty expertise and virtual surge capacity for overwhelmed local clinicians. The Regional Disaster Health Response System (RDHRS) is developing a disaster teleconsultation system for cross-jurisdictional care in the United States. In 2020, the Region 1 RDHRS provided Massachusetts hospitals access to disaster teleconsultation services with out-of-state critical care experts during the first wave of the COVID-19 pandemic response.

OBJECTIVE: We aimed to field-test (1) the acceptability and feasibility of using a prototype, web-based disaster teleconsultation platform with minimal-to-no user training and (2) the feasibility of deploying a national volunteer expert pool to access out-of-state expertise.

METHODS: This was a prospective, mixed methods, observational study. We recruited field clinicians from Massachusetts hospitals and out-of-state critical-care physicians as experts for a 2-week pilot (June 2020). Experts were trained to use a prototype platform, while field clinicians received a just-in-time tool. Field clinicians requested teleconsultations for hospitalized patients with COVID-19 (clinical call) or simulated patients (test call). We collected demographics, call performance data, and Telehealth Usability Questionnaire (TUQ) ratings to measure acceptability (primary outcome; total usability score ≥6 of 7) and feasibility (secondary outcome; interface, interaction quality, and reliability items), and interviewed participants. We report descriptive statistics and key themes using the Technology Acceptance Model framework.

RESULTS: Ten experts from 6 states and 17 field clinicians from 4 hospitals participated. All experts and 10 field clinicians completed postpilot questionnaires (74% response overall). Of these, 20% had previously used telemedicine in a disaster. In total, 50 test calls and no clinical calls were logged. Most (70%) made ≥1 call; 22% (95% CI 10%-34%) connected successfully. The median time to connect was 1.6 (IQR 3.2) minutes. Among field clinician respondents, 50% used smartphone devices, 40% hospital desktop computers, and 10% laptop computers to access RDHRS teleconsultation services. Calls failed due to platform routing errors (49%), hospital computers without cameras or microphones (10%), firewalls (8%), and expert notification failures (5%). The mean total usability score was 5.6 (SD 1.3). TUQ item scores were highest in usefulness (mean 6.0, SD 1.1) and ease-of-use (mean 6.0, SD 1.4), and lowest in reliability (mean 2.4, SD 1.4). Participants were comfortable using the platform. Those with difficulty identified discomfort with technology as the cause. All experts were willing to participate in a national expert registry and obtain emergency licensure, and most (80%) were willing to serve on a volunteer, unpaid basis.

CONCLUSIONS: Clinicians found the prototype platform acceptable, but the workflow requires revision to reduce call failure and improve feasibility and reliability for future use with minimal-to-no training. Using familiar clinical workflows for emergency consultation and mobile devices with camera and microphone capabilities could improve call performance and reliability.

PMID:40829123 | DOI:10.2196/73078

Neurology. 2025 Sep 9;105(5):e213996. doi: 10.1212/WNL.0000000000213996. Epub 2025 Aug 19.

ABSTRACT

BACKGROUND AND OBJECTIVES: While preclinical studies documented potential neuroprotective effects of estrogen/progesterone, the impact of biological sex on outcomes after traumatic spinal cord injury (tSCI) remains incompletely understood. The aim of this study was to compare male and female age-stratified subgroups, which presumably correspond to premenopausal, perimenopausal, and postmenopausal states, concerning access to optimal care and their outcomes after tSCI.

METHODS: A series of propensity score-matched cohort studies was performed, comparing female individuals with male individuals in the younger (age≤ 40 years), middle-aged (41-50 years), and older (>50 years) subgroups regarding baseline data; management strategies; access to optimal care; and hospital, neurologic, and functional outcomes after tSCI. Data were selected from 5,571 individuals with tSCI at C1-L2 who were enrolled in the Rick Hansen Spinal Cord Injury Registry from July 2004 to September 2019. Outcome measures included in-hospital mortality and motor and sensory score changes from admission to an acute care hospital to discharge from a rehabilitation center.

RESULTS: In the younger subgroups, female individuals (n = 320, mean age: 26 years) were more often White and had a greater proportion of tSCIs due to falls or transportation-related accidents than male individuals (n = 320, mean age: 26.5 years). Younger female and male subgroups had similar in-hospital mortality rates (0.6% vs 0.6%, p = 1) and motor (4 vs 5, p = 0.8919) and sensory (2 vs 5, p = 0.5) score changes after tSCI. In the middle-aged subgroups, female individuals (n = 133, mean age: 46 years) and male individuals (n = 113, mean age: 46 years) had statistically comparable baseline data, in-hospital mortality rates (2.3% vs 3.0%, p = 1), and motor (12 vs 5, p = 0.8766) and sensory (0 vs 2, p = 0.4918) score changes. In the older subgroups, female individuals (n = 531, mean age: 68 years) showed a higher frequency of fall-related tSCI but they had similar in-hospital mortality rates (7.7% vs 9.8%, p = 0.2324) and motor (9 vs 8, p = 0.7594) and sensory (5 vs 0, p = 0.7204) score changes after tSCI compared with male individuals (n = 531, mean age: 68 years).

DISCUSSION: The results of this study suggest that biological sex does not significantly affect in-hospital mortality and neurologic recovery after tSCI when optimal care is applied, according to data from a Canadian registry. Those findings support the notion that sex equity in management strategies promotes equal outcomes after tSCI.

PMID:40829102 | DOI:10.1212/WNL.0000000000213996