Tag: pubmed

Sci Total Environ. 2025 Nov 19;1008:180964. doi: 10.1016/j.scitotenv.2025.180964. Online ahead of print.

ABSTRACT

Phytomining is a sustainable mineral extraction method that employs metal-tolerant hyperaccumulator plant species to recover metals from surface soils. Our preliminary study explored the survivability and effectiveness of rare earth element (REE) hyperaccumulators of 45 species when grown in naturally occurring REE-rich soil sourced from Idaho, finding that Idaho native grass Pseudoroegneria spicata is an effective REE hyperaccumulator. This study then evaluated the REE hyperaccumulation ability of P. spicata and Phalaris arundinacea, assessing the performance of seven varieties within each species. Plants were grown in a greenhouse and harvested biomass was ashed or pyrolyzed, acid digested, and characterized by elemental analysis. Results showed that P. spicata and P. arundinacea accumulated an average of 26,044 and 27,761 μg/g total mixed REEs in their shoot tissues, respectively. Species and variety were found to mostly have a significant effect on dry biomass yield while tissue type (root vs. shoot) significantly impacted internal plant REE concentration, with roots accumulating more than shoots. This study concludes that using these hyperaccumulating grass species, especially P. spicata, for Idaho-based phytomining has promise and should be further studied and developed.

PMID:41264944 | DOI:10.1016/j.scitotenv.2025.180964

Cancer Control. 2025 Jan-Dec;32:10732748251399963. doi: 10.1177/10732748251399963. Epub 2025 Nov 20.

ABSTRACT

IntroductionDiscrimination exacerbates disparities among breast cancer survivors (BCS), yet how different reasons for experiencing perceived discrimination (e.g., race, age) influence health remains understudied. We explored the association between self-reported discrimination, psychosocial health, and quality of life (QOL), identified clusters based on reasons for perceived discrimination, and examined differences in QOL and psychosocial outcomes between these clusters.MethodsIn this cross-sectional study, we examined correlations between reasons for perceived discrimination (Everyday Discrimination Scale; EDS), QOL domains (cognitive, physical, social, emotional, and functional QOL measured with FACT-G), social dysfunction (Social Difficulties Inventory), and a psychological distress composite score (included measures of stress [Perceived Stress Scale], anxiety [PROMIS Anxiety], and depression [PROMIS Depression]), among 174 breast cancer survivors (stage 0-IV; ≥21 years). We used k-modes clustering to identify discrimination groups. Differences in demographics, clinical characteristics, and outcomes across clusters were assessed using Chi-square, analysis of variance, covariance, or non-parametric tests, followed by post hoc analyses.ResultsOverall, experiences of discrimination were associated with poorer QOL and psychosocial health (|0.306|<r<|0.452|, P < 0.001). Six distinct clusters emerged based on reasons for perceived discrimination from the EDS. Compared to Cluster 4 (no discrimination), participants in Cluster 1 (discrimination due to gender, age, and physical characteristics) had lower cognitive and physical QOL (4.3 < mean difference [MD]< 5.0, P < 0.001). Participants in Cluster 3 (discrimination due to physical characteristics) had poorer functional QOL, greater social disfunction, and higher psychological distress composite scores (0.3<MD <9.4, P < 0.001) than Cluster 4. Differences between Clusters 2 (discrimination due to gender) and 5 (discrimination due to gender, race/ethnicity) with all other Clusters were not statistically significant (P > 0.05).ConclusionQOL and psychosocial health scores varied between clusters based on reasons for perceived discrimination. Future interventions to improve QOL for breast cancer survivors should consider addressing stigma related to gender, physical appearance, and other forms of discrimination.

PMID:41264928 | DOI:10.1177/10732748251399963

J Am Acad Orthop Surg. 2025 Nov 18. doi: 10.5435/JAAOS-D-25-00022. Online ahead of print.

ABSTRACT

INTRODUCTION: A recent survey found that 68% of women reported experiencing sexual harassment (SH) during their orthopaedic training. This study aims to (1) characterize Title IX understanding; (2) describe SH occurrences, subtypes, and reporting rates; (3) evaluate the impact of Title IX understanding on SH reporting; and (4) compare these findings by level of training.

METHODS: An anonymous survey was distributed between June 1, 2023, and July 31, 2023, to Ruth Jackson Orthopaedic Society members. Surgeon demographics, SH experiences through the Racialized Sexual Harassment Scale, and Title IX understanding were assessed. Descriptive and comparative statistics analyzed SH occurrences and reporting. Pearson correlation and Fisher exact tests assessed relationships between Title IX knowledge and SH reporting.

RESULTS: Twenty percent (178 of 891) of Ruth Jackson Orthopaedic Society members completed the survey. Fifty-one percent (91/178) of orthopaedic surgeons endorsed experiencing SH during their careers, of whom 35% reported. The most common form of SH was “nonphysical” (34.1%). Formal reporting rates varied by SH type, with “watching” (67.0%) and “fear” (39.0%) being the most reported. The median score on the Title IX survey was 81.8%, with 47% knowing the reporting timeframe and 53% knowing who to report to. No significant associations were found between SH incident reporting rate and Title IX understanding (rho = 0.03, P = 0.9). Attending surgeons had significantly higher Racialized Sexual Harassment Scale scores (25.8 vs. 21.1, P = 0.004) and reported more occurrences (1.1 vs. 0.3, P < 0.001) compared with orthopaedic trainees.

DISCUSSION: Although most orthopaedic surgeons reported experiencing SH and understood Title IX policies, SH reporting rates remained low. Improved understanding of policy is important but may not lead to greater reporting of SH based on this study, suggesting other barriers to reporting.

PMID:41264921 | DOI:10.5435/JAAOS-D-25-00022

JMIR Med Educ. 2025 Nov 20;11:e80576. doi: 10.2196/80576.

ABSTRACT

BACKGROUND: Digital tools are increasingly used to support clinical decision-making in dental education. However, the accuracy and efficiency of different support tools, including generative artificial intelligence, in the context of dental trauma management remain underexplored.

OBJECTIVE: This study aimed to evaluate the accuracy of various information sources (chatbot, textbook, mobile app, and no support tool) in conveying clinically relevant educational content related to decision-making in the primary care of traumatically injured teeth. Additionally, the effect of the input strategy on the chatbot’s output response was evaluated.

METHODS: Fifty-nine dental students with limited prior experience in dental trauma were randomly assigned to one of 4 groups: chatbot (based on generative pretrained transformer [GPT]-4o, n=15), digital textbook (n=15), mobile app (AcciDent app 3.5, n=15), and control group (no support tool, n=14). Participants answered 25 dichotomous questions in a digital examination format using the information source allocated to their group. The primary outcome measures were the percentage of correct responses and the time required to complete the examination. Additionally, for the group using ChatGPT-4o, the quality of prompts and the clarity of chatbot responses were independently evaluated by 2 calibrated examiners using a 5-point Likert scale. Statistical analyses included nonparametric analyses using Kruskal-Wallis tests and mixed-effects regression analyses with an α level of .05.

RESULTS: All support tools led to a significantly higher accuracy compared with the control group (P<.05), with mean accuracies of 87.47% (SD 5.63%), 86.40% (SD 5.19%), and 86.40% (SD 6.38%) for the textbook, the AcciDent app, and ChatGPT-4o, respectively. The groups using the chatbot and the mobile app required significantly less time than the textbook group (P<.05). Within the ChatGPT-4o group, higher prompt quality was associated with greater clarity of the chatbot’s responses (odds ratio 1.44, 95% CI 1.13-1.83, P<.05), which in turn increased the likelihood of students selecting the correct answers (odds ratio 1.89, 95% CI 1.26-2.80, P<.05).

CONCLUSIONS: ChatGPT-4o and the AcciDent app can serve dental students as an accurate and time-efficient support tool in dental trauma care. However, the performance of ChatGPT-4o varies with the precision of the input prompt, underscoring the necessity for users to critically evaluate artificial intelligence-generated responses.

TRIAL REGISTRATION: OSF Registries 10.17605/OSF.IO/XW62J; https://osf.io/xw62j/overview.

PMID:41264912 | DOI:10.2196/80576

Psychol Rep. 2025 Nov 20:332941251399176. doi: 10.1177/00332941251399176. Online ahead of print.

ABSTRACT

A recent trial in older adults with anxiety symptoms in primary care found no differences in outcome between an ACT and CBT intervention. The current study aimed to identify moderators and non-specific predictors of treatment response to these two interventions. The sample consisted of 314 older adults who were randomized to either ACT or CBT. Anxiety symptom severity (measured with the GAD-7) was the main outcome variable. Demographics, (psycho)pathology, social support, and psychological processes were examined as predictors. No moderator variables were identified. More severe anxiety and depression symptoms at baseline predicted a worse short- and long-term response to ACT and CBT, while higher levels of mastery predicted a better short-term treatment response in both conditions. When interpreting these results, the lack of sufficient statistical power to detect multiple modest interaction effects should be taken into account. Based on the results of the present study, it is not possible to allocate patients to the intervention that is likely to be most effective for them. The prognostic effects of anxiety and depression symptom severity and mastery may hold implications regarding treatment enhancement strategies in general. The study was registered in the Netherlands Trial Register (NL6131; NTR6270).

PMID:41264911 | DOI:10.1177/00332941251399176

Hepatol Commun. 2025 Nov 20;9(12):e0857. doi: 10.1097/HC9.0000000000000857. eCollection 2025 Dec 1.

ABSTRACT

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common pediatric liver disease, yet known biological risk factors do not fully explain its development. This study evaluated the association between social determinants of health (SDH)-including income, education, housing, and environmental factors-and MASLD in children with overweight or obesity.

METHODS: This cross-sectional study included children with overweight or obesity evaluated in pediatric gastroenterology clinics, stratified by the presence of MASLD. Participants’ residential census tracts were linked to the California Healthy Places Index (HPI), where higher scores indicate greater socioeconomic advantage. Generalized linear regression models, adjusted for age, sex, race, ethnicity, and body mass index (BMI), assessed associations between SDH and MASLD.

RESULTS: The study included 888 children (mean age: 12.8±2.9 y, mean BMI: 30.6±6.4 kg/m2). Children with MASLD lived in neighborhoods with significantly lower HPI scores than those without MASLD (-0.22 vs. -0.03; 41st vs. 49th percentile, p=0.01). They also resided in areas with significantly lower socioeconomic advantage across multiple HPI subdomains, including housing (-0.16 vs. 0.03; 44th vs. 51st percentile, p<0.001) and economic (-0.38 vs. -0.12; 36th vs. 55th percentile, p<0.001) scores.

CONCLUSIONS: Children with MASLD were more likely to live in neighborhoods with greater socioeconomic and environmental disadvantage than their peers with overweight or obesity but without MASLD. These findings highlight potential SDH targets for public health interventions aimed at reducing MASLD risk in children.

PMID:41264907 | DOI:10.1097/HC9.0000000000000857

J Craniofac Surg. 2025 Nov 20. doi: 10.1097/SCS.0000000000012190. Online ahead of print.

ABSTRACT

This study aims to compare the clinical outcomes of bioresorbable and titanium fixation systems used in anterior maxillary segmental osteotomy (AMSO) procedures, with a focus on skeletal stability, postoperative complications, and hardware-related morbidity. A prospective, randomized clinical trial was conducted on 50 patients undergoing AMSO. Participants were randomly assigned to 2 groups: bioresorbable fixation using poly-L-lactic acid/polyglycolic acid (PLLA/PGA) (n=15) and conventional titanium miniplates (n=35). Standardized panoramic and cephalometric radiographs were taken preoperatively and at 1 and 12 months postoperatively. Primary outcome measures included skeletal stability assessed by horizontal and vertical movement of the anterior maxillary segment. Secondary outcomes included postoperative infection, wound dehiscence, plate palpability, radiographic verification of correct segmental positioning, and the need for hardware removal. At 1 and 12 months, cephalometric radiographs in both groups demonstrated comparable skeletal stability, with no statistically significant differences in relapse rates. The incidence of infection and wound dehiscence was similar across groups. However, the titanium group had a significantly higher rate of hardware removal requests (8.6% vs. 0%, P < 0.05). No major adverse events were reported in either group. Bioresorbable fixation systems provide comparable skeletal stability to titanium plates in AMSO, while eliminating the need for secondary hardware removal. These findings support the selective use of bioresorbable fixation, particularly in patients for whom hardware removal is undesirable.

PMID:41264905 | DOI:10.1097/SCS.0000000000012190

JCO Precis Oncol. 2025 Nov;9:e2500560. doi: 10.1200/PO-25-00560. Epub 2025 Nov 20.

ABSTRACT

In clinical trials, the initial step typically involves assessing a new drug’s toxicity profile, aiming to identify a tolerable dose level for subsequent studies. In phase I trials, the primary objective is to determine the maximum tolerated dose, defined as the highest dose associated with an acceptable level of toxicity. Numerous methods have been developed to guide dose escalation and de-escalation decisions during trial conduct. Among these approaches, the calibration-free odds (CFO) design has demonstrated superior operating characteristics and has emerged as one of the most effective approaches for dose finding. To facilitate the application of the CFO design in clinical trial practice, an R package and a Shiny app have been released. This study presents CFO decision tables in Excel files to further remove the barrier of applying the CFO design to real trials. Anyone involved in the trial conduct can implement the CFO design with no difficulties. During the trial, dose movement decisions can be made simply by referring to the cumulative data (including numbers of patients treated and observed toxicities) and the pregenerated decision tables, without any additional statistical calculation. This approach significantly enhances the usability of the CFO design and reduces the operational complexity associated with its implementation in clinical trials. The Excel CFO decision tables can be downloaded from CFO Shiny App.

PMID:41264898 | DOI:10.1200/PO-25-00560

JMIR Med Inform. 2025 Nov 20;13:e66764. doi: 10.2196/66764.

ABSTRACT

BACKGROUND: In Switzerland, sexual assault reports have historically been documented on paper, which limited standardization, completeness, and challenges to produce reliable statistics.

OBJECTIVE: This study describes the development and implementation of an Electronic Sexual Assault Record (eSAR) within Geneva University Hospitals’ Electronic Medical Record (EMR) system, with the aim of improving data quality, documentation, and multidisciplinary coordination.

METHODS: The eSAR was developed by a multidisciplinary team including forensic doctors, gynecologists, nurses (clinical and informatics), epidemiologists, and IT specialists. Its structure was based on existing hospital protocols and international recommendations. Variables were defined as “essential” or “highly recommended,” with structured fields to ensure completeness and comparability. Confidentiality was safeguarded through restricted access and regular audits.

RESULTS: The eSAR was launched in June 2022 and revised in 2023 after user feedback and training. Since implementation, 382 reports have been completed. Data quality improved substantially, with major reductions in missing information. The system also streamlined workflows and strengthened collaboration across specialties.

CONCLUSIONS: The eSAR improved documentation and data reliability, providing a replicable model for standardized sexual assault reporting in Switzerland.

PMID:41264873 | DOI:10.2196/66764

JMIR Form Res. 2025 Nov 20;9:e76618. doi: 10.2196/76618.

ABSTRACT

BACKGROUND: The integration of artificial intelligence (AI) in medical education is evolving, offering new tools to enhance teaching and assessment. Among these, script concordance tests (SCTs) are well-suited to evaluate clinical reasoning in contexts of uncertainty. Traditionally, SCTs require expert panels for scoring and feedback, which can be resource-intensive. Recent advances in generative AI, particularly large language models (LLMs), suggest the possibility of replacing human experts with simulated ones, though this potential remains underexplored.

OBJECTIVE: This study aimed to evaluate whether LLMs can effectively simulate expert judgment in SCTs by using generative AI to author, score, and provide feedback for SCTs in cardiology and pneumology. A secondary objective was to assess students’ perceptions of the test’s difficulty and the pedagogical value of AI-generated feedback.

METHODS: A cross-sectional, mixed methods study was conducted with 25 second-year medical students who completed a 32-item SCT authored by ChatGPT-4o (OpenAI). Six LLMs (3 trained on the course material and 3 untrained) served as simulated experts to generate scoring keys and feedback. Students answered SCT questions, rated perceived difficulty, and selected the most helpful feedback explanation for each item. Quantitative analysis included scoring, difficulty ratings, and correlations between student and AI responses. Qualitative comments were thematically analyzed.

RESULTS: The average student score was 22.8 out of 32 (SD 1.6), with scores ranging from 19.75 to 26.75. Trained AI systems showed significantly higher concordance with student responses (ρ=0.64) than untrained models (ρ=0.41). AI-generated feedback was rated as most helpful in 62.5% of cases, especially when provided by trained models. The SCT demonstrated good internal consistency (Cronbach α=0.76), and students reported moderate perceived difficulty (mean 3.7, SD 1.1). Qualitative feedback highlighted appreciation for SCTs as reflective tools, while recommending clearer guidance on Likert-scale use and more contextual detail in vignettes.

CONCLUSIONS: This is among the first studies to demonstrate that trained generative AI models can reliably simulate expert clinical reasoning within a script-concordance framework. The findings suggest that AI can both streamline SCT design and offer educationally valuable feedback without compromising authenticity. Future studies should explore longitudinal effects on learning and assess how hybrid models (human and AI) can optimize reasoning instruction in medical education.

PMID:41264864 | DOI:10.2196/76618