Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2.

BACKGROUND: Large language models (LLMs) have garnered significant attention in the AI domain owing to their exemplary context recognition and response capabilities. However, the potential of LLMs in specific clinical scenarios, particularly in breast cancer diagnosis, treatment, and care, has not been fully explored. This study aimed to compare the performances of three major LLMs in the clinical context of breast cancer. METHODS: In this study, clinical scenarios designed specifically for breast cancer were segmented into five pivotal domains (nine cases): assessment and diagnosis, treatment decision-making, postoperative care, psychosocial support, and prognosis and rehabilitation. The LLMs were used to generate feedback for various queries related to these domains. For each scenario, a panel of five breast cancer specialists, each with over a decade of experience, evaluated the feedback from LLMs. They assessed feedback concerning LLMs in terms of their quality, relevance, and applicability. RESULTS: There was a moderate level of agreement among the raters (Fleiss' kappa=0.345, P<0.05). Comparing the performance of different models regarding response length, GPT-4.0 and GPT-3.5 provided relatively longer feedback than Claude2. Furthermore, across the nine case analyses, GPT-4.0 significantly outperformed the other two models in average quality, relevance, and applicability. Within the five clinical areas, GPT-4.0 markedly surpassed GPT-3.5 in the quality of the other four areas and scored higher than Claude2 in tasks related to psychosocial support and treatment decision-making. CONCLUSION: This study revealed that in the realm of clinical applications for breast cancer, GPT-4.0 showcases not only superiority in terms of quality and relevance but also demonstrates exceptional capability in applicability, especially when compared to GPT-3.5. Relative to Claude2, GPT-4.0 holds advantages in specific domains. With the expanding use of LLMs in the clinical field, ongoing optimization and rigorous accuracy assessments are paramount.

Does enhanced cognitive performance reduce fracture risk? a Mendelian randomization study.

OBJECTIVE: While observational studies have suggested a link between cognitive performance and fracture risk, the causality and site-specific nature are unclear. We applied Mendelian randomization (MR) to elucidate these associations. METHODS: 147 single-nucleotide polymorphisms (SNPs) tied strongly to cognitive performance (p< 5e-8) were selected. We performed MR analysis to investigate the causal relationship between cognitive performance and fractures at specific sites, including the wrist, upper arm, shoulder, ribs, sternum, thoracic spine, lumbar spine, pelvis, femur, leg, and ankle. The primary estimate was determined using the inverse variance-weighted method. Additionally, we examined heterogeneity using the MR Pleiotropy RESidual Sum Outlier test and Cochran Q, and employed MR-Egger regression to identify horizontal pleiotropy. RESULTS: MR analysis identified a causal association between cognitive performance and fractures at the lumbar-spine-pelvis (odds ratio [OR] = 0.727, 95% CI = 0.552-0.956, p = 0.023), and ribs-sternum-thoracic spine sites (OR = 0.774, 95% CI = 0.615-0.974, p = 0.029). However, no causal association was found for fractures at other sites. CONCLUSIONS: This study provided evidence of a causal connection between cognitive performance and fracture risk at certain locations. These findings underline the potential of cognitive enhancement strategies as innovative and effective methods for fracture prevention.

Causal Link between Gut Microbiota, Neurophysiological States, and Bone Diseases: A Comprehensive Mendelian Randomization Study.

Increasing evidence highlights a robust correlation between the gut microbiota and bone diseases; however, the existence of a causal relationship between them remains unclear. In this study, we thoroughly examined the correlation between gut microbiota and skeletal diseases using genome-wide association studies. Linkage disequilibrium score regression and Mendelian randomization were used to probe genetic causality. Furthermore, the potential mediating role of neuropsychological states (i.e., cognition, depression, and insomnia) between the gut microbiota and bone diseases was evaluated using mediation analysis, with genetic colocalization analysis revealing potential targets. These findings suggest a direct causal relationship between Ruminococcaceae and knee osteoarthritis (OA), which appears to be mediated by cognitive performance and insomnia. Similarly, a causal association was observed between Burkholderiales and lumbar pelvic fractures, mediated by cognitive performance. Colocalization analysis identified a shared causal variant (rs2352974) at the TRAF-interacting protein locus for cognitive ability and knee OA. This study provides compelling evidence that alterations in the gut microbiota can enhance cognitive ability, ameliorate insomnia, and potentially reduce the risk of site-specific fractures and OA. Therefore, strategies targeting gut microbiota optimization could serve as novel and effective preventive measures against fractures and OA.

Intertemporal decision-making as a mediator between personality traits and self-management in type 2 diabetes: a cross-sectional study.

Objectives: The aims to investigate the mediating effect of intertemporal decision-making on the association between personality traits and self-management among individuals with in Type 2 Diabetes (T2DM). Method: Patients with T2DM in the early stages of hospitalization at two tertiary hospitals in Shenyang and Jinzhou, Liaoning Province, May 2022 to January 2023. Questionnaires, including General Demographic, Self-Management, Big Five Personality, and Intertemporal Decision-Making, were administered. Pearson correlation analysis examined relationships between personality traits, intertemporal decision-making, and self-management. Hierarchical regression analysis identified self-management predictors. Mediation analysis used the PROCESS SPSS Macro version 3.3 model 4 to investigate intertemporal decision-making as mediator between personality traits and self-management. Results: Pearson correlation analysis revealed significant associations between self-management scores, personality traits, and intertemporal decision-making. Hierarchical regression revealed that Neuroticism and Conscientiousness accounted for 20.8% of the variance in self-management, while intertemporal decision-making explained 4.5% of the variance. Finally, using the Bootstrap method, the mediation analysis showed that intertemporal decision-making partially mediated the effect of personality traits on self-management. Conclusion: This study emphasizes the importance of intertemporal decision-making in improving self-management behaviors among patients with T2DM. Interventions targeted at modifying intertemporal decision-making preferences could be effective in enhancing self-management behaviors, leading to better health outcomes.

The chloroplast GATA-motif of Mahonia bealei participates in alkaloid-mediated photosystem inhibition during dark to light transition.

Mahonia bealei and Mahonia fortunei are important plant resources in Traditional Chinese Medicine that are valued for their high levels of benzylisoquinoline alkaloids (BIAs). Although the phytotoxic activity of BIAs has been recognized, information is limited on the mechanism of action by which these compounds regulate photosynthetic activity. Here, we performed comparative chloroplast genome analysis to examine insertions and deletions in the two species. We found a GATA-motif located in the promoter region of the ndhF gene of only M. bealei. K-mer frequency-based diversity analysis illustrated the close correlation between the GATA-motif and leaf phenotype. We found that the GATA-motif significantly inhibits GUS gene expression in tobacco during the dark-light transition (DLT). The expression of ndhF was downregulated in M. bealei and upregulated in M. fortunei during the DLT. NDH-F activity was remarkably decreased and exhibited a significant negative correlation with BIA levels in M. bealei during the DLT. Furthermore, the NADPH produced through photosynthetic metabolism was found to decrease in M. bealei during the DLT. Taken together, our results indicate that this GATA-motif might act as the functional site by which BIAs inhibit photosynthetic metabolism through downregulating ndhF expression during the DLT.

Identification of Immune-Related Hub Genes in Thymoma: Defects in CD247 and Characteristics of Paraneoplastic Syndrome.

Background: Thymomas (Ts) and thymic carcinomas (TCs) are rare primary tumors of the mediastinum. Paraneoplastic syndrome (PNS) is an important feature of thymoma, which presents great challenges to clinicians. Methods: The present study uses the weighted gene co-expression network analysis (WGCNA) to identify possible immunologic mechanisms of thymoma. RNA sequencing data from thymoma samples were downloaded from the TCGA. Core genes were taken from the module that is closely related to the WHO's stage of classification. Enhanced analysis using the online database "Metascape" and an overall survival (OS) analysis were carried out via the Kaplan-Meier method. The hub genes were obtained from the protein-protein interaction (PPI) network. In addition, we jointly analyzed multiple sets of PNS data related to thymomas from other sources to verify the correlation between thymomas and PNS. The impact of hub genes on the prognosis of PNS was evaluated via the ROC curve, with simultaneous analysis of immune infiltration by CIBERSORT. Findings: The 14 immune hub genes closely related to thymomas were found to be jointly involved in the T-cell receptor signaling pathway. Compared to the normal thymus and type B1/B2 thymoma, there is a lower number of T-cells in type A/B3 thymoma and thymic carcinoma. The expression of genes related to the T-cell receptor signaling pathway appeared defective. The low expression of CD247 and the decrease in the number of mature T-cells are common features among thymomas, specific pulmonary fibrosis, rheumatoid arthritis, and systemic lupus erythematosus.

Development and validation of an LC-MS/MS method for simultaneous quantification of levodopa and MD01 in rat plasma and its application to a pharmacokinetic study of mucuna pruriens extract.

Mucuna pruriens, an ancient Indian herbal medicine containing levodopa, is widely used for Parkinson's disease. In order to simultaneously determine levodopa and 1,1-dimethyl-3-carboxy-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline (MD01) in rat plasma, an improved LC-MS/MS method was developed and validated for a pharmacokinetic study in rats orally administered levodopa or Mucuna pruriens extract (MPE). Elimination of matrix effect and improvement of extraction recovery were achieved through systematic optimization of reversed-phase and hydrophilic interaction chromatographic conditions together with sample clean-up procedures. A satisfactory chromatographic performance was obtained with a Thermo Aquasil C18 column (50 × 2.1 mm, 3 µm) using acetonitrile and water containing 0.2% formic acid as mobile phases. Futhermore, sodium metabisulfite and formic acid were used as stabilizers in neat solutions as well as rat plasma. The method was validated in a dynamic range of 20.0-10,000 ng/mL for levodopa and MD01; the intra- and inter-day precision and accuracy were acceptable. The method was successfully utilized to determine the levodopa level in plasma samples of rats administered levodopa or MPE. Pharmacokinetic results showed that an increase in the AUC of levodopa was observed in rats following oral administration of multiple doses of MPE. Copyright © 2016 John Wiley & Sons, Ltd.