[Efficiency of different large language models in China in response to consultations about PCa-related perioperative nursing and health education].

OBJECTIVE: To evaluate the efficiency of the four domestic language models, ERNIE Bot, ChatGLM2, Spark Desk and Qwen-14B-Chat, all with a massive user base and significant social attention, in response to consultations about PCa-related perioperative nursing and health education. METHODS: We designed a questionnaire that includes 15 questions commonly concerned by patients undergoing radical prostatectomy and 2 common nursing cases, and inputted the questions into each of the four language models for simulation consultation. Three nursing experts assessed the model responses based on a pre-designed Likert 5-point scale in terms of accuracy, comprehensiveness, understandability, humanistic care, and case analysis. We evaluated and compared the performance of the four models using visualization tools and statistical analyses. RESULTS: All the models generated high-quality texts with no misleading information and exhibited satisfactory performance. Qwen-14B-Chat scored the highest in all aspects and showed relatively stable outputs in multiple tests compared with ChatGLM2. Spark Desk performed well in terms of understandability but lacked comprehensiveness and humanistic care. Both Qwen-14B-Chat and ChatGLM2 demonstrated excellent performance in case analysis. The overall performance of ERNIE Bot was slightly inferior. All things considered, Qwen-14B-Chat was superior to the other three models in consultations about PCa-related perioperative nursing and health education. CONCLUSION: In PCa-related perioperative nursing, large language models represented by Qwen-14B-Chat are expected to become powerful auxiliary tools to provide patients with more medical expertise and information support, so as to improve the patient compliance and the quality of clinical treatment and nursing.

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Baohuoside I suppresses the NLRP3 inflammasome activation via targeting GPER to fight against Parkinson's disease.

BACKGROUND: Accumulating evidence indicates the crucial role of microglia-mediated inflammation and the NLR family pyrin domain containing 3 (NLRP3) inflammasome-mediated pyroptosis in the pathogenesis of Parkinson's disease (PD). Baohuoside I, a natural flavonoid extracted from Herba Epimedii, has been shown to possess anti-inflammatory effects, but its potential neuroprotective effects and mechanism against PD have not been documented. STUDY DESIGN AND METHODS: The anti-inflammatory effects of Baohuoside I were evaluated by LPS-induced BV2 cells or primary microglia isolated from wide type or G protein-coupled estrogen receptor (GPER) gene knockout mice. The underlying mechanism related to GPER-mediated NLRP3 inflammasome inhibition was further explored using LPS-induced GPER+/+ or GPER-/- mouse models of PD. The neuroprotective effects of Baohuoside I were detected through western blot analysis, real-time PCR, molecular docking, mouse behavioral tests, immunofluorescence, and immunohistochemistry. RESULTS: Baohuoside I significantly alleviated LPS-induced neuroinflammation by inhibiting the activation of NF-κB signal and the increase of pyroptosis levels as evidenced by the downregulated expression of pyroptosis-related proteins (NLRP3, ASC, pro-Caspase-1, IL-1ß) in microglia cells. Intragastric administration of Baohuoside I protected against LPS-induced motor dysfunction and loss of dopaminergic neurons, reduced pro-inflammatory cytokines expressions, and inhibited microglial (Iba-1) and astrocyte (GFAP) activation in the nigrostriatal pathway in LPS-induced mouse model of PD. Pretreatment with GPER antagonist G15 in microglia cells or GPER gene deletion in mice significantly blocked the inhibitory effects of Baohuoside I on LPS-induced neuroinflammation and activation of the NLRP3/ASC/Caspase-1 pathway. Molecular docking further indicated that Baohuoside I might bind to GPER directly with a binding energy of -10.4 kcal/mol. CONCLUSION: Baohuoside I provides neuroprotective effects against PD by inhibiting the activation of the NF-κB signal and NLRP3/ASC/Caspase-1 pathway. The molecular target for its anti-inflammatory effects is proved to be GPER in the PD mouse model. Baohuoside I may be a valuable anti-neuroinflammatory agent and a drug with well-defined target for the treatment of PD.

[Nursing research progress of stigma for patients with benign prostatic hyperplasia].

Benign prostatic hyperplasia (BPH) commonly occurs in middle-aged and elderly men, affecting their physical health while also triggering varying degrees of stigma. This leads to reduced treatment compliance and a lower quality of life for patients. This article elaborates on the conceptual development of stigma, the current state of stigma in BPH patients, sources and impacts of stigma, tools for investigating stigma, and intervention measures. The aim is to enhance medical professionals' understanding of stigma and provide a basis for effective nursing interventions.