Diabetes mellitus, characterized by glucose metabolism disorders and marked by insulin deficiency or insulin resistance, has seen a continuous rise in prevalence. In recent years, islet transplantation has matured as a therapeutic approach for diabetes, becoming an important method for glycemic control and the reduction of diabetes-related complications. Donor selection directly influences transplant outcomes, and various research institutions worldwide have proposed multiple scoring systems to optimize donor assessment, such as the University of Alberta scoring system and the North American Islet Donor Score. This article explores the impact of key factors such as donor age, body mass index and ischemia time on islet transplantation. Combining practical experience in pancreatic donor selection from Shanghai Changzheng Hospital, it proposes screening criteria for pancreatic donors suitable for China, aiming to provide new evidence for improving the success rate of islet transplantation.

OBJECTIVE: To develop a user-friendly visualization application for the automatic annotation of Human Phenotype Ontology (HPO) terms based on large language models and retrieval-augmented generation (RAG) technology, and to validate its performance in an authoritative case dataset. METHODS: By integrating the domestic open-source large language model DeepSeek-V3 with RAG technology, an interactive web application was deployed on the Streamlit cloud platform. Using only the latest official HPO dataset as the data source, the lightweight sentence-embedding model BAAI/bge-small-en-v1.5 was employed to construct a FAISS vector index. During the online phase, a four-step closed-loop process is automatically completed: multilingual translation, phenotype phrase extraction, RAG candidate retrieval, term mapping, and official database validation. 121 English case reports publicly released by BMJ Case Reports and Oxford Medical Case Reports (with a gold-standard HPO set of 1 794 terms) were selected for application validation. Precision, recall, and F1 score were calculated and compared horizontally with traditional dictionary tools, standalone large language models, and the similar application "RAG-HPO". Finally, replace the model with the more advanced ChatGPT-5 and evaluate its performance on the newly extracted dataset. RESULTS: An HPO term automatic annotation visualization application named PhenoRAG, based on large language models and RAG technology, was successfully developed. Users can access it directly via a web link. Across the 112 cases, a total of 2 150 HPO terms were generated; 2,064 (96.0%) were fully validated by the official database, with a hallucination rate of 1.3% and an HPO ID-name mismatch rate of 2.7%. After deduplication, 1,906 terms remained for testing. The overall precision was 63.65%, recall was 67.34%, and F1 was 65.44%, significantly outperforming traditional annotation tools (F1: 0.45-0.49, P < 0.001). Although PhenoRAG's F1 was lower than that of RAG-HPO (F1 = 0.78, P < 0.001), which relies on a manually constructed synonym database of 54 000 entries plus the HPO dataset, it requires no additional dictionary maintenance and can be used without any background in computer programming. Moreover, after switching to the GPT-5 model, PhenoRAG exhibited no hallucination rate on the new dataset, and its F1 score significantly increased (P = 0.038). CONCLUSION Without constructing a synonym database, the PhenoRAG achieved high-accuracy automatic mapping from clinical text to standard HPO terms. It features a low usage threshold, free access, and a Chinese-language interface, and can directly serve rare disease diagnosis, genetic counseling, and research scenarios in China and worldwide, warranting further clinical promotion and multicenter validation.
Humans ; Phenotype ; Biological Ontologies ; Language ; Software ; Large Language Models

[摘 要] 目的：探讨蟾毒灵（BU）对肿瘤相关巨噬细胞（TAM）介导的结直肠癌（CRC）细胞程序性死亡蛋白-配体1（PD-L1）表达的调控作用及其分子机制。方法：采用HCT116细胞与THP-1来源巨噬细胞构建体外共培养体系。佛波酯（PMA）诱导THP-1细胞分化为M0型巨噬细胞，进一步以HCT116细胞条件培养基（CM）刺激形成TAM样细胞。流式细胞术检测CD11b、CD206表达，以评价巨噬细胞极化水平；RT-qPCR及WB法检测TGF-β、IL-10、STAT3/p-STAT3及PD-L1表达变化；慢病毒转染构建STAT3敲低细胞系HCT116sh-STAT3，结合BU干预验证STAT3/PD-L1信号通路作用。结果：HCT116细胞CM可诱导巨噬细胞向M2表型极化，表现为CD11b⁺CD206⁺细胞比例升高（P < 0.01）及TGF-β、IL-10表达增加（均P < 0.001）。TAM条件培养基可显著促进HCT116细胞STAT3磷酸化（P < 0.001）并上调PD-L1 mRNA及蛋白表达水平（P < 0.001或P < 0.01）。BU干预后，TAM介导的STAT3磷酸化水平明显下降，PD-L1表达同步下调（均P < 0.01）。STAT3敲低可降低PD-L1表达，其作用趋势与BU一致。结论：BU可通过抑制TAM介导的STAT3信号激活，下调CRC细胞PD-L1表达，提示其在肿瘤免疫微环境调控中具有潜在的应用价值。

ObjectiveTo investigate the expression level of mammalian sterile 20-like kinase 1 （MST1） in prostate cancer （PCa） tissues， its biological functions， and its regulatory effects on androgen receptor （AR） and vascular endothelial growth factor （VEGF） expression. MethodsImmunohistochemistry was performed to detect MST1 expression in 77 prostate cancer tissues and 34 benign prostatic hyperplasia （BPH） tissues， and the relationship between MST1 expression and clinicopathological parameters was analyzed. MST1-overexpressing C4-2 and LNCaP cell lines were constructed. CCK-8 assay， Transwell migration assay， and angiogenesis assay were conducted to evaluate the effects of MST1 on cell proliferation， migration， and angiogenesis. The expression changes of AR and VEGF were detected by qRT-PCR and Western blot. ResultsMST1 expression was significantly lower in PCa tissues compared with BPH tissues （P=0.012）. Low MST1 expression was significantly associated with tumor metastasis （P=0.033）. MST1 overexpression inhibited C4-2 cell proliferation and migration， with transmembrane migrated cells reduced by 53.6% （P<0.01）. MST1 overexpression decreased the mRNA and protein expression levels of AR and VEGF （P<0.05）. Angiogenesis assay demonstrated that the length of new vessel structure was significantly reduced （P<0.05）. ConclusionMST1 shows a low expression level in PCa tissues and is associated with tumor metastasis. MST1 exerts tumor-suppressive effects in prostate cancer by inhibiting cell proliferation， migration， and angiogenesis， as well as downregulating the expression of AR and VEGF， indicating its potential as a therapeutic target for prostate cancer.

The Janus kinase/signal transducers and activators of transcription (JAK-STAT) control natural killer (NK) cells development and cytotoxic functions, however, whether long non-coding RNAs (lncRNAs) are involved in this pathway remains unknown. We found that miR155HG was elevated in activated NK cells and promoted their proliferation and effector functions in both NK92 and induced-pluripotent stem cells (iPSCs)-derived NK (iPSC-NK) cells, without reliance on its derived miR-155 and micropeptide P155. Mechanistically, miR155HG bound to miR-6756 and relieved its repression of JAK3 expression, thereby promoting the JAK-STAT pathway and enhancing NK cell proliferation and function. Further investigations disclosed that upon cytokine stimulation, STAT3 directly interacts with miR155HG promoter and induces miR155HG transcription. Collectively, we identify a miR155HG-mediated positive feedback loop of the JAK-STAT signaling. Our study will also provide a power target regarding miR155HG for improving NK cell generation and effector function in the field of NK cell adoptive transfer therapy against cancer, especially iPSC-derived NK cells.

[This corrects the article DOI: 10.1016/j.apsb.2018.08.009.].

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0-10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.