ObjectiveTo investigate the effects of Simiaowan on intestinal barrier function and adenosine triphosphate （ATP） binding cassette transporter G2 （ABCG2） expression in hyperuricemic （HUA） rats， and elucidate its therapeutic mechanisms. MethodsForty male Sprague Dawley （SD） rats were randomized into a normal group， a model group， low-dose （282.6 mg·kg^-1） and high-dose （565.2 mg·kg^-1） Simiaowan groups， and a Benzbromarone （4.7 mg·kg^-1） group. The HUA model was established via intraperitoneal injection of potassium oxonate （ip） combined with oral gavage of hypoxanthine （ig） for 14 days. Following modeling， treatments were administered for 14 days. Samples were collected and weighed 4 h after final dosing. Blood uric acid and hepatic function were analyzed. Histopathological changes were evaluated by hematoxylin-eosin （HE） staining， and Chiu's scoring was conducted. Enzyme-linked immunosorbent assay （ELISA） quantified tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， interleukin-1β （IL-1β）， lipopolysaccharide （LPS）， diamine oxidase （DAO）， and D-lactic acid （D-LA） levels. Real-time polymerase chain reaction （Real-time PCR）， Western blot， and immunohistochemistry assessed the expression of Claudin-1， Occludin， occludens-1 （ZO-1）， and ABCG2 mRNAs and proteins. 16S rDNA amplicon sequencing characterized ileal microbiota. ResultsCompared with the normal group， the model group exhibited epithelial shedding in the ileal villus， structural disruption， infiltration of extensive inflammatory cells， and significantly elevated Chiu's scores （P<0.01）. The DAO， TNF-α， IL-6， IL-1β， LPS， and D-LA levels in the ileum were markedly increased （P<0.01）， while mRNA and protein expressions of Claudin 1， Occludin， ZO-1， and ABCG2， as well as positive staining area and proportion， were significantly reduced （P<0.01）. Compared with the model group， the Simiaowan groups at all doses showed improved epithelial damage in the ileal villus， significantly lowered Chiu's scores （P<0.01）， significantly reduced DAO， TNF-α， IL-6， IL-1β， LPS， and D-LA levels in the ileum （P<0.01）， and upregulated mRNA and protein expressions of Claudin 1， Occludin， ZO-1， and ABCG2， as well as positive staining area and proportion （P<0.01）. The 16S rDNA results showed that in the model group， the α-diversity index of the ileal microbiota was increased， and species diversity and richness were enhanced， with microbiota dysfunction observed. The community structure of the gut microbiota was significantly different from that of the normal microbiota. The abundance of probiotics was decreased， and the abundance of pathogenic bacteria was increased， with butyrate-producing bacteria showing a low abundance. In contrast， Simiaowan at all doses reduced species diversity and richness， regulated microbiota dysfunction， and promoted the shift of the structure of the gut microbiota community towards a normal one. This increased the abundance of beneficial bacteria， decreased the abundance of harmful bacteria， and restored the abundance of butyrate-producing bacteria. ConclusionSimiaowan enhances ileal uric acid excretion and further alleviates HUA by modulating the gut microbiota composition to improve the intestinal barrier and upregulate the expression of the urate transporter ABCG2 in HUA rats.

Objective: To develop a clinical decision and prescription generation system (CDPGS) specifically for diarrhea in traditional Chinese medicine (TCM), utilizing a specialized large language model (LLM), Qwen-TCM-Dia, to standardize diagnostic processes and prescription generation. Methods: Two primary datasets were constructed: an evaluation benchmark and a fine-tuning dataset consisting of fundamental diarrhea knowledge, medical records, and chain-of-thought (CoT) reasoning datasets. After an initial evaluation of 16 open-source LLMs across inference time, accuracy, and output quality, Qwen2.5 was selected as the base model due to its superior overall performance. We then employed a two-stage low-rank adaptation (LoRA) fine-tuning strategy, integrating continued pre-training on domain-specific knowledge with instruction fine-tuning using CoT-enriched medical records. This approach was designed to embed the clinical logic (symptoms → pathogenesis → therapeutic principles → prescriptions) into the model’s reasoning capabilities. The resulting fine-tuned model, specialized for TCM diarrhea, was designated as Qwen-TCM-Dia. Model performance was evaluated for disease diagnosis and syndrome type differentiation using accuracy, precision, recall, and F1-score. Furthermore, the quality of the generated prescriptions was compared with that of established open-source TCM LLMs. Results: Qwen-TCM-Dia achieved peak performance compared to both the base Qwen2.5 model and five other open-source TCM LLMs. It achieved 97.05% accuracy and 91.48% F1-score in disease diagnosis, and 74.54% accuracy and 74.21% F1-score in syndrome type differentiation. Compared with existing open-source TCM LLMs (BianCang, HuangDi, LingDan, TCMLLM-PR, and ZhongJing), Qwen-TCM-Dia exhibited higher fidelity in reconstructing the “symptoms → pathogenesis → therapeutic principles → prescriptions” logic chain. It provided complete prescriptions, whereas other models often omitted dosages or generated mismatched prescriptions. Conclusion By integrating continued pre-training, CoT reasoning, and a two-stage fine-tuning strategy, this study establishes a CDPGS for diarrhea in TCM. The results demonstrate the synergistic effect of strengthening domain representation through pre-training and activating logical reasoning via CoT. This research not only provides critical technical support for the standardized diagnosis and treatment of diarrhea but also offers a scalable paradigm for the digital inheritance of expert TCM experience and the intelligent transformation of TCM.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

ObjectiveTo investigate the mechanism by which Simiao Wan improve intestinal uric acid excretion in hyperuricemic （HUA） rats by inhibiting ferroptosis via the solute carrier family 7 member 11/glutathione peroxidase 4 （SLC7A11/GPX4） signaling pathway. MethodsForty-eight male SD rats were randomly assigned to a normal group， a model group， a low-dose Simiao Wan group （282.6 mg·kg^-1）， a high-dose Simiao Wan group （565.2 mg·kg^-1）， an etoricoxib group （5.4 mg·kg^-1）， and a ferroptosis inhibitor （Fer-1） group （2 mg·kg^-1）. Except for the normal group， rats in all other groups were intraperitoneally injected with potassium oxonate （100 mg·kg^-1） combined with intragastric administration of hypoxanthine （500 mg·kg^-1） to establish the HUA rat model. After 21 days， rats in each administration group received the corresponding dose of drug by gavage， rats in the Fer-1 group received intraperitoneal injection of Fer-1， and rats in the normal and model groups were given an equal volume of normal saline by gavage. After sampling， serum levels of uric acid （SUA）， creatinine （Cr）， and blood urea nitrogen （BUN） were measured using biochemical assays. The content of ferrous ion （Fe²⁺）， reduced glutathione （GSH）， and malondialdehyde （MDA）， as well as superoxide dismutase （SOD） activity in ileal tissues were determined. Hematoxylin and eosin （HE） staining was performed to observe the histopathological changes in the ileum， and transmission electron microscopy was used to observe mitochondrial alterations in the ileal tissue. Immunohistochemistry （IHC） and Western blot were used to detect the protein expression levels of GPX4， ferritin heavy chain 1 （FTH1）， acyl-CoA synthetase long-chain family member 4 （ACSL4）， SLC7A11， and ATP-binding cassette transporter G2 （ABCG2） in ileal tissue. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to determine the mRNA expression of GPX4， FTH1， ACSL4， SLC7A11， and ABCG2 in the ileal tissue. ResultsCompared with the normal group， the model group exhibited significantly elevated serum UA， Cr， and BUN levels （P<0.01）， significantly increased content of MDA and Fe²⁺ in ileal tissue， and significantly decreased GSH content and SOD activity （P<0.01）. HE staining showed extensive shedding of the ileal villous epithelium， disrupted and disorganized villous structure， and incomplete local tissue architecture. Transmission electron microscopy revealed reduced mitochondrial volume， decreased or even vanished cristae， indicating ultrastructural features characteristic of ferroptosis. Molecular and immunohistochemical results demonstrated that the protein and mRNA expression levels of GPX4， FTH1， SLC7A11， and ABCG2 were significantly downregulated， whereas those of ACSL4 were significantly upregulated （P<0.05， P<0.01）. Compared with the model group， after intervention with Simiao Wan， the serum UA， Cr， and BUN levels significantly decreased in all dose groups （P<0.05，P<0.01）， the MDA and Fe²⁺ content in ileal tissues were significantly reduced （P<0.01）， and the GSH content and SOD activity significantly increased （P<0.01）. HE staining showed that the shedding of ileal villous epithelium was markedly alleviated， the villous structure became relatively intact and regularly arranged， and local tissue damage was obviously improved. Transmission electron microscopy showed attenuated mitochondrial damage， improvement in mitochondrial shrinkage， and partial restoration of mitochondrial cristae. Molecular and immunohistochemical results showed that Simiao Wan upregulated GPX4， FTH1， SLC7A11， and ABCG2， and downregulated ACSL4 in a dose-dependent manner. In the high‑dose group， all indices improved significantly （P<0.05，P<0.01）， whereas in the low‑dose group， only improving trends were observed for FTH1， SLC7A11 mRNA， and ABCG2 protein. ConclusionSimiao Wan may inhibit ferroptosis of ileal epithelial cells by regulating the SLC7A11/GPX4 signaling pathway， and upregulate the expression of the uric acid transporter ABCG2， thereby promoting intestinal uric acid excretion and improving HUA.

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Objective To investigate the impact of sleep modes on the risk for diseases of the body systems.Methods Based on a subset of UK Biobank dataset comprising 87 617 participants,3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer,that is sleep duration and onset,sleep rhythm(relative amplitude and stability),and sleep quality(sleep efficiency and number of awakenings).Latent profile analysis(LPA)was applied to identify and classify distinct sleep modes.Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.Results LPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups,the subgroup 4 had relatively optimal levels in above sleep indicators.Compared to the subgroup 4,the other 4 subgroups exhibited variations in different sleep dimensions,with at least one indicator demonstrating an unfavorable trend.These subgroups also revealed differences in racial composition,shift work and social deprivation index.Moreover,there were notable differences in the risk of various system diseases among the subgroups(P<0.05).When compared to the subgroup 4,the other 4 subgroups exhibited an elevated risk for certain diseases(comprising a total of 126 diseases),with the diseases of the circulatory system,digestive system and musculoskeletal system most common.Among the 5 subgroups,the subgroup 2(shorter sleep duration and later sleep onset)and the subgroup 5(rhythm disorder)had the highest counts of associated risks,amounting to 85 and 91 types,respectively,but there was certain difference in their systematic composition.Conclusion There are different sleep modes within the participants,and the modes are potentially associated with an increased risk for diseases of body systems.Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.

Objective To investigate the effect of β-arrestin1(ARRB1)on cell proliferation,migration and invasion in oral squamous cell carcinoma(OSCC).Methods Based on The Cancer Genome Atlas(TCGA)database,the expression profiles of ARRB1 in OSCC were analyzed,and then Gene Set Enrichment Analysis(GSEA)was used to suggest the possible signaling pathways involved,and to explore its potential impact on the prognosis of OSCC patients.Immuinohistochemistry(IHC)was performed to detect the expression of ARRB1 in OSCC tumor tissues and adjacent tissues,and the correlation between ARRB1 expression and clinicopathological features was statistically analyzed.The expression profiles of ARRB1 in SCC-15,CAL-27 and HOK cell lines were verified by qPCR and Western blotting.The ARRB1 overexpression plasmid model was constructed,and its effects on the proliferation,migration and invasion of OSCC cells were analyzed by clone formation,EdU,scratch and Transwell assays.Results TCGA showed that the expression level of ARRB1 was significantly lower in head and neck squamous cell carcinoma(HNSC)and OSCC tissues than the corresponding normal tissues(P<0.01).The expression of ARRB1 in OSCC tissues was correlated with tumor differentiation,lymph node metastasis and TNM stage(P<0.05).The OSCC patients with high expression of ARRB1 had a lower survival rate than those with low expression(P<0.01),which was consistent with the results of bioinformatics analysis.The expression level of ARRB1 in SCC-15 and CAL-27 cells was lower than that of HOK cells(P<0.01),and its overexpression significantly inhibited cell proliferation(P<0.05),migration(P<0.01)and invasion(P<0.01).Conclusion ARRB1 is lowly expressed in OSCC,its overexpression inhibits the proliferation,migration and invasion of OSCC cells,and it is related to prognosis improvement.

Objective:To describe the body mass index (BMI) level and long-term trends of Chinese older adults aged 65 and above.Methods:Older adults aged 65 and above from six waves (2002-2018) of the China Longitudinal Healthy Longevity Survey were selected as the study population. Multiple cross-sectional design with six survey waves conducted in 2002, 2005, 2008, 2011, 2014, and 2018 was adopted, enrolling 15 647, 15 358, 15 622, 9 166, 6 302, and 12 417 participants, respectively. Additionally, a total of 13, 755 participants were included in the cohort study design. Relevant information was collected through questionnaires and physical examinations. The χ2 trend test was used to compare the changes in the rates of underweight and overweight/obesity over the years, and the linear mixed-e?ects model (LMM) was used to fit trajectory curves of BMI changes with advancing age in older adults. Results:The baseline ages of the participants included in 2002, 2005, 2008, 2011, 2014, and 2018 were (85.16±11.26), (84.23±11.83), (84.99±12.16), (81.10±11.86), (78.89±11.30), and (83.08±12.42) years, respectively, with a relatively high proportion of females and rural residents. In the cohort study, the 13 755 participants had a median ( Q1, Q3) follow-up time of 6.5 (5.2, 10.0) years, with a cumulative follow-up duration of 109 041 person-years. In each wave, males had higher BMI than females, urban residents had higher BMI than rural residents, and BMI gradually decreased with increasing age (all P<0.001). The mean BMI of older adults in China increased from (19.37±3.80) kg/m2 in 2002 to (22.04±4.01) kg/m2 in 2018 ( P<0.001). Across all survey years, the prevalence of underweight was consistently higher in women than in men and in rural areas than in urban areas, with an upward trend as age increased (all P<0.001). In 2018, the underweight rates in the 65-79, 80-89, 90-99, and ≥100-year-old age groups were 8.0%, 16.7%, 26.2%, and 35.5%, respectively. Meanwhile, the prevalence of overweight/obesity was higher in men than in women and in urban areas than in rural areas, showing a declining trend with advancing age (all P<0.001). The prevalence of underweight among the older adults decreased significantly from 45.2% in 2002 to 18.9% in 2018 ( P<0.001), while the prevalence of overweight/obesity increased from 11.0% in 1998 to 29.6% in 2018 ( P<0.001). The trajectory curves fitted by the LMM model showed that individuals born in later decades had higher BMI levels at the same age compared to earlier cohorts. Conclusion:From 2002 to 2018, the BMI level among Chinese older adults showed an increasing trend. The prevalence of underweight showed a declining trend, while the rates of obesity and overweight increased. However, the underweight rate remained notably high among the oldest old.

Objective To mine and analyze signals of acute kidney injury(AKI)related to drugs,comprehensively summarize the potential risk drugs,and provide a reference for clinically safe medication.Methods The AKI reports from January 2004 to September 2023 in the US FDA Adverse Event Reporting System(FAERS)were retrieved.Disproportionality methods were used to explore the relationship between drugs and AKI,and demographic information,time to onset,and patient outcomes were analyzed.Results Out of 1 253 drugs,159 were identified as AKI signal drugs.Among these,there were 49 antimicrobial agents(30.82%),including 35 antibiotics and 14 antiviral agents;33 antineoplastic agents(20.75%);and 25 hypotensive agents(15.72%).Drug-related AKI occurred mostly in the elderly,and the male-to-female ratio was 124∶100.The median time to onset for AKI related to antibiotics was≤8 d,with the third quartile≤21 d.Rivaroxaban and aspirin had higher proportions of death reports,with 33.03%and 31.44%respectively.Conclusions A multitude of drugs pose a risk for acute kidney injury,necessitating caution in their clinical application and the implementation of monitoring of renal function.The elderly are a high-risk group for drug-related AKI,and there are more males than females.For antibiotics,the first 21 days are the key monitoring period.For drugs that require long-term use,regular monitoring is necessary.