AIM: To investigate the diagnostic and prognostic value of differential expression of Cyclin D1 and p53 in eyelid tumors.METHODS: This retrospective study enrolled patients who underwent surgical resection for eyelid tumors at our hospital between March 2018 and March 2023. Participants were categorized into benign and malignant groups based on tumor characteristics. Clinical data were collected. Genetic data for eyelid tumors were obtained from the GEO database, and differential gene analysis, including volcano plot visualization and KEGG pathway enrichment analysis, was performed using the Sangerbox 3.0 platform. Immunohistochemistry was used to detect the expression levels of Cyclin D1, p53, and BAX in tissue samples. Correlations with clinical features were analyzed using Spearman analysis, and prognostic factors were identified via Logistic regression analysis.RESULTS: This study included 69 patients with eyelid tumors(78 eyes), categorized into a benign group(37 patients, 41 eyes)and a malignant group(32 patients, 37 eyes)based on tumor characteristics. There were significant differences between the two groups in histological subtype, TNM staging, vascular invasion, differentiation status, and local infiltration(all P<0.05). Among benign tumors: pigmented nevi in 11 eyes(27%), hemangiomas in 9 eyes(22%), squamous cell papillomas in 5 eyes(12%), epidermoid cysts in 5 eyes(12%), seborrheic keratoses in 4 eyes(10%), neurofibromas in 3 eyes(7%), and both calcifying epithelioma and xanthelasma in 2 eyes each(5%); among malignant tumors: basal cell carcinoma in 18 eyes(49%), meibomian gland carcinoma in 8 eyes(22%), squamous cell carcinoma in 5 eyes(14%), sebaceous gland carcinoma in 4 eyes(11%), lymphoma and malignant melanoma each in 1 eye(3%). At the follow-up cutoff date of March 2025, the 2-year survival rate in the benign group(95%)was significantly higher than that in the malignant group(78%; P<0.05). Bioinformatics analysis identified 4 103 differentially expressed genes, including Cyclin D1, p53, and BAX, which were predominantly involved in pathways such as the p53 signaling pathway and calcium-related signaling. Spearman analysis revealed that local invasion(rs=0.71, P<0.05)and TNM stage(rs=0.73, P<0.05)correlated with Cyclin D1 expression; local invasion(rs=0.76, P<0.05)and histological subtype(rs=0.65, P<0.05)correlated with p53 expression. Logistic regression results indicated that Cyclin D1, p53, TNM staging, and local invasion were prognostic risk factors. ROC curve analysis demonstrated that the combined detection of these four indicators had the highest predictive value for prognosis(AUC=0.83).CONCLUSION: High expression of cyclin D1 and p53 serves as molecular markers for distinguishing benign from malignant eyelid tumors and assessing prognosis. Combined detection of these markers with TNM staging and local invasion demonstrates high predictive value for prognosis.

OBJECTIVE To form an expert consensus on the clinical application of parenteral direct thrombin inhibitors （DTIs） in patients during the perioperative period. METHODS Led by Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital （the Affiliated Hospital of UESTC）， a multidisciplinary working group was established. Through literature review and the Delphi method， clinical questions related to the rational perioperative use of parenteral DTIs were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” framework； systematic searches were conducted in CNKI， Medline， Embase and other databases. Relevant evidence from randomized controlled trials and cohort studies was included and synthesized. Evidence quality was assessed using the Grades of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through multiple rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven recommendations （each with an expert consensus rate exceeding 90%） on the use of parenteral DTIs in perioperative patients were developed. These recommendations specify drug selection， dosing ranges， key monitoring points， and safety management strategies for parenteral DTIs in various scenarios， including the perioperative period of ventricular assist device implantation， the perioperative period of cardiac surgery， perioperative patients with lower-extremity atherosclerotic disease， the perioperative period of percutaneous coronary intervention in patients with acute coronary syndrome， the perioperative period of carotid artery stenting in patients with carotid stenosis， the perioperative period of patients with right heart thrombosis， and patients who develop related thrombosis and dysfunction after a central venous catheter insertion. In addition， warning and management pathways for perioperative bleeding and thrombotic events were proposed. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in perioperative period.

Atopic dermatitis （AD） is a common pruritic and chronic inflammatory dermatosis in clinical practice and is one of the diseases responding specifically to traditional Chinese medicine （TCM）. With the launch of biological agents and small molecule drugs and the development and implementation of guidelines of diagnosis and treatment， clinical pathways of treatment of moderate to severe AD， and consensus on the whole-process management of AD， the clinical efficacy of moderate to severe AD has been significantly improved. However， there are still many unmet clinical needs that require more effective methods to meet. In response to the Opinions of the CPC Central Committee and the State Council on Facilitating the Inheritance， Innovation， and Development of Traditional Chinese Medicine and the spirit of the National Conference on TCM， the China Association of Chinese Medicine organized more than 20 experts in TCM dermatology， Western medicine dermatology， interdisciplinary fields， and industries to discuss the difficulties and advantages of TCM in the treatment of AD. TCM treatment for AD can not only improve rash and relieve itching but also solve many concomitant syndromes. The abundant external treatment methods of TCM have advantages for different special populations and rash characteristics. The concept of treating disease before its onset in TCM is in line with the chronic disease management mode of prevention and treatment of atopic march and prevention of recurrence. In addition， TCM therapy can reduce the use of topical glucocorticoids and has good safety. Regarding the comorbidity of AD， equal emphasis on TCM and Western medicine and multidisciplinary joint treatment should be advocated to achieve maximum benefit for patients. The exchange of TCM and Western medicine has clarified the positioning and advantages of TCM intervention in AD， providing guidance for clinical and scientific research.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

To summarize the current status in the application of digital and intelligent technologies in the field of pharmacovigilance and to provide reference to the selection and development of methods for pharmacovigilance of rare diseases.

OBJECTIVE To establish a method for determining the contents of clopidogrel （CLP）， clopidogrel carboxylate （CLP-C）， clopidogrel acyl-β-D-glucuronide （CLP-G） and contents of clopidogrel active metabolite （CAM） in rat plasma， and to investigate their in vivo pharmacokinetic characteristics. METHODS The Shisedo CAPCELL ADME column was used with a mobile phase consisting of water and acetonitrile （both containing 0.1% formic acid） in a gradient elution. The flow rate was 0.4 mL/min， and the column temperature was maintained at 20 ℃. The injection volume was 2 μL. The analysis was performed in positive ion mode using electrospray ionization with multiple reaction monitoring. The ion pairs for quantitative analysis were m/z 322.1→211.9 （for CLP）， m/z 308.1→197.9 （for CLP-C）， m/z 322.1→154.8 （for CLP-G）， m/z 504.1→154.9 [for racemic CAM derivative （CAMD）]. Six rats were administered a single intragastric dose of CLP （10 mg/kg）. Blood samples were collected before medication and at 0.08， 0.33， 0.66， 1， 2， 4， 6， 10， 23 and 35 hours after medication. The established method was used to detect the serum contents of various components in rats. Pharmacokinetic parameters were then calculated using WinNonlin 6.1 software. RESULTS The linear ranges for CLP， CLP-C and CAMD were 0.08-20.00， 205.00-8 000.00， and 0.04-25.00 ng/mL， respectively （r≥0.990）. The relative standard deviations for both intra-day and inter-day precision tests were all less than 15%， and the relative errors for accuracy ranged from －11.68% to 14.40%. The coefficients of variation for the matrix factors were all less than 15%， meeting the requirements for bioanalytical method validation. The results of the pharmacokinetic study revealed that， following a single intagastric administration of CLP in rats， the exposure to the parent CLP in plasma was extremely low. Both the area under the drug concentration-time curve （AUC0-35 h） and the peak concentration of the parent CLP were lower than those of its metabolites. The AUC0-35 h of the active metabolite CAM was approximately 43 times that of CLP， though it had a shorter half-life （2.53 h）. The inactive metabolite CLP-C exhibited the highest exposure level， but it reached its peak concentration the latest and was eliminated slowly. The AUC0-35 h of CLP-G was about four times that of CAM， and its half-life was similar to that of CLP-C. CONCLUSIONS This study successfully established an liquid chromatography-tandem mass spectrometry method for the determination of CLP and its three metabolites， and revealed their pharmacokinetic characteristics in rats. Specifically， the parent drug CLP was rapidly eliminated， while the inactive metabolites CLP-C and CLP-G exhibited long half-lives， and active metabolite CAM displayed a transient exposure pattern.

The Solomon four-group design， a critical method for improving internal validity in clinical research， can reduce bias and control the interference of Hawthorne effects and pretest sensitization on research results， which offers unique advantages in evaluating complex intervention outcomes. This paper systematically outlined the core framework and key points of statistical analysis of the Solomon four-group design， summarized its applications in clinical research at home and abroad， explored its advantages and limitations， and discussed the potential value in traditional Chinese medicine （TCM） clinical trials. It is believed that the Solomon four-group design can help distinguish between testing effects and intervention effects in TCM clinical studies， and reduce the bias in the evaluation of subjective indicators. Meanwhile， given the complexity of the Solomon four-group design and the particularity of TCM clinical research， it is proposed that future TCM clinical studies should focus on using psychological scales， know-ledge， attitude， and behavior measurements， and other similat evaluations as endpoints. It also advocates strengthening interdisciplinary collaboration to provide new methodological paths for TCM clinical research.

ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis （AIH）-related decompensated cirrhosis， to identify independent predictive factors， and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 （n=211）. The primary endpoint was achievement of recompensation， and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up， the patients were divided into the recompensation group （n=16） and the persistent decompensation group（n=150）.The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance， and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； the Kaplan-Meier method was used for survival analysis； the Cox proportional-hazards regression model was used to identify independent predictive factors， and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled， with a median age of 55.0 years and a median follow-up time of 44.0 months， and female patients accounted for 87.2%. Among the 211 patients， 61 （with a cumulative proportion of 35.5%） achieved recompensation. Compared with the persistent decompensation group， the recompensation group had significantly higher white blood cell count， platelet count （PLT）， total bilirubin （TBil）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total bile acid， prothrombin time， international normalized ratio （INR）， SMA positive rate， Model for End-Stage Liver Disease （MELD） score， Child-Pugh score， and rate of use of glucocorticoids （all P0.05）， as well as significantly lower age at baseline， number of complications， and death/liver transplantation rate （all P0.05）. At 3 and 12 months after treatment， the recompensation group had continuous improvements in AST， TBil， INR， IgG， MELD score， and Child-Pugh score， which were significantly lower than the values in the persistent decompensation group （all P0.05）， alongside with continuous increases in PLT and albumin， which were significantly higher than the values in the persistent decompensation group （P0.05）. The multivariate Cox regression analysis showed that baseline ALT （hazard ratio ［HR］=1.067， 95% confidence interval ［CI］： 1.010 — 1.127， P=0.021）， IgG （HR=0.463，95%CI：0.258 — 0.833， P=0.010）， SMA positivity （HR=3.122，95%CI：1.768 — 5.515， P0.001）， and glucocorticoid therapy （HR=20.651，95%CI：8.744 — 48.770， P0.001） were independent predictive factors for recompensation， and the nomogram model based on these predictive factors showed excellent predictive performance （C-index=0.87，95%CI：0.84 — 0.90）. ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity， a high level of ALT， a low level of IgG， and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.