ObjectiveTo construct a scale for the diagnosis of chronic atrophic gastritis （CAG） with turbid toxin accumulating in the stomach. MethodsFirst， a research group was established to construct the scale framework. Relevant literature of CAG with syndrome of turbid toxin accumulating in the stomach was searched in CNKI， Wanfang Database （WF）， and VIP Database （CQVIP） from April 1， 2003 to April 1， 2023， and items were preliminarily selected after standardization of terms. Through clinical investigation， the discrete trend method， correlation coefficient method， Cronbach's coefficient method， and factor analysis method were used to screen symptom items， and the frequency method was used to screen signs， tongue coating， and pulse conditions. Three rounds of Delphi expert consultation were conducted to determine the items of the scale. The weight of each item was obtained by the analytic hierarchy process. ResultsA total of 49 articles were included， and 45 items were obtained after primary screening， including 28 symptoms， 2 signs， 10 tongue coatings， and 5 pulse conditions. After clinical investigation， 15 symptoms were retained， and 8 signs and pulse conditions of tongue coating were retained. The positive coefficients of experts in three rounds of Delphi expert consultation were 100%， 96.67%， and 100%， respectively. The expert authority coefficients were 0.86， 0.87， and 0.87， respectively， and the coordination coefficients were 0.18， 0.25， and 0.30. After core group discussion， Delphi method investigation， and AHP weight assignment， the diagnostic scale items of CAG with turbid toxin accumulating in stomach syndrome were finally established， namely， dark red or purplish tongue proper with yellow greasy （or dry） coating （30 points）， epigastric stuffiness and fullness or pain （15 points）， sticky and unsmooth defecation （10 points）， taste disturbance （sticky mouth， fetid breath， bitter taste， 7 points）， heartburn or acid regurgitation （6 points）， dizziness and clouding （5 points）， general heaviness and fatigue （5 points）， slippery， string‑slippery， or slippery‑rapid pulse （5 points）， dysuria （or yellow or deep yellow urine， 4 points）， poor appetite （4 points）， dull complexion （3 points）， sticky， greasy， and fetid secretions （3 points）， and poor sleep （3 points）. ConclusionBased on the establishment， screening， confirmation， and weighting of an item pool， combined with subjective and objective approaches as well as qualitative and quantitative methods， a diagnostic scale for CAG with the syndrome of turbid toxin accumulating in the stomach was successfully constructed.

The emergence of generative pre-training transformer(GPT)and large language models(LLMs)has brought transformative applications to the medical field.In traditional Chinese medicine,LLMs offer unique opportunities to address in efficiencies in clinical workflows and improve the patient experience.However,the seprospects have challenges,including data quality,security and privacy,disinformation,ethics,and other issues.This paper systematically elaborates on the application of Large Language Models(LLMs)in Traditional Chinese Medicine(TCM),highlighting their value in improving TCM services,enhancing teaching effectiveness,and optimizing healthcare management processes,while conducting an in-depth analysis of potential technical and ethical challenges during real-world implementation.Preventive measures are necessary to ensure the safe and unbiased use of large language models in TCM clinical practice.We encourage clinicians and researchers to address current challenges and optimize largelanguage models while reducing associated risks.The deployment and implementation of large language models in TCM clinical practice will significantly contribute to the dissemination and development of TCM culture.

Objective To explore the identification method,pathogenesis,clinical characteristics and individualized pharmacotherapy of asymptomatic hyperuricemia after renal transplantation.Methods The pharmacist was on duty at the organ transplant outpatient clinic.During this time,they analyzed and sorted out the medications,identified and differentiated a case of asymptomatic hyperuricemia related to spironolactone in a patient who had undergone a renal transplant,and provided comprehensive care throughout the entire process.Results The asymptomatic hyperuricemia in this patient might be associated with spironolactone,and the adverse reactions of the patient were alleviated by pharmacists through optimizing clinical treatment.Up to now,no hyperuricemia occurred.Conclusions Pharmacists are required to collaborate closely with clinicians to establish medication profiles for patients under long-term follow-up and to closely monitor and evaluate drug-related adverse reactions.Additionally,they should assess the renal function and immune status of transplant recipients promptly and formulate individualized treatment plans in order to enhance the long-term survival of both the transplanted kidneys and the recipients.

The emergence of generative pre-training transformer(GPT)and large language models(LLMs)has brought transformative applications to the medical field.In traditional Chinese medicine,LLMs offer unique opportunities to address in efficiencies in clinical workflows and improve the patient experience.However,the seprospects have challenges,including data quality,security and privacy,disinformation,ethics,and other issues.This paper systematically elaborates on the application of Large Language Models(LLMs)in Traditional Chinese Medicine(TCM),highlighting their value in improving TCM services,enhancing teaching effectiveness,and optimizing healthcare management processes,while conducting an in-depth analysis of potential technical and ethical challenges during real-world implementation.Preventive measures are necessary to ensure the safe and unbiased use of large language models in TCM clinical practice.We encourage clinicians and researchers to address current challenges and optimize largelanguage models while reducing associated risks.The deployment and implementation of large language models in TCM clinical practice will significantly contribute to the dissemination and development of TCM culture.

Objective:To summarize the clinical characteristics of plaque psoriasis patients with thrombocytopenia, and to evaluate the efficacy and safety of biologics in such patients.Methods:A single-center retrospective cohort study was conducted. Clinical data were collected from plaque psoriasis patients with thrombocytopenia at the Department of Dermatology, Peking University Third Hospital between January 2017 and October 2024. Comparative analysis was conducted on clinical data, such as platelet counts, before and after the use of biologics, and the efficacy and safety of biologics were evaluated.Results:Eleven patients (10 males, 1 female; age range: 33 - 72 years) had thrombocytopenia prior to biologic therapy. Thrombocytopenia was caused by hypersplenism secondary to liver cirrhosis in 7 patients, and the causes of cirrhosis including prior medications for psoriasis (5 cases) and viral hepatitis (2 cases) ; 3 patients were diagnosed with primary immune thrombocytopenia (ITP), and 1 patient with aplastic anemia. All the 11 patients achieved a Psoriasis Area and Severity Index (PASI) 90 response after biologic therapy. Only one patient experienced a transient episode of further decrease in platelet counts, which was considered potentially related to anti-tuberculosis drugs. The Wilcoxon signed-rank test showed no significant decrease in platelet counts after biologic therapy in the 11 patients (pre-treatment platelet counts M [ Q1, Q3]: 77 [55, 87] × 10 9/L, post-treatment platelet counts: 84 [65, 114] × 10 9/L, P = 0.083) ; notably, 3 patients with ITP showed an upward trend in platelet counts after treatment with interleukin (IL) -17A or IL-23 inhibitors. Conclusions:Thrombocytopenia may not be a contraindication for biologic therapy in patients with plaque psoriasis. Plaque psoriasis patients with ITP may obtain dual benefits from the use of IL-17A inhibitors or IL-23 inhibitors.

Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Bone grafting is a primary method for treating bone defects. Among various graft materials, xenogeneic bone substitutes are widely used in clinical practice due to their abundant sources, convenient processing and storage, and avoidance of secondary surgeries. With the advancement of domestic production and the limitations of imported products, an increasing number of bone filling or grafting substitute materials isentering clinical trials. Relevant experts have drafted this consensus to enhance the management of medical device clinical trials, protect the rights of participants, and ensure the scientific and effective execution of trials. It summarizes clinical experience in aspects, such as design principles, participant inclusion/exclusion criteria, observation periods, efficacy evaluation metrics, safety assessment indicators, and quality control, to provide guidance for professionals in the field.
Humans ; Bone Substitutes/therapeutic use* ; Randomized Controlled Trials as Topic/methods* ; Consensus ; Bone Transplantation ; Research Design

The p21-activated kinase 4 (PAK4), a key regulator of malignancy, is negatively correlated with immune infiltration and has become an emergent drug target of cancer therapy. Given the lack of high efficacy PAK4 inhibitors, we herein reported the identification of a novel inhibitor 13 bearing a tetrahydrobenzofuro[2,3-c]pyridine tricyclic core and possessing high potency against MIA PaCa-2 and Pan02 cell lines with IC₅₀ values of 0.38 and 0.50 μmol/L, respectively. This compound directly binds to PAK4 in a non-ATP competitive manner. In the mouse Pan02 model, compound 13 exhibited significant tumor growth inhibition at a dose of 100 mg/kg, accompanied by reduced levels of PAK4 and its phosphorylation together with immune infiltration in mice tumor tissue. Overall, compound 13 is a novel allosteric PAK4 inhibitor with a unique tricyclic structural feature and high potency both in vitro and in vivo, thus making it worthy of further exploration.

Objective:To summarize the clinical characteristics of plaque psoriasis patients with thrombocytopenia, and to evaluate the efficacy and safety of biologics in such patients.Methods:A single-center retrospective cohort study was conducted. Clinical data were collected from plaque psoriasis patients with thrombocytopenia at the Department of Dermatology, Peking University Third Hospital between January 2017 and October 2024. Comparative analysis was conducted on clinical data, such as platelet counts, before and after the use of biologics, and the efficacy and safety of biologics were evaluated.Results:Eleven patients (10 males, 1 female; age range: 33 - 72 years) had thrombocytopenia prior to biologic therapy. Thrombocytopenia was caused by hypersplenism secondary to liver cirrhosis in 7 patients, and the causes of cirrhosis including prior medications for psoriasis (5 cases) and viral hepatitis (2 cases) ; 3 patients were diagnosed with primary immune thrombocytopenia (ITP), and 1 patient with aplastic anemia. All the 11 patients achieved a Psoriasis Area and Severity Index (PASI) 90 response after biologic therapy. Only one patient experienced a transient episode of further decrease in platelet counts, which was considered potentially related to anti-tuberculosis drugs. The Wilcoxon signed-rank test showed no significant decrease in platelet counts after biologic therapy in the 11 patients (pre-treatment platelet counts M [ Q1, Q3]: 77 [55, 87] × 10 9/L, post-treatment platelet counts: 84 [65, 114] × 10 9/L, P = 0.083) ; notably, 3 patients with ITP showed an upward trend in platelet counts after treatment with interleukin (IL) -17A or IL-23 inhibitors. Conclusions:Thrombocytopenia may not be a contraindication for biologic therapy in patients with plaque psoriasis. Plaque psoriasis patients with ITP may obtain dual benefits from the use of IL-17A inhibitors or IL-23 inhibitors.