Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveTo observe the effects of Yifei Tongluo prescription on the NOD-like receptor protein 3 （NLRP3）/Caspase-1/gasdermin D （GSDMD） pathway and epithelial-mesenchymal transition （EMT） in rats with pulmonary fibrosis. MethodsTracheal instillation of bleomycin was conducted to establish a rat model of pulmonary fibrosis. Thirty Sprague-Dawley （SD） rats were randomly divided into a blank group， a model group， a prednisone acetate group （1.17 mg·kg^-1）， and low- and high-dose Yifei Tongluo prescription groups （10.62 and 21.24 g·kg^-1， respectively）. Administration started on the 7th day after modeling， once a day for 28 consecutive days. The lung coefficient of each group was calculated. The pathological changes of lung tissues in each group were observed by hematoxylin-eosin （HE） staining and Masson staining. The expression of α-smooth muscle actin （α-SMA） and vimentin in rat lung tissues was detected by immunohistochemistry. The expression of NLRP3 inflammasome， E-cadherin （E-cad）， and typeⅠ collagen （ColⅠ） in lung tissues was detected by immunofluorescence. The content of hydroxyproline （HYP）， tumor necrosis factor （TNF）-α， interleukin （IL）-18， and IL-1β in rat serum was detected by enzyme-linked immunosorbent assay （ELISA）. The mRNA expression levels of NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， IL-1β， and transforming growth factor （TGF）-β₁ in rat lung tissues were determined by real-time quantitative polymerase chain reaction （Real-time PCR）. The protein expression levels of NLRP3， GSDMD， ASC， and Caspase-1 in rat lung tissues were determined by Western blot. ResultsCompared with the blank group， the model group exhibited a significantly increased lung coefficient （P<0.01） and significantly increased range of pulmonary interstitial inflammation and collagen deposition. In addition， the levels of α-SMA， Vimentin， E-cad， and ColⅠ in lung tissues were significantly increased （P<0.01）. The levels of fibrosis- and inflammation-related factors HYP， TNF-α， IL-18， and IL-1β in serum were significantly upregulated （P<0.01）. The levels of factors related to the activation of NLRP3 inflammasome in lung tissues， including NLRP3， GSDMD， ASC， Caspase-1， IL-1β， and TGF-β₁， were significantly upregulated （P<0.01）. Compared with the model group， the Yifei Tongluo prescription groups showed improved lung coefficients. Additionally， the extent of lung inflammation and collagen deposition was significantly reduced. The expression of α-SMA， Vimentin， E-cad， and ColⅠ in lung tissue was significantly decreased （P<0.01）. The levels of HYP， TNF-α， IL-18， and IL-1β in serum were significantly reduced （P<0.01）. The expression levels of NLRP3， GSDMD， ASC， Caspase-1， IL-1β， and TGF-β₁ in lung tissue were also significantly decreased （P<0.01）. ConclusionYifei Tongluo prescription can regulate the NLRP3/Caspase-1/GSDMD pathway， down-regulate release of pro-inflammatory and pro-fibrotic cytokines， alleviate NLRP3 inflammasome-mediated pyroptosis and EMT， and thereby improve pulmonary fibrosis in rats.

OBJECTIVE To study the improvement effect and mechanism of Tripterygium wilfordii multiglucoside （TWM） on nephrotic syndrome in rats. METHODS The nephrotic syndrome model was established by intravenous injection of adriamycin via the tail vein. The modeling rats were randomly divided into the model group （distilled water）， prednisone group （10 mg/kg）， and TWM high- and low-dose groups （10 and 5 mg/kg， respectively）. Additionally， blank group （distilled water） without model induction was established. Each group consisted of 9 rats. Rats in each group were administered the corresponding drugs or distilled water by gavage， once a day， for 6 consecutive weeks. The histopathological morphology of kidney tissues in rats was observed； the levels of 24-hour urinary protein （24 h-UTP） and serum biochemical indicators [albumin （ALB）， blood urea nitrogen （BUN）， serum creatinine （SCr）， cholesterol （CHOL）， and triglyceride （TG）] in rats were determined； the levels of oxidative stress indicators [superoxide dismutase （SOD）， malondialdehyde （MDA）] in kidney tissue of rats were determined； expressions of hypoxia-inducible factor-1α （HIF-1α）/microRNA-155-5p （miR-155-5p）/nuclear factor erythriod 2- related factor 2 （Nrf2） signaling pathway-related mRNA and protein in the renal tissues of rats were detected. RESULTS Compared with the blank group， the rats in the model group exhibited disordered renal tissue structure， with a small amount of glomerular necrosis and edema of the renal tubular epithelial cells. 24 h-UTP， serum levels of SCr， BUN， CHOL and TG， MDA content， mRNA and protein expressions of HIF-1α and Keap1 as well as the expression of miR-155-5p in renal tissues were increased significantly （ P ＜0.05）. Serum level of ALB， SOD level in renal tissue as well as mRNA and protein expressions of Nrf2 were decreased significantly （ P ＜0.05）. Compared with the model group， TWM high-dose and low-dose groups exhibited significant improvements in renal injury， with notable reversals in the levels of the above quantitative indicators （ P ＜0.05）. CONCLUSIONS TWM can alleviate oxidative stress-induced damage and thereby improve nephrotic syndrome in rats by regulating the HIF-1α/miR-155-5p/Nrf2 signaling pathway.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

OBJECTIVE To provide reference for improving the pre-prescription review system and reducing the occurrence of medication error by analyzing the drug-related problems （DRPs） in the pre-prescription review orders of pediatric outpatient clinics using the Pharmaceutical Care Network Europe （PCNE） classification system. METHODS The data of pre-prescription review orders were retrospectively collected from outpatient department of Shanghai Children’s Medical Center， Shanghai Jiao Tong University School of Medicine from July 2022 to June 2023； DRPs in the pre-prescription review orders were classified and summarized by using the PCNE classification system （version 9.1）， and then analyzed in terms of types and causes of issues， and the acceptance of interventions. RESULTS A total of 66 017 DRPs orders were included， involving 41 165 patients. The proportion of DRPs orders in children aged ≤5 years old was the highest （58.25%）， followed by children aged 6-12 years old （33.52%）； the department with the highest proportion of DRPs was internal medicine of pediatrics department （71.41%）； the department with the highest incidence of DRPs was thoracic surgery department （9.73%）； top three drug categories of DRPs orders were systemic anti- infective drugs （25.26%）， Chinese patent medicines （24.74%） and respiratory drugs （22.38%）. Referring to PCNE classification system， the types of DRPs mainly focused on treatment safety （64.86%）； the reasons of DRPs orders mainly focused on dose selection （82.09%）， of which 41.26% were due to excessive drug dosage； 92.13% of interventions could be accepted and fully executed by doctors. CONCLUSIONS DRPs orders identified by the pre-prescription review system can be effectively analyzed by using PCNE classification system. Pharmacists should focus on medication use in children aged ≤5 years old， update and develop personalized prescription review rules timely， and meet the rational needs of clinical medication for children.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Purpose: This research observed the efficacy and safety of soft tissue expansion combined with recombinant human epidermal growth factor (rhEGF) in repairing second-degree scald scars. Methods: This study conducted a prospective, single-blind, randomized controlled trial. Eighty-four patients with deep second-degree scald scars were evenly divided into the control and observation groups. The control group was treated with soft tissue expansion, and the observation group was additionally treated with rhEGF. The skin expansion and wound healing times were compared. The changes in wound exudate and inflammation around the wound were observed after first-stage surgery. The hydroxyproline (OHP) and collagen I/III ratios were compared during the second stage of surgery.The complications and repair effects during treatment were evaluated. Results: The observation group exhibited lower expansion time, immediate retraction rate, and wound healing time, higher skin expansion rate, higher wound exudate score and inflammation score, higher OHP, lower collagen I/III, lower complication rate, and higher total effective rate than the control group (all P < 0.05). Conclusion Skin soft tissue expansion combined with rhEGF is more effective in repairing second-degree scald scars, which can effectively increase skin expansion area and reduce wound infection and complications.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective: To investigate the urban and rural differences in adverse outcomes of pulmonary tuberculosis (PTB) in patients with pulmonary tuberculosis-diabetes mellitus comorbidity (PTB-DM), so as to provide insights into improving the prevention and treatment measures for PTB-DM. Methods: Patients with PTB-DM who were admitted and discharged from 14 designated tuberculosis hospitals in Hangzhou City from 2018 to 2022 were selected. Basic information, and history of diagnosis and treatment were collected through hospital information systems. The adverse outcomes of PTB were defined as endpoints, and the proportions of adverse outcomes of PTB in urban and rural patients with PTB-DM were analyzed. Factors affecting the adverse outcomes of PTB were identified using a multivariable Cox proportional hazards regression model. Results: A total of 823 patients with PTB-DM were enrolled, including 354 (43.01%) urban and 469 (56.99%) rural patients. There were 112 (13.61%) patients with adverse outcomes of PTB. The proportions of adverse outcomes of PTB in urban and rural patients were 14.41% and 13.01%, respectively, with no statistically significant difference (P>0.05). Multivariable Cox proportional hazards regression analysis identified first diagnosed in county-level hospitals or above (HR=2.107, 95%CI: 1.181-3.758) and drug resistance (HR=3.303, 95%CI: 1.653-6.600) as the risk factors for adverse outcomes of PTB in urban patients with PTB-DM, while the treatment/observed management throughout the process (HR=0.470, 95%CI: 0.274-0.803) and fixed-dose combinations throughout the process (HR=0.331, 95%CI: 0.151-0.729) as the protective factors for adverse outcomes in rural patients with PTB-DM. Conclusions There are differences in influencing factors for adverse outcomes of PTB in urban and rural patients with PTB-DM. The adverse outcomes of PTB are associated with first diagnosed hospitals and drug resistance in urban patients, and are associated with the treatment/observed management and fixed-dose combinations throughout the process in rural patients.