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 explore the impact of number of positive regional lymph nodes (nPRLN) in N1 stage on the prognosis of non-small cell lung cancer (NSCLC) patients. Methods Patients with TxN1M0 stage NSCLC who underwent lobectomy and mediastinal lymph node dissection from 2010 to 2015 were screened from SEER database (17 Regs, 2022nov sub). The optimal cutoff value of nPRLN was determined using X-tile software, and patients were divided into 2 groups according to the cutoff value: a nPRLN≤optimal cutoff group and a nPRLN>optimal cutoff group. The influence of confounding factors was minimized by propensity score matching (PSM) at a ratio of 1 : 1. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate overall survival (OS) and lung cancer-specific survival (LCSS) of patients. Results A total of 1316 patients with TxN1M0 stage NSCLC were included, including 662 males and 654 females, with a median age of 67 (60, 73) years. The optimal cutoff value of nPRLN was 3, with 1165 patients in the nPRLN≤3 group and 151 patients in the nPRLN>3 group. After PSM, there were 138 patients in each group. Regardless of before or after PSM, OS and LCSS of patients in the nPRLN≤3 group were superior to those in the nPRLN>3 group (P<0.001). N1 stage nPRLN>3 was an independent prognostic risk factor for OS [HR=1.52, 95%CI (1.22, 1.89), P<0.001] and LCSS [HR=1.72, 95%CI (1.36, 2.18), P<0.001]. Conclusion N1 stage nPRLN>3 is an independent prognostic risk factor for NSCLC patients in TxN1M0 stage, which may provide new evidence for future revision of TNM staging N1 stage subclassification.

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.

Objective To establish an individualized nomogram model and evaluate its efficacy to provide a possible evaluation basis for the prognosis of lower third and abdominal part of oesophageal adenocarcinoma (EAC). Methods Lower third and abdominal part of EAC patients from 2010 to 2015 were chosen from the SEER Research Plus Database (17 Regs, 2022nov sub). The patients were randomly allocated to the training cohort and the internal validation cohort with a ratio of 7∶3 using bootstrap resampling. The Cox proportional hazards regression analysis was used to determine significant contributors to overall survival (OS) in EAC patients, which would be elected to construct the nomogram prediction model. C-index, calibration curve and receiver operating characteristic (ROC) curve were performed to evaluate its efficacy. Finally, the efficacy to evaluate the OS of EAC patients was compared between the nomogram prediction model and TNM staging system. Results In total, 3945 patients with lower third and abdominal part of EAC were enrolled, including 3475 males and 470 females with a median age of 65 (57-72) years. The 2761 patients were allocated to the training cohort and the remaining 1184 patients to the internal validation cohort. In the training and the internal validation cohorts, the C-index of the nomogram model was 0.705 and 0.713, respectively. Meanwhile, the calibration curve also suggested that the nomogram model had a strong capability of predicting 1-, 3-, and 5-year OS rates of EAC patients. The nomogram also had a higher efficacy than the TNM staging system in predicting 1-, 3-, and 5-year OS rates of EAC patients. Conclusion This nomogram prediction model has a high efficiency for predicting OS in the patients with lower third and abdominal part of EAC, which is higher than that of the current TNM staging system.

OBJECTIVE To improve the efficiency and quality of dispensed oral drug management in the inpatient pharmacy， and ensure the safety of drug use in patients. METHODS SWOT （strength， weakness， opportunity， threat） analysis method was used to analyze the internal strengths and weaknesses， as well as the external opportunities and threats in the construction of a closed-loop management system for dispensed oral drugs in the inpatient pharmacy of our hospital， and propose improvement strategies. RESULTS & CONCLUSIONS A refined， full-process， closed-loop traceability management system for dispensed oral drugs in the inpatient pharmacies was successfully established， which is traceable in origin， trackable in destination， and accountable in responsibility. After the application of this system， the registration rate of dispensed drug information and the correctness rate of registration content both reached 100%. The proportion of overdue drug varieties in the same period of 2024 decreased by 77.78% compared to March 2020， the inventory volume decreased by 29.50% compared to the first quarter of 2020， the per-bed medication volume decreased by 32.14% compared to the first quarter of 2020； the average workload per post in the same period of 2023 increased by 49.09% compared to 2019， the dispensing accuracy rate reached 100%， and the improvement rate of quality control problem increased by 25.25% compared to 2021. This system effectively improves the safety and accuracy of dispensed oral drug management in the inpatient pharmacy.

ObjectiveTo explore the possible mechanisms of Wenyang Huazhuo Formula （温阳化浊方， WHF） in improving reproductive aging from the perspective of the ovarian mechanical microenvironment. MethodsThe experiment included five groups， 3-month group （20 female mice at 3 months of age）， 6-month group （20 female mice at 6 months of age）， 6-month + WHF group （20 female mice at 5 months of age treated with WHF）， 9-month group （20 female mice at 9 months of age）， and 9-month + WHF group （20 female mice at 8 months of age treated with WHF）. The 6-month + WHF group and 9-month + WHF group were orally administered WHF 41.2 g/（kg·d） once daily for 4 consecutive weeks. The other three groups received no intervention. Reproductive hormone levels were measured by ELISA. HE staining was used to count the numbers of various stages of follicles. Ovarian hyaluronic acid （HA） content and collagen fiber content were measured to evaluate the ovarian mechanical microenvironment. Superovulation was performed to observe the number of eggs obtained， as well as the number of offspring and birth weight to assess fertility. The in vitro fertilization and blastocyst culture of oocytes from female offspring in each group were observed to evaluate the effect of WHF on offspring reproductive potential. ResultsCompared with the 3-month group， the 6-month group and 9-month group showed significantly decreased serum levels of gonadotropin-releasing hormone （GnRH）， follicle-stimulating hormone （FSH）， and luteinizing hormone （LH）， decreased ovarian collagen content， and reduced numbers of primordial and secondary follicles. In contrast， the numbers of primary follicles， antral follicles， and atretic follicles increased. The levels of anti-Müllerian hormone （AMH）， ovarian HA content， and the fertilization rate， cleavage rate， and blastocyst formation rate of oocytes from offspring were significantly lower （P＜0.05）. Compared with the 6-month group， the 6-month + WHF group showed significantly reduced serum levels of GnRH， FSH， and LH， with a significant decrease in primary follicles， antral follicles， and atretic follicles as well as increase of AMH levels， ovarian HA content， number of primordial and secondary follicle， egg count， and offspring birth weight （P＜0.05）. Compared with the 9-month group， the 9-month + WHF group exhibited reduced GnRH， FSH， and collagen fiber content， as well as reduced number of primary follicles， antral follicles， and atretic follicles. However， AMH levels， ovarian HA content， number of primordial and secondary follicle， egg count， offspring numbers， birth weight， fertilization rate， cleavage rate， and blastocyst formation rate of oocytes from offspring all significantly increased （P＜0.05）. ConclusionWHF can significantly improve the ovarian reserve， fertility， and reproductive potential in offspring during reproductive mid-life and late-life stages. Its effect may be related to the remodeling of the mechanical microenvironment of aging ovaries. Moreover， the effect on the mechanical microenvironment remodeling of late-stage ovaries and the improvement of the offspring reproductive potential is more significant.

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.