Objective To explore factors associated with early postoperative hormonal remission in patients with prolactinoma and to develop prediction models based on clinical and radiological features. Methods Data from 107 patients with prolactinoma who underwent transsphenoidal surgery at The First People’s Hospital of Huai’an, Nanjing Medical University between January 2020 and December 2024 was collected, included general clinical characteristics, preoperative laboratory indicators, and imaging features. Based on whether early postoperative prolactin (PRL) levels normalized, patients were divided into a remission group (n=76) and a non-remission group (n=31). Univariate logistic regression was used for preliminary evaluation of candidate variables, followed by LASSO regression for feature selection. Multiple machine learning models were constructed, including logistic regression, random forest, support vector machine, K-nearest neighbors, naive Bayes, decision tree, neural network, and gradient boosting decision tree (GBDT). All models were trained and evaluated using ten-fold cross-validation, with comprehensive assessment of model performance based on the area under the ROC curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score. Results The maximum diameter of tumors in the non remission group was larger than that in the remission group (P=0.019), and the incidence of tumor stroke and preoperative PRL levels were significantly higher than those in the remission group (P＜0.001). Univariate analysis showed that sex, maximum tumor diameter, tumor stroke, and preoperative PRL levels were influencing factors for early postoperative hormone response in patients with prolactinoma (P＜0.05). The comparison results of machine learning models show that the neural network model performs the best (AUC=0.921) and has good clinical application value, followed by the GBDT model (AUC=0.893) and the support vector machine model (AUC=0.884). Other models also show certain predictive ability. Conclusions Sex, preoperative PRL levels, maximum tumor diameter, Hounsfield unit value, and tumor stroke are important factors affecting early hormone response after prolactinoma surgery. The machine learning model constructed based on the above variables has good predictive performance, and performs the best and has good clinical application value.

Allergic comorbidity is a common allergic-related disease in the department of pediatrics,which is called atopic triad in modern medicine.Professor Xu Youjia believes that the children with allergic comorbidity have a more distinctive constitution of insufficiency of immature yang.Children with allergic comorbidity initially have the spleen-qi deficiency pathogenesis,and then the kidney yang will be further involved if the children fail in timely regulation and supplementation,which will result in kidney yang deficiency.In the view of spleen-kidney deficiency-cold pathogenesis of children with allergic comorbidity,Professor Xu Youjia suggested that,during the treatment,attention should be paid to the protection of the spleen(earth)of the middle energizer,thus to ensure the postnatal fire warm congenital kidney yang,and then the efficacy of raising qi and reinforcing yang can be achieved.The core medicines used for the treatment of deficiency-cold snineling nose include seven herbs,and they were Glycyrrhizae Radix et Rhizoma,Atractylodis Macrocephalae Rhizoma,Angelicae Dahuricae Radix,Saposhnikoviae Radix,Xanthii Fructus,Magnoliae Flos,and Schisandrae Chinensis Fructus.For children with severe deficiency-cold,the treatment needs to start from supplementing kidney-qi and protecting the root of yang,and the medicinals such as Psoraleae Fructus,Cimicifugae Rhizoma,Eucommiae Cortex,and Cinnamomi Cortex can be used.Professor Xu stressed the importance of adjusting the children's dietary structure and habits for protecting the spleen and stomach.The application of therapy of mediating the middle earth,raising qi and strengthening yang should accord with the growth and development of children,and the therapy is suitable for guiding the clinical treatment of diseases related to deficiency-cold syndrome.The selection of prescriptions should be based on the identification of the pathogenesis of deficiency-cold and its severity.

OBJECTIVE To explore the effects of meropenem exposure and degradation levels on clinical efficacy in patients with purulent meningitis （PM）. METHODS A total of 131 PM patients treated with meropenem at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2022 to June 2025 were prospectively included. Relevant data were collected and divided into a cured group （91 cases） and a non-cured group （40 cases） based on the efficacy. High-performance liquid chromatography-tandem mass spectrometry was used to determine the concentration of meropenem and its open-loop metabolites. Risk factors that affect efficacy were screened， and their predictive power and correlation were evaluated by univariate analysis， and multivariate Logistic regression analysis， receiver operating characteristic （ROC） curves， and correlation analysis. RESULTS Univariate analysis showed that serum creatinine， creatinine clearance rate， minimum inhibitory concentration of meropenem ≥16 μg/mL， cerebrospinal fluid red blood cell count， cerebrospinal fluid white blood cell count， cerebrospinal fluid glucose content， blood trough concentration， blood open-loop metabolite concentration/trough concentration ratio， and intrathecal injection were all correlated with efficacy （P＜0.05）. The results of multiple Logistic regression analysis showed that serum creatinine blood open-loop metabolite concentration/trough concentration ratio， intrathecal injection， and cerebrospinal fluid glucose content were influencing factors for suboptimal anti-infective ltt efficacy （P＜0.05）. ROC curve analysis showed that when the blood open-loop metabolite concentration/trough concentration ratio was greater than 2.854 （AUC＝0.647）， serum creatinine was less than 59.5 μmol/L （AUC＝0.647）， and cerebrospinal fluid glucose content was less than 3.37 mmol/L （AUC＝0.709）， the risk of treatment failure significantly increased （P＜0.05）. Correlation analysis showed that the blood trough concentration of meropenem was positively correlated with the concentration of its open-loop metabolites （R 2＝0.134 5， P＜0.000 1）. CONCLUSIONS Insufficient exposure level and rapid degradation of meropenem are key mechanisms affecting the anti-infective efficacy of PM. Elevated blood open-loop metabolite concentration/ trough concentration ratio， low serum creatinine level， lack of intrathecal injection， and low cerebrospinal fluid glucose content are independent risk factors for poor efficacy.

OBJECTIVES: To investigate the effects of different filtration fractions (FFs) during continuous venovenous hemodiafiltration (CVVHDF) post-dilution. METHODS: This study employed a single-blind, head-to-head randomized controlled design. Patients who underwent daytime continuous renal replacement therapy (CRRT) in the Department of Nephrology, the Second Affiliated Hospital of Nanchang University between April 2022 and June 2023 were prospectively enrolled. They were randomly assigned to either a low FF group (FF set at 20%-<25%) or a high FF group (FF set at 25%-30%). All patients received post-dilution CVVHDF with systemic heparin anticoagulation. The primary outcome was extracorporeal circuit coagulation, comprehensively assessed through dynamic monitoring of arterial pressure, venous pressure, and transmembrane pressure, combined with filter clotting grading at the end of the session. Secondary outcomes included changes in serum creatinine, urea, potassium, and pH levels before and after treatment to evaluate efficacy. RESULTS: A total of 40 patients were included in each the low FF group and the high FF group. The baseline characteristics showed no statistically significant differences between the two groups (all P>0.05). All patients completed the treatment successfully, with a treatment duration of 10-12 hours, and no filter required replacement during the sessions. The differences in arterial pressure, venous pressure, and transmembrane pressure at 2 h, 6 h, and the end of treatment compared to values at 1 h showed no statistically significant differences between the two groups (all P>0.05). Furthermore, no significant difference was found in filter clotting grades (including Grade Ⅰ and Grade Ⅱ clotting) at the end of treatment between the two groups (all P>0.05). The creatinine clearance efficiency was significantly higher in the high FF group compared to the low FF group (P<0.01). However, no statistically significant differences were observed between the groups regarding urea reduction, or the changes in serum potassium and pH levels before and after treatment (all P>0.05). CONCLUSIONS For patients with a relatively short treatment duration of 10-12 h undergoing post-dilution CVVHDF, employing a FF of 25%-30% does not pose a higher risk of extracorporeal circuit coagulation compared to a FF of 20%-25%, but shows a trend towards higher creatinine clearance.

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease lacking effective therapy. Metformin, an antidiabetic medication, has shown promising therapeutic properties in preclinical fibrosis models; however, its precise cellular targets and associated mechanisms in fibrosis resolution remain incompletely defined. Most research on metformin's effects has focused on mesenchymal and inflammatory responses with limited attention to epithelial cells. In this study, we utilized Sftpc lineage-traced and Fgfr2b conditional knockout mice, along with BMP2/PPARγ and AMPK inhibitors, to explore metformin's impact on alveolar epithelial cells in a bleomycin-induced pulmonary fibrosis model and cell culture. We found that metformin increased the proliferation and differentiation of alveolar type 2 (AT2) cells, particularly the recently identified injury-activated alveolar progenitors (IAAPs)-a subpopulation characterized by low SFTPC expression but enriched for PD-L1. Single-cell RNA sequencing revealed a reduction in apoptosis among mature AT2 cells. Interestingly, metformin's therapeutic effects were not significantly affected by BMP2 or PPARγ inhibition, which blocked the lipogenic differentiation of myofibroblasts. However, Fgfr2b deletion in Sftpc lineage cells significantly impaired metformin's ability to promote fibrosis resolution, a process linked to AMPK signaling. In conclusion, metformin alleviates fibrosis by directly activating AT2 cells, especially the IAAPs, through a mechanism that involves AMPK and FGFR2b signaling, but is largely independent of BMP2/PPARγ pathways.

Objective A safe and effective medication model was put forward through the treatment of a patient with Trousseau syndrome complicated with ovarian cancer by clinical pharmacist.Methods Clinical pharmacists participated in the treatment team to make individual treatment plan for Trousseau syndrome patients with ovarian cancer through consultation,clinical ward rounds,evidence-based medicine and discussion.Results The clinical pharmacist participated in the entire pharmaceutical care for the patients.They assisted the doctor to make individual anticoagulation and chemotherapy plan.The anticoagulation treatment was safe and effective,with no thromboembolism and hemorrhage.The chemotherapy process was smooth,with no adverse reaction occurred,and the patients condition improved,leading to discharged.Conclusion Clinical pharmacists participated in clinical evaluation of the feasibility of tumor chemotherapy plan,balanced the risk of patients with thrombosis and bleeding,formulated individualized anticoagulation treatment plan,and carried out pharmaceutical education and adverse reaction monitoring,which improved the efficacy and safety of medication in patients with ovarian cancer combined with multiple organ thromboembolism.

In recent years,protein and polypeptide drugs have developed rapidly and have been widely used to treat cancer,hepatitis,and other diseases.The activity of proteins and polypeptides is closely related to their structure.Protein structures can be divided into four levels:primary,secondary,tertiary,and quaternary structures.The primary structure determines the advanced structure and biological functions of proteins.To ensure drug safety,it is necessary to carry out structural characterization and quality control.The advanced structure is the basis for proteins to express their functions and activities,and changes in spatial structure can lead to alterations in functions.This article reviews the progress of research on the primary and advanced structure characterization of proteins and polypeptides,including techniques such as reversed-phase high-performance liquid chromatography,Edman degradation,mass spectrometry,and spectroscopy.It aims to provide a reference for the structural characterization and quality control of other protein and polypeptide drug products.