Objective To investigate the therapeutic effect of Huangkui capsules on targeted drug-related proteinuria in patients with hepatocellular carcinoma (HCC). Methods A retrospective analysis was conducted on clinical data of HCC patients with targeted drug-related proteinuria from June 2023 to December 2024 at Zhongshan Hospital, Fudan University. According to the treatment plan, patients were divided into the conventional treatment group and the Huangkui combination treatment group (Huangkui capsules combined with conventional treatment), and the clinical efficacy between the two groups was compared. The logistic regression analysis was used to identify the main factors affecting treatment efficacy. Results The Huangkui combination treatment group (n＝29) showed a significantly higher overall effective rate (79.3% vs 42.3%, P＝0.005), and an earlier proteinuria improvement (median time: 3 months vs 6 months, P＝0.008) than the conventional treatment group (n＝26) . The multivariate logistic regression analysis showed angiotensin-converting enzyme inhibitor (ACEI) or angiotensin Ⅱ receptor blocker (ARB) using (OR＝0.190, 95%CI 0.045-0.808, P＝0.025), targeted drug adjustment (OR＝0.132, 95%CI 0.030-0.581, P＝0.007), and Huangkui capsules using (OR＝0.168, 95%CI 0.039-0.730, P＝0.017) were protective factors for treatment efficacy of targeted drug-related proteinuria. Conclusions On the basis of conventional treatment, additive treatment with Huangkui capsules can alleviate targeted drug-related proteinuria faster and more effectively in HCC patients.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

Objective To explore the principle of antibacterial drug therapy and the strategy of program optimization in elderly patients with Helicobacter pylori（Hp）. Methods The common therapeutic regimen of Hp was summarized, and the better therapeutic regimen of elderly Hp patients was screened ultimately. Results Amoxicillin and cefuroxime were relatively safe compared with other recommended antibacterial drugs. Using other commonly antibiotics for Hp should pay attention to the disease of patients and current drug. Conclusion Elderly patients usually suffered from a variety of diseases and required multiple drugs. The application of therapeutic regimen for elderly patients with Hp should be supposed to fully weigh the risks and benefits.

Objective: To explore the active components, key targets, and mechanism of action of turnip in alleviating pulmonary fibrosis(PF) based on network pharmacology and animal experiments. Methods: The active components and targets of Brassica rapa L. were screened using the traditional Chinese medicine systems pharmacology database and analysis platform database, and PF-related targets were obtained from disease databases such as online mendelian inheritance of man(OMIM) and DrugBank. The intersection targets were used to construct a protein-protein interaction(PPI) network to identify core targets, followed by gene oncology(GO)/Kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment analysis. In the animal experiments, a bleomycin-induced PF mouse model was established. Pathological changes in lung tissue were evaluated using HE and Masson staining. qRT-PCR was used to detect the mRNA expression of tumor necrosis factor-α(TNF-α), phosphatidylinositol 3-kinase(PI3K), and akstrain transforming 1(AKT1), and immunofluorescence staining was used to measure the protein expression of TNF-α, PI3K, and AKT1. Results: The 68 active components identified in Brassica rapa L. may regulate PI3K-Akt signaling pathway by acting on 89 potential targets such as TNF-α and AKT1. The results of animal experiments showed that polysaccharide of Brassica rapa L.(BRPs) could significantly reduce the degree of bleomycin induced pulmonary fibrosis in mice; HE and Masson staining of lung tissue showed that compared with the model group, the damage of alveolar structure, the infiltration of inflammatory cells and the deposition of collagen fibers in the BRPs treatment group were significantly reduced. Further mechanism studies showed that BRPs could significantly down-regulate the mRNA and protein expression levels of TNF-α, PI3K and AKT1 in lung tissue of pulmonary fibrosis mice. Conclusion Brassica rapa L. can synergistically alleviate pulmonary fibrosis through “multi-component, multi-target and multi-channel” approach; BRPs is one of the main active components, and plays an anti-fibrosis role by inhibiting TNF-α/PI3K Akt signaling pathway.

Objective To understand the willingness of general practitioner(GP) to enhance working competence in community healthcare centers in Shanghai and provide a basis for the competence training of GPs in community healthcare centers. Methods In August 2023,GPs were selected from some community healthcare centers in Shanghai and their willingness to enhance working competence were studied by a questionnaire survey.The survey included 39 secondary indicators in three dimensions:general practice theory,skills,and humanity. Results A total of 1 192 GPs completed the questionnaire,with an effective rate of 100%.The total score of GPs' willingness to enhance their working competence was 258.45±80.93,and the mean score of the three dimensions was 6.63±2.08.The score for the general practice theory was the highest (6.92±1.95),while that for general practice humanity was the lowest (6.44±2.34) among the three dimensions.The score of willingness to enhance working efficiency differed across different age ranges (P<0.001),professional titles (P<0.001),years of work (P<0.001),and educational backgrounds of GPs (P=0.039).Those with the age younger than 30 years old,junior professional titles,less than 5 years of work experience,and a college degree or below had the highest willingness score to enhance their working competence.Among the top three secondary indicators of willingness score in each dimension,the top three methods of working competence enhancement were community general practice and specialized healthcare services combined with outpatient learning,flexible further training,and continuing education courses.Conclusions There is an urgent need for young GPs in community healthcare centers in Shanghai to enhance their working competence.Targeted enhancement plans can be provided to different groups of GPs with different characteristics through community general practice and specialized healthcare services combined with outpatient learning,flexible further training,and continuing education courses,which can further enhance the ability and quality of the GP team.
Humans ; China ; General Practitioners/psychology* ; Surveys and Questionnaires ; Community Health Centers ; Clinical Competence ; Female ; Adult ; Male ; Attitude of Health Personnel ; Middle Aged

Primary female genital system lymphoma(PFGSL)is a rare subtype of extranodal lymphoma and patients commonly present in the department of gynecology.At present,there is a lack of uniform standards for the treatment of PFGSL.Although the classification of lymphoid neoplasmas was updated by the World Health Organization classification of haematolymphoid tumors in 2016,PFGSL was still not elaborated in sufficient detail.Most cases of PFGSL are non-Hodgkin lymphoma,involving the ovary and cervix.In some cases,involvement of uterine corpus,vagina,and vulva is reported.In this article,we report two cases of non-Hodgkin lymphoma in the female genital system,one from the uterus and the other from the ovary.By presenting the diagnosis and treatment of the two cases and reviewing the literature,we aim to provide a reference for clinicians in recognizing and treating rare cases.
Female ; Humans ; Genital Neoplasms, Female/diagnosis* ; Lymphoma, Non-Hodgkin/diagnosis* ; Ovarian Neoplasms

Objective:To explore the effect of CO2 fractional laser combined with glucocorticoid(GC)on T follicular helper cell(Tfh)and B cell subsets in patients with advanced vitiligo(VL).Methods:Patients with advanced VL(128 cases)who were treated in Affiliated Hospital of Hebei University of Engineering from August 2019 to March 2022 were selected as research objects,and divided into group A(64 cases,CO2 fractional laser combined with GC)and group B(64 cases,CO2 fractional laser)according to different treatment methods,clinical efficacy and safety of the two groups were compared.Another healthy subjects(64 cases)were selected as control group.Collected clinical data of the three groups of subjects for comparative analysis.Randomized walking model was used to evaluate the effect of CO2 fractional laser combined with GC on immune function and inflammatory response in patients with advanced VL.Results:Compared with group B,group A had a higher clinical total effective rate(P<0.05)and a lower probability of adverse reactions(P<0.05).After treatment,compared with control group,proportion of Tfh2 and Tfh17 in group A had no significant difference(P>0.05),while proportion of Tfh2 and Tfh17 in group B still had significant difference(P<0.05);compared with group B,proportion of Tfh2 in group A after treatment was higher(P<0.05),while proportion of Tfh17 type was lower(P<0.05).After treat-ment,compared with control group,proportion of memory transformed B cell in group B was still significantly different(P<0.05).After treatment,compared with control group,levels of IgA,IgE and IgM in group B were still significantly different(P<0.05);compared with group B,level of IgM in group A was higher after treatment(P<0.05).After treatment,compared with control group,levels of IL-21 and IL-1β in group B were still significantly different(P<0.05);compared with group B,level of IL-10 in group A after treatment was higher(P<0.05),while levels of IL-21 and IL-1β were lower(P<0.05).Evaluation results of random walking model showed that the improvement of immune function and inflammatory reaction in group A was better than that in group B.Conclusion:CO2 fractional laser combined with GC can improve the immune function and inflammatory reaction of patients with advanced VL better after treatment,and the probability of adverse reactions is lower.

Objective:To investigate the characteristics of the endometrial microbiota in patients with varying degrees of intrauterine adhesion (IUA).Methods:This single-center cross-sectional observational study enrolled 115 patients with IUA who were treated at the Hysteroscopic Center of Fuxing Hospital, Capital Medical University, from May 2022 to October 2023. After quality control and data preprocessing, 81 samples met the inclusion criteria for analysis. Patients were grouped according to an established IUA scoring and grading system into mild IUA ( n=38) and moderate-to-severe IUA ( n=43). Endometrial tissue was collected under sterile conditions. Bacterial genomic DNA was extracted, the 16S rRNA V3-V4 region was amplified, and sequencing was performed on an Illumina platform. Differences in endometrial microbiota diversity and composition were compared between the two groups. Results:Patients with varying degrees of IUA exhibited comparable species richness, evenness and diversity of endometrial microbiota. At the phylum level, the endometrial microbiota across all subjects was predominantly composed of Proteobacteria, Firmicutes, Cyanobacteriota, Bacteroidota, and Actinobacteriota, with Proteobacteria (32.29%) and Firmicutes (23.82%) showing the highest mean relative abundances. At the genus level, Ralstonia (16.67%), Lactobacillus (13.45%), and Streptococcus (7.07%) were the most abundant genera. Group comparisons showed that the abundance of Ralstonia was higher in the mild IUA group, whereas Lactobacillus, Vibrio and Pseudoalteromonas were more abundant in the moderate-to-severe IUA group; however, these differences did not reach statistical significance (all P>0.05). LEfSe analysis further indicated that Lactobacillus, Vibrio, Pseudoalteromonas, Aeromonas, Ureaplasma and Acetobacterium were relatively enriched in the moderate-to-severe IUA group, while Geobacillus, Stomatobaculum and Fusicatenibacter were more abundant in the mild IUA group. Conclusion:The composition of the endometrial microbiota differs among patients with varying IUA severity. IUA progression may be associated with alterations in the endometrial microbiota; however, causal relationships and underlying mechanisms require further investigation.

Objective:To investigate the clinical value of dynamic AI ultrasonic intelligent assisted diagnosis system for preoperative evaluation of thyroid nodules with diameter ≤1.0 cm.Methods:From Apr. 1, 2023, to Dec. 30, 2023, 742 thyroid nodules with diameter ≤1.0 cm were removed from 532 patients with thyroid nodule disease who received surgical treatment in the Department of Thyroid (hernia) of the First Medical Center of the Chinese People’s Liberation Army General Hospital. Among them, 423 were d≤0.5 cm. 319 cases (235 males and 507 females) with 0.5

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.