Stem cell treatment may enhance erectile dysfunction (ED) in individuals with cavernous nerve injury (CNI). Nevertheless, no investigations have directly ascertained the implications of varying amounts of human umbilical cord-derived mesenchymal stem cells (HUC-MSCs) on ED. We compare the efficacy of three various doses of HUC-MSCs as a therapeutic strategy for ED. Sprague-Dawley rats (total = 175) were randomly allocated into five groups. A total of 35 rats underwent sham surgery and 140 rats endured bilateral CNI and were treated with vehicles or doses of HUC-MSCs (1 × 10 6 cells, 5 × 10 6 cells, and 1 × 10 7 cells in 0.1 ml, respectively). Penile tissues were harvested for histological analysis on 1 day, 3 days, 7 days, 14 days, 28 days, 60 days, and 90 days postsurgery. It was found that varying dosages of HUC-MSCs enhanced the erectile function of rats with bilateral CNI and ED. Moreover, there was no significant disparity in the effectiveness of various dosages of HUC-MSCs. However, the expression of endothelial markers (rat endothelial cell antigen-1 [RECA-1] and endothelial nitric oxide synthase [eNOS]), smooth muscle markers (alpha smooth muscle actin [α-SMA] and desmin), and neural markers (neurofilament [RECA-1] and neurogenic nitric oxide synthase [nNOS]) increased significantly with prolonged treatment time. Masson's staining demonstrated an increased in the smooth muscle cell (SMC)/collagen ratio. Significant changes were detected in the microstructures of various types of cells. In vivo imaging system (IVIS) analysis showed that at the 1 st day, the HUC-MSCs implanted moved to the site of damage. Additionally, the oxidative stress levels were dramatically reduced in the penises of rats administered with HUC-MSCs.
Male ; Animals ; Erectile Dysfunction/metabolism* ; Rats, Sprague-Dawley ; Mesenchymal Stem Cell Transplantation/methods* ; Rats ; Penis/pathology* ; Humans ; Disease Models, Animal ; Umbilical Cord/cytology* ; Peripheral Nerve Injuries/complications* ; Mesenchymal Stem Cells ; Nitric Oxide Synthase Type III/metabolism* ; Actins/metabolism* ; Nitric Oxide Synthase Type I/metabolism*

Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism,and the frames in which the adrenal veins are presented are called key frames.Currently,the selection of key frames relies on the doctor's visual judgement which is time-consuming and laborious.This study proposes a key frame recognition algorithm based on deep learning.Firstly,wavelet denoising and multi-scale vessel-enhanced filtering are used to preserve the morphological features of the adrenal veins.Furthermore,by incorporating the self-attention mechanism,an improved recognition model called ResNet50-SA is obtained.Compared with commonly used transfer learning,the new model achieves 97.11%in accuracy,precision,recall,F1,and AUC,which is superior to other models and can help clinicians quickly identify key frames in adrenal veins.

This article reports a case of primary Müllerian adenosarcoma(MA)of the ovary admitted to the Obstetrics and Gynecology Hospital,Fudan University in 2022,reviews the literature on this rare disease,and shares the experience of its diagnosis and treatment.The patient was a 29-year-old unmarried woman who underwent laparoscopic resection of an ovarian lesion in another hospital.Intraoperatively,it was observed that"the right ovary was enlarged with a cauliflower-shaped mass at the lower pole,measuring about 11 cm×8 cm,unencapsulated,with a fish-like texture,which was completely excised and sent for examination."Postoperative consultation with a(tertiary)hospital in Beijing and our pathology department suggested the diagnosis of ovarian adenosarcoma.Therefore,we performed a comprehensive staged surgery for the patient,i.e.,laparoscopic right salpingo-oophorectomy,cystectomy of the left ovary,omentectomy,multiple peritoneal biopsies,and hysteroscopic resection of cervical canal lesions.The patient received four cycles of postoperative chemotherapy with paclitaxel and ifosfamide.After chemotherapy,the patient has been regular followed up and showed no signs of recurrence during the almost 2-year postoperative follow-up period.

Objective:To screen the main characteristic variables affecting the incidence of cardiovascular and cerebrovascular diseases,and to construct the Bayesian network model of cardiovascular and cerebrovascular disease incidence risk based on the top 10 characteristic variables,and to provide the reference for predicting the risk of cardiovascular and cerebrovascular disease incidence.Methods:From the UK Biobank Database,315 896 participants and related variables were included.The feature selection was performed by categorical boosting(CatBoost)algorithm,and the participants were randomly divided into training set and test set in the ratio of 7∶3.A Bayesian network model was constructed based on the max-min hill-climbing(MMHC)algorithm.Results:The prevalence of cardiovascular and cerebrovascular diseases in this study was 28.8％.The top 10 variables selected by the CatBoost algorithm were age,body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),the triglyceride-glucose(TyG)index,family history,apolipoprotein A/B ratio,high-density lipoprotein cholesterol(HDL-C),smoking status,and gender.The area under the receiver operating characteristic(ROC)curve(AUC)for the CatBoost training set model was 0.770,and the model accuracy was 0.764;the AUC of validation set model was 0.759 and the model accuracy was 0.763.The clinical efficacy analysis results showed that the threshold range for the training set was 0.06-0.85 and the threshold range for the validation set was 0.09-0.81.The Bayesian network model analysis results indicated that age,gender,smoking status,family history,BMI,and apolipoprotein A/B ratio were directly related to the incidence of cardiovascular and cerebrovascular diseases and they were the significant risk factors.TyG index,HDL-C,LDL-C,and TC indirectly affect the risk of cardiovascular and cerebrovascular diseases through their impact on BMI and apolipoprotein A/B ratio.Conclusion:Controlling BMI,apolipoprotein A/B ratio,and smoking behavior can reduce the incidence risk of cardiovascular and cerebrovascular diseases.The Bayesian network model can be used to predict the risk of cardiovascular and cerebrovascular disease incidence.

Objective To explore the acupoint selection rules of acupuncture for the treatment of lower limb spasm after stroke based on data mining technology.Methods Through the computer retrieval of CNKI,Wanfang,VIP,PubMed,EMbase,web of science databases and other databases,the literature that meets the inclusion criteria was selected to establish a database.Descriptive analysis,cluster analysis and association rule analysis were performed on the data through Microsoft Excel 2016,IBM SPSS Statistics 21 and IBM SPSS Modeler 18.0 software.Results(1)A total of 68 acupuncture prescriptions were included,involving 100 acupoints and a total frequency of 536 uses;(2)the top five in terms of frequency of use of acupoints were Yanglingquan(GB34),Zusanli(ST36),Xuanzhong(GB39),Qiuxu(GB40),Sanyinjiao(SP6);(3)the core acupoint pairing was Yanglingquan(GB34)-Xuanzhong(GB39),and five valid clustering clusters were obtained,which were Shenmai(BL62)-Zhaohai(KI6),Weizhong(BL40)-Kunlun(BL60),Xuehai(SP10)-Huantiao(GB30)-Fenglong(ST40)-Zusanli(ST36),Taixi(KI3)-Yinlingquan(SP9)-Sanyinjiao(SP6),Jiexi(ST41)-Taichong(LR3)-Xuanzhong(GB39)-Qiuxu(GB40)-Yanglingquan(GB34).Conclusion Through data mining,it is found that acupuncture treatment of lower limb spasm after stroke is mostly based on Yanglingquan,Zusanli,Xuanzhong,Qiuxu and Xuanzhong.Priority should be given to the application of three yang channels of the foot and five shu acupoint,syndrome differentiation and treatment,and modification should be adjusted according to the syndromes,so as to provide reference for clinical treatment of lower limb spasm after stroke.

Objective:To explore the prognostic factors of elderly patients with community-acquired pneumonia-related sepsis and to construct a prediction model.Methods:The clinical data of elderly patients with community-acquired pneumonia-associated sepsis from October 2020 to October 2022 in the General Hospital of Ningxia Medical University from October 2020 to October 2022 were retrospectively included, and the clinical data of the two groups were divided into the modeling population and the validation population in the ratio of 7:3 by random number table method, and the clinical data of the two groups were compared. According to the 30-day outcomes of admission, the patients were divided into survival group and death group, and the independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-related sepsis were screened out by LASSO regression and multivariate logistic regression analysis, and the nomogram prediction model was constructed by R software. The area under the curve (AUC), calibration curve and decision curve of the receiver operating characteristic curve were used to validate the nomogram prediction model in the modeling population and the validation population to judge its discrimination, calibration and clinical practicability.Results:A total of 472 patients were included, with 331 and 141 models and validations, respectively, indicating that the clinical data were comparable between the modeled and validated populations. LASSO regression and multivariate logistic regression analysis showed that pneumonia severity index (PSI) score and sequential organ failure assessment (SOFA) score were independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-associated sepsis. The AUC of the modeled population prediction model was 0.984 (95% CI: 0.975-0.994), and the AUC of the validated population prediction model was 0.961 (95% CI: 0.926-0.996). The nomogram prediction model has good discrimination, calibration and clinical practicability in both the modeled and validated populations. Conclusions:The nomogram prediction model established in the study has high accuracy for early identification and risk of sepsis in elderly patients with CAP and can guide for clinicians to formulate personalized interventions.

Objective An exploratory study of the mechanisms for achieving successful aging at work of clinicians in public hospitals by applying grounded theory and proposing appropriate management recommendations.Methods 24 medical staff from 5 public hospitals in Hubei and Shandong Provinces were interviewed in semi-structured interviews by using purposive sampling methods from June to August in 2023.The interview records were coded,analyzed and integrated with grounded theory.Results Through open coding,spindle coding and selective coding,204 original concepts,47 categories,16 main categories and 5 core category related to model of the mechanism for achieving successful aging at work of clinicians.Conclusion Successful aging at work of senior clinicians encompasses five main areas:physical and mental health,work adaptation,relationships and legacy,internal and external compensation,and value realization.Organizational support factors,individual job crafting affect successful aging at work of senior clinicians by meeting the psychological needs,achieving effective resource management,and promoting person-job matching;individual characteristic factors play a moderating role;job crafting mediates the effect of organizational support factors on successful aging at work among clinicians.

Objective An exploratory study of the mechanisms for achieving successful aging at work of clinicians in public hospitals by applying grounded theory and proposing appropriate management recommendations.Methods 24 medical staff from 5 public hospitals in Hubei and Shandong Provinces were interviewed in semi-structured interviews by using purposive sampling methods from June to August in 2023.The interview records were coded,analyzed and integrated with grounded theory.Results Through open coding,spindle coding and selective coding,204 original concepts,47 categories,16 main categories and 5 core category related to model of the mechanism for achieving successful aging at work of clinicians.Conclusion Successful aging at work of senior clinicians encompasses five main areas:physical and mental health,work adaptation,relationships and legacy,internal and external compensation,and value realization.Organizational support factors,individual job crafting affect successful aging at work of senior clinicians by meeting the psychological needs,achieving effective resource management,and promoting person-job matching;individual characteristic factors play a moderating role;job crafting mediates the effect of organizational support factors on successful aging at work among clinicians.

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal hematopoietic stem cell disease caused by abnormal expression of glycosylphosphatidylinositol (GPI) on the cell membrane due to mutations in the phosphatidylinositol glycan class A(PIGA) gene. It is commonly characterized by intravascular hemolysis, repeated thrombosis, and bone marrow failure, as well as multiple systemic involvement symptoms such as renal dysfunction, pulmonary hypertension, swallowing difficulties, chest pain, abdominal pain, and erectile dysfunction. Due to the rarity of PNH and its strong heterogeneity in clinical manifestations, multidisciplinary collaboration is often required for diagnosis and treatment. Peking Union Medical College Hospital, relying on the rare disease diagnosis and treatment platform, has invited multidisciplinary clinical experts to form a unified opinion on the diagnosis and treatment of PNH, and formulated the Expert Consensus of Multidisciplinary Diagnosis and Treatment for Paroxysmal Nocturnal Hemoglobinuria (2024), with the hope of promoting the standardization of PNH diagnosis and treatment.

Objective To investigate the value of computer-assisted quantification of pulmonary embolism volume(PEV)in identifying mild-to-high-risk acute pulmonary embolism(APE).Methods We retrospectively enrolled 143 patients with suspected APE confirmed by computed tomography pulmonary angiography(CTPA)at Yan'an University Affiliated Hospital from January 2017 to December 2020.According to the 2018 Chinese Guidelines for Diagnosis,Treatment and Prevention of Pulmonary Thromboembolism,all the patients were divided into low-risk group(n=88)and mild-to-high-risk group(n=55).We collected the patients'basic demographic data,clinical manifestations,and serum levels of N-terminal-B type natriuretic peptide precursor(NT-proBNP)and D-dimer.Based on CTPA images,the degree of pulmonary thromboembolism was artificially evaluated to obtain the pulmonary artery occlusion index(PAOI).The thrombus was segmented using the pulmonary embolism detection tool based on digital lung,and PEV was calculated.We compared the differences in clinical and laboratory indicators and PAOI and PEV between the two risk groups.We analyzed the value of PAOI and PEV in identifying mild-to-high-risk APE using receiver operating characteristic(ROC)curves,and used Logistic regression analysis to identify independent risk factors in predicting mild-to-high-risk APE.Different models were established.Results Compared with the low-risk group,APE patients in the mild-to-high-risk group were older(P＜0.05),had lower diastolic blood pressure(P＜0.05),higher levels of D-dimer and NT-proBNP(P＜0.05),lower levels of platelet count,arterial oxygen partial pressure and arterial carbon dioxide partial pressure(P＜0.05),and higher levels of PAOI and PEV(P＜0.001).ROC curve analysis showed that the area under the curve for PEV in identifying mild-to-high-risk APE was 0.809(95％CI:0.734-0.884),while that for PAOI was 0.753(95％CI:0.667-0.839).Logistic regression analysis showed that PEV and NT-proBNP were independent risk factors for mild-to-high-risk APE(P＜0.05).Conclusion PEV and NT-proBNP are independent risk factors for mild-to-high-risk APE.