Objective: To explore the key factors affecting the selection and effectiveness of bladder management modalities in patients with spinal cord injury，so as to provide reference for the optimization of individualized bladder management strategies. Methods: The clinical and follow-up data of 78 patients with spinal cord injury treated in our hospital during Jan.1,2013 and Dec.31,2022 were retrospectively analyzed.The distribution of bladder management modalities among different grades of injuries was analyzed. Bowker symmetry test was used to evaluate the difference between bladder management modalities at discharge and at the end of follow-up. Multiple linear regression was used to explore the influencing factors of bladder management effects. Plotting Kaplan-Meier survival curves were adopted to calculate the median time of changes in bladder management. Results: At discharge，there were 9 cases of self-catheterization，19 cases of intermittent catheterization，22 cases of reflexive voiding，26 cases of long-term catheterization，and 2 cases using urinary collector.At the end of follow-up，there were 15 cases of self-catheterization，8 cases of intermittent catheterization，34 cases of reflexive voiding，14 cases of long-term catheterization，and 7 cases using urinary collector.There was a significant difference between the modalities of bladder management at discharge and at the end of follow-up (χ =21.43，P=0.018).Multiple linear regression showed a significant decrease of 8.60 in the total neurogenic bladder symptom score (NBSS) for grade D injuries compared with grade A injuries (P=0.026). The median time to bladder management change was 7.93 months (95%CI:5.44-9.44), with approximately 50% of patients experiencing a change in bladder management within 8 months after discharge. Conclusion: The modalities of bladder management changed significantly after discharge.The grade of injury was a key factor affecting the effectiveness of bladder management.Higher grade was associated with worse effectiveness of bladder management.

Smoking is a well-established risk factor for periodontitis, yet the precise mechanisms by which smoking contributes to periodontal disease remain poorly understood. Recent advances in spatial transcriptomics have enabled a deeper exploration of the periodontal tissue microenvironment at single-cell resolution, offering new opportunities to investigate these mechanisms. In this study, we utilized Visium HD single-cell spatial transcriptomics to profile gingival tissues from 12 individuals, including those with periodontitis, those with smoking-associated periodontitis, and healthy controls. Our analysis revealed that smoking disrupts the epithelial barrier integrity, induces fibroblast alterations, and dysregulates fibroblast-epithelial cell communication, thereby exacerbating periodontitis. The spatial analysis showed that endothelial cells and macrophages are in close proximity and interact, which further promotes the progression of smoking-induced periodontal disease. Importantly, we found that targeting the endothelial CXCL12 signalling pathway in smoking-associated periodontitis reduced the proinflammatory macrophage phenotype, alleviated epithelial inflammation, and reduced alveolar bone resorption. These findings provide novel insights into the pathogenesis of smoking-associated periodontitis and highlight the potential of targeting the endothelial-macrophage interaction as a therapeutic strategy. Furthermore, this study establishes an essential information resource for investigating the effects of smoking on periodontitis, providing a foundation for future research and therapeutic development for this prevalent and debilitating disease.
Humans ; Gingiva/cytology* ; Smoking/adverse effects* ; Male ; Periodontitis/pathology* ; Single-Cell Analysis ; Female ; Adult ; Middle Aged ; Macrophages ; Fibroblasts ; Endothelial Cells ; Case-Control Studies ; Chemokine CXCL12/metabolism*

Traditional Chinese medicine(TCM), with diverse structural types of active components and remarkable clinical efficacy, holds a significant position in the pharmacological research. As the key substances, active components of TCM are of great importance in revealing the material basis of TCM efficacy and mechanism of action. However, the conventional approaches of discovering active components in TCM are characterized by tedious procedures, lengthy cycles, and unclear mechanisms, which struggle to meet the current demands for drug development. In recent years, major breakthroughs have been made in target discovery technologies, and new drug targets are constantly being discovered, which has facilitated the development of target-driven approaches. The target-guided active component discovery strategy provides a new paradigm for discovering active components in TCM. This article systematically summarizes two mainstream target-based technologies-virtual screening and ligand fishing-for TCM active component discovery. By analyzing relevant application cases, this article evaluates the strengths and limitations of each technology. The review aims to provide frameworks for expediting bioactive component discovery in complex systems like TCM, so as to accelerate the development of innovative drugs based on the active components of TCM and promote the modernization and internationalization of TCM.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Medicine, Chinese Traditional ; Drug Discovery/methods* ; Animals

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

Objective To investigate the improvement effects of homogeneous fecal microbiota transplantation(FMT)on chemotherapy-induced diarrhea(CID)in mice.Methods Fifteen C57BL/6N mice were divided into control group,CID model group and CID+FMT group according to the random number distribution and remainder grouping method,with 5 mice per group.Control group received no intervention,and their feces were used to prepare fecal bacteria suspension.CID model group was injected intraperitoneally with fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,followed by gavage with 0.1 ml of saline on alternate days.CID+FMT group was given 0.1 ml fecal bacteria suspension gavage on alternate days for one week,followed by intraperitoneal injection of fluorouracil(65 mg/kg)for 5 consecutive days to construct the CID mouse model,with the experiment ending on the 14th day.During the experiment,the mice's food intake and body weight were recorded.At the end of the experiment,the mice were euthanized with deep carbon dioxide anesthesia,and the mice colonic specimens from cecum to anus were collected for hematoxylin and eosin(HE)staining and histopathological examination.Fecal samples were collected for 16S rRNA gene sequencing.Shannon index,Simpson index and Chao1 algorithm were used to analyze the α-diversity species of the intestinal flora in each group of mice.Similarity analysis(Anosim)was used to perform non-parametric on the inter-group differences of intestinal flora among the mice.Linear discriminate analysis size effect(LEfSe)and nonmetric multidimensional scaling(NMDS)were employed to analyze the intestinal dominant flora and the similarity classification relationships in each group of mice.Results The colonic specimen's length from cecum to anus in CID model group was significantly shorter than that in control group(P<0.05),while there was no significant difference between CID+FMT group and CID model group(P>0.05).The weight of mice in CID model group decreased by 42.04%,while control group mice gained 10.24%,with a significant difference between the two groups(P<0.05).The weight of mice in CID+FMT group decreased by 8.12%,which was significantly improved compared to CID model group(P<0.05).HE staining results revealed the intestinal mucosal structure in CID model group was severely damaged,with atrophy and deformation,accompanied by inflammatory cell infiltration,and the pathological score was higher than that of control group(P<0.05).Compared with CID model group,the intestinal mucosal integrity and crypt cells in the CID+FMT group were improved,with less damage,and the pathological score was lower than that of CID model group,but the difference was not statistically significant(P>0.05).The α-diversity analysis showed that there were significant differences in the Shannon,Simpson and Chao1 indices among the three groups(P<0.05).ANOSIM and NMDS analysis revealed that the intestinal flora in CID+FMT group was closer to the normal intestinal flora compared to CID model group.LEfSe analysis showed that the intestinal flora in CID model group was enriched in famliy_Bacteroidaceae,and the intestinal flora in CID+FMT group was similar to that of control group,with an enrichenment of familiy_Enterobacteriaceae.Conclusion Homogeneous FMT can improve the abundance of intestinal flora in CID mice,making it more similar to normal intestinal flora,thereby protecting intestinal mucosa,reducing damage and alleviating the severity of CID.

Objective:To analyze the learning curve of TiRobot-assisted lumbar pedicle screw fixation (LPSF) by cumulative sum (CUSUM) test method.Methods:The clinical data of 50 patients who underwent TiRobot-assisted LPSF from January 2020 to December 2022 in Beijing Friendship Hospital, Capital Medical University were retrospectively analyzed. CUSUM analysis and learning curve fitting were performed with robot usage time as the main indicator with the time for each step refined (robot registration time, path planning time and guide wire placement time), to select the best learning curve fitting model with the R2 value closest to 1. Using the turning point of the learning curve as the boundary, the learning curve was divided into two stages as learning stage and maturity stage, and then the observation indexes were compared between the two stages. Results:All 50 patients successfully completed the surgery without perioperative complications, with a total of 244 pedicle screws implanted. The total robot usage time and robot registration time showed a gradually decreasing trend with the increase of case number, and the learning curves were successfully fitted and reached their peaks at the seventeenth and thirteenth cases respectively. The entire learning process was divided into learning stage (17 cases) and maturity stage (33 cases) based on the turning point of the learning curve of total robot usage time. The path planning time and guide wire placement time did not show significant changes with the increase in the case number. The total robot usage time, robot registration time and the intraoperative blood loss in the learning stage were significantly higher than those in the maturity stage: (35.35 ± 1.58) min vs. (30.61 ± 0.43) min, (20.83 ± 1.56) min vs. (14.94 ± 0.29) min and 400 (150, 500) ml vs. 200 (110, 300) ml, the guide wire placement time of per screw was significantly lower than that in the maturity stage: 2.00 (1.83, 2.34) min/screw vs. 2.33 (2.13, 2.69) min/screw, and there were statistical differences ( P<0.05 or <0.01). There were no statistical difference in the path planning time, path planning time of per screw, guide wire placement time and the accuracy of screw placement between two stages ( P>0.05). Conclusions:TiRobot-assisted LPSF is a new technology with safety and effectiveness, and it has a relatively short learning curve. To achieve technological maturity, at least 17 surgeries are required with accumulated experience, and the robot registration is the main step of the learning process. After reaching maturity stage, the robot usage time is significantly shortened and intraoperative trauma is significantly reduced while the relatively high screw placement accuracy is ensured.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective To explore the current situation,hot spots and trends of clinical research on the treatment of carotid atherosclerosis(CAS)with traditional Chinese medicine.Methods Search CNKI,Wanfang,VIP,Web of Science core collection database related literature,using Python 3.9.6 cleaning data,using CiteSpace and VOSviewer for visual analysis of authors,institutions,keywords,etc.Results 910 Chinese literatures and 5 English literatures were included.The most published authors were Wang Changyin and Yin Chunping,and the institution was Handan Hospital of Traditional Chinese Medicine,Hebei Province.The cooperation between institutions was independent and regional.Research focus on:phlegm stasis interjunction,dyslipidemia,inflammatory factors,vascular endothelial function,nerve function defect,Banxia Baizhu Tianma decoction,coronary heart disease and so on;The treatment of CAS from"interjunction of phlegm and blood stasis"will continue to become a research hotspot in this field.Conclusion The clinical research of traditional Chinese medicine in the treatment of CAS should be closely combined with the observation of curative effect and the revelation of mechanism,and the law of traditional Chinese medicine in the treatment of CAS should be explored.In the future,the treatment of CAS should focus on the treatment of"phlegm and blood stasis",and the pathogenesis principle of"phlegm and blood stasis",the efficacy and mechanism of resolving phlegm and removing blood stasis in the treatment of CAS should be systematically and deeply explored.

Objective To explore the effects of different education and examination methods on the examination results during the screening/evaluation of patent foramen ovale by contrast-enhanced transcranial Doppler(cTCD).Methods Patients who underwent cTCD screening/evaluation for patent foramen ovale in our hospital from May 2023 to February 2024 were retrospectively selected as the research subjects.The patients were divided into the observation group and the control group according to different education and examination methods during the peri-examination period.Patients who received video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe were included into the observation group,and patients who received artificial education,Valsalva maneuver,and injection of contrast agent with 10 mL syringe were included into the control group.The positive detection rate of patent foramen ovale,right-to-left shunt microbubble grading during Valsalva/modified Valsalva maneuver,systolic blood flow velocity,pulsatility index(PI),resistive index(RI),examination duration,total physician-patient communication time,whether occlusion surgery was performed,and patient satisfaction were compared between the two groups.Results The positive detection rate of patent foramen ovale by cTCD(82.93%vs.95.92%),the detection rate of the maximum amout(grade Ⅲ)of microbubbles(39.02%vs.61.22%),the total physician-patient communication time during the peri-examination period[11.30(10.00,14.00)minutes vs.8.23(7.00,10.00)minutes],the rate of occlusion surgery(48.78%vs.73.47%),and the total patient satisfaction(80.49%vs.91.84%)showed statistically significant differences between the control group and the observation group(P<0.05).Additionally,the receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC)for diagnosing patent foramen ovale were 0.718 in the control group and 0.855 in the observation group.Conclusion Peri-examination interventions such as video education,modified Valsalva maneuver,and injection of contrast agent with 20 mL syringe can improve the positive detection rate of patent foramen ovale,reduce ineffective physician-patient communication,and improve patient satisfaction.