Objective: To investigate the influencing factors for delay in healthcare-seeking, definitive diagnosis and identification in patients with pulmonary tuberculosis (PTB) in Minhang District, Shanghai Municipality, so as to provide the basis for effectively reducing delay in PTB patients. Methods: Data of PTB patients in Minhang District from 2017 to 2022 were collected from the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. The prevalence rates of delay in healthcare-seeking, definitive diagnosis and identification were analyzed, and factors affecting delay in healthcare-seeking, definitive diagnosis and identification were identified using multivariable logistic regression models. Results: A total of 4 214 PTB patients were reported in Minhang District from 2017 to 2022, including 2 802 males and 1 412 females, with a male-to-female ratio of 1.98∶1. The majority of patients were aged 25 to <45 years (1 664 cases, 39.49%). The prevalence rates of delay in healthcare-seeking, definitive diagnosis and identification were 36.81%, 30.21% and 38.09%, respectively. Delay in healthcare-seeking was associated with the year (2018, OR=0.708; 2019, OR=0.549; 2020, OR=0.670; 2021, OR=0.682), gender (female, OR=1.199), occupation (worker, OR=1.379; housekeeping service/housework/unemployed, OR=1.481), case identification route (symptom-based consultation, OR=11.159), and level of the first-diagnosed hospital (city-level, OR=1.528). Delay in definitive diagnosis was associated with age (45 to <65 years, OR=1.476), occupation (commercial service, OR=0.687; housekeeping service/housework/unemployed, OR=0.672), household registration (non-local, OR=0.820), case identification route (symptom-based consultation, OR=0.616), pathogen test result (negative/not tested, OR=1.903), and the level of the first-diagnosed hospital (city-level, OR=0.311). Delay in identification was associated with the year (2018, OR=0.785; 2019, OR=0.647; 2020, OR=0.790; 2021, OR=0.710), occupation (commercial service, OR=0.687), household registration (non-local, OR=0.848) and level of the first-diagnosed hospital (city-level, OR=0.560) Conclusions Year, gender, occupation, case identification route and level of the first-diagnosed hospital are influencing factors for delay in healthcare-seeking in PTB patients. Age, occupation, household registration, case identification route, pathogen test result and level of the first-diagnosed hospital are influencing factors for delay in definitive diagnosis. Year, occupation, household registration and level of the first-diagnosed hospital are influencing factors for delay in identification.

Objective To investigate and analyze clinical characteristics and related factors of elderly patients with type 2 diabetes mellitus (T2DM) and frailty. Methods A total of 310 elderly patients with T2DM admitted to the hospital from January 2023 to June 2024 were selected as the research subjects. Their general information and disease-related information was collected through questionnaires. The Fried Frailty Scale was used to evaluate frailty status, and the patients were divided into frailty group and non-frailty group based on the Fried Frailty Scale score. Factors related to T2DM with frailty in the elderly were analyzed. Results The incidence of frailty in this study was 31.61% (98/310), and those without frailty accounted for 68.39% (212/310). There were statistically significant differences between the two groups in terms of age, body mass index (BMI), Self-rating Depression Scale (SDS) score, number of chronic complications, glycosylated hemoglobin (HbA1c) level, hemoglobin level, Mini-Nutritional Assessment-Short Form (MNA-SF) score, and Charlson Comorbidity Index (CCI) score (P<0.05). Multivariate logistic regression analysis showed that age, HbA1c level, SDS score, MNA-SF score, and CCI score were risk factors for frailty in elderly patients with T2DM (P<0.05). Conclusion The incidence of frailty is relatively high in elderly patients with T2DM. It is influenced by factors such as age , SDS score , HbA1c level , MNA-SF score and CCI score, and deserves clinical attention.

Cardiomyopathy is a group of heterogeneous myocardial diseases with a variety of specific phenotypes that can lead to cardiovascular death or progressive heart failure in severe cases.Because of the severity and complexity of these diseases,the search for new regulatory mechanisms to prevent and treat cardiomyopathy is particularly urgent.Iron death is a form of programmed cell death that differs from other forms of iron dependence and is characterized by the accumulation of iron-dependent lipid peroxides.Studies have shown that iron death can be involved in the occurrence and progression of cardiomyopathy through different signaling pathways.Therefore,targeted regulation of iron death is a new strategy to prevent cardiomyopathy.In this paper,the mechanism of iron death and its important role in cardiomyopathy were reviewed to find the potential relationship between iron death and cardiomyopathy and provide more ideas for the treatment of various cardiomyopathies in the future.

OBJECTIVE:To systematically evaluate the efficacy of transcranial direct current stimulation on the motor function of patients with Parkinson's disease,and to compare the efficacy of transcranial direct current stimulation at different targets on the motor function of patients with Parkinson's disease,so as to provide a theoretical basis for the target selection of transcranial direct current stimulation in clinical practice. METHODS:Cochrane Library,PubMed,Web of Science,CNKI,VIP,WanFang Data were retrieved for randomized controlled trials on the improvement of motor function in patients with Parkinson's disease by transcranial direct current stimulation published from the database inception to January 2023.The keywords were"Parkinson,transcranial direct current stimulation"in English and Chinese.The quality of the included studies was evaluated using the Cochrane 5.1.0 risk of bias assessment tool and the PEDro scale.Meta-analysis of outcome indicators was performed using RevMan 5.4 and Stata 17.0 software. RESULTS:Fifteen randomized controlled trials were finally included,and the PEDro scale showed that all were high-quality or very high-quality studies.Meta-analysis showed that transcranial direct current stimulation significantly improved Unified-Parkinson Disease Rating Scale part III score[mean difference(MD)=-2.49,95%confidence interval(CI):-4.42 to-0.55,P<0.05),step frequency score(MD=0.07,95%CI:0.03-0.11,P<0.05)and step speed score(MD=0.02,95%CI:0.00-0.05,P<0.05),but not for Berg Balance Scale scores(MD=2.57,95%CI:-0.74 to 5.87,P>0.05).Network Meta-analysis probability ranking:In terms of Unified-Parkinson Disease Rating Scale part III scores,the probability ranking results of target stimulation efficacy were dorsal lateral prefrontal cortex(52.4%)>primary motor cortex(45.8%)>central point of the brain(1.8%)>conventional rehabilitation(0%);in terms of gait frequency scores,the probability probability ranking results of target stimulation efficacy were cerebellum(50.1%)>central point of the brain(45.8%)>dorsal lateral prefrontal cortex(3.9%)>primary motor cortex(0.2%)>conventional rehabilitation(0%);in terms of gait speed scores,the probability ranking results of target stimulation efficacy were cerebellum(64.8%)>dorsal lateral prefrontal cortex(23.8%)>central point of the brain(9.4%)>primary motor cortex(1.7%)>conventional rehabilitation(0.4%);in terms of Berg Balance Scale scores,the probability ranking results of target stimulation efficacy were cerebellum(77.4%)>dorsal lateral prefrontal cortex(20.7%)>central point of the brain(0.7%)>conventional rehabilitation(0.2%). CONCLUSION:Transcranial direct current stimulation significantly improves motor function of patients with Parkinson's disease,with better motor coordination in the dorsolateral prefrontal cortex and better walking and balance in the cerebellum.

Objective This study aimed to explore the effects of bone morphogenetic protein 2(BMP-2)encapsula-ted in poly(lactic-co-glycolic acid)(PLGA)microcap-sules with different molecular weights on the osteogenic ability of osteoblasts.Methods PLGA microcapsules with different molecular weights(12 000,30 000)encap-sulating BMP-2,were prepared using a dual-channel mi-croinjection pump.The morphology and structure of the microcapsules were characterized by optical microscopy and scanning electron microscopy.The sustained-release performance of the microcapsules was characterized by phosphate buffered saline immersion method.The cell compatibility of the microcapsules was detected by the Calcein-AM/PI stain-ing and CCK-8 method.The chemotactic effect of BMP-2-encapsulated microcapsules on MC3T3-E1 cells after 48 h of treatment was detected by the Transwell assay.The alkaline phosphatase activity assay and Alizarin Red S staining were used to characterize the effect of microcapsules on the osteogenic ability of MC3T3-E1 cells.Results Both types of mi-crocapsules with different molecular weights exhibited smooth surfaces,as well as uniform and good cell compatibility.The chemotactic effect of the 12 000 microcapsules was outstanding.The 30 000 microcapsules had a longer sustained-release time,and the initial burst release was reduced by approximately 25%compared with the 12 000 microcapsules.In addition,30 000 microcapsules performed better in long-term osteogenesis induction than 12 000 microcapsules.Conclu-sion In this study,the release of BMP-2 is regulated by adjusting the molecular weight of PLGA,and the results indi-cate that 30 000 microcapsules can better induce the long-term osteogenic ability of MC3T3-E1 cells.

Sleep is an important activity of daily life for individuals,and sleep disorders can seriously affect their physical and mental health.This article summarizes the impact of vestibular stimulation on sleep,and reviews feasible and effective intervention methods from swing movement,galvanic vestibular stimulation,and weighted blankets stimulation,in order to provide new ideas and methods for the diagnosis and treatment of sleep disorders.

Objective This paper aims to explore patient satisfaction with mobile medical payments in ethnic minority areas and its influencing factors.Methods From May to August 2023,565 ethnic minority patients from 6 villages in 4 ethnic minority autonomous counties in Dehong Prefecture and Pu'er City,Yunnan Province,were selected as research subjects,and 186 Han patients in Kunming were selected as controls.The general information questionnaire,the mobile medical payment will-ingness and attitude survey scale,and the medical cost mobile payment satisfaction survey scale were used to investigate their sat-isfaction with actual situation of medical mobile payment.Additionally,this paper discussed influencing factors affecting satisfac-tion.Results The ethnic minority patients exhibited a significantly lower level of satisfaction compared to the Han patients(39.65±10.43 vs.49.54±7.88,P＜0.05).ethnic minority patients scored significantly lower on the dimensions of satisfac-tion,such as perceived safety,ease of use and usefulness of mobile medical payment compared to the group of Han patients(all P＜0.05).Additionally,they ethnic minority patients showed significantly lower level of willingness and attitude to use mobile medical payment compared to the group of Han patients(P＜0.05).The main factors influencing the significant difference in satisfaction with mobile medical payment were ethnic group,number of hospital visits in previous year,first-time use of mobile medical payment,and educational background(P＜0.05).Conclusion Ethnic minority patients have a low perception of secur-ity,ease of use,and usefulness of mobile medical payments,as well as a low willingness and characteristics for mobile medical payment.Therefore it is necessary to further enhance their experience and satisfaction.In the development of mobile medical pay-ment services hospitals should fully consider the current situation of"illiteracy""semi-illiteracy"and"lack of resources"in re-mote ethnic areas.They should actively develop service platforms and applications suitable for mobile medical payment in ethnic minority areas to continuously enhance service efficiency and quality.

Objective:To evaluate the efficacy and safety of hypomethylating agents (HMA) in patients with myelodysplastic syndromes (MDS) .Methods:A total of 409 MDS patients from 45 hospitals in Zhejiang province who received at least four consecutive cycles of HMA monotherapy as initial therapy were enrolled to evaluate the efficacy and safety of HMA. Mann-Whitney U or Chi-square tests were used to compare the differences in the clinical data. Logistic regression and Cox regression were used to analyze the factors affecting efficacy and survival. Kaplan-Meier was used for survival analysis. Results:Patients received HMA treatment for a median of 6 cycles (range, 4-25 cycles) . The complete remission (CR) rate was 33.98% and the overall response rate (ORR) was 77.02%. Multivariate analysis revealed that complex karyotype ( P=0.02, OR=0.39, 95% CI 0.18-0.84) was an independent favorable factor for CR rate. TP53 mutation ( P=0.02, OR=0.22, 95% CI 0.06-0.77) was a predictive factor for a higher ORR. The median OS for the HMA-treated patients was 25.67 (95% CI 21.14-30.19) months. HMA response ( P=0.036, HR=0.47, 95% CI 0.23-0.95) was an independent favorable prognostic factor, whereas complex karyotype ( P=0.024, HR=2.14, 95% CI 1.10-4.15) , leukemia transformation ( P<0.001, HR=2.839, 95% CI 1.64-4.92) , and TP53 mutation ( P=0.012, HR=2.19, 95% CI 1.19-4.07) were independent adverse prognostic factors. There was no significant difference in efficacy and survival between the reduced and standard doses of HMA. The CR rate and ORR of MDS patients treated with decitabine and azacitidine were not significantly different. The median OS of patients treated with decitabine was longer compared with that of patients treated with azacitidine (29.53 months vs 20.17 months, P=0.007) . The incidence of bone marrow suppression and pneumonia in the decitabine group was higher compared with that in the azacitidine group. Conclusion:Continuous and regular use of appropriate doses of hypomethylating agents may benefit MDS patients to the greatest extent if it is tolerated.

Multiple sclerosis(MS)is a chronic autoimmune disease of the central nervous system characterized by neuroinflammation and neurodegeneration.The pathogenesis of the disease is complex,and involves various central nervous system and peripheral cells.Single-cell sequencing has recently been increasingly applied in the study of neurological disorders,leading to important advances in our understanding of intercellular heterogeneity,disease development mechanisms,and treatment strategies.This review summarizes research progress in single-cell sequencing and its applications in MS.

Objective:To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their families, and provide data support for clinical decision-making.Methods:A retrospective study was conducted. The clinical information of stroke patients ( n = 53?793) were extracted from the Yidu cloud big data server system of the Second Affiliated Hospital of Dalian Medical University from January 1, 2001 to July 31, 2023. Combined with the results of single factor screening and the opinions of experts with senior professional titles in neurology, the input variable was determined, and the output variable was the National Institutes of Health Stroke Scale (NIHSS) representing the severity of the disease at admission. Python 3.7 was used to build DeepFM algorithm model, and five data mining models including Logistic regression, CART decision tree, C5.0 decision tree, Bayesian network and deep neural network (DNN) were built at the same time. The original data were randomly divided into 80% training set and 20% test set, which were used to train and test the models, adjust the parameters of each model, respectively calculate the accuracy, sensitivity and F-index of the six models, carry out the comprehensive comparison and evaluation of the model. The receiver operator characteristic curve (ROC curve) and calibration curve were drawn, compared the prediction performance of DeepFM model and the other five algorithms. In addition, the data of stroke patients ( n = 1?028) were extracted from Dalian Central Hospital for external verification of the model. Results:A total of 14?015 stroke patients with complete information were selected, including 11?212 in the training set and 2?803 in the testing set. After univariate screening, 14 indicators were included to construct the model, including gender, age, recurrence, physical impairment, facial problems, speech disorders, head reactions, disturbance of consciousness, visual disorders, abnormal cough and swallowing, high risk factor, family history, smoking history and drinking history. DeepFM model adopted the two-order crossover feature. The number of hidden layers in DNN layer was 3. Dropout was used to discard the neurons in the neural network. Rule was used as the activation function. Each layer used Dense full connection. The objective function was random gradient descent. The number of iterations was 15. There were 133?922 training parameters in total. Comparing the predictive value of the six models showed that the accuracy of DeepFM model was 0.951, the sensitivity was 0.992, the specificity was 0.814, the F-index was 0.950, and the area under the curve (AUC) was 0.916. The accuracy of the other five data mining models were between 0.771-0.780, the sensitivity were between 0.978-0.987, the F-index were between 0.690-0.707, and the AUC were between 0.568-0.639. The calibration curve of the DeepFM model was more aligned with the ideal curve than the other five data mining models. Suggesting that the prediction performance of DeepFM model was the best. External validation was conducted on the DeepFM model, and its accuracy was 0.891, indicating good generalization performance of the model.Conclusion:The pre-hospital non-invasive screening prediction model based on DeepFM can accurately predict the severity grading of stroke patients, and has potential application value in rapid screening and early clinical decision-making of stroke.