Objective: To investigate the urban and rural differences in adverse outcomes of pulmonary tuberculosis (PTB) in patients with pulmonary tuberculosis-diabetes mellitus comorbidity (PTB-DM), so as to provide insights into improving the prevention and treatment measures for PTB-DM. Methods: Patients with PTB-DM who were admitted and discharged from 14 designated tuberculosis hospitals in Hangzhou City from 2018 to 2022 were selected. Basic information, and history of diagnosis and treatment were collected through hospital information systems. The adverse outcomes of PTB were defined as endpoints, and the proportions of adverse outcomes of PTB in urban and rural patients with PTB-DM were analyzed. Factors affecting the adverse outcomes of PTB were identified using a multivariable Cox proportional hazards regression model. Results: A total of 823 patients with PTB-DM were enrolled, including 354 (43.01%) urban and 469 (56.99%) rural patients. There were 112 (13.61%) patients with adverse outcomes of PTB. The proportions of adverse outcomes of PTB in urban and rural patients were 14.41% and 13.01%, respectively, with no statistically significant difference (P>0.05). Multivariable Cox proportional hazards regression analysis identified first diagnosed in county-level hospitals or above (HR=2.107, 95%CI: 1.181-3.758) and drug resistance (HR=3.303, 95%CI: 1.653-6.600) as the risk factors for adverse outcomes of PTB in urban patients with PTB-DM, while the treatment/observed management throughout the process (HR=0.470, 95%CI: 0.274-0.803) and fixed-dose combinations throughout the process (HR=0.331, 95%CI: 0.151-0.729) as the protective factors for adverse outcomes in rural patients with PTB-DM. Conclusions There are differences in influencing factors for adverse outcomes of PTB in urban and rural patients with PTB-DM. The adverse outcomes of PTB are associated with first diagnosed hospitals and drug resistance in urban patients, and are associated with the treatment/observed management and fixed-dose combinations throughout the process in rural patients.

BACKGROUND:Traditional methods of urinary tract reconstruction are limited by donor scarcity,high complication rates,and suboptimal functional recovery.Tissue engineering strategies offer new directions in this field.Since the urinary tract is mainly composed of muscle tissue,the key is to find suitable seed cells and efficiently induce them to differentiate into smooth muscle cells.Comparative studies on the efficacy of different smooth muscle cell induction regimens are still lacking. OBJECTIVE:To isolate,culture,and identify human urine-derived stem cells,and to compare the effects of two different induction protocols. METHODS:Human urine-derived stem cells were isolated from urine samples of 11 healthy adult volunteers by multiple centrifugations.Surface markers were identified by flow cytometry.The multi-directional differentiation potential of human urine-derived stem cells was verified through osteogenic and adipogenic differentiation.Differentiation was induced by transforming growth factor-β1 or transforming growth factor-β1 combined with platelet derived growth factor for 14 days.Immunofluorescence staining and western blot assay were employed to compare the expression differences of smooth muscle-specific proteins(α-SMA and SM22). RESULTS AND CONCLUSION:(1)Urine-derived stem cells were successfully isolated from the eight urine samples of healthy people.These cells exhibit a"rice grain"-like morphology and possess a robust proliferative capacity.(2)Urine-derived stem cells exhibited high expression of mesenchymal stem cell surface markers(CD73,CD90,and CD44)and extremely low expression of hematopoietic stem cell surface markers(CD34 and CD45).These cells did not express CD19,CD105,and HLA-DR.(3)After osteogenic and adipogenic differentiation,the formation of calcium nodules and lipid droplets was observed,with positive staining results from Alizarin Red S and Oil Red O staining.(4)After 14 days of smooth muscle induction culture,immunofluorescence staining revealed that the smooth muscle differentiation rate of urine-derived stem cells treated with a combination of transforming growth factor-β1 and platelet derived growth factor was significantly higher compared to those treated with transforming growth factor-β1 alone(P<0.005).(5)After 14 days of smooth muscle induction culture,western blot assay further demonstrated that the expression levels of α-SMA and SM22 in the transforming growth factor-β1/platelet derived growth factor group were significantly elevated compared to those in the transforming growth factor-β1 only group(P<0.005).These findings confirm that urine-derived stem cells can be non-invasively isolated using multiple rounds of centrifugation.Compared with transforming growth factor-β1 alone,the combination of transforming growth factor-β1 and platelet derived growth factor can improve the efficiency of inducing urine-derived stem cells to differentiate into smooth muscle cells.

Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

Objective To investigate the efficacy and safety of transcutaneous electrical acupoint stimulation(TEAS)in reducing the consumption of analgesics after total knee arthroplasty(TKA).Methods Totally 124 patients undergoing unilateral TKA were included and divided into an intervention group and a control group according to random number table method,with 62 cases in each group.Both groups received routine postoperative analgesic protocols,with the intervention group additionally receiving TEAS treatment,30 min per time,twice a day.The additional doses of intravenous patient-controlled analgesia pumps and opioid analgesic consumption in two groups of patients after surgery were analyzed,as well as the adverse events and laboratory test results(WBC,PLT,SCr,BUN,ALT and AST)in both groups.Results The number of additional doses in the intervention group with the patient-controlled analgesia pump and the consumption of opioid analgesic were both lower than those in the control group(P<0.05);the incidence of postoperative nausea symptoms in the intervention group was lower than that in the control group,while other adverse reactions showed no significant difference(P>0.05).There was no significant difference in laboratory test results(WBC,PLT,SCr,BUN,ALT and AST)between the two groups on the day before surgery and on the 1st and 7th days after surgery(P>0.05).Conclusion TEAS can reduce the consumption of analgesics after TKA,decrease some adverse reactions associated with the use of analgesics,and has good safety.

Objective To systematically search the research literature related to the application of machine learning models in hospice care,with a view to providing references for clinical practice.Methods A systematic search of Wanfang database,CNKI,VIP database,China Biomedical Literature Database,PubMed,Embase,Scopus,Cochrane Library,Web of Science,and CINAHL was conducted in accordance with the methodology of the scoping review as a guideline,with the timeframe of searching from the establishment of the database to August 30,2024,and the included literature was screened,summarized,extracted,and analyzed.Results Totally 17 studies were included.Analysis revealed that supervised machine learning algorithms(including random forest,decision tree,and neural networks)predominated in palliative care applications.Data sources and collection methods varied widely,with models applied across diverse scenarios.Model functions include assessing hospice needs,predicting a patient's risk of death,assisting with symptom management,analyzing hospice communication content,and more.Conclusion Machine learning models in palliative care demonstrate considerable utility and broad applicability.Future research should enhance data quality,optimize model development workflows,and improve model performance.

Aim Biomarkers of vascular endothelial injury serve as crucial indicators for assessing vascular endo-thelial function and provide a basis for the diagnosis and treatment of cardiovascular diseases(CVD).Currently,the mechanisms and clinical significance of classical biomarkers,such as C-reactive protein and intercellular adhesion mole-cule,in CVD have been extensively studied.However,their limited sensitivity and specificity make it difficult to compre-hensively reflect the progression of CVD.With the advancement of liquid biopsy and novel molecular biology detection technologies,emerging biomarkers of vascular endothelial injury have become a research focus.This article systematically reviews biomarkers of vascular endothelial injury,with a particular emphasis on the research progress and clinical applica-tions of novel biomarkers in CVD.

Objective To provide a scientific basis for the quality control of Chrysanthemi Indici Flos medicinal materials and the sustainable development of this resource,the germplasm differences,tissue distribution,and developmental stage changes of flavonoid content in Chrysanthemum indicum was explored.Methods High-performance liquid chromatography(HPLC)was used to quantitatively analyze the five main flavonoid compounds,including linarin,tilianin,cynaroside,apigenin,and acacetin.Real-time fluorescence quantitative PCR(qPCR)technology was used to evaluate the relative expression levels of the rhamnosyltransferase(RhaT)gene at different developmental stages.Results The study found significant differences in flavonoid accumulation among different Chrysanthemum indicum germplasms,with the highest content of linarin observed in the Hubei diploid.Flavonoid content was significantly higher in leaves,flower buds,and flowers compared to stems and roots.Linarin and tilianin peaked at the flower bud stage and then gradually decreased,while the contents of apigenin and acacetin increased with flower development.The qPCR analysis further showed that the expression level of the RhaT gene was highly consistent with the accumulation pattern of linarin.Conclusion The results reveal that flavonoid content in Chrysanthemum indicum is significantly affected by germplasm,tissue type,and developmental stage,providing important data support for the quality evaluation of Chrysanthemum indicum medicinal materials and the rational development of this resource.

Objective To compare the clinical and functional differences between transoral and submandibular approach in mandibu-lar segmental resection and reconstruction with free fibula flaps(FFFs).Methods Patients who underwent mandibular segmental re-section and FFFs reconstruction in the Department of Oral and Maxillofacial Surgery of the Affiliated Stomatological Hospital of Nanjing Medical University from January 2015 to March 2023 were retrospectively analyzed.All cases were divided into transoral approach and submandibular approach groups.Clinical characteristics of the patients were recorded including age,gender,follow-up time,pathologi-cal diagnosis,body mass index(BMI),American Society of Anesthesiologists(ASA)classification,James Brown classification of mandibular defect and number of fibular segments.The perioperative indexes,such as average operation time,average bleeding vol-ume,average blood transfusion volume,average drainage volume,average hospitalization time and postoperative complications such as malocclusion,fistula,infection,flap failure,and restriction of mouth opening were compared between the two groups.The University of Washington Quality of Life Questionnaire was used to investigate the appearance,function of swallow and speech more than 6-month postoperatively.Results The average intraoperative bleeding and postoperative drainage were significantly lower in the transoral ap-proach group than in the submandibular approach group(P=0.013 9,P=0.001 9).The appearance score was significantly higher in the transoral approach group than in the submandibular approach group(83.52±12.37)vs.(67.19±13.64)(P＜0.000 1).The differ-ences between the two groups in other variables were not statistically significant.Conclusion Cases of transoral approach had signifi-cantly better aesthetic outcomes compared with those of submandibular approach.

Objective:To summarize the clinical characteristics of elderly patients with stage Ⅰ diffuse large B-cell lymphoma (DLBCL) and analyze the factors associated with prognosis.Methods:A case series study was conducted by retrospectively collecting clinical data from patients aged over 60 years with newly diagnosed stage Ⅰ DLBCL across 20 medical centers in Jiangsu Province, China, between June 2010 and April 2023. The involved site, classification and treatment plan were summarized. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Statistical analyses were performed using the Kaplan-Meier method, and Cox regression model.Results:The study included 255 patients with a median age of 69 years, of whom 130 (51.0%) were male, 66 (25.9%) were aged ≥75 years and 26 (10.1%) had a high Charlson Comorbidity Index (CCI) score of ≥2. Extranodal involvement was observed in 163 (63.9%) patients, with the stomach (37.4%, 61/163), intestine (19.0%, 31/163), testes (11.0%, 18/163), and breast (7.4%, 12/163) being the most frequently affected sites. The non-germinal center B-cell (non-GCB) subtype was prevalent in 63.7% of patients (142/223), with no significant difference between the nodal and extranodal groups ( P=0.681). Furthermore, 73.9% (184/249) and 11.7% (29/249) of patients received the R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and R-miniCHOP regimen, respectively. The overall 3-year PFS rate was 81.5%, and the 3-year OS rate was 85.6%. Patients aged ≥75 years ( HR=2.910, 95% CI 1.565-5.408, P=0.001) and/or with a CCI score ≥2 ( HR=2.324, 95% CI 1.141-4.732, P=0.020) had a significantly poorer PFS. Incorporating age ≥75 years and CCI score ≥2 into the stage-modified international prognostic index (sm-IPI) can better stratify the prognosis of elderly patients with stage Ⅰ DLBCL. The 3-year PFS rate was 48.7% in the high-risk group versus 85.7% in the low-risk group ( P<0.001). Conclusions:Our findings show that the elderly patients with stage Ⅰ DLBCL were predominantly characterized by extranodal involvement (particularly in the stomach and intestinal tract) and non-GCB subtype. Age ≥75 years and CCI ≥2 were identified as independent prognostic factors. The newly established sm-IPI-75-CCI incorporating these factors demonstrated superior prognostic discrimination compared to conventional risk assessment systems.

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.