Objective To investigate the proportions of myeloid-derived suppressor cells(MDSCs)and their subsets,including poly-morphonuclear MDSCs(PMN-MDSCs),early-stage MDSCs(e-MDSCs),monocytic MDSCs(M-MDSCs),and lectin-like oxidized low-density lipoprotein receptor-1(LOX-1)positive PMN-MDSCs,in the peripheral blood of ovarian cancer(OC)patients and ana-lyze their correlations with clinicopathological parameters of the patients.Methods The proportions of MDSCs and their subsets in the peripheral blood of 38 OC patients(OC group)and 46 healthy individuals(healthy control group)were detected by flow cytometry.The levels of serum IL-10 and TGF-β were detected using ELISA.The OC group was further divided into LOX-1 high and low expres-sion subgroups based on the median proportion of LOX-1+PMN-MDSCs in MDSCs.Results The proportions of MDSCs,PMN-MDSCs,and LOX-1+PMN-MDSCs in the peripheral blood mononuclear cells(PBMCs)of the OC group were significantly higher than those in the healthy control group(U=492,P＜0.001;t=8.741,P＜0.000 1;U=223,P＜0.000 1).The proportions of M-MDSCs and e-MDSCs in the OC group were significantly lower than those in the healthy control group(t=4.366,P＜0.000 1;t=6.927,P＜0.000 1).The proportion of LOX-1+PMN-MDSCs in the lymph node metastasis group of OC patients was significantly higher than that in the non-metastasis group(t=2.249,P＜0.05).The levels of serum IL-10 and TGF-β in the OC group were significantly higher than those in the healthy control group(P＜0.05).In addition,the level of serum TGF-β in the LOX-1 high expression group was significantly higher than that in the LOX-1 low expression group(t=2.302,P＜0.05).Conclusion The proportion of LOX-1+PMN-MDSCs in the peripheral blood of OC patients is significantly increased and closely related to lymph node metastasis.

Objective To address the challenges of accurately capturing critical features in small-sample diabetic retinopathy(DR)recognition models in real-world applications,and the overly smooth distribution of true and false feature coefficients,we propose an enhanced small-sample DR recognition method based on an improved capsule network.Methods Firstly,the method enhances image feature representation by removing redundant boundary information and employing discrete wavelet transform based on the Haar wavelet function,thereby high-lighting critical pathological features.Secondly,the convolutional layer of the capsule network is optimized through a multi-branch architecture to extract multi-scale features from retinal images,while incorporating a convolutional block attention module that is subsequently fed into the capsule layer.Finally,the sigmoid function replaces the soft-max function in dynamic routing,thereby improving the model's robustness.Result The enhanced neural network model achieved an accuracy of 98.62%on the Kaggle public dataset following a rigorous selection and preprocessing procedure.Conclusion The enhanced capsule network demonstrated superior precision in identifying diabetic reti-nopathy within small sample sizes compared to other state-of-the-art algorithms currently available.

Objective:To develop a scientific and practical questionnaire for general practice residents, and to conduct multidimensional and comprehensive evaluation of the quality of general practice teaching clinics.Methods:A preliminary draft of the questionnaire items was formulated based on a literature review and in-depth interviews. The Delphi method was employed to conduct two rounds of consultation with 14 experts. Following revisions, a convenience sampling method was used to invite general practice residents from three standardized residency training bases to test the reliability and validity of the questionnaire.Results:The questionnaire consisted of 23 items, covering the three dimensions of preparation, implementation process, and comprehensive evaluation of the teaching clinics. The response rates for the two rounds of the expert consultation were both 100.00%, with expert authority coefficients of 0.89 and 0.90, respectively. The overall Cronbach's α coefficient of the questionnaire was 0.93, and the correlation coefficients between each item score and the total score were all >0.30. Structural validity analysis revealed that three common factors were extracted from the questionnaire, with a cumulative variance contribution rate of 77.89%. Conclusions:The General Practice Teaching Clinic Quality Evaluation Questionnaire for Residents developed in this study demonstrates high reliability and validity. The questionnaire provides a scientific basis for the standardized assessment of teaching quality in general practice clinics. By incorporating resident feedback on the teaching process, the questionnaire promotes the development of a teaching clinic quality improvement mechanism focused on residents and plays a significant role in enhancing the teaching capabilities of supervising physicians in clinics.

Gastric carcinoma(GC),a highly prevalent malignant tumor globally,often progresses to advanced stages by the time of diagnosis due to its insidious clinical presentation,thereby significantly reducing therapeutic effectiveness and patient quality of life.Accurate screening and histopathological characterization of early gastric cancer(EGC)are essential for developing individualized treatment approaches.Although endoscopic techniques remain the gold standard for early GC detection,their diagnostic accuracy is largely dependent on the operator's skill,a challenge that current artificial intelligence(AI)-assisted innovations aim to address by stan-dardizing diagnostic procedures.Deep learning(DL)-based computer vision systems have demonstrated remarkable performance in identifying subtle EGC features,not only improving lesion detection sensitivity but also enabling automated assessment of key pathological indicators.These technological advances offer objective,visualized diag-nostic support for clinical decision-making.This review provides a systematic overview of recent developments in DL applications for endoscopic image analysis of EGC and evaluates their potential for clinical integration.

Gastric carcinoma(GC),a highly prevalent malignant tumor globally,often progresses to advanced stages by the time of diagnosis due to its insidious clinical presentation,thereby significantly reducing therapeutic effectiveness and patient quality of life.Accurate screening and histopathological characterization of early gastric cancer(EGC)are essential for developing individualized treatment approaches.Although endoscopic techniques remain the gold standard for early GC detection,their diagnostic accuracy is largely dependent on the operator's skill,a challenge that current artificial intelligence(AI)-assisted innovations aim to address by stan-dardizing diagnostic procedures.Deep learning(DL)-based computer vision systems have demonstrated remarkable performance in identifying subtle EGC features,not only improving lesion detection sensitivity but also enabling automated assessment of key pathological indicators.These technological advances offer objective,visualized diag-nostic support for clinical decision-making.This review provides a systematic overview of recent developments in DL applications for endoscopic image analysis of EGC and evaluates their potential for clinical integration.

Objective:To explore the predictive value of systemic immune inflammation index combined with stress response index for postoperative urinary tract infection in patients with complicated kidney stones.Methods:From June 2021 to June 2023,97 patients who underwent treatment for urinary tract infection after complex kidney stone operation in Cangzhou Hospital of Integrated Traditional and Western Medicine were selected as infected group,and 87 patients who did not develop urinary tract infection after complex kidney stone operation were selected as uninfected group.Systemic immunoinflammatory index(SII),neutrophils,lympho-cyte,platelet,malondialdehyde(MDA),superoxide dismutase(SOD),catalase(CAT)levels were detected.Multivariate Logistic regression analysis was performed to analyze risk factors of postoperative urinary tract infection,and ROC curve was drawn to analyze the predictive value of SII,MDA,SOD and CAT alone and combined detection for postoperative urinary tract infection in patients with complex kidney stones.Results:Compared with uninfected group,levels of SII,neutrophils and MDA were increased in infected group,while levels of SOD and CAT were decreased(P<0.05).Levels of lymphocytes and platelets were decreased,the difference was not statistically significant(P>0.05).Multivariate Logistic regression analysis showed that presence of urinary tract history,opera-tion time≥100 min,urinary catheter retention time≥7 d,presence of preoperative urinary tract infection,stone load≥1 000 mm2,combined renal dysfunction,and preoperative blood glucose≥6.15 mmol/L were main risk factors for postoperative urinary tract infection in patients with complex kidney stones.ROC curve showed that combined detection was significantly more effective than single detec-tion of SII,MDA,SOD and CAT in the diagnosis of postoperative urinary tract infection in patients with precomplex kidney stones.Conclusion:Patients with urinary tract infection after complicated kidney stones have increased SII and MDA,decreased SOD and CAT levels,and the abnormal increased or decreased expression level are the predictors of risk of urinary tract infection after compli-cated kidney stones,which may be related with the diagnosis,development and prognosis of the disease.

Objective:To analyze the abnormal results of health surveillance for workers exposed to dimethylformamide (DMF), and to provide reference for the formulation of relevant policies and standards.Methods:In April 2024, 11, 224 workers who participated in occupational health examinations in Jiangsu Province in 2023 were selected as the research subjects. Among them, 5, 615 people exposed to DMF were taken as the exposure group, and 5, 609 people not exposed to hepatotoxic chemicals were taken as the control group. By inquiring about related symptoms and combining with the occupational health examination of workers, the abnormal rates of blood pressure, blood routine, urine routine, electrocardiogram, liver function and B-ultrasonography of the survey subjects were statistically analyzed.Results:Compared with the control group, the abnormal detection rates of indicators such as blood pressure, blood routine, urine routine, and electrocardiogram were higher, and the difference was statistically significant P<0.05). The abnormal rates of various liver function indicators in the DMF exposure group were all higher than those in the control group. Among them, the abnormal rates of alanine aminotransferase, total protein, total bilirubin, and liver B-ultrasound in the exposure group were all higher than those in the control group, and the differences were statistically significant ( χ2=34.88, 42.49, 43.07, 55.28, P<0.001). Compared with the control group, the detected values of alanine aminotransferase, total protein and total bilirubin in the DMF exposure group were higher, and the difference was statistically significant ( F=5.367, 29.543, 37.766, P<0.05). In the DMF exposure group, the abnormal rates of liver function, electrocardiogram and liver B-ultrasound in men were much higher than those in women, and the differences were statistically significant ( χ2=185.05, 10.06, 141.94, P<0.001, P=0.002, P<0.001). Grouped by length of service, the abnormal detection rate of liver function was similar in each length of service segment, and the difference was not statistically significant ( χ2=0.34, P>0.05). The abnormal detection rate of electrocardiogram increased with the increase of length of service, among which it was the highest in the 10-20 years of service, and the difference was statistically significant ( χ2=7.26, P=0.026). The abnormal rate detected by liver B-ultrasound significantly increased with the increase of working years, and was the highest in the section of ≥20 years of working years. The difference was statistically significant ( χ2=44.15, P<0.001) . Conclusion:Occupational exposure to DMF can affect the health of workers, especially increasing the detection rate of abnormal liver function and liver B-ultrasound. It is very important to strengthen the occupational health monitoring of personnel exposed to DMF, improve the working environment, and pay attention to the chronic liver damage caused by DMF occupational exposure to workers.

OBJECTIVE To explore the potential mechanisms and bioactive compounds of licorice against COVID-19 based on a multidimensional interaction of"component-disease-symptom-target".METHODS Firstly,candidate target sets for licorice compo-nents were obtained from the ETCM2.0 database based on the Encyclopedia of Traditional Chinese Medicine,and the disease symp-toms and associated target sets for COVID-19 were derived from the GeneCards and HPO databases.And then a protein interaction network was constructed using the String database(version 12.0).By calculating topological eigenvalues and functional enrichment analysis,the potential mechanisms of action were explored.Combined with Schr?dinger molecular docking virtual screening,candidate pharmacodynamic substances were identified.Fluorescence resonance energy transfer was used for experimental verification.RESULTS Licorice might improve symptoms of COVID-19(fever,chest pain and so on)by regulating the imbalance of"immune-inflammation"network and signal transduction abnormalities during the development and progress of COVID-19,such as coronavirus disease-COVID-19,Toll-like receptor signaling pathway and NOD-like receptor signaling pathway.The components,such as Isos-chaftoside and Hesperidin,were identified to possess high binding affinity with the critical enzymes for viral replication.Isoschaftoside,Hesperidin,Isoliquiritin apioside and Vicenin-2 exhibited varying degrees of inhibition on the enzyme of 3CLpro at different concentra-tions while excluding the interference of the compounds' fluorescence.CONCLUSION Through experimental verification using a multidimensional interaction network of"component-disease-symptom-target",the key pharmacologically active substances of licorice in the fight against COVID-19 are preliminarily identified,and their mechanism of action through overall regulation is elucidated.

Microfibrino-associated protein (MFAP) 2 is an extracellular matrix glycoprotein and a member of the MFAP family. It participates in the assembly of extracellular elastic microfibers.Upregulation of MFAP2 can promote the occurrence and development of various tumors and regulate multiple cancer-related signaling pathways and is related to their prognosis, making it a potential target for tumor treatment. This article summarizes the research progress on the pathogenesis, targeted therapy and prognosis of MFAP2 in malignant tumors.

Objective:To explore the predictive value of systemic immune inflammation index combined with stress response index for postoperative urinary tract infection in patients with complicated kidney stones.Methods:From June 2021 to June 2023,97 patients who underwent treatment for urinary tract infection after complex kidney stone operation in Cangzhou Hospital of Integrated Traditional and Western Medicine were selected as infected group,and 87 patients who did not develop urinary tract infection after complex kidney stone operation were selected as uninfected group.Systemic immunoinflammatory index(SII),neutrophils,lympho-cyte,platelet,malondialdehyde(MDA),superoxide dismutase(SOD),catalase(CAT)levels were detected.Multivariate Logistic regression analysis was performed to analyze risk factors of postoperative urinary tract infection,and ROC curve was drawn to analyze the predictive value of SII,MDA,SOD and CAT alone and combined detection for postoperative urinary tract infection in patients with complex kidney stones.Results:Compared with uninfected group,levels of SII,neutrophils and MDA were increased in infected group,while levels of SOD and CAT were decreased(P<0.05).Levels of lymphocytes and platelets were decreased,the difference was not statistically significant(P>0.05).Multivariate Logistic regression analysis showed that presence of urinary tract history,opera-tion time≥100 min,urinary catheter retention time≥7 d,presence of preoperative urinary tract infection,stone load≥1 000 mm2,combined renal dysfunction,and preoperative blood glucose≥6.15 mmol/L were main risk factors for postoperative urinary tract infection in patients with complex kidney stones.ROC curve showed that combined detection was significantly more effective than single detec-tion of SII,MDA,SOD and CAT in the diagnosis of postoperative urinary tract infection in patients with precomplex kidney stones.Conclusion:Patients with urinary tract infection after complicated kidney stones have increased SII and MDA,decreased SOD and CAT levels,and the abnormal increased or decreased expression level are the predictors of risk of urinary tract infection after compli-cated kidney stones,which may be related with the diagnosis,development and prognosis of the disease.