ObjectiveTo analyze the genomic characteristics of Streptococcus pyogenes (GAS) isolated from children with respiratory tract infections in a tertiary hospital in Jinshan District of Shanghai during 2013‒2024, to compare the changes in trend for genomic characteristics before and after 2000, and to provide scientific data for the prevention and control of GAS infections. MethodsGAS strains isolated from children with respiratory tract infections in this hospital were collected from 2013 to 2024. Antimicrobial susceptibility of the isolated strains to 12 antibiotics, including penicillin, cefotaxime, cefepime, linezolid, vancomycin, meropenem, chloramphenicol, ofloxacin, levofloxacin, erythromycin, clindamycin, and tetracycline, was determined using broth microdilution plate method. Besides, whole genome sequencing (WGS) was used to analyze multilocus sequence type (MLST), emm typing, carriage of superantigen genes, mobile genetic element (MGE), carriage of virulence gene, and genomic phylogenetic tree of the isolated strains. ResultsA total of 50 GAS strains were collected and identified from children with respiratory tract infections aged 4‒14 years old, and the resistance rates of those isolates to erythromycin, clindamycin, and tetracycline were 100.00%, 100.00%, and 86.00%, respectively. There were two emm types in the GAS isolates; the emm12 type accounted for 76.00% (38/50), corresponding to ST36 type, and the emm1 type accounted for 24.00% (12/50), corresponding to ST28, ST1274, and new-1 types. There was a statistically significant difference in the constitution of the MLST before and after 2020 (P=0.015). All the isolates carried the superantigen genes speC, speG, ssa, and smeZ. The predominant emm12 isolates belonged to the Clade Ⅱ, carrying the mobile elements ICE-emm12 (harboring erythromycin-resistance gene ermB and tetracycline-resistance gene tetM) and ΦHKU.vir (carrying virulence genes speC and ssa). The emm1 isolates carried the mobile elements ICE-HKU488 (harboring erythromycin-resistance gene ermB and tetracycline-resistance gene tetM) and ΦHKU488.vir (carrying virulence genes speC and ssa), and had close phylogenetical relationships with isolates from Hong Kong, China. No M1_UK new clone strains were found. The ST1274 isolates of emm1 were newly discovered in 2020‒2024, and belonged to a separate phylogenetic clade. ConclusionGAS strains isolated from children with respiratory tract infections in a tertiary hospital in Jinshan District of Shanghai exhibit a high resistance to erythromycin, clindamycin, and tetracycline. It is recommended that the clinical treatments change to use other antimicrobial drugs, such as penicillin, third-generation cephalosporins, and fluoroquinolones. During 2020‒2024, a new ST1274 clone strain is discovered in emm1 GAS isolates, without M1_UK new clone strains being found. It is essential to continuously concern locally prevalent GAS strains and perform early identification of MLST types to promptly monitor the internal changes of the bacterial population and potential prevalence of new clones.

Vascular damage plays a significant role in the onset and progression of Alzheimer's disease (AD). However, the precise molecular mechanisms underlying the induction of neuronal injury by vascular damage remain unclear. The present study aimed to examine the impact of fibrinogen (Fg) on tau pathology. The results showed that Fg deposits in the brains of tau P301S transgenic mice interact with tau, enhancing the cytotoxicity of pathological tau aggregates and promoting tau phosphorylation and aggregation. Notably, Fg-modified tau fibrils caused enhanced neuronal apoptosis and synaptic damage compared to unmodified fibrils. Furthermore, intrahippocampal injection of Fg-modified tau fibrils worsened the tau pathology, neuroinflammation, synaptic damage, neuronal apoptosis, and cognitive dysfunction in tau P301S mice compared to controls. The present study provides compelling evidence linking Fg and tau, thereby connecting cerebrovascular damage to tau pathology in AD. Consequently, inhibiting Fg-mediated tau pathology could potentially impede the progression of AD.
Animals ; tau Proteins/metabolism* ; Alzheimer Disease/metabolism* ; Fibrinogen/metabolism* ; Mice, Transgenic ; Mice ; Disease Models, Animal ; Memory Disorders/metabolism* ; Male ; Mice, Inbred C57BL ; Brain/metabolism* ; Hippocampus/metabolism* ; Protein Aggregation, Pathological/metabolism* ; Apoptosis ; Phosphorylation

Objective: To assess the impact of long-term antiretroviral therapy (ART) on human immunodeficiency virus (HIV) blood screening outcomes in post-exposure prophylaxis (PEP) failure cases through a longitudinal analysis of blood screening results over a 7-year period in a patient with HIV PEP failure. Methods: This study conducted 13 follow-up assessments for a high-risk individual who initiated ART shortly after exposure. The effectiveness of various blood screening methods, including immunological assays and nucleic acid testing (NAT), was analyzed. Blood samples were also tested with HIV RNA quantification testing, Western blot (WB) confirmation testing, chemiluminescence immunoassay (CLIA), and HIV rapid tests utilizing gold and selenium labels. A comprehensive analysis was performed to evaluate the changes in diagnostic capabilities of different testing methods for HIV biomarkers over an extended period following PEP failure. Results: The patient had two high-risk exposures: one day before ART initiation (BA1) and seven days preceding treatment (BA7). On the first day after the ART treatment (AA1), the HIV RNA concentration (viral load) was 9.07×10 copies/mL; by day five (AA5), the viral load decreased to 1.04×10 copies/mL. At day eleven (AA11), NAT and ELISA tests were both positive, with the WB result remaining indeterminate (gp160+). At day 48 (AA48), the S/CO value of the fourth generation ELISA reagent was 1.07, while results from a 6-sample pool and quantitative NAT were negative. However, a single sample NAT returned a positive result and WB tests indicated positivity for p17, p24, and gp160. At AA74, the quantitative NAT rebounded to 2.83×10 copies/mL, with positive NAT results for single and 6-sample pool NAT tests. The S/CO values of the imported and domestic ELISA reagents were 3.39 and 23.44, respectively. At AA201, 6-sample pool and quantitative NAT were negative again, while single sample NAT remained positive. From AA319 to AA2221, all NAT results have remained consistently below the minimum detection limit. At AA2221, S/CO values of the imported and domestic ELISA reagents were 3.47 and 23.44, respectively. Conclusion: The findings indicate that patients experiencing PEP failure after high-risk HIV exposure are at a higher risk of being missed by mixed-sample NAT pools and individual serological tests. Nonetheless, anti-HIV antibody levels are sustained at elevated values for an extended duration, underscoring antibody testing as an effective measure for blood screening.

Objective To build a dataset encompassing a large number of stained tongue coating images and process it using deep learning to automatically recognize stained tongue coating images. Methods A total of 1 001 images of stained tongue coating from healthy students at Hunan University of Chinese Medicine and 1 007 images of pathological(non-stained)tongue coat-ing from hospitalized patients at The First Hospital of Hunan University of Chinese Medicine with lung cancer,diabetes,and hypertension were collected.The tongue images were randomi-zed into the training,validation,and testing datasets in a 7:2:1 ratio.A deep learning model was constructed using the ResNet50 for recognizing stained tongue coating in the training and validation datasets.The training period was 90 epochs.The model's performance was evaluated by its accuracy,loss curve,recall,F1 score,confusion matrix,receiver operating characteristic(ROC)curve,and precision-recall(PR)curve in the tasks of predicting stained tongue coating images in the testing dataset.The accuracy of the deep learning model was compared with that of attending physicians of traditional Chinese medicine(TCM). Results The training results showed that after 90 epochs,the model presented an excellent classification performance.The loss curve and accuracy were stable,showing no signs of overfitting.The model achieved an accuracy,recall,and F1 score of 92%,91%,and 92%,re-spectively.The confusion matrix revealed an accuracy of 92%for the model and 69%for TCM practitioners.The areas under the ROC and PR curves were 0.97 and 0.95,respectively. Conclusion The deep learning model constructed using ResNet50 can effectively recognize stained coating images with greater accuracy than visual inspection of TCM practitioners.This model has the potential to assist doctors in identifying false tongue coating and prevent-ing misdiagnosis.

ObjectiveTo investigate the genotyping and drug resistance trends of 461 strains of diarrheagenic Escherichia coli (DEC) isolated and identified in Suzhou, Jiangsu Province from 2019 to 2023. MethodsDEC detected in Suzhou in the past 5 years was used as the research subject, and the virulence genotyping was tested by real-time fluorescence quantitative polymerase chain reaction (PCR). The microbroth dilution method was used to perform drug susceptibility test, and the corresponding susceptibility (S), intermediate (I) and resistance (R) results were obtained based on the minimum inhibitory concentration (MIC) values, according to the criteria of United States Clinical and Laboratory Standardization Committee (CLSI) 2017. Differences of DEC drug resistance among different virulence genotypes were compared by χ² test or Fisher exact probability method. ResultsA total of 461 DEC strains were detected in Suzhou from 2019 to 2023, of which the highest proportion was enterotoxigenic Escherichia coli (ETEC) accounting for 45.77% (211/461), followed by enteropathogenic Escherichia coli (EPEC) accounting for 32.32% (149/461) and enteroaggregative Escherichia coli (EAEC) accounting for 20.39% (94/461), while enterohemor-rhagic Escherichia coli (EHEC) and enteroinvasive Escherichia coli (EIEC) were individually distributed. The antimicrobial drug with the highest resistance rate was ampicillin (61.61%), followed by cefazolin (49.89%) and nalidixic acid (44.47%). There were statistically significant differences in drug resistence rates of the three major virulence genotypes of DEC (ETEC, EPEC and EAEC) to ampicillin (AMP), ampicillin/sulbactam (AMS), amoxicillin/clavulanic acid (AMC), cefoxetine (CFX), gentamicin (GEN), streptomycin (STR), tetracycline (TET), nalidixic acid (NAL), and chloramphenicol (CHL), and methotrexate/sulfamethoxazole (SXT). The multi-drug resistance (MDR) rate of DEC was 59.87% (276/461), and the MDR rate of each genotype, from high to low, was EIEC (75.00%), EAEC (71.28%), EHEC (66.66%), EPEC (61.74%) and ETEC (52.86%). ConclusionETEC, EPEC and EAEC are the main genotypes prevalent in DEC in Suzhou in recent years. The drug resistance strains and MDR are still serious, which should arouse wide public health concern and take targeted prevention and control measures.

More than 70%of tumor patients require radiotherapy.Medical electron linear accelerators are important high-end radiotherapy equipment for tumor radiotherapy.With the application of artificial intelligence technology in medical electron linear accelerator,radiotherapy has evolved from ordinary radiotherapy to today's intelligent radiotherapy.This study introduces the development history,working principles and system composition of medical electron linear accelerators.It outlines the key technologies for improving the performance of medical linear electron accelerators,including beam control,multi-leaf collimator,guiding technology and dose evaluation.It also looks forward to the development trend of major radiotherapy technologies,such as biological guided radiotherapy,FLASH radiotherapy and intelligent radiotherapy,which provides references for the development of medical electron linear accelerators.

Objective To investigate the relationship between systemic immune-inflammation index (SII)and lower extremity vascular disease in patients with type 2 diabetes mellitus (T2DM).Methods A cross-sectional study was conducted on 390 T2DM patients admitted in our department from January 2013 to January 2024.According to the diagnostic criteria for lower extremity vascular disease in T2DM patients,they were divided into a lower extremity vascular disease group (n=158)and a control group (n=232).General data and results of laboratory tests were compared between the 2 groups.Spearman correlation analysis was used to identify the related factors for lower extremity vascular diseases in T2DM patients.The correlation between SII and lower extremity vascular diseases in T2DM patients was analyzed using the Row Mean Scores and Cochran-Armitage Trend analysis.Multivariate logistic regression analysis was applied to identify the risk factors for lower limb vascular lesions in T2DM patients.Receiver operating characteristic (ROC)curve was plotted to evaluate the diagnostic efficacy of SII for lower extremity vascular disease in the patients.Results Compared with T2DMpatients without lower extremity vascular disease,those with lower extremity vascular disease were older,had higher levels of total cholesterol (TC),low-density lipoprotein cholesterol (LDL-C),SII,larger proportion of carotid vascular lesions,and increased proportion of no-taking statins.The lower extremity vascular disease in T2DM patients was positively correlated with SII/100 (r=0.429,P<0.001),age (r=0.517,P<0.001),TC (r=0.161,P=0.001),LDL-C (r=0.117,P=0.021),carotid artery lesions (r=0.101,P=0.047),no-taking statins (r=0.266,P<0.001).Logistic regression analysis showed that SII,age,LDL-C,and no-taking statins were the risk factors for lower extremity vascular lesions in T2DM patients (P<0.01).The area under the curve (AUC)value of SII combined with age,LDL-C,and no-taking statins in predicting lower extremity vascular disease in T2DM patients was 0.896.Conclusion SII is not only a risk factor,but also a simple marker for lower extremity vascular disease in T2DM patients,suggesting that inflammatory response plays an important role in the occurrence and development of lower extremity vascular disease in T2DM.

Objective:To understand the real experience and needs of early exercise rehabilitation in elderly patients with total hip arthroplasty (THA), so as to provide a preliminary basis for intervention research to meet the needs of patients.Methods:Using the purposive sampling method, a total of 12 elderly patients with THA from the First Affiliated Hospital of Naval Medical University from June to September 2021 were selected as the research objects for semi-structured in-depth interviews. Colaizzi 7-step method was used to analyze, summarize and extract the data.Results:The early exercise rehabilitation experience and needs of elderly THA patients could be summarized into four themes such as postoperative exercise being a difficult journey, the need for professional support, the need for external support and internally driven needs and 14 sub themes.Conclusions:There are various problems and needs for early exercise rehabilitation in elderly patients undergoing THA. It is necessary to strengthen communication among doctors, nurses and patients, understand their true feelings and provide personalized care and rehabilitation guidance to improve their treatment experience and enhance their satisfaction.

Objective:To analyze the differences in whole blood selenium (Se), zinc (Zn), copper (Cu), magnesium (Mg), calcium (Ca), and iron (Fe) levels of rural older adults among areas with different soil selenium levels, and explore the main factors associated with the six nutrient elements status, so as to provide a basis for further evaluating the health risks of people in areas with different soil selenium levels.Methods:Four administrative villages were randomly selected from the Se-deficient (soil Se content < 0.175 mg/kg), Se-sufficient (soil Se content 0.175 - < 0.400 mg/kg), Se-rich (soil Se content 0.400 - < 3.000 mg/kg) and Se-excessive (soil Se content ≥3.000 mg/kg) areas, respectively, in Enshi Tujia and Miao Autonomous Prefecture (Enshi Prefecture) of Hubei Province in 2017 - 2018. And 100 elderly people aged 60 years or older (half male and half female) were randomly selected as the survey subjects in each servey site. The basic information such as general demography and lifestyle was collected through face-to-face questionnaires. Physical examination was performed and fasting venous blood was collected in the morning. The contents of blood Se, Zn, Cu, Mg, Ca, and Fe were determined by inductively coupled plasma mass spectrometry. The main factors associated with the six nutrient elements status were analyzed.Results:A total of 416 subjects were included, including 208 males and 208 females, whose average age was (72.43 ± 5.25) years, and body mass index (BMI) was (22.67 ± 3.49) kg/m 2. There were significant differences of blood Se, Zn, Cu, Mg, Ca and Fe levels between the areas with different Se levels ( Z/F = 288.30, 3.24, 14.81, 29.14, 131.28, 3.37, P < 0.05). Compared with Se-deficient and Se-sufficient areas, blood Se level was higher in Se-rich and Se-excessive areas and blood Zn level was lower in Se-excessive area ( P < 0.05); compared with Se-sufficient area, blood Cu level was lower in Se-deficient, Se-rich and Se-excessive areas, but blood Mg and Ca levels were higher ( P < 0.05), and the blood Fe level was lower in Se-excessive area ( P < 0.05). There were significant differences in the deficiency rates of Se, Zn, Cu, Mg, Ca and Fe among the elderly in different Se level areas (χ 2 = 140.83, 15.39, 31.90, 17.49, 157.60, 30.33, P < 0.01). There were significant differences in blood Zn, Cu, Ca and Fe levels between two gender groups ( P < 0.05); the blood Zn and Fe levels of the smokers were higher than those of the non-smokers, and the blood Cu level was lower than that of the non-smokers ( P < 0.05); the blood Zn and Fe levels of the drinkers were higher than those of the non-drinkers ( P < 0.05). Conclusions:The levels of six nutrient elements in the whole blood of the elderly in areas with different soil Se levels are different. To assess the health risks of the population in areas with different soil Se levels, it is necessary to consider the levels of multiple nutrient elements at the same time.