Gut microbial communities are likely remodeled in tandem with accumulated physiological decline during aging, yet there is limited understanding of gut microbiome variation in advanced age. Here, we performed a metagenomics-based enterotype analysis in a geographically homogeneous cohort of 367 enrolled Chinese individuals between the ages of 60 and 94 years, with the goal of characterizing the gut microbiome of elderly individuals and identifying factors linked to enterotype variations. In addition to two adult-like enterotypes dominated by Bacteroides (ET-Bacteroides) and Prevotella (ET-Prevotella), we identified a novel enterotype dominated by Escherichia (ET-Escherichia), whose prevalence increased in advanced age. Our data demonstrated that age explained more of the variance in the gut microbiome than previously identified factors such as type 2 diabetes mellitus (T2DM) or diet. We characterized the distinct taxonomic and functional profiles of ET-Escherichia, and found the strongest cohesion and highest robustness of the microbial co-occurrence network in this enterotype, as well as the lowest species diversity. In addition, we carried out a series of correlation analyses and co-abundance network analyses, which showed that several factors were likely linked to the overabundance of Escherichia members, including advanced age, vegetable intake, and fruit intake. Overall, our data revealed an enterotype variation characterized by Escherichia enrichment in the elderly population. Considering the different age distribution of each enterotype, these findings provide new insights into the changes that occur in the gut microbiome with age and highlight the importance of microbiome-based stratification of elderly individuals.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Bacteroides ; China ; Diabetes Mellitus, Type 2/microbiology* ; Escherichia coli/classification* ; Gastrointestinal Microbiome/genetics* ; Metagenomics ; East Asian People

Objective To investigate the correlation between serum vascular endothelial growth factor(VEGF)level and the development and severity of diabetes mellitus cystoid macular edema(CME).Methods A total of 57 patients(57 eyes)with diabetic CME(the case group)and diabetes without eye complications(the control group)admitted to the Vitreoretinal Surgery Department of Tangshan Eye Hospital from June 2023 to June 2024 were prospectively selected,and all of them underwent systematic ophthalmic specialty examination and serum VEGF detection.Multivariate Logistic regression analysis was used to identify the risk factors of diabetes mellitus CME.The diagnostic value of VEGF in patients with diabetes CME was analyzed by receiver operating characteristic(ROC)curve.Spearman correlation was used to analyze the relationship between VEGF levels and the severity of CME in patients with diabetes,such as corrected visual,number of cystoid edema and non-round index of macular foveal avascular zone(FAZ).Results Compared with the control group,the course of diabetes in the case group was longer,the incidence of hypertension was higher,levels of glycosylated hemoglobin(HbA1c),serum creatinine and serum VEGF were higher,and the estimated glomerular filtration rate(eGFR)was lower(P＜0.05).Multivariate Logistic regression results showed that long duration of diabetes,increased levels of HbA1c and VEGF were risk factors for CME in diabetes mellitus patients,while elevated eGFR was protective factor(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of VEGF in diagnosing diabetes mellitus CME was 0.758(95%CI:0.669-0.834).The AUC of the combined application of diabetes duration,HbA1c,eGFR and VEGF in the diagnosis of diabetes mellitus CME was 0.916(95%CI:0.877-0.941),which was significantly higher than that of the application of VEGF alone(P＜0.05).The VEGF level was negatively correlated with the corrected visual acuity[0.34(0.24,0.44)]in patients with diabetic CME,and positively correlated with the detection of cystoid macular edema[3(2,5)]and FAZ non-roundness index[1.16(1.08,1.20)](rs were 0.771,0.700,respectively,P＜0.05).Conclusion Serum VEGF levels are closely related to the onset and severity of CME,and which can be used as a reliable reference index for the diagnosis of CME.

Objective To investigate the correlation between serum vascular endothelial growth factor(VEGF)level and the development and severity of diabetes mellitus cystoid macular edema(CME).Methods A total of 57 patients(57 eyes)with diabetic CME(the case group)and diabetes without eye complications(the control group)admitted to the Vitreoretinal Surgery Department of Tangshan Eye Hospital from June 2023 to June 2024 were prospectively selected,and all of them underwent systematic ophthalmic specialty examination and serum VEGF detection.Multivariate Logistic regression analysis was used to identify the risk factors of diabetes mellitus CME.The diagnostic value of VEGF in patients with diabetes CME was analyzed by receiver operating characteristic(ROC)curve.Spearman correlation was used to analyze the relationship between VEGF levels and the severity of CME in patients with diabetes,such as corrected visual,number of cystoid edema and non-round index of macular foveal avascular zone(FAZ).Results Compared with the control group,the course of diabetes in the case group was longer,the incidence of hypertension was higher,levels of glycosylated hemoglobin(HbA1c),serum creatinine and serum VEGF were higher,and the estimated glomerular filtration rate(eGFR)was lower(P＜0.05).Multivariate Logistic regression results showed that long duration of diabetes,increased levels of HbA1c and VEGF were risk factors for CME in diabetes mellitus patients,while elevated eGFR was protective factor(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of VEGF in diagnosing diabetes mellitus CME was 0.758(95%CI:0.669-0.834).The AUC of the combined application of diabetes duration,HbA1c,eGFR and VEGF in the diagnosis of diabetes mellitus CME was 0.916(95%CI:0.877-0.941),which was significantly higher than that of the application of VEGF alone(P＜0.05).The VEGF level was negatively correlated with the corrected visual acuity[0.34(0.24,0.44)]in patients with diabetic CME,and positively correlated with the detection of cystoid macular edema[3(2,5)]and FAZ non-roundness index[1.16(1.08,1.20)](rs were 0.771,0.700,respectively,P＜0.05).Conclusion Serum VEGF levels are closely related to the onset and severity of CME,and which can be used as a reliable reference index for the diagnosis of CME.

[Objective]To discuss the appearance of overseas dissemination of traditional Chinese medicine(TCM)in Zhejiang during the Republic of China era from the perspective of publications,and reveal the contribution of Zhejiang to the overseas dissemination of TCM.[Methods]Using literature research and historical research methods,the article sorts out the publishing characteristics and representative achievements of Zhejiang TCM books and periodicals during the Republic of China era,and analyzes the situation of overseas dissemination of Zhejiang TCM academic publications during the period.[Results]During the Republic of China era,medical experts in Zhejiang sought to enhance the global influence of TCM by compiling TCM textbooks,publishing integrated Chinese and western works,editing large-scale TCM series,and translating representative TCM publications.They further strengthened the dissemination of TCM overseas by promoting the sale of Zhejiang TCM journals abroad,placing advertisements overseas,and preserving TCM texts overseas.[Conclusion]The role of Zhejiang's TCM publications in the dissemination of TCM abroad during the Republic of China era cannot be ignored.It not only promotes the cross-border dissemination of TCM knowledge,but also further enhances the world's recognition of the scientific value of TCM,which is enlightening for building a new era of foreign dissemination discourse system with Zhejiang characteristics.

In response to the challenges of small scale and huge labor cost in biomedical feature modeling in current skin disease assisted diagnosis,as well as the inability to accurately describe the time series of patient disease features,a fusion text classification algorithm is used to integrate commonly used text classification models(TextLSTM,TextCNN,and RCNN)to obtain a model based on transfer learning and neural networks(TLNN model).By extracting the medical features of image sensors and quantizing them,the pretreatment reduces the number of foci and eliminates the feature information with large deviations,thus improving the accuracy of decision data.TLNN model achieves an accuracy of 72.36%on ISIC2018 and PH2 datasets,which is higher than those of the other 3 text classification models.The diagnostic accuracy of TLNN model is close to doctor's diagnosis(92%vs 94%),but the effective diagnostic efficiency is significantly higher than doctor's diagnosis(1.17 min/case vs 4.57 min/case),and the overall efficiency is improved by 290%.The results demonstrate that the fusion text classification algorithm model can obtain accurate diagnosis in less time than the traditional manual diagnosis.TLNN model can be applied to disease diagnosis,and assist doctors in medical decision-making,thereby providing patients with high-quality and convenient intelligent diagnosis and treatment services.

Objective:Parathyroidectomy(PTX)is an effective treatment for refractory secondary hyperparathyroidism(SHPT),but it can lead to hungry bone syndrome(HBS),significantly threatening the health of maintenance haemodialysis(MHD)patients.While previous studies have analyzed the risk factors for HBS post-PTX,the predictive performance and clinical applicability of these risk models need further validation.This study aims to construct and validate a risk prediction model for HBS in MHD patients with SHPT post-PTX. Methods:A retrospective analysis was conducted on 368 MHD patients with SHPT who underwent PTX at Changsha Jieao Nephrology Hospital from January 2020 to December 2021.Patients were divided into a HBS group and a non-HBS group based on the occurrence of HBS.General data,surgical information,and biochemical indicators were compared between the 2 groups.Multivariate logistic regression was used to identify factors influencing HBS,and a risk prediction model was established.The model's performance was evaluated using receiver operator characteristic(ROC)curves,decision curves,and calibration curves.External validation was performed on 170 MHD patients with SHPT who underwent PTX at the Third Xiangya Hospital of Central South University from January to December 2022. Results:The incidence of HBS post-PTX in MHD patients with SHPT was 60.60%.Logistic regression analysis identified preoperative bone involvement(OR=3.908,95%CI 2.179 to 7.171),preoperative serum calcium(OR=7.174,95%CI 2.291 to 24.015),preoperative intact parathyroid hormone(iPTH)(OR=1.001,95%CI 1.001 to 1.001),preoperative alkaline phosphatase(ALP)(OR=1.001,95%CI 1.000 to 1.001),and serum calcium on the first postoperative day(OR=0.006,95%CI 0.001 to 0.038)as independent risk factors for HBS(all P<0.01).The constructed risk prediction model demonstrated good predictive performance in both internal and external validation cohorts.The internal validation cohort showed an accuracy of 0.821,sensitivity of 0.890,specificity of 0.776,Youden index of 0.666,and area under the curve(AUC)of 0.882(95%CI 0.845 to 0.919).The external validation cohort showed an accuracy of 0.800,sensitivity of 0.806,specificity of 0.799,Youden index of 0.605,and AUC of 0.863(95%CI 0.795 to 0.932). Conclusion:Preoperative bone involvement,serum calcium,iPTH,ALP,and serum calcium on the first postoperative day are influencing factors for HBS in MHD patients with SHPT post-PTX.The constructed risk prediction model based on these factors is reliable.

Male ; Humans ; Liquid Chromatography-Mass Spectrometry ; Chromatography, Liquid ; Tandem Mass Spectrometry ; Varicocele/diagnosis* ; Biomarkers

ObjectiveTo determine the serum antibody level and risk factors in the adolescent population in a county in Zhejiang Province， following the immunization with inactivated COVID-19 vaccine， and to construct a prediction model for antibody concentration. MethodsWe conducted the study in a county in Zhejiang Province， employing a stratified cluster random sampling strategy in school children who had received the inactivated COVID-19 vaccine. Data on gender， age， type of vaccine， and time of vaccination was collected. Serum samples were also collected to test for anti-S and N IgG antibody against the SARS-CoV-2 by using chemiluminescent immunoassay （CLIA）. Risk factors were determined to construct a prediction model for antibody concentration. ResultsThe IgG antibody concentration was significantly higher in girls， those who received two doses， and those who had simply received the KX vaccine . It decreased with age and time interval between the sampling and last vaccination. The prediction model constructed by random forest regression in the study had a better model fit and predictive ability than that by the multivariable linear stepwise regression. ConclusionGender， age， vaccination dose， type of vaccine， and time of vaccination are associated with vaccination effectiveness of inactivated COVID-19 vaccines in adolescents. Prediction model could predict the antibody level in the vaccinated population， which can provide a new tool for better evaluation of vaccination effectiveness against emerging infectious diseases in future.

ObjectiveAntibiotic resistance genes （ARGs） have received wide attention all over the world. The purpose of this study was to explore the bacterial community structure， the types and levels of antibiotic resistance genes in a water body in east China， and to compare and analyze the characteristics of microbial species distribution and antibiotic resistance gene distribution in various water environments. MethodsA total of 10 households in Haimen City， Jiangsu Province were selected and their surrounding water environment samples were collected. 21 water samples including river water （4）， Mingou water （9） and well water （8） were collected for metagenomics sequencing， assembled with MetaWRAP， annotated with CARD database， and analyzed with R software. ResultsIn various water bodies， the dominant bacteria phyla was Proteobacteria， the dominant bacteria genera were Deuterostomia， Pseudomonas， Flavobacteriales and Streptomycetaceae. The ARGs annotated were mainly composed of quinolones， aminoglycosides， macrolides and beta-lactams antibiotic resistance genes. The top four relative abundance of resistance genes were macB， RanA， evgS and TxR， The average absolute abundance and expression of resistance genes in well water and Mingou water were higher than those in river water. ConclusionMultiple ARGs are detected to varying degrees in well water， river water， and Mingou water bodies， and the expression of resistance genes in well water and Mingou water bodies is higher than that in river water bodies， possibly due to human production and living activities.

Aerosol microorganisms are important constituents of aerosols. They participate in physical and chemical reactions in the air and are also closely related to disease transmission and human health. With the SARS-CoV-2 pandemic， aerosol microorganisms have become a public health topic of great concern. Studying the composition and influencing factors of the air microbiome therefore has significant public health implications. Due to the limitations of traditional technologies for sampling and determination， the aerosol microbiome has not been fully understood. However， with the development and maturity of high-throughput sequencing technology， the aerosol microbiome has shown promising research prospects. This article reviews the composition， characteristics， detection methods and influencing factors of aerosol microorganisms， providing basic knowledge for further research on the air microbiome. In-depth research on microbial aerosols has significant implications on urban air quality control， national security and public health.