ObjectiveTo find out whether there is any difference in the monitoring results of mosq-ovitraps placed in different orientations in multi-storey residential areas, so as to provide a scientific basis for routine and emergency monitoring of Aedes albopictus with mosq-ovitraps in residential areas. MethodsFrom July 6th to October 26th 2023, one mosquito ovitrap was set up in each of the 4 orientations of east, south, west and north around the buildings in a multi-storey residential area in Jinhui Town, Fengxian District, Shanghai. Data was collected and recorded 72 hours after placement. The chi-square test was used to compare the mosquito ovitrap indices (MOIs) of two independent samples, and the Kruskal⁃Wallis H test was used to compare the MOIs of multiple independent samples. ResultsAfter 16 weeks of surveillance, 997 mosquito ovitraps were recovered, of which 211 were positive, with the mosquito ovitrap index (MOI) of 21.16% and the Aedes albopictus density index of 1.03 mosquitoes·ovitrap^-1. The MOIs were higher in September (24.22%) and October (23.96%), and the MOIs in the west, south and north within the two months were all above 20.00%. From July to October, the MOIs in the east, west, south and north were 20.70%, 22.20%, 25.50% and 16.20%, respectively, and the difference in MOIs among the 4 orientations was not statistically significant (χ²=6.647, P=0.084). Stratified analysis by month showed that in August, the south side of the multi-storey residential areas had the highest MOI (31.30%), the north side had the lowest MOI (1.30%), and there was a statistically significant difference in MOI in the east, west, south and north (χ²=25.986, P<0.001). In October, the MOI in the west was the highest (33.30%) and the MOI in the east was the lowest (6.30%), the difference in MOIs of the 4 orientations was statistically significant (χ²=12.007, P=0.007). The MOIs in the south side of the building in the outskirts of the residential area from the 1st week in July to the 4th week in October was lower (19.20%) than that in the south side of the inner building (31.70%), and the difference in MOI was statistically significant (χ²=5.118, P=0.024). ConclusionThe study of MOI in different orientations in a multi-storey residential area is a preliminary exploration based on field work, and the results show that there is a difference in MOIs in different orientations during the peak breeding period of mosquitoes. Further indicators such as temperature, humidity and wind speed in different orientations can be collected to explore the influencing factors of MOIs.

Objective To investigate the effects of Echinococcus multilocularis infection on levels of memory T (Tm) cells and their subsets in lymph nodes of mice at different stages of infection, so as to provide new insights into immunotherapy for alveolarechinococcosis. MethodsTwenty-four C57BL/6J mice aged 6 to 9 weeks were randomly divided into the infection group and the control group, of 12 mice in each group. Mice in the infection group were administered with 3 000 E. multilocularis protoscoleces via portal venous injection, while animals in the control group were administered with an equal volume of physiological saline. Three mice from each group were sacrificed 4, 12 weeks and 24 weeks post-infection, and lymph nodes were sampled and stained with hematoxylin and eosin (HE) to investigate the histopathological changes of mouse lymph nodes in the infection group. The expression and localization of T lymphocyte surface markers CD3, CD4, and CD8 were observed in mouse lymph nodes using immunohistochemical staining. In addition, lymphocyte suspensions were prepared from mouse lymph nodes in both groups at different time points post-infection, and the levels of Tm cell subsets and their secreted cytokines were detected using flow cytometry. Results HE staining showed diffuse structural alterations in the subcapsular cortical and paracortical regions of mouse lymph nodes in the infection group 4 weeks post-infection with E. multilocularis. Immunohistochemical staining detected CD3, CD4 and CD8 expression in mouse lymph nodes in both groups. Flow cytometry revealed higher proportions of CD4⁺ Tm cells [(55.3 ± 4.8)% vs. (38.8 ± 6.1)%; t = -4.259, P < 0.05] and CD4⁺ tissue-resident Tm (Trm) cells [(57.7 ± 3.7)% vs. (34.1 ± 11.2)%; t = -3.990, P < 0.05] in mouse lymph nodes in the infection group than in the control group 4 weeks post-infection, and higher proportions of CD4⁺ Tm cells [(34.6 ± 3.2)% vs. (23.3 ± 7.5)%; t = -2.764, P < 0.05] and CD4⁺ Trm cells [(44.0 ± 1.9)% vs. (31.2 ± 1.5)%; t = -4.039, P < 0.05] in mouse lymph nodes in the infection group than in the control group 24 weeks post-infection. The proportions of CD8⁺ Tm cells were higher in the infection group than in the control group 4 weeks [(56.8 ± 2.7)% vs. (43.9 ± 5.2)%; t = -4.416, P < 0.01] and 12 weeks post-infection [(25.4 ± 2.7)% vs. (12.0 ± 2.6)%; t = -2.552, P < 0.05], while the proportions of tumor necrosis factor (TNF)-α⁺ CD4⁺ T cells [(15.7 ± 5.0)% vs. (49.4 ± 6.4)%; t = 7.150, P < 0.01], TNF-α⁺CD8⁺ T cells [(20.7 ± 5.5)% vs. (57.5 ± 8.4)%; t = -6.694, P < 0.01], and TNF-α⁺ CD8⁺ Tm cells [7.0% (1.0%) vs. 31.0% (11.0%); Z = -2.236, P < 0.05] were lower in the infection group than in the control group 24 weeks post-infection. Conclusions Tm cells levels are consistently increased in lymph nodes of mice at different stages of E. multilocularis infection, with Trm cells as the predominantly elevated subset. The impaired capacity of CD8⁺ Tm cells to secrete the effector molecule TNF-α in mouse lymph nodes at the late-stage infection may facilitate chronic parasitism of E. multilocularis.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

OBJECTIVE: To investigate the association of various polycyclic aromatic hydrocarbon (PAH) metabolites with diverse subtypes of cardiovascular disease (CVD) risk. METHODS: A novel predicting risk of cardiovascular disease EVENTs PREVENT equation was used to estimate the 10-year diverse subtypes of CVD risk, and their associations with PAH metabolites were analyzed using multiple logistic regression models, the weighted quantile sum (WQS) model, the quantile g-computation (qgcomp) model, and a stratified analysis of subgroups. RESULTS: For this study, six thousand seven hundred and forty-five participants were selected, and significant positive associations were observed between PAHs, naphthalene (NAP), and fluorene (FLU), and the risks of total CVD, atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). NAP and FLU were the primary contributors to the effects of PAH mixtures, and their associations with total CVD, ASCVD, and HF risk were significant in younger participants (30 ≤ age < 50 years); however, the associations of phenanthrene (PHEN) with ASCVD, HF, coronary heart disease (CHD), and stroke were dominant in aging participants (age ≥ 50 years). Notably, pyrene (PYR) was negatively associated with the risk of ASCVD, HF, CHD, and stroke. Similarly, negative associations of PYR with the four CVD subtypes were noticeable in aging participants. CONCLUSION Different PAHs metabolites had different impacts on each CVD subtype among different age groups. Notably, the protective effects of PYR on ASCVD, HF, CHD, and stroke were noticeable in aging individuals.
Humans ; Cardiovascular Diseases/chemically induced* ; Middle Aged ; Polycyclic Aromatic Hydrocarbons/metabolism* ; Male ; Female ; Adult ; Aged ; Risk Factors ; China/epidemiology*

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective In this study,we analyzed the transcriptome sequences of Kupffer cells exposed to simulated microgravity for 3 d and conducted biological experiments to determine how microgravity initiates apoptosis in Kupffer cells. Methods Rotary cell culture system was used to construct a simulated microgravity model.GO and KEGG analyses were conducted using the DAVID database.GSEA was performed using the R language.The STRING database was used to conduct PPI analysis.qPCR was used to measure the IL1B,TNFA,CASP3,CASP9,and BCL2L11 mRNA expressions.Western Blotting was performed to detect the level of proteins CASP3 and CASP 9.Flow cytometry was used to detect apoptosis and mitochondrial membrane cells.Transmission electron microscopy was used to detect changes in the ultrastructure of Kupffer cells. Results Transcriptome Sequencing indicated that simulated microgravity affected apoptosis and the inflammatory state of Kupffer cells.Simulated microgravity improved the CASP3,CASP9,and BCL2L11 expressions in Kupffer cells.Annexin-V/PI and JC-1 assays showed that simulated microgravity promoted apoptosis in Kupffer cells.Simulated microgravity causes M1 polarization in Kupffer cells. Conclusion Our study found that simulated microgravity facilitated the apoptosis of Kupffer cells through the mitochondrial pathway and activated Kupffer cells into M1 polarization,which can secrete TNFA to promote apoptosis.

Objective:To explore the application of viral load (VL) testing in human immunodeficiency virus (HIV) antibody screening positive but western blot (WB) negative samples, provide scientific basis for laboratory diagnosis of such populations.Methods:For the HIV antibody retest samples from the initial screening laboratory of Zaozhuang City Center for Disease Control and Prevention from 2021 to 2023, as well as samples from the voluntary counseling and testing at outpatient clinic of our unit that showed a negative WB test result, VL and CD4 + T lymphocyte counts were tested. Four weeks later, the patients were followed up and blood samples were collected by the current district (city) Center for Disease Control and Prevention, and sent to the confirmation laboratory for confirming testing. Results:Among the thirty-two patients, there were fifteen cases with target not detected (TND) by using VL. After four weeks, the follow-up results were all negative. There was one case with a VL test result of 20-5 000 copies/ml, and after four weeks, the follow-up result was positive. There were sixteen cases with a VL test result of >5 000 copies/ml. After four weeks, the follow-up results were all positive. Person correlation analysis was conducted between the log value of VL and CD4 + T lymphocyte count, and the result showed a certain degree of negative correlation ( r=-0.63, P=0.006). Conclusions:VL testing can assist in distinguishing patients with positive HIV antibody screening and negative WB results, and VL testing and WB testing should complement each other, combined with CD4 + T lymphocyte count and epidemiological history to make a diagnosis.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective To identify inflammation-related genes in atrial fibrillation(AF)and explore the possible role and mechanism of these genes and infiltrating immune cells in the development of AF.Methods A series of bioinformatics analysis combined with machine learning algorithms to identify biomarkers of AF,the receiver operating characteristic(ROC)curves were used to verify the prediction and diagnostic value of key genes,and Spearman correlation analysis was used to clarify the correlation between key genes and infiltrating immune cells.Results 593 differential genes(| log2(fold change,FC)|>1,P<0.05),7 immune cell subtypes(P<0.05)were selected,190 immune-related differential genes were obtained,3 biomarkers(IGF1,PTGS 2 and PPARG),and the correlation analysis showed that 3 markers were significantly associated with infiltrating immune cells(P<0.05).Conclusion IGF1,PTGS2 and PPARG are inflammation-related genes of AF,which are speculated to be closely related to the process and pathway of immune cell infiltration.