Objective : To investigate the expression and clinical significance of kynurenine-3-monooxygenase (KMO) in peripheral blood mononuclear cells ( PBMC ) ，synovial tissue ，and fibroblastic-like synovial cells (FLS) of rheumatoid arthritis (RA) patients． Methods : Peripheral blood samples from 25 healthy control ( HC) individuals and 25 patients diagnosed with RA were collected ，and real-time fluorescence quantitative PCR and Western blot were used to detect KMO gene and protein expression in PBMC of RA and HC groups，and to analyze the correlation between the expression level of the KMO gene in the PBMC of the RA patients and the indexes of the laboratory tests．Meanwhile，immunohistochemistry and immunofluorescence were used to detect KMO expression in synovial tissue and FLS in RA and HC groups． Results : ① KMO gene and protein expression in PBMC of RA group were higher than that of HC group，and the difference was statistically significant (P＜0. 001) ．② The level of KMO gene expression in PBMC of RA group was positively correlated with disease activity index 28 score，blood sedimentation，and rheumatoid factor (rs = 0. 417，P = 0. 038 ; r = 0. 545，P = 0. 005 ; rs = 0. 433，P = 0. 031) ， and had no correlation with C-reactive protein and anti-cyclic citrullinated polypeptide antibody．③ KMO expres- sion in synovial tissue of RA group was higher than that of HC group，and the difference was statistically significant (P＜0. 01) ; KMO expression in FLS of synovial tissue of RA group was higher than that of HC group，and the difference was statistically significant (P ＜0. 001) ． Conclusion KMO expression increases in PBMC ，synovial tissue and FLS of RA patients，and the level of KMO gene expression is correlated with the disease activity of RA patients，suggesting that KMO may promote the course of RA．

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To investigate the role of tryptophan 2,3-dioxygenase(TDO2)in cisplatin-acute kidney in-jury(Cis-AKI)and to explore the mechanism of TDO2 in relation to apoptosis in tubular epithelial cells(TECs)to investigate the mechanism of TDO2 associ-ated with apoptosis.Methods An AKI model was es-tablished by intraperitoneal injection of cisplatin(Cis).Colorimetric assay was used to detect CRE and BUN levels,and PAS staining was employed to observe renal injury in mice.Immunohistochemistry was used to detect TDO2 protein expression and distribution and macrophage(F4/80+)infiltration;immunofluores-cence was used to detect the co-localization of TDO2 with the tubular marker LTL;TUNEL staining was used to detect apoptosis in mouse kidney;flow cytome-try was used to detect overexpression of human renal cortical proximal tubular epithelial cells(HK2)and apoptosis after administration of the TDO2 inhibitor 680C91;Western blot was used to detect TDO2 and NF-κB pathway protein levels in HK2 cells after over-expression and inhibition of TDO2.Results In the o-verall animal experiments,Cis-AKI mice showed signif-icantly higher levels of CRE and BUN and obvious tu-bular damage compared with the control group;at the same time,the renal tissues of Cis-AKI mice showed increased expression of F4/80,and the proportion of apoptotic cells in kidney cells was increased.Immuno-histochemistry and immunofluorescence showed that the expression of TDO2 increased,mainly localized in TECs.In cellular experiments,HK2 cells overexpress-ing TDO2 increased the proportion of apoptosis,and the expression of TDO2,p-IKBα,and p-p65 proteins was elevated,and p-IKBα/IκBα and p-p65/p65 were ele-vated;furthermore,the proportion of apoptosis was re-duced by the administration of 680C91,and the expres-sion of p-IκBα,and p-p65 proteins decreased,and the expression of p-IKBα/IKBα,and p-p65/p65 de-creased.Conclusions Elevated TDO2 in TECs is in-volved in the pathological mechanism of Cis-AKI,which may be related to its induction of apoptosis in TECs and activation of the NF-κB signaling pathway and consequently renal injury.

Aim To investigate the role of tryptophan 2,3-dioxygenase(TDO2)in cisplatin-acute kidney in-jury(Cis-AKI)and to explore the mechanism of TDO2 in relation to apoptosis in tubular epithelial cells(TECs)to investigate the mechanism of TDO2 associ-ated with apoptosis.Methods An AKI model was es-tablished by intraperitoneal injection of cisplatin(Cis).Colorimetric assay was used to detect CRE and BUN levels,and PAS staining was employed to observe renal injury in mice.Immunohistochemistry was used to detect TDO2 protein expression and distribution and macrophage(F4/80+)infiltration;immunofluores-cence was used to detect the co-localization of TDO2 with the tubular marker LTL;TUNEL staining was used to detect apoptosis in mouse kidney;flow cytome-try was used to detect overexpression of human renal cortical proximal tubular epithelial cells(HK2)and apoptosis after administration of the TDO2 inhibitor 680C91;Western blot was used to detect TDO2 and NF-κB pathway protein levels in HK2 cells after over-expression and inhibition of TDO2.Results In the o-verall animal experiments,Cis-AKI mice showed signif-icantly higher levels of CRE and BUN and obvious tu-bular damage compared with the control group;at the same time,the renal tissues of Cis-AKI mice showed increased expression of F4/80,and the proportion of apoptotic cells in kidney cells was increased.Immuno-histochemistry and immunofluorescence showed that the expression of TDO2 increased,mainly localized in TECs.In cellular experiments,HK2 cells overexpress-ing TDO2 increased the proportion of apoptosis,and the expression of TDO2,p-IKBα,and p-p65 proteins was elevated,and p-IKBα/IκBα and p-p65/p65 were ele-vated;furthermore,the proportion of apoptosis was re-duced by the administration of 680C91,and the expres-sion of p-IκBα,and p-p65 proteins decreased,and the expression of p-IKBα/IKBα,and p-p65/p65 de-creased.Conclusions Elevated TDO2 in TECs is in-volved in the pathological mechanism of Cis-AKI,which may be related to its induction of apoptosis in TECs and activation of the NF-κB signaling pathway and consequently renal injury.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Interleukin-35(IL-35)is an important immunosuppressive cytokine that has been shown to play a role in the immune response of various diseases.In this study,we cloned the coding sequence of human IL-35 gene,constructed single subunit expression vectors pXC17.4-p35 and pcDNA3.1(+)-EBI3,and co-transfected CHO-K1 cells to express IL-35 in vitro.No binding was found between subunits of p35 and EBI3.Knobs-into-Holes(KIH)can solve the problem of heavy chain mismatch of heterolo-gous antibodies.Therefore,expression vectors pXC17.4-p35-Fch and pcDNA3.1(+)-EBI3-Fck were constructed by fusing KIH structures on the basis of the original sequences to express the recombinant fu-sion protein of KIH-IL-35.The expression vectors of two subunits were exchanged at the same time to verify the influence of different vectors on the expression level of KIH-IL-35.The analysis of various pro-tein detection methods showed that the correct expression rate of KIH-IL-35 structure was significantly im-proved.Affinity purification of KIH-IL-35 was performed after large amount of expression,and the bind-ing activity of KIH-IL-35 to glycoprotein 130(gp130)was detected by ELISA.The results showed that the binding of KIH-IL-35 to gp130 was concentration dependent.The indirect activity of KIH-IL-35 and M1 cells was detected by cell activity assay.Further results showed that the inhibition rate of M1 cells in-creased in a dose-dependent manner with the concentration of KIH-IL-35.In addition,a method for de-termining IL-35 activity by activated human peripheral blood mononuclear cells was successfully estab-lished.Activated PBMCs increased in a dose-dependent manner with KIH-IL-35 concentration.In sum-mary,this study utilized the KIH-IL-35 model to enhance the expression of recombinant human IL-35 and validated its high activity in vitro,providing new ideas for the study of IL-35 and the recombinant expres-sion of similar heterodimeric cytokines.

Aim To investigate the effect of Toddalia asiatica(TA)on bone destruction in rheumatoid ar-thritis(RA)and its possible mechanism by network pharmacology and in vitro experiments.Methods The active components and targets of TA against RA bone damage were analyzed by network pharmacology.Mo-lecular docking was performed by using AutoDock and PyMOL software pairs.MC3T3-e1 cells were cultured in vitro,and the effect of Toddalia asiatica alcohol ex-tract(TAAE)on cell viability was detected by CCK-8,and appropriate drug concentration and intervention time were screened.The osteoblast model was induced by osteogenic induction medium,and the osteogenic differentiation was detected by ALP staining,activity detection and alizarin red staining.The expression of pathway-related proteins Wnt3a and β-catenin was de-tected by Western blot,and the pathway inhibitor DKK-1 was used to further verify whether TAAE regulated osteoblast differentiation through the Wnt/β-catenin signaling pathway.Results A total of 158 anti-RA bone destruction targets and 56 core targets were se-lected.The enrichment of KEGG signaling pathway mainly included cancer pathway,phosphatidylinositol 3-kinase/protein kinase B signaling pathway and cAMP signaling pathway.The results of CCK-8 showed that 1 g·L-1 TAAE could significantly improve cell survival rate.The results of ALP staining and ALP activity de-tection showed that TAAE could significantly increase the staining positive rate and ALP activity of cells in-duced by osteogenic induction medium.Western blot showed that TAAE could increase the expression of Wnt3a and β-catenin.The expression of these proteins decreased after DKK-1 inhibitors were used.Conclu-sion TAAE can regulate osteoblast differentiation through Wnt/β-catenin signaling pathway to treat os-teodestruction in rheumatoid arthritis.

Objective:To establish a practical and systematic pre-deployment base-based training course for medical units in peacekeeping level-II hospitals.Methods:We surveyed the current status of pre-deployment training of medical teams in peacekeeping level-II hospitals, and organized expert discussions to preliminarily construct centralized training course contents. At the same time, the Delphi method was used to conduct two rounds of questionnaire-based consultation to evaluate the overall framework design of the course and the rationality and importance scores of each module. The contents of the pre-deployment training course were further selected and optimized based on the positive coefficient (%), authority coefficient (Cr), coefficient of concordance ( W), and coefficient of variation (Cv). Results:The contents of the pre-deployment training course for the medical units of peacekeeping level-II hospitals were preliminarily established. The experts scored high for the combat onsite first-aid skills module [rationality score, (9.32±0.75) points; importance score, (9.45±0.65) points] and the combat wound treatment module [rationality score, (9.33±0.75) points; importance score, (9.28±0.74) points], and scored lowest for the field survival module [rationality score, (7.95±2.28) points; importance score, (7.87±2.16) points].Conclusions:The established contents of the pre-deployment base-based training course for the medical units of peacekeeping level-II hospitals are reasonable and practical, which lays the foundation for perfecting the pre-deployment training system of peacekeeping medical teams.

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
Male ; Humans ; Prostate/pathology* ; Prostate-Specific Antigen/analysis* ; Prostatic Neoplasms/diagnostic imaging* ; Biopsy ; Nomograms ; Retrospective Studies