Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

Objective To explore an artificial intelligence (AI)-based method for automated hand hygiene monitoring and to compare the effectiveness of three algorithms (UniFormerV2, TDN, C3D) in recognizing hand hygiene steps in surgical settings, thereby aiding hospital infection control. Methods From April to October 2024, we non-invasively collected 641 video recordings of healthcare staff performing hand hygiene at four-bay scrub sinks in two tertiary hospitals using overhead HD cameras. The dataset was annotated by five trained experts for model training and validation. Results Following training on 385 samples, internal validation (n=119) showed the C3D model achieved 81% accuracy, 87% recall, and an 83% F1-score. The TDN model achieved 93%, 91%, and 92% for the same metrics. The UniFormerV2 model outperformed both, with an accuracy, recall, and F1-score of 93%—an improvement of over 10 percentage points compared to traditional CNNs (TDN, C3D). It also achieved an 84% accuracy in external validation, demonstrating strong generalization. Conclusion The UniFormerV2 model is more accurate than CNN-based models for hand hygiene step recognition and shows robust performance in external validation. It presents a viable tool for healthcare facilities to enhance hand hygiene management, ultimately improving medical quality and patient safety.

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 explore the possible regulatory effect of leptin on acyl-CoA synthetase long chain fami-ly member ACSL5 and their effect on migration and in-vasion of breast cancer cell,and to explore the underly-ing mechanism.Methods The expression of leptin receptor was detected by immunofluorescence assay.The migration and invasion ability of MCF-7 cells were detected by wound healing assay and Transwell assay respectively.The downstream target gene of leptin was analyzed by PCR microarray data.The expression of ACSL5 in breast cancer and its correlation with the staging and prognosis of breast cancer patients were as-sessed uing bioinformatics methods.The expression of ACSL5 in MCF-7 cells treated with different concentra-tions of leptin was detected using real time fluorescence quantitative polymerase chain reaction(RT-qPCR).Overexpressing ACSL5 was constructed by lentiviral transfection;the expressions of EMT related proteins,AMPK-α and p-AMPK-α were detected by Western blot.Results Leptin promoted breast cancer cell mi-gration and invasion and EMT.ACSL5 was significant-ly low expressed in breast cancer and related to progno-sis.Leptin downregulated the expression of ACSL5 through OBR.Leptin activated AMPK pathway to downregulate ACSL5 and promote migration,invasion and EMT of breast cancer cells.Conclusions Leptin may promote the migration,invasion and EMT of breast cancer by downregulating ACSL5 through activating AMPK pathway.

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 intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Aim To investigate the effects of rosavin on hepatocellular steatosis and its mechanism of action.Methods AML-12 and HepG2 cells were induced to undergo hepatocellular steatosis by free fatty acids(FFA),and the optimal inducing concentration was determined by oil red O staining and CCK-8 assay.The cell activity was detected by CCK-8 assay after ro-savin treatment,and the lipid droplet accumulation was observed by oil red O staining.The levels of triglycer-ide(TG),total cholesterol(TC),glutamic oxalacetic transaminase(AST),glutamic pyruvic transaminase(ALT),superoxide dismutase(SOD),glutathione per-oxidase(GSH-Px),and malondialdehyde(MDA)were detected by kits.The potential targets of rosavin in non-alcoholic fatty liver disease(NAFLD)were ana-lyzedby network pharmacology and molecular docking,and the expression of core candidate targets before and after the rosavin intervention was detected by real-time fluorescence quantitative PCR.Results Hepatocyte steatosis was induced by FFA,and the intervention of rosavin(25,50 μmol·L-1)reduced the number of intracellular lipid droplets in hepatocytes in a dose-de-pendent manner,also lowered the cellular levels of TG,TC,AST,ALT,elevated the levels of SOD and GSH-Px,and reduced the levels of MDA.Network pharma-cological analysis and molecular docking yielded five core candidate targets:NOS3,MAPK14,PPARG,TNF-α,and IGF-1,and real-time fluorescence quantitative PCR showed that the action of loxavir significantly re-duced the gene expression of TNF-α and PPARG in hepatocytes after FFA induction.Conclusions Rosa-vin can attenuate the inflammatory response,oxidative stress level,and lipid accumulation in hepatocytes by modulating TNF-α and PPARG,thereby ameliorating FFA-induced hepatocellular steatosis.

Background and Aims:Microsatellite-stable(MSS)colorectal cancer(CRC)generally exhibits poor responsiveness to immune checkpoint inhibitors(ICIs),and effective immunotherapy strategies remain lacking.Anti-angiogenic agents such as bevacizumab(BEV)can improve the tumor immune microenvironment and act synergistically with ICIs.This multicenter real-world study compared the efficacy of different immunotherapy-based combination regimens in patients with MSS/MSI-L/pMMR advanced CRC,aiming to identify the optimal treatment strategy.Methods:A total of 100 patients with MSS/MSI-L/pMMR advanced CRC who received systemic treatment between November 2019 and February 2025 at four tertiary hospitals in Hunan,China,were retrospectively enrolled.Patients were classified into six treatment groups:chemotherapy alone,chemotherapy+targeted therapy,immunotherapy alone,immunotherapy+chemotherapy,immunotherapy+targeted therapy,and immunotherapy+chemotherapy+targeted therapy.The primary endpoints were overall survival(OS)and progression-free survival(PFS),while secondary endpoints were objective response rate(ORR)and disease control rate(DCR).Additionally,among patients receiving immunotherapy,subgroup analysis was performed according to BEV administration.Results:Among all 100 patients,the immunotherapy+chemotherapy+targeted therapy group achieved the highest ORR(32.0%)and DCR(76.0%)and was the only regimen yielding a complete response(CR).Compared with chemotherapy or immunotherapy alone,the triplet regimen significantly improved OS(P<0.05);although PFS improvement did not reach statistical significance,a clear late-stage separation of survival curves was observed.In the immunotherapy subgroup,BEV-containing regimens achieved markedly better outcomes than non-BEV regimens,with DCR of 75.0%vs.48.8%,median OS of 18.9 vs.11.5 months,and median PFS of 13.8 vs.7.2 months(all P<0.001).Cox regression analysis showed that compared with chemotherapy alone,the triplet regimen significantly reduced the risk of death(HR=0.11)and disease progression(HR=0.25)(both P=0.002).Vascular invasion was identified as an adverse prognostic factor for PFS(HR=3.0,P=0.007).Conclusion:This multicenter real-world study demonstrated that combining immunotherapy with chemotherapy and targeted therapy significantly improves DCR and survival outcomes in patients with MSS/MSI-L/pMMR advanced CRC,with BEV-containing triplet regimens providing the most pronounced benefit.BEV may enhance immune responsiveness by modulating the tumor microenvironment and promoting effector T-cell infiltration,offering a promising therapeutic direction for"immune-cold"CRC.Prospective randomized studies are warranted to further validate its clinical value and define appropriate patient populations.

Background and Aims:Microsatellite-stable(MSS)colorectal cancer(CRC)generally exhibits poor responsiveness to immune checkpoint inhibitors(ICIs),and effective immunotherapy strategies remain lacking.Anti-angiogenic agents such as bevacizumab(BEV)can improve the tumor immune microenvironment and act synergistically with ICIs.This multicenter real-world study compared the efficacy of different immunotherapy-based combination regimens in patients with MSS/MSI-L/pMMR advanced CRC,aiming to identify the optimal treatment strategy.Methods:A total of 100 patients with MSS/MSI-L/pMMR advanced CRC who received systemic treatment between November 2019 and February 2025 at four tertiary hospitals in Hunan,China,were retrospectively enrolled.Patients were classified into six treatment groups:chemotherapy alone,chemotherapy+targeted therapy,immunotherapy alone,immunotherapy+chemotherapy,immunotherapy+targeted therapy,and immunotherapy+chemotherapy+targeted therapy.The primary endpoints were overall survival(OS)and progression-free survival(PFS),while secondary endpoints were objective response rate(ORR)and disease control rate(DCR).Additionally,among patients receiving immunotherapy,subgroup analysis was performed according to BEV administration.Results:Among all 100 patients,the immunotherapy+chemotherapy+targeted therapy group achieved the highest ORR(32.0%)and DCR(76.0%)and was the only regimen yielding a complete response(CR).Compared with chemotherapy or immunotherapy alone,the triplet regimen significantly improved OS(P<0.05);although PFS improvement did not reach statistical significance,a clear late-stage separation of survival curves was observed.In the immunotherapy subgroup,BEV-containing regimens achieved markedly better outcomes than non-BEV regimens,with DCR of 75.0%vs.48.8%,median OS of 18.9 vs.11.5 months,and median PFS of 13.8 vs.7.2 months(all P<0.001).Cox regression analysis showed that compared with chemotherapy alone,the triplet regimen significantly reduced the risk of death(HR=0.11)and disease progression(HR=0.25)(both P=0.002).Vascular invasion was identified as an adverse prognostic factor for PFS(HR=3.0,P=0.007).Conclusion:This multicenter real-world study demonstrated that combining immunotherapy with chemotherapy and targeted therapy significantly improves DCR and survival outcomes in patients with MSS/MSI-L/pMMR advanced CRC,with BEV-containing triplet regimens providing the most pronounced benefit.BEV may enhance immune responsiveness by modulating the tumor microenvironment and promoting effector T-cell infiltration,offering a promising therapeutic direction for"immune-cold"CRC.Prospective randomized studies are warranted to further validate its clinical value and define appropriate patient populations.

Objective To explore the differences in coronary-based and lesion-based fat attenuation index(FAI)in patients with coronary artery disease(CAD)across different risk stratifications,and to compare the diagnostic efficiency of coronary-based and lesion-based FAI in stable CAD patients with myocardial ischemia.Methods The patients with CAD,who underwent preoperative coronary CT angiography(CCTA)and invasive coronary angiography(ICA)with coronary fractional flow reserve(FFR)measurement between Apr 2019 and Oct 2022 in Zhongshan Hospital,Fudan University,were retrospectively collected.There were 57 cases of acute coronary syndrome(ACS)patients and 206 cases of stable CAD patients included following inclusion criteria.The coronary-based and lesion-based FAI were measured,and the differences in these indices were recorded and analyzed among ACS patients,ischemic and non-ischemic groups of stable CAD patients(FFR=0.8 as the threshold).ROC curves were utilized to assess the diagnostic efficiency of coronary-based and lesion-based FAI for myocardial ischemia in stable CAD patients.Results The coronary-based FAI and lesion-based FAI in ACS patients were significantly higher than those in stable CAD patients[coronary-based FAI:(-72.40±6.83)HU vs.(-76.82±9.01)HU,P<0.001;lesion-based FAI:(-65.65±4.79)HU vs.(-77.48±8.64)HU,P<0.001].Among stable CAD patients,the lesion-based FAI in the ischemic group was significantly higher than that in the non-ischemic group[(-69.28±5.65)HU vs.(-80.10±7.75)HU,P<0.001].The diagnostic efficiency of lesion-based FAI for predicting myocardial ischemia in stable CAD patients was superior to coronary-based FAI(AUC:0.892 vs.0.525,Z=9.803,P<0.001).Conclusion Coronary-based and lesion-based FAI tended to be higher in ACS patients than in stable CAD patients,suggesting a potential for stratifying CAD patients with different risks.Lesion-based FAI showed some promise in evaluating myocardial ischemia among stable CAD patients.