This study was aimed at developing an in vitro fluorescent substrate assay for the activity of leucyl aminopeptid-ase(LAP)from Echinococcus multilocularis and comparing it with the chemical chromogenic substrate enzyme activity assay.Through the establishment of reaction conditions for the fluorescent substrate-based in vitro enzyme activity assay,we com-pared the differences between the fluorescent substrate L-Leucine-7-amido-4-methylocoumarin(Leu-AMC)and the chemical chromogenic substrate L-Leucine-4-nitroanilide(Leu-pNA)through molecular docking,inhibition rates,and precision measures.Molecular docking revealed that the fluorescent substrate Leu-AMC had higher affinity for the protein than the chemical chromogenic substrate Leu-pNA.Through analysis of the effects of varying reaction conditions on fluorescence intensi-ty,we optimized the fluorescent substrate enzyme activity assay to demonstrate favorable performance at a reaction temperature of 37℃,a pH of 9.0,a protein concentration of 800 nmol/L,and a reaction duration of 60 minutes.Leu-AMC exhibited significant and distinct responses at a 5 μmol/L substrate concentration,under varying substrate conditions.The fluo-rescent substrate assay demonstrated more significant intergroup differences than the chemical chromogenic substrate assay when various inhibitors were added.This study established a fluorescence-based enzyme activity assay for leucyl aminopeptidase from Echinococcus multilocularis by using Leu-AMC as the substrate;this method demonstrated a more significant intergroup difference and sensitivity than the chemical chromogenic substrate assay.

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.

This study was aimed at developing an in vitro fluorescent substrate assay for the activity of leucyl aminopeptid-ase(LAP)from Echinococcus multilocularis and comparing it with the chemical chromogenic substrate enzyme activity assay.Through the establishment of reaction conditions for the fluorescent substrate-based in vitro enzyme activity assay,we com-pared the differences between the fluorescent substrate L-Leucine-7-amido-4-methylocoumarin(Leu-AMC)and the chemical chromogenic substrate L-Leucine-4-nitroanilide(Leu-pNA)through molecular docking,inhibition rates,and precision measures.Molecular docking revealed that the fluorescent substrate Leu-AMC had higher affinity for the protein than the chemical chromogenic substrate Leu-pNA.Through analysis of the effects of varying reaction conditions on fluorescence intensi-ty,we optimized the fluorescent substrate enzyme activity assay to demonstrate favorable performance at a reaction temperature of 37℃,a pH of 9.0,a protein concentration of 800 nmol/L,and a reaction duration of 60 minutes.Leu-AMC exhibited significant and distinct responses at a 5 μmol/L substrate concentration,under varying substrate conditions.The fluo-rescent substrate assay demonstrated more significant intergroup differences than the chemical chromogenic substrate assay when various inhibitors were added.This study established a fluorescence-based enzyme activity assay for leucyl aminopeptidase from Echinococcus multilocularis by using Leu-AMC as the substrate;this method demonstrated a more significant intergroup difference and sensitivity than the chemical chromogenic substrate assay.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.

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.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.

ObjectiveTo investigate the genetic polymorphism and structure of 47 autosomal microhaplotypes in the Han population in Changshu City, Jiangsu Province, and to evaluate the forensic efficiencies and forensic parameters. MethodsThe DNA library of unrelated individual samples was prepared according to MHSeqTyper47 kit manual and sequenced on the MiSeq FGx platform. Microhaplotype genotyping and sequencing depth statistics were processed using MHTyper. The genetic information of samples was then evaluated. The fixation index and genetic distance between the Jiangsu Changshu population and the reference populations in the 1000 Genomes Project phase 3 (1KG) were calculated, and forensic parameters were evaluated. ResultsThe fixation index and genetic distance between the Han population in Changshu, Jiangsu, and the CHB (Han Chinese in Beijing, China) reference population in 1KG were the lowest. The effective allele number (A_e) of each locus is also the closest between the two populations. The combined matching probability (CMP) of the Changshu Han population is close to the 5 populations of the East Asian reference super-population in 1KG, which is 1.25×10^-36, and the combined probability of exclusion reached 0.999 999 999 964 1. ConclusionThis study reported the genetic polymorphism and allele frequency of 47 microhaplotypes in a Han population in Changshu City, Jiangsu Province. This information provides a data basis for 47 microhaplotypes in forensic applications. In addition, the polymorphism differences between the 1KG reference population and the Han population in Changshu, Jiangsu were compared, and the genetic structure of 47 microhaplotypes in the Han population in Changshu, Jiangsu was revealed. In general, the reference data of the East Asian super-population in 1KG is more in line with the genetic characteristics of Han population in Changshu, Jiangsu.

Objective:To investigate the clinical efficacy and safety of anlotinib combined with radiotherapy as a third-line treatment regimen for extensive stage small-cell lung cancer (ES-SCLC) in a real-world background.Methods:Forty ES-SCLC patients enrolled in a single center of Affiliated Cancer Hospital of Xinjiang Medical University in China between November 2018 and July 2021 were treated with radiotherapy added on anlotinib as a third-line treatment regimen. Overall survival (OS), progression-free survival (PFS), safety, and quality of life were analyzed, and the survival status was statistically analyzed using Kaplan-Meier method.Results:Among the 40 patients, partial remission, stable disease, and progressive disease was confirmed in 7, 24 and 9 patients, respectively. The obtained objective remission rate (ORR) was 18%, the disease control rate (DCR) was 78%, and median PFS and median OS were 4.5 months and 9 months, respectively. The most common adverse reactions included fatigue (28%), bleeding (20%), anorexia (13%), and hand-foot syndrome (8%). Most of them were grade 1-2 in severity, 4 cases were documented as ≥grade 3, and no grade 5 toxicity was recorded.Conclusions:In the real world, radiotherapy added on anlotinib as a third-line regimen can prolong PFS and OS of the ES-SCLC patients, and the adverse reactions are generally tolerated. This combination treatment regimen is worthy of further investigation.

Objective:To investigate the factors contributing to frailty in very elderly patients with multimorbidity.Methods:This cross-sectional study enrolled 119 very elderly patients with multimorbidity who were hospitalized in the Department of Geriatrics of Huadong Hospital Affiliated to Fudan University from August 2022 to March 2023.The study aimed to understand the basic status of multimorbidity by collecting general information, the number and types of diseases, and frailty status.The subjects were divided into frail and non-frail groups through comprehensive geriatric assessment.Various factors including gender, age, Tinetti balance gait score, risk of sarcopenia, dementia, depression, risk of deep vein thrombosis, dysphagia, comorbidity index, medication count, Basic Activities of Daily Living(BADL)score, Instrumental Activities of Daily Living(IADL)score, Nutritional Risk Screening 2002(NRS-2002)score, Norton pressure injury risk assessment score, and Social Support Rating Scale(SSRS)score were compared.The correlation between each factor and the occurrence of frailty was analyzed using univariate analysis and multivariate Logistic regression analysis.Results:A total of 119 elderly inpatients with multimorbidity, with an average age of 90.8±5.9 years old, were included in the study.The incidence of frailty was 68.9%(82 cases).Univariate analysis revealed significant statistical differences between the frail group and the non-frail group in various factors including age( t=-3.131, P=0.002), Tinetti score( Z=-5.544, P<0.001), risk of sarcopenia( χ2=39.205, P<0.001), dysphagia( χ2=5.937, P=0.015), Charlson comorbidity index( Z=-2.565, P=0.010), medication count( Z=-3.325, P<0.001), BADL( Z=-5.871, P<0.001), IADL( Z=-5.062, P<0.001), Norton score( Z=-5.922, P<0.001), and SSRS social support( Z=-2.637, P=0.008).Multivariate logistic regression analysis showed that the Tinetti score( OR=0.843, 95% CI: 0.737-0.966, P=0.014), decreased muscle strength( OR=11.226, 95% CI: 2.157-58.432, P=0.004), sarcopenia( OR=18.084, 95% CI: 2.041-106.211, P=0.009), Norton score( OR=0.462, 95% CI: 0.254-0.838, P=0.011), and medication count( OR=1.153, 95% CI: 1.000-1.329, P=0.049)were independently associated with frailty. Conclusions:In very elderly patients with multimorbidities, the occurrence of frailty is notably increased.Frailty is linked to multiple risks including falls, muscle weakness/sarcopenia, pressure ulcer risk, and polypharmacy, and these risks are independent of other factors.

Objective To investigate the role of macrophages in the process of fine particulate matter (PM2.5)exposure induced damage to pulmonary blood-air barrier.Methods Eighteen male BALB/C mice (aged of 10 weeks,weighing 24～27 g)were randomly divided into control group and low-and high-dose PM2.5 exposure groups (receiving 1 .8 and 16.2 mg/kg,respectively),with 6 mice in each group.The control group received tracheal instillations of normal saline on days 1,4,and 7,whereas the exposure groups were administered corresponding dose of PM2.5 exposure at the same time points.In 24 h after last exposure,pathological changes in the lung tissues were observed,and the contents of total protein (TP ),lactate dehydrogenase (LDH ),and alkaline phosphatase (AKP ) in bronchoalveolar lavage fluid (BALF ),and F4/80 protein level in lung tissue were measured to evaluate the blood-air barrier damage and macrophage infiltration within the lung tissues.Additionally,an in vitro model of the blood-air barrier was established using A549 alveolar epithelial cells and EA.hy926 vascular endothelial cells.In combination with a THP-1 macrophage model,the supernatant PM2.5 supernatant,macrophage supernatant,and PM2.5-macrophage supernatant were incubated with the barrier model for 24 h,respectively.Transmembrane electrical resistance (TEER),sodium fluorescein permeability of the barrier model,and LDH release from the barrier cells were measured to ascertain the extent of macrophage-mediated enhancement in barrier damage induced by PM2.5 exposure.Furthermore,the expression of inflammatory cytokines,such as TNF-α,IL-1β,IL-6,and IL-8 in the macrophages after PM2.5 exposure was analyzed with quantitative real-time PCR (qPCR)and enzyme-linked immunosorbent assay (ELISA).Results PM2.5 exposure induced lung tissue damage in mice in a dose-dependent manner,significantly elevated the contents of TP,LDH and AKP in the BALF and caused marked infiltration of macrophages into the lung tissue,especially the high-dose exposure when compared with the mice from the control group (P<0.01 ).In vitro barrier model exposure experiments showed that in comparison with the treatment of 150 and 300 μg/mL PM2.5 and macrophage supernatant,the same doses of PM2.5-macrophage supernatant resulted in notably decreased TEER and significantly enhanced permeability in the barrier model (P<0.01 ),and markedly increased LDH release from epithelial and endothelial barrier cells (P<0.01 ).Additionally,the exposure of 150 and 300μg/mL PM2.5 led to a significant up-regulation of TNF-α,IL-1β,IL-6,and IL-8 in the macrophages (P<0.01 ).Conclusion Macrophages deteriorate PM2.5-induced functional impairment of the pulmonary blood-air barrier.