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 evaluate the predictive value of a nomogram model developed by integrating clinical and ultrasound multiparameters for HER-2-positive breast cancer.Methods This study retrospectively enrolled 343 patients with pathologically confirmed breast cancer from three medical centers and randomly divided them into training and validation cohorts.Univariate analysis,LASSO regression,and multivariate logistic regres-sion were conducted on the training set to identify independent prognostic factors and construct a nomogram model.Bootstrap resampling with 1000 iterations was performed to evaluate the model's robustness.Model calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test.Receiver operating characteristic(ROC)curves were generated to evaluate model discrimination,and the area under the curve(AUC)along with other performance metrics were calculated.Decision curve analysis was employed to assess the clinical utility of the model,and the validation cohort was used for external validation.Results Univariate,LASSO,and multivariate regression analyses demonstrated that age,TTP(time to peak),and the presence of a filling defect sign were independent predictors of HER-2-positive breast cancer(all P<0.05).Based on these independent predictors,a nomogram model was constructed.Bootstrap validation with 1,000 resamples indicated that the model's predictive performance was stable.The Hosmer-Lemeshow test confirmed satisfactory model calibration,while the calibration curve illustrated accurate prediction probabilities.The area under the curve(AUC)for the training set was 0.863(95%CI:0.806～0.920),and for the validation set,it was 0.846(95%CI:0.764～0.929),indicating strong discriminative and generalization capabilities.Additionally,the clinical decision curve analysis demonstrated favor-able clinical utility.Conclusion A nomogram model integrating clinical and multimodal ultrasound parameters demonstrates potential utility in predicting HER-2-positive breast cancer.

Hepatocellular carcinoma(HCC)expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming.Aldolase A(ALDOA)plays a prominent role in glycolysis;however,little is known about its role in HCC development.In the present study,we aim to explore how ALDOA is involved in HCC proliferation.HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout,which is consistent with ALDOA overexpression encouraging HCC prolifera-tion.Mechanistically,ALDOA knockout partially limits the glycolytic flux in HCC cells.Meanwhile,ALDOA translocated to nuclei and directly interacted with c-Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase;ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function.A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun,and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells.In HCC patients,the expression level of ALDOA was correlated with the phosphorylation level of c-Jun(Thr93)and poor prognosis.Remarkably,hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models,and the knockdown of Aldoa strikingly decreased HCC development in vivo.Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription,opening additional avenues for anti-cancer therapies.

Background: Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials. Microbial agents, as environmentally friendly and efficient plant growth promoters and soil conditioners, have increasingly attracted attention in eco-agriculture research. Objective: Our understanding remains limited regarding how the application of microbial agents, alone or in combination, affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials. Methods: In this study, Epimedium pubescens Maxim. was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis) applied individually and in combination on plant growth and the accumulation of bioactive components. Additionally, this study explored the relationship between the rhizosphere microbiome and plant development. Results: The application of microbial agents increased the yield of E. pubescens leaves by 20.30% to 33.66% and enhanced the total flavonol glycosides content by 11.40% to 29.94%. Meanwhile, microbial treatments reshaped the rhizosphere microbiome, promoted the enrichment of beneficial microorganisms (e.g., Frankia and Paenibacillus), suppressed phytopathogenic fungi such as Didymella and Scytalidium, and enhanced the stability of the soil microbial co-occurrence network. The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumulation of bioactive components by modulating the soil microbiome. Conclusion: These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere microbiomes as mediated by microbial agents. They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

AIM To establish an HPLC method for the simultaneous content determination of 5-hydroxymethylfurfural,chlorogenic acid,caffeic acid,strychnine,paeoniflorin,ferulic acid,paeoniflorin Ⅰ,epimedium glycoside,psoralen,isopsoralen and glycyrrhetinic acid in Bunao Soft Capsules.METHODS The analysis was performed on a 35 ℃ thermostatic Waters Symmetry C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelengths were set at 230,280 nm.RESULTS Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 98.47％-103.30％with RSDs of 1.13％-2.80％.CONCLUSION This simple and reliable method can be used for the quality control of Bunao Soft Capsules.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

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.

Endometriosis(EMs)is a common estrogen-depend-ent clinical disease with the pathological characteristics of malig-nant tumors,which has great impact on women's physical and mental health.In recent years,experimental exploration has re-vealed that ectopic foci are in a hypoxic environment outside the uterine cavity,and mitochondria,as the"functional factories"of the cells,play an important role in the process of planting and in-vasion,and the mitochondrial quality control system,which in-cludes mitochondrial oxidative stress,kinetics,autophagy,bio-genesis and calcium homeostasis,is a key mechanism for the e-quilibrium of the mitochondrial function.The mitochondrial quality control system,including mitochondrial oxidative stress kinetics,autophagy,biogenesis and calcium homeostasis,is a key mechanism for mitochondrial functional balance.Therefore,to clarify the role of the mitochondrial quality control system in the development of EMs with the help of rational and rigorous experi-mental and clinical studies can not only help to clarify the patho-genesis of the disease,but also explore the key targets in the prevention and treatment of the disease.Therefore,this article summarizes the research progress of mitochondrial quality control system in endometriosis,with a view to providing reference and theoretical basis for the etiology,pathogenesis and prevention strategies of EMs.

Objective To evaluate the predictive value of a nomogram model developed by integrating clinical and ultrasound multiparameters for HER-2-positive breast cancer.Methods This study retrospectively enrolled 343 patients with pathologically confirmed breast cancer from three medical centers and randomly divided them into training and validation cohorts.Univariate analysis,LASSO regression,and multivariate logistic regres-sion were conducted on the training set to identify independent prognostic factors and construct a nomogram model.Bootstrap resampling with 1000 iterations was performed to evaluate the model's robustness.Model calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test.Receiver operating characteristic(ROC)curves were generated to evaluate model discrimination,and the area under the curve(AUC)along with other performance metrics were calculated.Decision curve analysis was employed to assess the clinical utility of the model,and the validation cohort was used for external validation.Results Univariate,LASSO,and multivariate regression analyses demonstrated that age,TTP(time to peak),and the presence of a filling defect sign were independent predictors of HER-2-positive breast cancer(all P<0.05).Based on these independent predictors,a nomogram model was constructed.Bootstrap validation with 1,000 resamples indicated that the model's predictive performance was stable.The Hosmer-Lemeshow test confirmed satisfactory model calibration,while the calibration curve illustrated accurate prediction probabilities.The area under the curve(AUC)for the training set was 0.863(95%CI:0.806～0.920),and for the validation set,it was 0.846(95%CI:0.764～0.929),indicating strong discriminative and generalization capabilities.Additionally,the clinical decision curve analysis demonstrated favor-able clinical utility.Conclusion A nomogram model integrating clinical and multimodal ultrasound parameters demonstrates potential utility in predicting HER-2-positive breast cancer.

Objective:To investigate the protective effect of achyranthes bidentata(AB)on sperm quality in mice with sper-matogenic disorder through the glycolytic metabolic pathway and its action mechanism.Methods:We equally randomized 40 Kun-ming mice into a normal control,a model control,a low-dose AB(3.5 g/kg)and a high-dose AB group(7.0 g/kg),and established the model of spermatogenic disorder in the latter three groups of mice by intraperitoneal injection of doxorubicin(30 mg/kg).Two days after modeling,we collected the testis and kidney tissues and blood samples from the mice for observation of the pathological changes in the testis tissue by HE staining,detection of perm motility with the sperm quality analyzer,examination of the apoptosis of testis cells by flow cytometry,measurement of the levels of testosterone(T),malondialdehyde(MDA),superoxide dismutase(SOD)and cata-lase(CAT)in the serum and testis tissue by ELISA,and determination of expressions of the key enzymes of glycolysis hexokinase Ⅱ(HK2),pyruvate kinase M2(PKM2),platelet phosphofructokinase(PFKP),lactate dehydrogenase A(LDHA)and the meiosis pro-teins REC8 and SCP3 by Western blot,and the mRNA expressions of glycolytic phosphofructokinase 1(PFK1),phosphoglycerate ki-nase 1(PGK1),tumor necrosis factor-α(TNF-α)and interleukin-1 β(IL-1β)by fluorescence quantitative PCR(FQ-PCR).Results:Compared with the model controls,the mice in the AB groups showed significant increases in the testis coefficient,kidney in-dex,sperm concentration,sperm motility,spermatogonia,primary spermatocytes,spermatids,sperm count and the serum T level(P＜0.05 orP＜0.01),but dramatic decreases in the apoptosis of testis cells and percentage of morphologically abnormal sperm(P＜0.01).Achyranthes bidentata also significantly elevated the levels of SOD and CAT,and down-regulated the mRNA expressions of MDA,TNF-α and IL-1β(P＜0.05 or P＜0.01),and up-regulated the protein expressions of HK2,PKM2,PFKP,LDHA,REC8 and SCP3,and expressions of the glycolysis key genes Pfk1 and Pgk1(P＜0.05 orP＜0.01).Conclusion:Achyranthes bidentata ameliorates doxorubicin-induced spermatogenic disorder in mice by regulating the glycolytic pathway and reducing oxidative stress and the expressions of inflammatory factors.