Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Important forensic diagnostic indicators of sudden death in coronary atherosclerotic heart dis-ease,such as acute or chronic myocardial ischemic changes,sometimes make it difficult to locate the ischemic site due to the short death process,the lack of tissue reaction time.In some cases,the de-ceased died of sudden death on the first-episode,resulting in difficulty for medical examiners to make an accurate diagnosis.However,clinical studies on coronary instability plaque revealed the key role of coronary spasm and thrombosis caused by their lesions in sudden coronary death process.This paper mainly summarizes the pathological characteristics of unstable coronary plaque based on clinical medi-cal research,including plaque rupture,plaque erosion and calcified nodules,as well as the influencing factors leading to plaque instability,and briefly describes the research progress and technique of the atherosclerotic plaques,in order to improve the study on the mechanism of sudden coronary death and improve the accuracy of the forensic diagnosis of sudden coronary death by diagnosing different patho-logic states of coronary atherosclerotic plaques.

Cysteine dioxygenase 1 (CDO1) gene is a non-heme structured, iron-containing metalloenzyme involved in the conversion of cysteine to cysteine sulfinic acid to regulate cysteine accumulation in vivo. Elevated levels of cysteine have been shown to be cytotoxic and neurotoxic, and this is the first important step in the breakdown of cysteine metabolism in mammalian tissues. The human CDO1 gene is located on chromosome 5q23.2. Studies have shown that deletion or epigenetic silencing of this chromosomal region contributes to tumorigenesis. It is highly expressed in the liver and placenta, and weakly in the heart, brain and pancreas. CDO1 is a tumor suppressor gene (TSG) with a wide range of functions, which can be involved in various biological processes such as tumor cell proliferation, differentiation, apoptosis and iron death, thus affecting the tumor development. CDO1 is epigenetically regulated in human cancers, compared to normal tissues. The CDO1’s mRNA or protein expression levels were significantly down-regulated in tumor tissues, whereas promoter DNA methylation of the CDO1 gene usually accumulates with the progression of human cancers. Aberrant hypermethylation on the CDO1 promoter is a common event in tumor cells, which leads to transcriptional inactivation and silencing of the CDO1 gene. High frequency of methylation of CDO1 gene promoter methylation region in a variety of tumors including breast, oesophageal, lung, bladder, gastric and colorectal cancers. CDO1 gene promoter methylation levels reflect cancer progression and malignant tumorigenesis, which is a common molecular indicator explaining poor prognosis in human cancers. Treatment with 5-aza-2′-deoxycytidine (a drug that promotes demethylation) reactivated the CDO1 expression in most cancer cell lines, indicating that the transcriptional expression of CDO1 is closely correlated with its promoter methylation level, CDO1 gene promoter methylation and tumor progression have also received increasing attention from researchers. It was found that CDO1 gene promoter hypermethylation can be used as an early tumor marker for clinical aid diagnosis and helps to differentiate cancerous from benign diseases. It was also found that CDO1 promoter DNA methylation showed reliable tumor monitoring potential in human body fluids, and furthermore, the degree of CDO1 promoter methylation was strongly correlated with resistance to chemotherapy with tumor drugs, which would be helpful in evaluating the efficacy of chemotherapeutic drugs. Thus, CDO1, a common promoter methylation gene in human cancers, is closely associated with the development of a wide range of tumors and is one of the most promising candidate genes for assessing tumor-specific epigenetic changes. This article reviews the biological functions of CDO1 and its promoter DNA methylation in tumors, focusing on the mechanism of CDO1 DNA promoter methylation in tumors, with a view to providing theoretical guidance for the clinical diagnosis and treatment of tumors with CDO1 as a potential therapeutic target.

Osteoarthritis(OA),characterized by cartilage degeneration,synovial inflammation,and subchondral bone remodeling,is among the most common musculoskeletal disorders globally in people over 60 years of age.The initiation and progression of OA involves the abnormal metabolism of chondrocytes as an important pathogenic process.Cartilage degeneration features mitochondrial dysfunction as one of the important causative factors of abnormal chondrocyte metabolism.Therefore,maintaining mitochondrial homeostasis is an important strategy to mitigate OA.Mitophagy is a vital process for autophagosomes to target,engulf,and remove damaged and dysfunctional mitochondria,thereby maintaining mitochondrial homeostasis.Cumulative studies have revealed a strong association between mitophagy and OA,suggesting that the regulation of mitophagy may be a novel therapeutic direction for OA.By reviewing the literature on mitophagy and OA published in recent years,this paper elaborates the potential mechanism of mitophagy regulating OA,thus providing a theoretical basis for studies related to mitophagy to develop new treatment options for OA.

The endoplasmic reticulum is a key site for protein production and quality control.More than one-third of proteins are synthesized and folded into the correct three-dimensional conformation in the endoplasmic reticulum.However,during protein folding,unfolded and/or misfolded proteins are prone to occur,which may lead to endoplasmic reticulum stress.Organisms can monitor the quality of the proteins produced by endoplasmic reticulum quality control(ERQC)and endoplasmic reticulum-associated degradation(ERAD),which maintain endoplasmic reticulum protein homeostasis by degrading abnormally folded proteins.The underlying mechanisms of protein folding and ERAD in mammals have not yet been fully explored.Therefore,this paper reviews the process and function of protein folding and ERAD in mammalian cells,in order to help clinicians better understand the mechanism of ERAD and to provide a scientific reference for the treatment of diseases caused by abnormal ERAD.

Objective:To establish auto verification rules for the routine coagulation assays,and to provide reference for clinical laboratories to improve the quality and efficiency of results verification.Methods:A total of 24,510 specimens of sodium citrate anticoagulation routine coagulation test from the laboratory departments of eight hospitals including the First Medical Center,Chinese PLA General Hospital during January to March 2020 were collected and randomly divided into a rule establishment group and a rule verification group,with 6,670 specimens in the rule establishment group,including 2,056 Delta checks,and 17,840 specimens in the rule validation group,including 3,210 Delta checks.The activities of prothrombin time(PT),activated partial thromboplastin time(APTT),fibrinogen(Fib),thrombin time(TT),D-dimer(DD)and/or antithrombin(AT)were detected by Stago STA R Max automatic coagulation analyzer and supporting reagents.Taking the manual verification results as the standard,the auto verification and manual false negative rate(invalid verification),false positive rate(invalid interception),pass rate,positive coincidence rate,negative coincidence rate,verification consistency rate and specimen turnaround time(TAT)of the two groups were calculated.Results:The auto verification rules and the application process were preliminarily established,including internal quality control,alarm information,auto verification scope,critical value and deviation value inspection.In the rule establishment group,the single item pass rate was 82.6%-92.4%,and the overall pass rate was 73.8%.The consistency rate between auto verification and manual verification was 98.2%,and the positive coincidence rate and negative coincidence rate were 24.4%and 73.8%,respectively.In the rule verification group,the single item pass rate was 86.4%-91.5%,and the overall review pass rate was 71.5%.By simulating the application of auto verification rules,the average TAT of two hospitals among the eight hospitals was shortened by 1.5 hours and 2.1 hours,respectively.Conclusion:The application of auto verification rules can reduce workload of manual verification,and significantly shorten the TAT,and improve the report efficiency of the laboratory.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

Objective To investigate the association between the serum creatinine/cystatin C ratio(SCr/Cys C)as a Sarcopenia index(SI)and the incidence of in-hospital adverse events in patients with acute myocardial infarction(AMI)undergoing emergency percutaneous coronary intervention(PCI).Additionally,we evaluate the predictive efficacy of the SI in predicting major adverse cardiovascular events(MACEs)during hospitalization.Methods A total of 306 patients with AMI who underwent emergency PCI in the 904th Hospital of PLA Joint Logistics Support Force from January 2020 to March 2023 were consecutively included in this retrospective analysis.Patients were divided into two groups based on the occurrence of MACEs during hospitalization:MACEs group(n=43)and non-MACEs group(n=263).Clinical characteristics and pre-PCI laboratory test results were collected.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for MACEs.The predictive performance of SI was assessed using receiver operating characteristic(ROC)curve analysis.Results The incidence of in-hospital MACEs in AMI patients was 14.1%.The results of the independent samples t-test showed that the SI level in MACEs group was significantly lower than that in non-MACEs group,with a statistically significant difference(P<0.001).The results of the multivariate logistic regression analysis suggested that new-onset atrial fibrillation,Killip class 2-4,SI,and TG were independent risk factors for in-hospital adverse events after emergency PCI.The ROC curve results showed that the predictive value of SI(AUC=0.741,95%CI 0.666-0.816)using the SCr/Cys C ratio was superior to that of single Cys C(AUC=0.658,95%CI 0.570-0.746)for predicting post-PCI MACEs,with a statistically significant difference(P<0.05),and the optimal cutoff value for SI was 78.14.After stratifying SI based on the cutoff value,the results of the independent samples t-test showed that compared to the higher SI group,the lower SI group had a higher occurrence of specific adverse events such as heart failure(P<0.001),malignant arrhythmias(P=0.009),and strokes(P=0.003),with statistically significant differences.Conclusions The results highlight SI as an independent risk factor for MACEs during hospitalization after emergency PCI in AMI patients.Furthermore,SI has proven to be an effective prognostic index for patient outcomes.