Acute-on-chronic liver failure （ACLF） is a syndrome of acute liver function decompensation in patients with chronic liver disease and is characterized by a high short-term mortality rate. Liver transplantation is an effective radical treatment method for ACLF and can significantly improve the survival rate of patients. However， in the context of a shortage of donor organs globally， how to achieve a balance between saving lives and avoiding futile transplantation while optimizing organ utilization is a critical challenge in clinical decision-making. This article systematically reviews the evolution of the evaluation and decision-making system for liver transplantation in ACLF patients and points out s that the core of this system has shifted from relying solely on the MELD score to a model based on multidimensional prognostic assessment， dynamic evaluation， and multidisciplinary collaboration. In the future， the integration of Eastern and Western criteria， the application of artificial intelligence for precise prediction， and the establishment of a more equitable priority and allocation system will be the key directions for development in this field.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Acute-on-chronic liver failure （ACLF） is an acute decompensation syndrome that develops on the background of chronic liver disease and is characterized by high mortality， rapid disease progression， complex clinical phenotypes， and a narrow window for reversibility. At present， there is still a lack of a unified standardized diagnostic system for ACLF globally， and there are significant differences between different diagnostic criteria in terms of liver failure， extrahepatic organ failure， and high-risk states within specific etiological contexts. To achieve individualized risk stratification of ACLF patients and optimize the allocation of clinical resources， it is urgently needed to establish a scientifically sound and precise classification system. Traditional static diagnostic models are confined only to baseline assessment and mortality prediction and fail to reflect dynamic disease evolution or effectively distinguish treatment response across different groups of patients. This article systematically reviews the major definitions and classification systems of ACLF at the current stage， analyzes the application value and limitations of various classification frameworks in clinical treatment decision-making， prognostic risk assessment， and clinical trial design， and proposes that the clinical classification system for ACLF should move beyond the single baseline evaluation approach toward a dynamic， treatment-oriented， and cross-etiology integrated assessment model， in order to provide a more precise theoretical basis for clinical diagnosis and treatment regarding artificial liver support， intensive care management， liver regeneration therapies， and determination of indications for liver transplantation.

ObjectiveTo investigate the effects and potential mechanisms of morning and evening fasting on postprandial lipid responses, a post hoc analysis based on a crossover randomized controlled trial was conducted to assess the effects of different fasting strategies on postprandial lipid metabolism in community residents in Shanghai. MethodsA total of 23 participants took part in a randomized crossover trial involving two intervention days: morning fasting and evening fasting, with a washout period of 6 days between intervention days. Two-way analysis of variance was used to test the differences in total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and the relative expression of circadian clock genes before and after the next meal under fasting. Wilcoxon rank sum tests were used to analyze the different metabolites between the two groups. Principal component analysis and Orthogonal partial least squares-discriminant analysis were conducted to evaluate the ability of metabolites to differentiate between morning fasting and evening fasting and identify the important differential metabolites. After adjusting for age, sex, and BMI, a partial correlation analysis was performed to identify metabolites associated with plasma lipids. In addition, important metabolites associated with plasma lipids were computed by pathway enrichment analysis. ResultsAfter evening fasting intervention, fasting TG level [(0.37±0.29) vs (0.27±0.18)] mmol·L^-1, fasting and postprandial change values in TC [(2.74±0.47) vs (2.51±0.27)] mmol·L^-1 and LDL-C [(1.32±0.38) vs (0.99±0.27)] mmol·L^-1 were significantly lower than those after morning fasting (P<0.05). While, change values of fasting LDL-C [(0.89±0.37) vs (1.14±0.37)] mmol·L^-1 and TG [(1.14±0.19) vs (1.28±0.17)] mmol·L^-1 were significantly higher than those after morning fasting intervention (P<0.05). After fasting intervention, the relative expression of AMPK, CRY1, CLOCK, MTNR1B, AANAT, and ASMT was correlated with the amount of plasma lipid changes (P<0.05). Specifically, CLOCK and AANAT were upregulated following evening fasting and downregulated after morning fasting. Among the 217 important differential metabolites, 111 were correlated with plasma lipids, and which were primarily enriched in the cysteine and methionine metabolism pathways (P<0.05). ConclusionCompared to morning fasting, evening fasting was more effective in improving postprandial lipid responses, indicating that an evening fasting window during intermittent fasting could be conducive to cardiovascular disease prevention in adults. Meanwhile, it is suggested that morning and evening fasting may affect lipid responses through circadian rhythm oscillations and the cysteine and methionine metabolism pathways.

Health behavior motivation significantly affects the quality of life of patients with cardiovascular diseases.Assessing the level of health behavior motivation can measure the health behavior of individuals,help to promote the participation rate of cardiac rehabilitation,reduce the readmission rate of patients,and promote patients'healthy lifestyles.This article reviews the content,characteristics and application of assessment tools for health behavior motivation of patients with cardiovascular diseases at home and abroad,with the aim of providing references for the development and application of such tools in China,and offering a basis for scientifically assessing their health behavior motivation level and formulating effective strategies to promote health behavior motivation.

In 2025,Severe Liver Disease and Artificial Liver Group and Nutrition and Regeneration in End-Stage Liver Disease Group of Chinese Society of Hepatology,Chinese Medical Association,convened a panel of national experts to jointly develop China's first guideline for the diagnosis and treatment of acute-on-chronic liver failure(ACLF).Based on the latest research findings and clinical practice in China and globally,this guideline establishes a standardized definition of ACLF and provide recommendations for its diagnosis,treatment,and clinical management.This article gives an interpretation of the key points in the guideline,in order to provide a reference for standardized diagnosis and treatment of ACLF.

OBJECTIVE: To explore the clinical and genetic characteristics of a child with intellectual development disorder and seizures due to a variant of AP2M1 gene. METHODS: Clinical data of a child with intellectual development disorder and epilepsy who was admitted to the Department of Pediatric Neurology of the Third Affiliated Hospital of Zhengzhou University in January 2021 were retrospectively analyzed. Peripheral blood samples of the child and his parents were collected for whole exome sequencing. Candidate variant was verified by Sanger sequencing and pathogenicity analysis. The three-dimensional structure of the AP2M1 protein was visualized using Chimera v1.10.1 software. Pathogenicity of candidate variant was classified according to the Standards and Guidelines for the Interpretation of Sequence Variants from the American College of Medical Genetics and Genomics American College of Medical Genetics (ACMG). With "AP2M1 gene" "epilepsy" "intellectual disability" as the keywords, relevant cases were searched from CNKI, Wanfang Data knowledge service platform and PubMed databases with the search time spanning from the establishment of the database to September 2024. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2020-57). RESULTS: The child was a 8-years-and-6-months-old boy, who could raise his head at 3 months and sit alone at 8 months old. He could not walk alone at 1 year old and underwent 2 months' rehabilitation treatment, and could walk alone and call his parents at 1-and-a-half-years-old. At 4-years-and-10-months-old, he started to have frequent seizures, manifesting as low level of consciousness, body shaking, accompanied by blinking, lasting about a few seconds several times a day and could be relieved. With the treatment of sodium valproate combined with lamotrigine, the convulsions were controlled, but his movement and cognition were lagged behind. DNA sequencing revealed that he has harbored a novel variant of the AP2M1 gene (NM_004068.3) c.508C>T (p.Arg170Trp). Sanger sequencing confirmed that both of his parents were of the wild-type. According to the guidelines from the American College for Medical Genetics and Genomics (ACMG), the variant was rated as pathogenic (PS2+PS4+PM1+PM2+PP2+PP3). The difference between the wild-type and mutant AP2M1 proteins can be clearly viewed through its three-dimensional structure. Two previous reports have included 5 cases due to the same variant. Common manifestations have included seizures (100%, 5/5), motor retardation (100%, 5/5), intellectual impairment (100%, 5/5), autism spectrum disorder (60%, 3/5), ataxia (100%, 5/5), and special facial features (20%, 1/5). CONCLUSION The c.508C>T (p.Arg170Trp) variant of the AP2M1 gene may underlie the intellectual retardation and seizure in this child.
Humans ; Male ; Child ; Intellectual Disability/genetics* ; Seizures/genetics* ; Exome Sequencing ; Mutation

Acute-on-chronic liver failure (ACLF) is an acute deterioration of liver function occurring on the basis of chronic liver disease, accompanied by failure of the liver and extrahepatic organs, and is associated with a high short-term mortality rate. Liver transplantation is the only curative treatment for patients with ACLF. However, the shortage of donor livers and limitations of the organ allocation system mean that only a minority of patients can receive transplants. The current organ allocation system based on the model for end-stage liver disease (MELD) score may underestimate the urgency of liver transplantation for ACLF patients. Therefore, it is urgent to develop better assessment tools to determine which ACLF patients are most likely to benefit from liver transplantation. This article reviews the current mainstream definitions of ACLF, the selection of candidates for liver transplantation in ACLF, and the prognostic scoring systems for liver transplantation in ACLF, both domestically and internationally, in order to provide a reference for the prognostic assessment of liver transplantation in ACLF patients.