Acute-on-chronic liver failure （ACLF） is a form of acute hepatic insufficiency that occurs in the context of a chronic liver disease， with a relatively high mortality rate. To improve the prognosis of ACLF patients， it is essential to early identify the patients with pre-ACLF and constantly optimize and innovate treatment regimens for the disease in the progressive stage. With more than 10 years of research， the Chinese CLIF consortium has developed an early warning model for ACLF and established a system for transferring high-risk patients to tertiary hospitals. At present， the real-world study has also confirmed the consistency between the early warning model and actual conditions in clinical practice， making contributions to the early screening， diagnosis， and treatment of ACLF. The treatment options for the progressive stage of ACLF are also expanding， from the development of innovative pharmaceuticals to the use of artificial liver support and stem cell therapy， and such treatment modalities have made significant achievements in clinical studies and are expected to be implemented in the near future. The development of a more efficient diagnostic system and novel treatment modalities has led to a significant improvement in the diagnosis and treatment of ACLF.

ObjectiveTo monitor the real-time changes in ammonia concentration in the laboratory animal facility environment before, during, and after the air conditioning system stops supplying air, so as to provide a basis and reference for developing emergency plans for the shutdown of the air conditioning system. MethodsThe laboratory animal facilities of the Wuhan Institute of Biological Products were used as the research object. Ammonia concentration detectors were used to monitor ammonia concentration continuously in the environment of conventional rabbit production facility, SPF hamster production facility, and SPF guinea pig experimental facility before and after the passive shutdown due to repairs and active maintenance shutdown of the air conditioning system, as well as the time for the ammonia concentration to return to daily levels after resuming air supply. ResultsUnder both shutdown modes of the air conditioning system, the trend of ammonia concentration changes in different laboratory animal facilities was consistent, showing a rapid increase after shutdown and a rapid decrease after resuming air supply. Under active maintenance shutdown, the maximum ammonia concentrations in the conventional rabbit production facilities, SPF hamster production facilities, and SPF guinea pig experimental facilities were 9.81 mg/m³, 14.27 mg/m³, and 6.98 mg/m³, respectively. Within 12 minutes after resuming air supply, ammonia concentration could return to normal daily levels. Under passive long-term shutdown, ammonia concentration value was positively correlated with the duration of air supply suspension. As the shutdown duration increased, ammonia concentration continued to increase. The maximum ammonia concentration values in the three facilities occurred at 88 minutes (38.06 mg/m³), 40 minutes (18.43 mg/m³), and 34 minutes (15.61 mg/m³) after air supply suspension, respectively.Within 11 minutes after resuming air supply, ammonia concentration could return to normal daily levels. ConclusionShutdown of the air conditioning system causes a rapid increase in ammonia concentration in laboratory animal facilities, and the rise in ammonia concentration is positively correlated with the duration of air supply suspension. Therefore, when an emergency shutdown of the air-conditioning system is required due to maintenance or other reasons, backup fans should be provided in accordance with the requirements of GB 50447-2008 "Architectural and Technical Code for Laboratory Animal Facilities". Older facilities should make adequate preparations and develop a scientifically sound emergency plan.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To explore the safety and effects of alpha-lipoic acid (ALA) in patients with ischemic heart failure (IHF). Methods A randomized, double-blind, placebo-controlled trial was designed (ClinicalTrial.gov registration number NCT03491969). From January 2019 to January 2023, 300 patients with IHF were enrolled in four medical centers in China, and were randomly assigned at a 1∶1 ratio to receive ALA (600 mg daily) or placebo on top of standard care for 24 months. The primary outcome was the composite outcome of hospitalization for heart failure (HF) or all-cause mortality events. The second outcome included non-fatal myocardial infarction (MI), non-fatal stroke, changes of left ventricular ejection fraction (LVEF) and 6-minute walking distance (6MWD) from baseline to 24 months after randomization. Results Finally, 138 patients of the ALA group and 139 patients of the placebo group attained the primary outcome. Hospitalization for HF or all-cause mortality events occurred in 32 patients (23.2%) of the ALA group and in 40 patients (28.8%) of the placebo group (HR＝0.753, 95%CI 0.473-1.198, P＝0.231; Figure 1A-1C). The absolute risk reduction (ARR) was 5.6%, the relative risk reduction (RRR) associated with ALA therapy was approximately 19.4% compared to placebo, corresponding to a number needed to treat (NNT) of 18 patients to prevent one event. In the secondary outcome analysis, the composite outcome of the major adverse cardiovascular events (MACE) including the hospitalization for HF, all-cause mortality events, non-fatal MI or non-fatal stroke occurred in 35 patients (25.4%) in the ALA group and 47 patients (33.8%) in the placebo group (HR＝0.685, 95%CI 0.442-1.062, P＝0.091; Figure 1D). Moreover, greater improvement in LVEF (β＝3.20, 95%CI 1.14-5.23, P＝0.002) and 6MWD (β＝31.7, 95%CI 8.3-54.7, P＝0.008) from baseline to 24 months after randomization were observed in the ALA group as compared to the placebo group. There were no differences in adverse events between the study groups. Conclusions These results show potential long-term beneficial effects of adding ALA to IHF patients. ALA could significantly improve LVEF and 6MWD compared to the placebo group in IHF patients.

The research and application progress of medical robots in oral surgery was introduced for soft tissue surgery,hard tissue surgery,passive dental implant,autonomous dental implant and etc.The deficiencies of oral surgical robots were analyzed in terms of high cost,long learning curve,limitations for adaptability,low patient acceptance and privacy and ethical issues.It's pointed out the future development trends of medical robots in the field of oral surgery invovled in multifunctionality,intelligence,telemedicine,cost reduction and popularization.[Chinese Medical Equipment Journal,2024,45(7):86-93]

Objective To summarize and explore the individualized surgical treatment strategy and prognosis of anomalous aortic origin of coronary artery (AAOCA). Methods The clinical data of children with AAOCA admitted to Shanghai Children's Medical Center from March 2018 to August 2021 were retrospectively analyzed. Results A total of 17 children were enrolled, including 13 males and 4 females, with a median age of 88 (44, 138) months and a median weight of 25 (18, 29) kg. All patients received operations. The methods of coronary artery management included coronary artery decapitation in 9 patients, coronary artery transplantation in 5 patients and coronary artery perforation in 3 patients. One patient with severe cardiac insufficiency (left ventricular ejection fraction 15%) received mechanical circulatory assistance after the operation for 12 days. No death occurred in the early postoperative period, the average ICU stay time was 4.3±3.0 d, and the total hospital stay was 14.4±6.1 d. All the children received regular anticoagulation therapy for 3 months after discharge. The median follow-up time was 15 (13, 24) months. All patients received regular anticoagulation therapy for 3 months after discharge. No clinical symptoms such as chest pain and syncope occurred again. The cardiac function grade was significantly improved compared with that before operation. Imaging examination showed that the coronary artery blood flow on the operation side was unobstructed, and no restenosis occurred. Conclusion AAOCA is easy to induce myocardial ischemia and even sudden cardiac death. Once diagnosed, operation should be carried out as soon as possible. According to the anatomic characteristics of coronary artery, the early effect of individualized surgery is satisfactory, and the symptoms of the children are significantly improved and the cardiac function recovers well in the mid-term follow-up.