Metabolic dysfunction-associated steatohepatitis (MASH), a severe type of metabolic dysfunction-associated steatotic liver disease (MASLD), is a leading etiology of end-stage liver disease worldwide, posing significant health and economic burdens. microRNA-320 (miR-320), a ubiquitously expressed and evolutionarily conserved miRNA, has been reported to regulate lipid metabolism; however, whether and how miR-320 affects MASH development remains unclear. By performing miR-320 in situ hybridization with RNAscope, we observed a notable downregulation of miR-320 in hepatocytes during MASH, correlating with disease severity. Most importantly, miR-320 downregulation in hepatocytes exacerbated MASH progression as demonstrated that hepatocyte-specific miR-320 deficient mice were more susceptible to high-fat, high-fructose, high-cholesterol diet (HFHC) or choline-deficient, amino acid-defined, high-fat diet (CDAHFD)-induced MASH compared with control littermates. Conversely, restoration of miR-320 in hepatocytes ameliorated MASH-related steatosis and fibrosis by injection of adeno-associated virus 8 (AAV8) carrying miR-320 in different types of diet-induced MASH models. Mechanistic studies revealed that miR-320 specifically regulated fibroblast growth factor 1 (FGF1) production in hepatocytes by inhibiting regulator factor X1 (RFX1) expression. Notably, knockdown of Rfx1 in hepatocytes mitigated MASH by enhancing FGF1-mediated AMPK activation. Our findings underscore the therapeutic potential of hepatic miR-320 supplementation in MASH treatment by inhibiting RFX1-mediated FGF1 suppression.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Due to the limitations of current anti-HBV therapies, the HBV core (HBc or HBcAg) protein assembly modulators (CpAMs) are believed to be potential anti-HBV agents. Therefore, discovering safe and efficient CpAMs is of great value. In this study, we established a HiBiT-based high-throughput screening system targeting HBc and screened novel CpAMs from an in-house marine chemicals library. A novel lead compound 8a, a derivative of the marine natural product naamidine J, has been successfully screened for potential anti-HBV activity. Bioactivity-driven synthesis was then conducted, and the structure‒activity relationship was analyzed, resulting in the discovery of the most effective compound 11a (IC₅₀ = 0.24 μmol/L). Furthermore, 11a was found to significantly inhibit HBV replication in multiple cell models and exhibit a synergistic effect with tenofovir disoproxil fumarate (TDF) and IFNa2 in vitro for anti-HBV activity. Treatment with 11a in a hydrodynamic-injection mouse model demonstrated significant anti-HBV activity without apparent hepatotoxicity. These findings suggest that the naamidine J derivative 11a could be used as the HBV core protein assembly modulator to develop safe and effective anti-HBV therapies.

Objective:To investigate the effect of GRIM-19 on the resistance of carcinoma cells to the chemotherapeutic agent docetaxel in the treatment of PCa.Methods:Using siRNA technology to interfere with the gene expression in PCa cells,we estab-lished a model of GRIM-19 overexpression/knockdown in PCa cells.We investigated the effect of different expression levels of GRIM-19 on docetaxel-induced death of the PCa cells by qPCR,Western blot and flow cytometry,and assessed the value of GRIM-19 in re-ducing the chemotherapy-resistance of PCa cells.Results:GRIM-19 was down-regulated in PCa tissues and cells.Knockout of GRIM-19 significantly decreased the expression of siGRIM19 in the PC-3 and LNCaP cells,and reduced their death rate when treated with docetaxel compared with the control group.The expressions of GRIM-19 mRNA and protein were remarkably upregulated after transfection with GRIM-19,and the overexpressed GRIM-19 promoted the death of the PC-3 and LNCaP cells treated with docetaxel in a dose-dependent manner.Flow cytometry analysis showed a lower apoptosis rate of PC-3-R cells than that of PC-3 cells at different time points of docetaxel-induction at different doses.Conclusion:GRIM-19 is a PCa suppressor gene with a significant facilitating effect on the apoptosis of PCa cells,and the overexpression of GRIM-19 promotes docetaxel-induced PCa cell death and improves the sensitivity of chemotherapy.

Objective:To evaluate the efficacy of acute T-cell lymphoblastic leukemia(T-ALL)in children and explore the prognostic risk factors.Methods:The clinical data of 127 newly diagnosed children with T-ALL admitted to five hospitals in Fujian province from April 2011 to December 2020 were retrospectively analyzed,and compared with children with newly diagnosed acute precursor B-cell lymphoblastic leukemia(B-ALL)in the same period.Kaplan-Meier analysis was used to evaluate the overall survival(OS)and event-free survival(EFS),and COX proportional hazard regression model was used to evaluate the prognostic factors.Among 116 children with T-ALL who received standard treatment,78 cases received the Chinese Childhood Leukemia Collaborative Group(CCLG)-ALL 2008 protocol(CCLG-ALL 2008 group),and 38 cases received the China Childhood Cancer Collaborative Group(CCCG)-ALL 2015 protocol(CCCG-ALL 2015 group).The efficacy and serious adverse event(SAE)incidence of the two groups were compared.Results:Proportion of male,age ≥ 10 years old,white blood cell count(WBC)≥ 50 × 109/L,central nervous system leukemia,minimal residual disease(MRD)≥ 1％during induction therapy,and MRD ≥ 0.01％at the end of induction in T-ALL children were significantly higher than those in B-ALL children(P＜0.05).The expected 10-year EFS and OS of T-ALL were 59.7％and 66.0％,respectively,which were significantly lower than those of B-ALL(P＜0.001).COX analysis showed that WBC ≥ 100 x 109/L at initial diagnosis and failure to achieve complete remission(CR)after induction were independent risk factors for poor prognosis.Compared with CCLG-ALL 2008 group,CCCG-ALL 2015 group had lower incidence of infection-related SAE(15.8％vs 34.6％,P=0.042),but higher EFS and OS(73.9％vs 57.2％,PEFS=0.090;86.5％vs 62.3％,PoS=0.023).Conclusions:The prognosis of children with T-ALL is worse than children with B-ALL.WBC ≥ 100 × 109/L at initial diagnosis and non-CR after induction(especially mediastinal mass has not disappeared)are the risk factors for poor prognosis.CCCG-ALL 2015 regimen may reduce infection-related SAE and improve efficacy.

As a key ocular structure, ciliary muscle has a major role in accommodating both eye and aqueous humor drainage. Recent studies have found that the position and shape of ciliary muscles in myopia are significantly different from those in emmetropia or hyperopia, and the differences of ciliary muscle may affect the progress of myopia by altering ocular accommodation, choroidal tension and intraocular pressure. The present evidence indicating that the thickening of posterior ciliary muscle was associated with the development of myopia, but the mechanism has not been clearly confirmed. This paper summarizes the relationship between the differences of ciliary muscle and myopia, and the possible mechanism of myopia changes affected by ciliary muscle, so as to provide reference for follow-up research.

Objective To examine short-term outcomes and long-term survival of elderly patients (aged over 80 years) with colorectal cancer who received laparoscopic versus open surgery. Methods A total of 313 patients over 80 years old with colorectal cancer who underwent radical surgery were included.According to the surgical method, all patients were divided into open-surgery group (n=143) and laparoscopic surgery group (n=170).Baseline data were balanced between the two groups by using propensity score matching.Kaplan-Meier was used to draw the survival curve, and survival was compared by Log rank tests.Cox proportional risk model was used to analyze the effects of all factors on overall survival (OS) and disease-free survival (DFS). Results After matching, 93 patients were included in each group.The mean intraoperative blood loss, the incidence of overall postoperative complications and gradeⅠ-Ⅱ complications in the laparoscopic surgery group were significantly lower than those in the open surgery group (all P < 0.05).The time to first flatus, the time to oral feeding, and postoperative hospital stays in the laparoscopic surgery group were significantly shorter than those in the open surgery group (all P < 0.05).The mean number of lymph-node dissection was also significantly higher in the laparoscopic surgery group than in the open surgery group (P=0.030).Patients in both groups had similar 5-year OS (P=0.594) and DFS (P=0.295).Multivariate Cox prognostic analysis showed that CEA level > 5 ng/ml, pathological TNM stage Ⅲ, and perineural invasion were independent risk factors for poor OS and DFS. Conclusion Compared with open surgery, laparoscopic surgery can provide better short-term advantages and similar long-term outcomes for colorectal cancer patients over 80 years of age.