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.

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.

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*

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 investigate the expression of programmed death ligand-1 (PD-L1, SP142) and PD-L1 (22C3) in triple-negative breast cancer (TNBC), and analyze their correlation with the clinicopathological factors and prognosis. Methods: The clinicopathologic data of 259 patients with TNBC treated in Cancer Hospital from August 2010 to December 2013 were collected. Whole section of surgical tissue samples were collected to conduct PD-L1 (SP142) and PD-L1 (22C3) immunohistochemical (IHC) staining. The PD-L1 expression in tumor cells and tumor infiltrating immune cells were visually assessed respectively, the relationship between PD-L1 expression and clinicopathologic characterizes were analyzed. Univariable and multivariable Cox proportional hazards regression models were used to test the correlations between PD-L1 expression and disease-free survival (DFS) and overall survival (OS). Results: The positive rates of SP142 (immune cell score, ICs≥1%) and 22C3 (combined positive score, CPS≥1) were 42.1%(109/259) and 41.3%(107/259) in TNBC tissues, respectively, with a total coincidence rate of 82.3%. The Kappa value of positive expression cases was 0.571 and the distribution difference of SP142 and 22C3 positive expression cases was statistically significant (P<0.001). The PD-L1 positive patients were less likely to have vascular invasion (P<0.05), but with higher histological grade and Ki-67 proliferation index (P<0.05). The recurrence/metastasis cases(8) of the patients with positive PD-L1 (SP142) was significantly lower than that of patients with negative PD-L1(SP142, 27, P=0.016). The positive expression of PD-L1 (SP142) patients were longer DFS (P=0.019). The OS of patients with positive PD-L1 (SP142) were longer than those with negative PD-L1 (SP142), but without significance (P=0.116). The positive expression of PD-L1 (22C3) was marginally associated with DFS and OS of patients (P>0.05). Conclusions: The expression of PD-L1 (22C3) is different from that of PD-L1 (SP142) in TNBC, and the two antibodies can't be interchangeable for each other in clinical tests. PD-L1 (SP142) status is an independent prognostic factor of DFS in TNBC. The DFS is significantly prolonged in patients with positive expression of PD-L1 (SP142).
B7-H1 Antigen/genetics* ; Humans ; Immunohistochemistry ; Prognosis ; Triple Negative Breast Neoplasms/pathology*

Objective: To investigate the clinical value of the bipolar tweezers-clamp for the hepatic parenchymal transection in the resection of hepatocellular carcinoma. Methods: From January 2020 to January 2021,63 patients with the hepatocellular carcinoma for hepatectomy at Department of Hepatopancreatobiliary Surgery,Yuebei People's Hospital Affiliated to Shantou University Medical College were analyzed retrospectively.According to the different instruments used in the hepatic parenchymal transection,the patients were divided into bipolar tweezers-clamp group and ultrasonic scalpel group.There were 32 patients in bipolar tweezers-clamp group,with age of (55.5±10.5)years(range:37 to 78 years),including 22 males and 10 females,tumor size was (6.0±3.4)cm(range:2.4 to 13.4 cm). There were 6 patients with portal vein tumor thrombus and 5 patients with portal hypertension. There were 31 patients in ultrasonic scalpel group,with aged(57.8±10.1)years(range:37 to 79 years),including 27males and 4 females,tumor size was(7.9±5.1)cm(range: 2.4 to 21.3 cm),3 patients with portal vein tumor thrombus and 2 patients with portal hypertension. The preoperative baseline data,operation time,blood loss,postoperative liver function and the complications were compared between two groups using t test,χ² test and Fisher exact probabilityrespectively. Results: The operation was successfully completed in both groups.Compared with the ultrasonic scalpel group,the operation time was significantly shorter((219.3±76.4)minutes vs.(294.0±100.8)minutes,t=-3.322,P=0.002),the blood loss was less((250(475)ml vs. 500(1 050)ml,t=-2.307,P=0.026),the concentrate red blood cells transfusion volume was less(0.92(0.88)U vs. 2.32(4.00)U,Z=-1.987,P=0.047) in the bipolar tweezers-clamp group.The postoperative serum ALB level was higher in the bipolar tweezers-clamp group than that in the ultrasonic scalpel group((33.5±6.1)g/L vs. (29.5±4.2)g/L,t=3.226,P=0.020) on postoperative day 1;((35.7±4.5)g/L vs.(30.1±3.2)g/L,t=5.575,P<0.01) on postoperative day 3;((33.2±3.7)g/L vs. (31.0±4.4)g/L,t=3.020,P=0.004) on postoperative day 7. There was no significant difference in serum ALT,TBIL and PT level between the two groups(all P>0.05).No postoperative bile leakage occurred in both groups.The postoperative complications occurred in 8 cases(25.0%)in the bipolar tweezers-clamp group,including liver failure in one,and in 11 cases(35.5%)in the ultrasonic scalpel group,including liver failure in two(P>0.05). Conclusion: The bipolar tweezers-clamp is a safe and reliable method for the hepatic parenchymal transaction,which is quick and less bleeding during the hepatic resection.
Blood Loss, Surgical ; Carcinoma, Hepatocellular/surgery* ; Female ; Hemorrhage ; Hepatectomy/methods* ; Humans ; Hypertension, Portal/surgery* ; Liver Failure ; Liver Neoplasms/surgery* ; Male ; Retrospective Studies ; Treatment Outcome

China ; Manganese/toxicity* ; Stainless Steel