BACKGROUND:Dexamethasone and hindlimb suspension are commonly used methods for modeling sarcopenia in animal experiments due to their short modeling time,ease of operation,and low cost.OBJECTIVE:To compare the differences in muscle mass,strength and functional phenotypes and molecular mechanisms between two mouse sarcopenia models induced by dexamethasone and hindlimb suspension.METHODS:Thirty male C57BL/6 mice were randomly divided into three groups(n=10 per group).The normal control group received no intervention.The dexamethasone group received daily intraperitoneal injections of 1 mg/kg/d dexamethasone sodium phosphate solution for 6 continuous days to establish sarcopenia models in mice,while mice in the hindlimb suspension group were suspended by tail harness for 16 hours,once per day,to establish sarcopenia models.Within 6 weeks after modeling,changes in body mass were monitored.After 6 weeks of modeling,mice were tested for limb grip strength,mobility(swimming test),skeletal muscle wet mass,and skeletal muscle pathological morphology.Expressions of skeletal muscle protein synthesis and catabolism indexes as well as the AMPK/FoXO3α signaling pathway were detected by RT-PCR and western blot.RESULTS AND CONCLUSION:(1)Two weeks after modeling,both dexamethasone and hindlimb suspension groups showed a significant decrease in body mass compared with the normal control group(P<0.001).After 6 weeks of modeling,grip strength of mice in both dexamethasone and hindlimb suspension groups was lower than that in the normal control group(P<0.001).The wet mass of gastrocnemius and extensor digitorum longus muscles and the cross-sectional area of gastrocnemius and soleus muscles in the dexamethasone group were lower than those in the normal control group(P<0.05).Compared with the hindlimb suspension group,the cross-sectional area of gastrocnemius muscle was significantly smaller in the dexamethasone group(P<0.05),while the cross-sectional area of soleus muscle was larger in the dexamethasone group(P<0.05).Mice in the dexamethasone group had reduced mobility when compared with those in the normal control group and the hindlimb suspension group(P<0.05).(3)Compared with the normal control group,PI3K,mTOR,AMPK,and PGC-1α mRNA expression and P-AMPK/AMPK protein were decreased in the two modeling groups(P<0.05),and FoXO3α mRNA expression and PGC-1α and FoXO3 protein expression were elevated(P<0.05);in the dexamethasone group,Akt1 mRNA expression was decreased(P<0.05),while Atrogin-1 and MuRF-1 mRNA expression was elevated(P<0.05);in the hindlimb suspension group,Akt1 mRNA expression was elevated(P<0.05).(4)Compared with the dexamethasone group,mTOR,Akt1,and FoXO3α mRNA expression was elevated in the hindlimb suspension group(P<0.05),while Atrogin-1 and MuRF-1 mRNA expression was decreased(P<0.05).To conclude,both modeling methods could decrease the levels of mitochondrial energy metabolism in skeletal muscle,with the dexamethasone group mediating atrophy of skeletal muscle through the dual action of ubiquitin proteasome and energy metabolism pathways,and the hindlimb suspension group inducing atrophy of skeletal muscle by mediating the energy metabolism pathway through the AMPK/FoXO3α signaling pathway,subsequently causing a reduction in mass,strength,and function of skeletal muscle.

Background and Aims:Hepatocellular carcinoma(HCC)is the most prevalent type of liver malignancy,accounting for 80%of all primary liver cancer cases.Partial hepatectomy is widely considered to be the treatment of choice for HCC.However,post-hepatectomy liver failure(PHLF)is the most serious complication and the leading cause of perioperative death.Therefore,an accurate assessment of the risk of PHLF is particularly critical.Patients with large hepatocellular carcinoma have larger tumors(tumor diameter≥5 cm)and more resected liver tissue,and are more likely to develop PHLF.Previous studies have used various methods to assess the risk of PHLF,including liver function,Child-Pugh classification,model for end-stage liver disease,albumin-bilirubin(ALBI),and aspartate aminotransferase-to-platelet ratio index score.However,no model has been developed for data on hepatectomy for large HCC.Therefore,this study aims to analyze the risk factors of PHLF in HCC patients with large tumor and to construct a preoperative nomogram prediction model to guide and optimize clinical decision-making.Methods:The clinical data of 927 patients with large liver cancer who underwent radical hepatectomy in the First Affiliated Hospital of Anhui Medical University(721 cases,training cohort)and the Second Affiliated Hospital of Anhui Medical University(206 cases,validation cohort)from January 2018 to June 2023 were retrospectively collected.The patients'baseline data,laboratory examination,imaging data,and surgical information were collected.Univariate analysis combined with multivariate analysis was used to screen out the independent risk factors for inducing PHLF,and binary Logistic regression was used to construct a prediction model for PHLF.ROC,calibration,and clinical decision curves verified the model's performance.Results:There were no significant differences in all preoperative data between the training and validation cohorts(P>0.05).Grade B or C PHLF occurred in 192 of 927 patients(20.7%),including 8 patients with grade C PHLF.Univariate and multivariate Logistic regression analyses were used to determine the independent risk factors of PHLF,including tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss.These factors were included in the Logistic regression analysis,and a nomogram model was constructed to predict PHLF.The nomogram model was validated,and the C-index of the nomogram was 0.757.The ROC curve analysis of the prediction probability of the model showed that the AUC of the training set was 0.757(95%CI=0.703-0.811),and the AUC of the validation set was 0.779(95%CI=0.702-0.863).The validation showed that the model had good predictive ability.Conclusions:Tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss are independent risk factors for PHLF.The nomogram prediction model constructed in this study can accurately assess the risk of preoperative PHLF,which is helpful for better clinical management,reducing the occurrence of PHLF,and improving the postoperative prognosis of patients.

Background and Aims:Hepatocellular carcinoma(HCC)is the most prevalent type of liver malignancy,accounting for 80%of all primary liver cancer cases.Partial hepatectomy is widely considered to be the treatment of choice for HCC.However,post-hepatectomy liver failure(PHLF)is the most serious complication and the leading cause of perioperative death.Therefore,an accurate assessment of the risk of PHLF is particularly critical.Patients with large hepatocellular carcinoma have larger tumors(tumor diameter≥5 cm)and more resected liver tissue,and are more likely to develop PHLF.Previous studies have used various methods to assess the risk of PHLF,including liver function,Child-Pugh classification,model for end-stage liver disease,albumin-bilirubin(ALBI),and aspartate aminotransferase-to-platelet ratio index score.However,no model has been developed for data on hepatectomy for large HCC.Therefore,this study aims to analyze the risk factors of PHLF in HCC patients with large tumor and to construct a preoperative nomogram prediction model to guide and optimize clinical decision-making.Methods:The clinical data of 927 patients with large liver cancer who underwent radical hepatectomy in the First Affiliated Hospital of Anhui Medical University(721 cases,training cohort)and the Second Affiliated Hospital of Anhui Medical University(206 cases,validation cohort)from January 2018 to June 2023 were retrospectively collected.The patients'baseline data,laboratory examination,imaging data,and surgical information were collected.Univariate analysis combined with multivariate analysis was used to screen out the independent risk factors for inducing PHLF,and binary Logistic regression was used to construct a prediction model for PHLF.ROC,calibration,and clinical decision curves verified the model's performance.Results:There were no significant differences in all preoperative data between the training and validation cohorts(P>0.05).Grade B or C PHLF occurred in 192 of 927 patients(20.7%),including 8 patients with grade C PHLF.Univariate and multivariate Logistic regression analyses were used to determine the independent risk factors of PHLF,including tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss.These factors were included in the Logistic regression analysis,and a nomogram model was constructed to predict PHLF.The nomogram model was validated,and the C-index of the nomogram was 0.757.The ROC curve analysis of the prediction probability of the model showed that the AUC of the training set was 0.757(95%CI=0.703-0.811),and the AUC of the validation set was 0.779(95%CI=0.702-0.863).The validation showed that the model had good predictive ability.Conclusions:Tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss are independent risk factors for PHLF.The nomogram prediction model constructed in this study can accurately assess the risk of preoperative PHLF,which is helpful for better clinical management,reducing the occurrence of PHLF,and improving the postoperative prognosis of patients.

BACKGROUND:Dexamethasone and hindlimb suspension are commonly used methods for modeling sarcopenia in animal experiments due to their short modeling time,ease of operation,and low cost.OBJECTIVE:To compare the differences in muscle mass,strength and functional phenotypes and molecular mechanisms between two mouse sarcopenia models induced by dexamethasone and hindlimb suspension.METHODS:Thirty male C57BL/6 mice were randomly divided into three groups(n=10 per group).The normal control group received no intervention.The dexamethasone group received daily intraperitoneal injections of 1 mg/kg/d dexamethasone sodium phosphate solution for 6 continuous days to establish sarcopenia models in mice,while mice in the hindlimb suspension group were suspended by tail harness for 16 hours,once per day,to establish sarcopenia models.Within 6 weeks after modeling,changes in body mass were monitored.After 6 weeks of modeling,mice were tested for limb grip strength,mobility(swimming test),skeletal muscle wet mass,and skeletal muscle pathological morphology.Expressions of skeletal muscle protein synthesis and catabolism indexes as well as the AMPK/FoXO3α signaling pathway were detected by RT-PCR and western blot.RESULTS AND CONCLUSION:(1)Two weeks after modeling,both dexamethasone and hindlimb suspension groups showed a significant decrease in body mass compared with the normal control group(P<0.001).After 6 weeks of modeling,grip strength of mice in both dexamethasone and hindlimb suspension groups was lower than that in the normal control group(P<0.001).The wet mass of gastrocnemius and extensor digitorum longus muscles and the cross-sectional area of gastrocnemius and soleus muscles in the dexamethasone group were lower than those in the normal control group(P<0.05).Compared with the hindlimb suspension group,the cross-sectional area of gastrocnemius muscle was significantly smaller in the dexamethasone group(P<0.05),while the cross-sectional area of soleus muscle was larger in the dexamethasone group(P<0.05).Mice in the dexamethasone group had reduced mobility when compared with those in the normal control group and the hindlimb suspension group(P<0.05).(3)Compared with the normal control group,PI3K,mTOR,AMPK,and PGC-1α mRNA expression and P-AMPK/AMPK protein were decreased in the two modeling groups(P<0.05),and FoXO3α mRNA expression and PGC-1α and FoXO3 protein expression were elevated(P<0.05);in the dexamethasone group,Akt1 mRNA expression was decreased(P<0.05),while Atrogin-1 and MuRF-1 mRNA expression was elevated(P<0.05);in the hindlimb suspension group,Akt1 mRNA expression was elevated(P<0.05).(4)Compared with the dexamethasone group,mTOR,Akt1,and FoXO3α mRNA expression was elevated in the hindlimb suspension group(P<0.05),while Atrogin-1 and MuRF-1 mRNA expression was decreased(P<0.05).To conclude,both modeling methods could decrease the levels of mitochondrial energy metabolism in skeletal muscle,with the dexamethasone group mediating atrophy of skeletal muscle through the dual action of ubiquitin proteasome and energy metabolism pathways,and the hindlimb suspension group inducing atrophy of skeletal muscle by mediating the energy metabolism pathway through the AMPK/FoXO3α signaling pathway,subsequently causing a reduction in mass,strength,and function of skeletal muscle.

The incidence and mortality rate of hepatocellular carcinoma rank among the top of all cancer types,seriously threatening the life and health of human beings. In recent years,the rapid development of artificial intelligence and the deepening of the concept of precision medicine have led to a boom in interdisciplinary research. Pathomics,as an emerging omics technology driven by artificial intelligence,can mine massive information from high-resolution whole slide images,and shows broad application prospects in the diagnosis,treatment and prognosis assessment of hepatocellular carcinoma. However, pathomics research in hepatocellular carcinoma is still in its infancy, and its research patterns and clinical applications still face several controversies and challenges, including data security, ethics, and “black box” issues. Future research should focus on conducting prospective studies, integrating multimodal data, improving computational technologies, and establishing professional standards to promote the high-quality development of pathomics technology in both clinical and basic research of hepatocellular carcinoma.

The incidence and mortality rate of hepatocellular carcinoma rank among the top of all cancer types,seriously threatening the life and health of human beings. In recent years,the rapid development of artificial intelligence and the deepening of the concept of precision medicine have led to a boom in interdisciplinary research. Pathomics,as an emerging omics technology driven by artificial intelligence,can mine massive information from high-resolution whole slide images,and shows broad application prospects in the diagnosis,treatment and prognosis assessment of hepatocellular carcinoma. However, pathomics research in hepatocellular carcinoma is still in its infancy, and its research patterns and clinical applications still face several controversies and challenges, including data security, ethics, and “black box” issues. Future research should focus on conducting prospective studies, integrating multimodal data, improving computational technologies, and establishing professional standards to promote the high-quality development of pathomics technology in both clinical and basic research of hepatocellular carcinoma.

Pancreatic cancer is a highly malignant cancer with low survival rate. Early diagnosis, early treatment and early recurrence intervention are the most important keys to improve overall prognosis of pancreatic cancer. With the rapid development of artificial intelligence, it is an inevitable trend to apply it to the diagnosis and treatment of pancreatic cancer to achieve precision medicine for patients. By combining with clinical data, medical images and molecular biology, artifi-cial intelligence has shown broad application prospects in the whole-process management of pancreatic cancer. The authors briefly review the application status and problems of artificial intelligence in the diagnosis and treatment of pancreatic cancer, and discuss its future development direction.

Pancreatic cancer is a highly malignant cancer with low survival rate. Early diagnosis, early treatment and early recurrence intervention are the most important keys to improve overall prognosis of pancreatic cancer. With the rapid development of artificial intelligence, it is an inevitable trend to apply it to the diagnosis and treatment of pancreatic cancer to achieve precision medicine for patients. By combining with clinical data, medical images and molecular biology, artifi-cial intelligence has shown broad application prospects in the whole-process management of pancreatic cancer. The authors briefly review the application status and problems of artificial intelligence in the diagnosis and treatment of pancreatic cancer, and discuss its future development direction.

Objective:To investigate the influencing factors for textbook outcome (TO) after hepatectomy for hepatolithiasis.Methods:The retrospective case-control study was conducted. The clinicopathological data of 216 patients with hepatolithiasis who were admitted to The First Affi-liated Hospital of Anhui Medical University from January 2015 to March 2023 were collected. There were 69 males and 147 females, aged 61(range, 22-85)years. Observation indicators: (1) treatment situations; (2) TO after hepatectomy; (3) Influencing factors for TO after hepatectomy. Measurement data with normal distribution were represented as Mean± SD. Measurement data with skewed distribution were represented as M(range). Count data were expressed as absolute numbers. Logistic regression models were used for univariate and multifactorial analyses. Results:(1) Treatment situations. All the 216 patients underwent hepatectomy, including 45 cases of laparoscopic hepatectomies and 171 cases of open hepatectomies, 161 cases of anatomical hepatectomies and 55 cases of non-anatomical hepatectomies. All the 216 patients underwent intraoperative choledochoscopy exploration and lithotripsy. There were 170 patients with normal Oddi sphincter function and 46 patients with Oddi sphincter dysfunction. All the 216 patients underwent biliary drainage, including 198 cases of external T-tube drainage and 18 cases of internal bile-intestinal drainage. The operation time was (226±75)minutes and volume of intraoperative blood loss was (106±82)mL. There were 29 patients with perioperative blood transfusion and 14 patients with intraoperative severe adverse events. There were 189 patients achieved immediate stone clearance. Of 183 patients with intraoperative bile cultures, 76 cases were positive for bacteria culture. (2) TO after hepatectomy. Of 216 patients, 93 cases had postoperative complications, all of which were successfully discharged after active treatment. One patient had surgery-related death within 90 days after surgery, and the cause of death was liver failure. Five patients were readmitted within 90 days after surgery, and 18 patients had postoperative stone residual. Of 216 patients, 164 cases achieved TO postoperatively and 52 cases did not achieve TO postoperatively. (3) Influencing factors for TO after hepatectomy. Results of multivariate analysis showed that cholangitis, stone distribution, surgical approaches, anatomical hepatectomy, immediate stone removal and postoperative review of choledochoscopy were independent influencing factors for TO after hepatectomy in patients with hepatolithiasis ( P<0.05). Conclusion:Cholangitis, stone distribution, surgical approaches, anatomical hepatectomy, imme-diate stone removal and postoperative review of choledochoscopy are independent influencing factors for TO after hepatectomy in patients with hepatolithiasis.