BACKGROUND:Acute exercise tends to cause skeletal muscle tissue damage and lipid metabolism disorders in vivo,but the mechanism by which acute exercise combined with electroacupuncture modulates metabolic and autophagic pathways in vivo is unclear. OBJECTIVE:To observe the changes in metabolic enzymes and autophagy levels in skeletal muscle of rats subjected to acute exercise by electroacupuncture at the acupoints of"Zusanli"and"Huantiao." METHODS:Fifty male Sprague-Dawley rats were randomly divided into three groups:quiet control group(n=10),model group(n=20),and reverse electroacupuncture group(n=20).The latter two groups were set up with two time points,i.e.immediate and 3 hours after exercise groups(n=10 per time point).The model group and the reverse electroacupuncture group underwent acute exercise training after adaptive treadmill training.The rats in the reverse electroacupuncture group underwent electroacupuncture treatment(parameters:electroacupuncture on both sides of the rats at the acupoints of"Zusanli"and"Huantiao,"continuous wave,frequency of 2 Hz,intensity of 2 mA,leaving the needle in the body for 30 minutes,once a day for 7 consecutive days)before treadmill training.Bilateral gastrocnemius muscle tissues were taken under anesthesia immediately after exercise and 3 hours after exercise,and hematoxylin-eosin staining was used to observe the histopathological changes of rat skeletal muscle.ELISA kit was used to detect the activities of hepatic lipase,fatty acid synthase,hormone-sensitive lipase,and carnitine palmitoyltransferase 1 in rat skeletal muscle tissues.Immunohistochemistry and western blot were used to detect the changes in the expression of autophagy genes. RESULTS AND CONCLUSION:After hematoxylin-eosin staining,the arrangement of gastrocnemius muscle fibers in the model group was disturbed,swollen and ruptured immediately after exercise and 3 hours after exercise.In the reverse electroacupuncture group,gastrocnemius muscle fibers were tightly arranged and the number of swollen and ruptured cells was greatly reduced immediately after exercise and 3 hours after exercise,and there was no significant difference when compared with the quiet control group.Compared with the quiet control group,the activities of hepatic lipase and fatty acid synthase were lower while the activities of lipoprotein lipase,hormone-sensitive lipase,and carnitine palmitoyltransferase 1 were higher in the model group and the reverse electroacupuncture group 3 hours after exercise(P＜0.05 or P＜0.01).Compared with the model group,the activities of lipoprotein lipase and carnitine palmitoyltransferase 1 were higher in the reverse electroacupuncture group immediately after exercise(P＜0.05),while the activity of lipoprotein lipase was higher and the activity of hormone-sensitive lipase was lower in the reverse electroacupuncture group 3 hours after exercise(P＜0.01).Immunohistochemical results showed that compared with the quiet control group,the expression of P62,autophagy-related gene 5 and autophagy-related gene 7 was higher in the model group immediately and 3 hours after exercise,as well as in the reverse electroacupuncture group immediately after exercise(P＜0.05 or P＜0.01);compared with the model group,the expression of P62 and autophagy-related gene 7 was lower in the reverse electroacupuncture group immediately and 3 hours after exercise(P＜0.05).Western blot results showed that the protein expression of P62 and autophagy-related gene 7 in the reverse electroacupuncture group was lower than that in the model group immediately after exercise(P＜0.05);the protein expression of Parkin in the model group was higher than that in the quiet control group immediately and 3 hours after exercise(P＜0.05);and the protein expression of Parkin in the reverse electroacupuncture group was lower than that in the model group immediately and 3 hours after exercise(P＜0.05).To conclude,acute exercise induces disorders,swelling and rupture of gastrocnemius muscle fibers in rats and electroacupuncture on both sides of the acupoints of"Zusanli"and"Huantiao"can improve the level of lipid metabolism and regulate autophagy cells in rat skeletal muscle,preventing the disorders of lipid metabolism and damage of gastrocnemius muscle tissues caused by acute exercise.The mechanism may be closely related to the regulation of autophagy-related factor P62,autophagy-related gene 5,autophagy-related gene 7,and Parkin protein expression to promote the occurrence of autophagy or regulate the autophagy pathway in rat skeletal muscle cells.

BACKGROUND:Impaired postural control is an important risk factor for falls and secondary damage in patients with idiopathic normal pressure hydrocephalus.Most of the existing studies have analyzed the gait parameters of patients during straight-line walking,but few have analyzed the postural stability characteristics of patients during static and dynamic activities. OBJECTIVE:To analyze the characteristics of postural stability in elderly patients with idiopathic normal pressure hydrocephalus. METHODS:Twenty-two patients clinically diagnosed with idiopathic normal pressure hydrocephalus at the Department of Neurosurgery,Huadong Hospital Affiliated to Fudan University,Shanghai,China,from September 2022 to February 2023 were selected as the patient group,and 18 healthy accompanying family members were selected as the healthy control group.The postural stability characteristics of the subjects were assessed using the Timed Up-and-Go Test,Multi-Directional Reach Test,Berg Balance Scale,and Static Balance Function Test(reaction time,speed of movement,directional control,maximum offset distance,and endpoint travel). RESULTS AND CONCLUSION:The time required to complete the Timed Up-and-Go Test was significantly longer in the patient group than in the healthy control group(P＜0.05).The results of the stretching test in the four directions of anterior,posterior,leftand right were significantly lower in the patient group than in the healthy control group(P＜0.05).The Berg Balance Scale scores in the patient group were lower than those in the healthy control group(P＜0.05).In the Static Balance Function Test,the results of reaction,movement speed,directional control,maximum offset distance and endpoint travel index were smaller in the patient group than the healthy control group(P＜0.05).To conclude,patients with idiopathic normal pressure hydrocephalus exhibit overall postural control deficits,and impaired reaction and execution abilities make these patients unable to make timely and accurate motor responses in the face of disturbances from internal or external sources,resulting in postural instability and increasing the risk of falls.

OBJECTIVE To identify and analyze adverse drug event （ADE） signals associated with tirzepatide based on the FDA Adverse Event Reporting System （FAERS） database， providing a reference for clinical medication safety. METHODS ADE reports from January 1， 2022， to June 30， 2024， with tirzepatide as the primary suspected drug， were extracted from the FAERS database. Medical Dictionary for Regulatory Activities was used to systematically categorize the selected system organ class （SOC） and preferred term of ADE. Signal mining and analysis were performed using the reporting odds ratio method and the proportional reporting ratio method. RESULTS A total of 39 229 ADE reports related to tirzepatide were obtained， including 3 934 severe ADE reports （10.03%）. The majority of severe ADE reports were related to hospitalization or prolonged hospitalization （3.82%）， involving 131 positive ADE signals. Among the reports with documented patient gender and age， 26 195 were female （66.77%）， 7 869 were male （20.06%）， and the majority of patients were aged 18-64 years （54.26%）. The top three most frequently reported ADE were injection site pain， nausea， and injection site hemorrhage. Strong ADE signals not mentioned in the tirzepatide instruction included injection site coldness， starvation ketoacidosis， injection site hemorrhage， hunger， elevated adrenaline， injection site skin cracking， binge eating， skin laxity， intestinal sepsis， lack of satiety， and dysesthesia. Subgroup analysis for patient’s gender and age showed differences in the proportion of ADE reports across different SOC. Male patients or those aged≥65 years had a higher risk of gastrointestinal system disorders compared to female patients or those aged ＜65 years. CONCLUSIONS In clinical use of tirzepatide， in addition to monitoring ADE listed in the instruction， attention should also be paid to ADE not mentioned in the instruction， such as injection site coldness， starvation ketoacidosis， injection site hemorrhage， elevated adrenaline， and intestinal sepsis， to ensure patient safety.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

[Objective] To establish a new scoring system to predict the perioperative outcomes (operation time, intraoperative blood loss, and trifecta achievement) in patients undergoing robot-assisted partial nephrectomy (RAPN) by integrating the RENAL and Mayo adhesive probability (MAP) scores. [Methods] Clinical data of 178 patients with renal cell carcinoma who underwent RAPN performed by the same surgeon in our hospital during Jan.2015 and Jan.2022 were retrospectively analyzed.The RENAL and MAP scores of all patients were calculated.Linear regression and logistic regression were used to evaluate the associations between the components of the RENAL and MAP scores (a total of 6 variables) and perioperative outcomes.The factors with significant associations were then included into logistic regression analysis to identify independent predictors for constructing an assessment system for perioperative outcomes, and the receiver operating characteristic (ROC) curve was plotted to calculate the area under the curve (AUC) to predict its efficacy. [Results] Multivariate linear regression analysis showed that tumor size (β=6.14, 95%CI: 1.93—10.34, P=0.004), exophytic rate (β=10.60, 95%CI: 3.44—17.76, P=0.004), and perinephric fat thickness (β=16.48, 95%CI: 8.52—24.45, P<0.001) were significantly associated with operation time.Tumor size (β=10.55 95%CI: 5.60—15.49, P<0.001) was associated with both intraoperative blood loss and trifecta achievement (OR=1.73, 95%CI: 1.26—2.36, P=0.001). Multivariate logistic regression analysis of these 3 factors identified tumor size (OR=9.07, 95% CI: 1.18—69.45, P=0.03) and perinephric fat thickness (OR=2.28, 95%CI: 1.86—6.04, P=0.01) as independent predictors of perioperative outcomes.Based on these findings, the tumor size and perinephric fat thickness (RP) scoring was constructed, which demonstrated better predictive ability than RENAL score or MAP score alone (RP vs.RENAL vs.MAP: 0.766 vs.0.548 vs.0.684). [Conclusion] The RP score includes fewer variables than the RENAL and MAP scores but outperforms them.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Background::The effect of bariatric surgery on type 2 diabetes mellitus (T2DM) control can be assessed based on predictive models of T2DM remission. Various models have been externally verified internationally. However, long-term validated results after laparoscopic sleeve gastrectomy (LSG) surgery are lacking. The best model for the Chinese population is also unknown.Methods::We retrospectively analyzed Chinese population data 5 years after LSG at Beijing Shijitan Hospital in China between March 2009 and December 2016. The independent t-test, Mann–Whitney U test, and chi-squared test were used to compare characteristics between T2DM remission and non-remission groups. We evaluated the predictive efficacy of each model for longterm T2DM remission after LSG by calculating the area under the curve (AUC), sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV), and predicted-to-observed ratio, and performed calibration using Hosmer–Lemeshow test for 11 prediction models. Results::We enrolled 108 patients, including 44 (40.7%) men, with a mean age of 35.5 years. The mean body mass index was 40.3 ± 9.1 kg/m 2, the percentage of excess weight loss (%EWL) was (75.9 ± 30.4)%, and the percentage of total weight loss (% TWL) was (29.1 ± 10.6)%. The mean glycated hemoglobin A1c (HbA1c) level was (7.3 ± 1.8)% preoperatively and decreased to (5.9 ± 1.0)% 5 years after LSG. The 5-year postoperative complete and partial remission rates of T2DM were 50.9% [55/108] and 27.8% [30/108], respectively. Six models, i.e., "ABCD", individualized metabolic surgery (IMS), advanced-DiaRem, DiaBetter, Dixon et al’s regression model, and Panunzi et al’s regression model, showed a good discrimination ability (all AUC >0.8). The "ABCD" (sensitivity, 74%; specificity, 80%; AUC, 0.82 [95% confidence interval [CI]: 0.74–0.89]), IMS (sensitivity, 78%; specificity, 84%; AUC, 0.82 [95% CI: 0.73–0.89]), and Panunzi et al’s regression models (sensitivity, 78%; specificity, 91%; AUC, 0.86 [95% CI: 0.78–0.92]) showed good discernibility. In the Hosmer–Lemeshow goodness-of-fit test, except for DiaRem ( P <0.01), DiaBetter ( P <0.01), Hayes et al ( P = 0.03), Park et al ( P = 0.02), and Ramos-Levi et al’s ( P <0.01) models, all models had a satifactory fit results ( P >0.05). The P values of calibration results of the "ABCD" and IMS were 0.07 and 0.14, respectively. The predicted-to-observed ratios of the "ABCD" and IMS were 0.87 and 0.89, respectively. Conclusion::The prediction model IMS was recommended for clinical use because of excellent predictive performance, good statistical test results, and simple and practical design features.

Background::Breast cancer is ranked among the most prevalent malignancies in the Chinese female population. However, comprehensive reports detailing the latest epidemiological data and attributable disease burden have not been extensively documented.Methods::In 2018, high-quality cancer surveillance data were recorded in 700 population-based cancer registries in China. We extracted data on female breast cancers (International Classification of Diseases, Tenth Revision [ICD-10]: C50) and estimated the incidence and mortality in 2022 according to the baseline data and corresponding trends from 2010 to 2018. Pathological types were classified according to the ICD for Oncology, 3rd Edition codes. Disability-adjusted life years (DALYs) were calculated as the sum of the years of life lost (YLLs) and years lived with disability (YLDs).Results::In 2022, approximately 357,200 new female breast cancer cases and 75,000 deaths occurred in China, accounting for 15.59% and 7.94% of total new cancer cases and deaths, respectively. The age-standardized incidence rate (ASIR) was 33.04 per 100,000. When analyzed by pathological type, the ASIRs for papillary neoplasms, invasive breast carcinoma, rare and salivary gland-type tumors, and other types were 1.13, 29.79, 0.24, and 1.88 per 100,000, respectively. The age-standardized mortality rate (ASMR) was 6.10 per 100,000. A total of 2,628,000 DALYs were found to be attributable to female breast cancer in China, comprising 2,278,300 YLLs and 349,700 YLDs. The ASIR, ASMR, and age-standardized rate (ASR) for DALYs in urban areas were consistently higher than those in rural areas. We observed a four-fold increase in the ASIR and ASR for DALYs and an eight-fold increase in the ASMR among females over 55 years compared with those aged under 55 years.Conclusion::These data provide invaluable insights into the latest epidemiology of female breast cancer in China and highlight the urgency for disease prevention and control strategy formulation.