Metabolic diseases characterized by an imbalance in energy homeostasis represent a significant global health challenge. Individuals with metabolic diseases often suffer from complications related to disorders in lipid metabolism, such as obesity and non-alcoholic fatty liver disease (NAFLD). Understanding core genes involved in lipid metabolism can advance strategies for the prevention and treatment of these conditions. Stearoyl-CoA desaturase 1 (SCD1) is a key enzyme in lipid metabolism that converts saturated fatty acids into monounsaturated fatty acids. SCD1 plays a crucial regulatory role in numerous physiological and pathological processes, including energy homeostasis, glycolipid metabolism, autophagy, and inflammation. Abnormal transcription and epigenetic activation of Scd1 contribute to abnormal lipid accumulation by regulating multiple signaling axes, thereby promoting the development of obesity, NAFLD, diabetes, and cancer. This review comprehensively summarizes the key role of SCD1 as a metabolic hub gene in various (patho)physiological contexts. Further it explores potential translational avenues, focusing on the development of novel SCD1 inhibitors across interdisciplinary fields, aiming to provide new insights and approaches for targeting SCD1 in the prevention and treatment of metabolic diseases.
Stearoyl-CoA Desaturase/metabolism* ; Humans ; Metabolic Diseases/physiopathology* ; Lipid Metabolism/physiology* ; Animals ; Obesity/enzymology* ; Non-alcoholic Fatty Liver Disease

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective:To assess the clinical utility of vector flow mapping（VFM）for evaluating left ventricular wall shear stress（WSS）in individuals with non-obstructive hypertrophic cardiomyopathy（nHCM）.Methods:Forty patients with non-obstructive HCM（nHCM）and 46 healthy volunteers in Tangdu Hospital of Air Force Medical University from May 2020 to September 2023 were enrolled prospectively in this study. The left ventricular WSS of each of 18 segments was measured and analyzed by VFM during rapid filling phase（T1），slow filling phase（T2），isovolumetric contraction phase（T3）and rapid ejection phase（T4）.Results:① WSS decreased gradually from basal to apical segments in control group，while there was no such change pattern in nHCM group. ② Diastolic phase：When compared to the control group，the nHCM group demonstrated significantly increased WSS across all segments of the inferoseptal regions，the basal anteroseptal segment，and the middle and apical inferior segments during the T1 stage. Additionally，at the T2 stage，the WSS was significantly higher in the nHCM group across all segments of the inferoseptal and anteroseptal regions，the basal anterolateral segment，and the apical inferolateral and anterior segments（all P<0.05）. Conversely，during the T1 stage，the basal anterolateral segment，basal inferolateral segment，and the middle and apical anteroseptal segments，as well as during the T2 stage，the basal and middle inferior segments，exhibited lower WSS values compared to the control group，with these differences being statistically significant（all P<0.05）. ③Systolic Phase：During the T3 stage，the WSS values in all segments of the anteroseptal and anterolateral regions，as well as the apical inferior and anterior segments，were significantly elevated in the nHCM group compared to the control group（all P<0.05）.At the T4 stage，WSS in each segment of the inferolateral and inferior regions，as well as the basal and middle anterior segments，was significantly elevated in the nHCM group compared to the control group（all P<0.01）. Conversely，during the same stage，the WSS values in the basal inferolateral segment，the basal and middle anterolateral segments，and the basal and middle anteroseptal segments were significantly lower in the nHCM group than in the control group，with all differences reaching statistical significance（all P<0.01）.Regarding global WSS，the left ventricular global WSS in the nHCM group was significantly higher than that in the control group at both the T2 and T3 stages（all P<0.001）. Furthermore，the global WSS at the T3 stage was negatively correlated with left ventricular end-systolic volume，end-diastolic volume，and left ventricular stroke volume（ r=-0.226， P=0.036； r=-0.345， P=0.001； r=-0.303， P=0.005）. Conclusions:Significant differences in WSS are observed between patients with nHCM and control groups at various phases. WSS may serve as an early indicator of changes in cardiac function in nHCM patients.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective:To evaluate the early outcomes of total hip arthroplasty (THA) and discuss the revisions post THA in the treatment for Kashin-Beck disease (KBD) with severe hip problems.Methods:This retrospective cohort study enrolled 50 patients (64 hips) with a mean age of 52.4±8.7 years, including 25 male patients and 25 female patients (36 left hips and 28 right hips), who were diagnosed as KBD with hip problems and received THA at Arthritis Clinical and Research Centre, Peking University People's Hospital from October 2019 to January 2024. The leg length discrepancy (LLD), femoral offset (FO), abduction angle and anteversion angle were calculated preoperatively and one week post-operation. The postoperative radiological indexes and the functional outcomes in the last follow-up were compared with the preoperative assessment.Results:The surgical duration was 105(80, 120) min and the bleeding amount was 300(200, 400) ml. All the cases were followed up for an average of 37 months (ranging from 21 to 44 months). Significant differences were found on postoperative radiological images, with LLD improving to 0.50±0.78 cm from a preoperative value of -1.36±0.79 cm, and FO increasing to 3.28±1.01 cm from 2.72±0.83 cm ( P<0.05). The mean postoperative abduction angle and anteversion angle were 42.5°±7.7° and 15.1°±5.9°, respectively. A total of 71.8% and 95.3% hips fell within the Lewinnek safe zones of abduction angle and anteversion angle, respectively. In terms of functional outcomes, the average range of motion improved significantly to 185°(173°, 210°) from a preoperative value of 99°(76°, 123°), and the Harris Hip Score increased from 35(26, 43) preoperatively to 70(63, 80) postoperatively ( P<0.05). During the follow-up, there were complications for two cases of femoral stem loosening, one case of periprosthetic femoral fracture, one case of hip dislocation, and one case of acetabular component loosening with hip subluxation. Additionally, seven patients exhibited Trendelenburg gait. A total of five hips required revision surgery due to severe complications, including two cases of femoral stem loosening, one case of periprosthetic femoral fracture, one case of hip dislocation, and one case of acetabular component loosening with subluxation. Conclusions:Patients with KBD demonstrated significant early improvements in both radiological and functional outcomes following THA.

Objective:To explore the independent association between handgrip strength and chronic kidney disease (CKD) in adult residents in Anhui Province using data from the China Adult Chronic Disease and Risk Factor Surveillance (2023).Methods:A multi-stage stratified cluster random sampling method was used to select residents aged ≥18 years for surveys, physical measurements, and laboratory tests. Relevant covariates were adjusted, and a multivariable logistic regression model was established to infer the association between handgrip strength and CKD, followed by subgroup analysis.Results:A total of 7 295 participants were included in the study, with age of (61.5±13.2) years, and 55.6% of the study participants were women. The results of the multivariate logistic regression analysis showed that with each 1.0 kg increase in handgrip strength, the risk for CKD decreased by 1.3% ( OR=0.987, 95% CI: 0.978-0.997). Compared with those with low handgrip strength, the people with moderate hasdgrip strength ( OR=0.818, 95% CI: 0.694-0.964) and high handgrip strength ( OR=0.729, 95% CI: 0.598-0.989) had lower risk for CKD. In the subgroup analysis, the association between handgrip strength and risk for CKD remained unchanged regardless age, sex, smoking status, and alcohol consumption statuys, and the prevalence of hypertension and hyperlipidemia (interaction P>0.05), except BMI and diabetes. Conclusion:The decline in handgrip strength is associated with an increased risk for CKD in adult residents in Anhui.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the role of hippocampal activating transcription factor 5 (ATF5) in cognitive impairment induced by neuropathic pain and the relationship with mitochondrial unfolded protein response(mtUPR) in mice.Methods:This study was conducted in 2 parts. Experiment Ⅰ Twenty-four SPF healthy male C57BL/6 mice, aged 6-8 weeks, weighing 20-25 g, were divided into 2 groups ( n=12 each) using a random number table method: sham operation group (S1 group) and neuropathic pain group (NP group). Neuropathic pain was induced by chronic constriction injury to the sciatic nerve. The mechanical paw withdrawal threshold (MWT) and thermal paw withdrawal latency (TWL) were measured before developing the model and at 7, 14, 21 and 28 days after developing the model. Mouse cognitive function was assessed using the novel object recognition test from 30-31 days after developing the model. After the end of the novel object recognition test, mice were sacrificed and the hippocampal CA1 region was harvested for determination of the expression of ATF5 (by Western blot) and the expression of ATF5 in neurons, microglia and astrocytes (by immunofluorescence double staining). Experiment Ⅱ Thirty-six SPF healthy male C57BL/6 mice, aged 6-8 weeks, weighing 20-25 g, were divided into 3 groups ( n=12 each) using a random number table method: sham operation group (S2 group), neuropathic pain + ATF5 up-regulation group (NA group), and neuropathic pain + empty virus group (NE group). On day 14 after developing the model, a virus that specifically up-regulated ATF5 expression in neurons and empty virus were injected into the hippocampal CA1 region. The MWT and TWL were measured at days 28 and 35 after developing the model. The novel object recognition test was performed on day 36 after developing the model to evaluate the cognitive function. After the end of the behavioral test, mice were sacrificed and the hippocampal CA1 region was harvested for detection of the expression of ATF5 and mtUPR marker proteins (Lon protease [LONP1] and heat shock protein 60 [HSP60]) by Western blot. Results:Experiment Ⅰ Compared with S1 group, no statistically significant change was found in the MWT and TWL before developing the model ( P>0.05), the MWT and TWL were significantly decreased on days 7, 14, 21 and 28 after developing the model, the discrimination index (DI) was decreased at day 31 after developing the model, the expression of ATF5 was down-regulated, the expression of ATF5 in neurons was down-regulated ( P<0.05), and no statistically significant change was found in the expression of ATF5 in mircrolia and astrocytes in NP group ( P>0.05). Experiment Ⅱ Compared with S2 group, the MWT and TWL were significantly decreased on days 28 and 35 after developing the model in NE group and NA group, DI was decreased, and the expression of ATF5, LONP1 and HSP60 was down-regulated in NE group ( P<0.05), and no significant change was found in NA group ( P>0.05). Compared with NE group, no significant change was found in the MWT and TWL in NA group ( P>0.05), DI was significantly increased, and the expression of ATF5, LONP1 and HSP60 was up-regulated in NA group ( P<0.05). Conclusions:Down-regulated ATF5 in the hippocampus is involved in the process of cognitive impairment caused by neuropathic pain, and the mechanism may be related to the inhibition of mtUPR.