Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

At present, there is no cure for acquired immune deficiency syndrome (AIDS) due to HIV-1 latent reservoirs. Therefore, it urgently requires novel HIV-1 latency-regulating agents with high potency, low toxicity and favorable drug-like properties to achieve a functional cure for AIDS. Herein, we reviewed the advances in HIV-1 latency-regulating agents since 2019, including the drug discovery strategies, bioactivities, and mechanisms of these compounds. It is of great guiding significance in the development of latency-regulating agents with clinical value.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective:To investigate the effect of the ratio of the maximum diameter of aneurysm sac to age (R) on the long-term efficacy of endovascular aneurysm repair (EVAR) and open surgical repair (OSR) in patients with infrarenal abdominal aortic aneurysm (IAAA).Methods:This is a retrospective cohort study.The clinical data of 317 patients with IAAA who underwent surgical repair in the Department of Vascular Surgery,the Third Affiliated Hospital of Sun Yat-Sen University from January 2016 to October 2022 were retrospectively collected.There were 266 males and 51 females,aged (69.7±8.3) years (range:37 to 87 years).The R value of the patient was calculated and the receiver operating characteristic(ROC) curve was used to establish a model to calculate the optimal cut-off value.The propensity score matching method was used to match the baseline data of patients in the EVAR and OSR group by 3∶1 (the caliper value was 0.05),and the patients were stratified according to the cutoff value of R, and the postoperative efficacy and survival of the patients were analyzed.The primary endpoint was the total mortality rate,and the secondary endpoints included the occurrence of postoperative complications and reintervention.Pearson χ2 or Fisher ′s exact test was used for categorical variables, and independent sample t test or Wilcoxon rank sum test was used for continuous variables to compare differences between groups.The survival curves of the two groups were described by Kaplan-Meier method. Results:After propensity score matching,198 cases were in the EVAR group and 66 cases were in the OSR group.The ROC model showed that the best cut-off value of R value was 0.90,and the two groups were divided into two layers:R<0.90 and R≥0.90.Among them,112 patients with R<0.90 (84 cases of EVAR,28 cases of OSR);there were 152 patients with R≥0.90 (114 cases of EVAR and 38 cases of OSR).The follow-up time was (23.6±1.6) months (range:1 to 70 months).In the R≥0.90 stratification,the total mortality (26.3% vs.5.3%, χ2=7.600， P=0.006),complication rate (44.7% vs.26.3%, χ2=4.025， P=0.045), and secondary intervention rate (31.6% vs.13.2%, χ2=4.910， P=0.027) in the EVAR group were higher than those in the OSR group.In the R<0.90 stratification,there was no significant difference in the total mortality rate (13.1% vs.10.7%, χ2=0.109， P=0.741), complication rate (28.6% vs.35.7%, χ2=0.507， P=0.477) and secondary intervention rate (14.3% vs.21.4%, χ2=0.353， P=0.552) between the two groups. Conclusions:When R≥0.90 in IAAA patients,OSR maybe more beneficial to patients in terms of survival rate,postoperative complication rate and secondary intervention rate than EVAR.When R<0.90,there are no significant differences in survival rate,complication rate and secondary intervention rate between the two surgical methods.

Objective:To investigate the effect of the ratio of the maximum diameter of aneurysm sac to age (R) on the long-term efficacy of endovascular aneurysm repair (EVAR) and open surgical repair (OSR) in patients with infrarenal abdominal aortic aneurysm (IAAA).Methods:This is a retrospective cohort study.The clinical data of 317 patients with IAAA who underwent surgical repair in the Department of Vascular Surgery,the Third Affiliated Hospital of Sun Yat-Sen University from January 2016 to October 2022 were retrospectively collected.There were 266 males and 51 females,aged (69.7±8.3) years (range:37 to 87 years).The R value of the patient was calculated and the receiver operating characteristic(ROC) curve was used to establish a model to calculate the optimal cut-off value.The propensity score matching method was used to match the baseline data of patients in the EVAR and OSR group by 3∶1 (the caliper value was 0.05),and the patients were stratified according to the cutoff value of R, and the postoperative efficacy and survival of the patients were analyzed.The primary endpoint was the total mortality rate,and the secondary endpoints included the occurrence of postoperative complications and reintervention.Pearson χ2 or Fisher ′s exact test was used for categorical variables, and independent sample t test or Wilcoxon rank sum test was used for continuous variables to compare differences between groups.The survival curves of the two groups were described by Kaplan-Meier method. Results:After propensity score matching,198 cases were in the EVAR group and 66 cases were in the OSR group.The ROC model showed that the best cut-off value of R value was 0.90,and the two groups were divided into two layers:R<0.90 and R≥0.90.Among them,112 patients with R<0.90 (84 cases of EVAR,28 cases of OSR);there were 152 patients with R≥0.90 (114 cases of EVAR and 38 cases of OSR).The follow-up time was (23.6±1.6) months (range:1 to 70 months).In the R≥0.90 stratification,the total mortality (26.3% vs.5.3%, χ2=7.600， P=0.006),complication rate (44.7% vs.26.3%, χ2=4.025， P=0.045), and secondary intervention rate (31.6% vs.13.2%, χ2=4.910， P=0.027) in the EVAR group were higher than those in the OSR group.In the R<0.90 stratification,there was no significant difference in the total mortality rate (13.1% vs.10.7%, χ2=0.109， P=0.741), complication rate (28.6% vs.35.7%, χ2=0.507， P=0.477) and secondary intervention rate (14.3% vs.21.4%, χ2=0.353， P=0.552) between the two groups. Conclusions:When R≥0.90 in IAAA patients,OSR maybe more beneficial to patients in terms of survival rate,postoperative complication rate and secondary intervention rate than EVAR.When R<0.90,there are no significant differences in survival rate,complication rate and secondary intervention rate between the two surgical methods.

In order to provide a reference basis for the development of relevant compound preparations， this article takes a comprehensive analysis of the usage and dosage of famous classical formulas in Han dynasty from various perspectives， and gives corresponding countermeasures on this basis. Through the comprehensive analysis of the classification and statistics of Zhongjing's medication characteristics， decoction methods， administration and dosage， and combining conversion methods of weights and measures by ancient medical practitioners， along with the dosage and administration of the listed Han dynasty famous classical formulas， it was found that the "Jiangxi method" served as a general guideline for administration according to Zhongjing's original text. This method allowed for flexible dosing based on the conversion of the ancient measurements to modern equivalents［13.8 g per Liang（两）］， ensuring the safe and effective medication of these formulas. After combing， it is found that although the dosage of single medicine is large in famous classical formulas from Han dynasty， the administration is flexible. The crude drug amount per administration serves as the foundational dose， with the frequency of administration adjusted flexibly according to the condition. This dosing approach becomes the key for the rational development of compound formulations of famous classical formulas. Based on the conclusions of the study， it is recommended that when developing compound formulations of famous classical formulas in Han dynasty， the original administration method and dosage should be respected. The original crude drug amount per administration should be considered as the daily foundational dose， with the frequency of administration described within a range（1 to N times per day， where N is the maximum number of administrations as per the original text）. The specific frequency of administration can be adjusted flexibly by clinical practitioners based on the individual condition. This approach should also be adopted in toxicological studies， where the dosage per administration serves as the basis for toxicity research， and the toxicity profile at the maximum administration frequency should be observed， providing guidance on the clinical safety range. Corresponding drug labels should provide information within a range to indicate toxicological risk intervals.

Objective     To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods     A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. Results    Finally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion     Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.

Clinicians need to focus on various points in the diagnosis and treatment of insomnia.This article prescribed the treatment protocol based on the unique features,such as insomnia in the elderly,women experiencing specific physiologi-cal periods,children insomnia,insomnia in sleep-breathing disorder patients,insomnia in patients with chronic liver and kidney dysfunction.It pro-vides some reference for clinicians while they make decision on diagnosis,differentiation and treat-ment methods.