ObjectiveTo investigate the association between triglyceride-glucose (TyG) index and the risk of stroke in middle-aged and elderly individuals with hypertension, so as to provide more evidence for the prevention and treatment of stroke. MethodsMiddle-aged and elderly hypertensive individuals who took part in all four surveys in 2011, 2013, 2015, and 2018 were selected as the research subjects based on data from the China Health and Retirement Longitudinal Study (CHARLS). Participants were divided into four groups (≤Q1， >Q1~Q2， >Q2~Q3， and >Q3) based on TyG index quartiles, and the cumulative risk of stroke in different groups was analyzed using the Kaplan-Meier method. Different Cox proportional hazards regression models were constructed to analyze the relationship between the TyG index and stroke risk. Sensitivity analysis were performed to evaluate the robustness of the results. ResultsA total of 4 596 participants were included in the study. Among them, 338 individuals (7.35%) had a stroke during the 7-year follow-up period. The cumulative risk of stroke increased with higher TyG index levels. Results from the Cox regression models indicated that higher TyG levels were associated with an increased risk of stroke among middle-aged and elderly individuals with hypertension. Compared with the lowest TyG index quartile (≤Q1: TyG index ≤8.33) group, the highest quartile (>Q3: TyG index >9.17) group showed a 45.10% increased risk of stroke (HR=1.451, 95% CI:1.017‒2.072). ConclusionA higher TyG index is associated with an increased risk of stroke in middle-aged and elderly individuals with hypertension.

Epigenetic pathways play a critical role in the initiation, progression, and metastasis of cancer. Over the past few decades, significant progress has been made in the development of targeted epigenetic modulators (e.g., inhibitors). However, epigenetic inhibitors have faced multiple challenges, including limited clinical efficacy, toxicities, lack of subtype selectivity, and drug resistance. As a result, the design of new epigenetic modulators (e.g., degraders) such as PROTACs, molecular glue, and hydrophobic tagging (HyT) degraders has garnered significant attention from both academia and pharmaceutical industry, and numerous epigenetic degraders have been discovered in the past decade. In this review, we aim to provide an in-depth illustration of new degrading strategies (2017-2023) targeting epigenetic proteins for cancer therapy, focusing on the rational design, pharmacodynamics, pharmacokinetics, clinical status, and crystal structure information of these degraders. Importantly, we also provide deep insights into the potential challenges and corresponding remedies of this approach to drug design and development. Overall, we hope this review will offer a better mechanistic understanding and serve as a useful guide for the development of emerging epigenetic-targeting degraders.

BACKGROUND:With the deepening of the aging of the world population,the prevalence rate of osteoarthritis is increasing.In recent years,more and more attention has been paid to the study of osteoarthritis.Studies have shown that autophagy and apoptosis are strongly associated with the occurrence and development of osteoarthritis,and play an important role in it. OBJECTIVE:To review the molecular mechanisms of the interaction between autophagy and apoptosis in osteoarthritis,aiming to explore the relationship between autophagy and apoptosis in osteoarthritis and the coupling mechanism of the two to mediate the occurrence and development of osteoarthritis,so as to provide new ideas for the treatment of osteoarthritis. METHODS:The Chinese and English key words"osteoarthritis,autophagy,apoptosis"were searched in the CNKI and PubMed.After screening by reading the title,abstract and key words,the relevant literature was carefully read.After excluding studies unrelated to the content of the paper and repetitive studies,68 articles were finally included for the summary. RESULTS AND CONCLUSION:(1)The occurrence and development of osteoarthritis are related to autophagy and apoptosis of chondrocytes.Autophagy protects chondrocytes from stress damage,but excessive autophagy also induces or promotes chondrocyte apoptosis and reduces the survival rate of chondrocytes.The two perturb each other to regulate the degeneration of articular cartilage.(2)miRNA,Beclin-1 and oxidative stress are all involved in the regulation of autophagy and apoptosis on osteoarthritis,and affect the development of osteoarthritis.

Objective The high incidence, disability, and mortality rates of stroke result in a heavy economic and social burden. The aim of this study was to investigate the relationship between triglyceride-glucose (TyG) index and new-onset stroke to assist in the identification of high-risk groups for stroke and to provide ideas for effective prevention. Methods The study was based on data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018 and included 7630 eligible middle-aged and elderly participants. The association between TyG index and new-onset stroke was assessed by logistic regression modelling and restricted triple spline analysis. Results A total of 431 participants had a new stroke. The TyG index was found to be a risk factor for stroke occurrence when it was >8.523, and there was a positive linear association moderated by gender. Conclusion Elevated TyG index is a risk factor for new stroke. This study provides new ideas for the identification of high-risk groups for stroke and for intervention measures and timing.

Objective To explore the effect of task-oriented training of intelligent mirror gloves combined with low-frequency repeti-tive transcranial magnetic stimulation(rTMS)on hand function recovery in stroke patients. Methods From October 1st,2022 to June 30th,2023,136 stroke patients in Northern Jiangsu People's Hospital were ran-domly divided into control group,mirror group,rTMS group and combination group,with 34 patients in each group.All the groups received routine rehabilitation treatment.In addition,the mirror group received task-orient-ed training of intelligent mirror gloves,rTMS group received low-frequency rTMS,and the combination group received task-oriented training combined with low-frequency rTMS,for four weeks.The Fugl-Meyer Assess-ment-Upper Extremities(FMA-UE)score,Wolf Motor Function Test(WMFT)score,and surface electromyo-graphic root mean square(RMS)of forearm extensor and flexor muscle groups on the affected/healthy side be-fore and after treatment were compared.And the differences of transcranial magnetic stimulation-motor-evoked potentials(MEP)between rTMS group and combination group before and after treatment were also compared. Results Four cases in the control group,seven in the mirror group,five in rTMS group and six in the combination group dropped off.The intra-group effect(F>996.656,P<0.001),inter-group effect(F>20.333,P<0.001)and inter-action effect(F>72.796,P<0.001)were significant in the scores of FMA-UE and WMFT,and the RMS ratio of forearm extensor and flexor muscle groups among four groups,in which the combination group was the best.After treatment,the amplitude of MEP increased in rTMS group and combination group(|t|>3.842,P<0.05),and was higher in the combination group than in rTMS group(t=-3.060,P<0.01). Conclusion The task-oriented training of intelligent mirror gloves combined with low-frequency rTMS could effectively promote the recovery of hand function in stroke patients.

Objective To investigate the effect and mechanism of rhubarb Tangluo pill on liver injury in type 2 diabetic rats.Methods ZDF(fa/fa)rats were given high-fat diet to induce type 2 diabetes model,and were randomly divided into model group,positive control group(0.18 g·kg-1 metformin)and experimental-L,-M,-H groups(0.54,1.08 and 2.16 g·kg-1 rhubarb Tangluo pill),with 8 rats in each group.Eight ZDF(fa/+)rats were selected as control group.The control group and model group were given equal volume of pure water once a day for 12 weeks.An oral glucose tolerance test(OGTT)was performed after administration.Fasting blood glucose level,body mass and liver mass of rats were measured and liver index was calculated.The contents of glutamic-pyruvic transaminase(GPT),glutamic oxalacetic transaminase(GOT),triglyceride(TG)and total cholesterol(TC)in serum were detected.The histomorphologic changes of liver were observed by hematoxylin-eosin(HE)staining and Masson staining.The protein expression of phosphorylated insulin receptor substrate 1(p-IRS1),phosphorylated protein kinase B(p-Akt)and glucose transporter 4(GLUT4)were detected by Western blotting.Results After administration,the fasting blood glucose levels of control group,model group,positive control group and experimental-H group were(4.71±0.45),(29.9±2.97),(15.28±4.52)and(13.84±1.55)mmol·L-1,respectively;the liver index were 2.31±0.46,4.03±0.18,3.37±0.23 and 3.38±0.24;the relative expression level of p-IRS1 protein were 1.00±0.36,4.00±0.11,1.62±0.27 and 1.90±0.17,respectively;the relative expression levels of p-Akt protein were 1.00±0.25,0.21±0.04,0.73±0.15 and 0.54±0.04,respectively;GLUT4 protein relative expression levels were 1.00±0.11,0.40±0.08,0.86±0.04 and 0.70±0.06,respectively.Compared with the model group,the above indexes in the experimental-H group were statistically significant(P＜0.01,P＜0.05).Conclusion Rhubarb Tanglu pill can effectively improve glycolipid metabolism and liver injury in type 2 diabetes mellitus,and its mechanism may be related to the activation of IRS1/Akt signaling pathway.

Three-dimensional ordered porous carbon materials exhibit potential application prospects as excellent drug supports in drug delivery systems due to their high specific surface area, tunable pore structure, and excellent biocompatibility. In this study, three-dimensional ordered porous carbon materials were prepared using Acanthopanax senticosus herbal residues as raw material and KOH as activating agent through a one-step pyrolysis method. The prepared carbon-based material was systematically characterized by powder X-ray diffraction, scanning electron microscopy, N₂ adsorption-desorption and Fourier-transform infrared spectroscopy. The results show that the three-dimensional ordered porous carbon materials prepared with KOH as the activator via pyrolysis possess abundant functional groups, high porosity, and high specific surface area, with a specific surface area of 1 471.6 m²·g^-1. The three-dimensional ordered porous carbon materials prepared at 800 ℃ exhibits a high drug loading capacity (78.0%) and drug release rate (86.8%) for 5-fluorouracil. Three-dimensional orderly porous carbon materials show significant application advantages in drug construction, and their high specific surface area and adjustable pore size structure significantly improve the drug load rate and drug release rate, providing a solid foundation for the development of efficient and accurate drug delivery system.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

Warfarin is an irreplaceable oral anticoagulant for patients with mechanical heart valves, the stable pharmacogenetic-based warfarin dose prediction algorithms have improved the effectiveness and safety of warfarin anticoagulation therapy. Genetic factors are the main factors affecting the stable dose of warfarin. Single nucleotide polymorphisms such as VKORC1 and CYP2C9 affect the anticoagulation effect of warfarin through pharmacodynamic or pharmacokinetic pathways. Age, body surface area, combined use of drugs, and other nongenetic factors also affect the stable dose of warfarin. Previously published algorithms for warfarin dose prediction included mainly the white race, and most algorithms were constructed using traditional multiple linear regression. However, domestic studies have used machine learning methods to construct warfarin dose prediction algorithms based on the Chinese Han post-mechanical valve replacement population and have achieved better prediction efficiency. This article reviews the advances of warfarin anticoagulation influencing factors and the clinical application of stable dose prediction algorithms.

In automatic skin damage analysis,segmentation is a challenging and critical operation due to factors such as the shape and contrast of hair and skin lesions on the skin.Compared with traditional segmentation methods,deep learning seamlessly integrates feature extraction and task-specific decision-making,achieving segmentation tasks more accurately and efficiently,and effectively reducing the burden and cost of skin cancer screening.This article first introduces the background of dermoscopic segmentation and deep learning models,and introduces the application of deep learning in dermoscopic segmentation.Secondly,this article introduces the algorithm models of convolutional neural networks and attention mechanisms,reviews the application of fused attention convolutional neural networks in dermoscopic segmentation since Jan 2022,and summarizes the improvement strategies,the advantages and disadvantages of the model.The model is further analyzed based on commonly used datasets of dermoscopy and evaluation indicators of image segmentation.Finally,the application of fused attention convolutional neural network in dermoscopic segmentation is summarized and prospected.