Histone deacetylase 3 (HDAC3) is an epigenetic modification enzyme that plays a crucial role in the development and progression of diabetes and its complications. Studies have reported that increased HDAC3 activity is associated with pancreatic β-cell dysfunction in type 1 diabetes, while in type 2 diabetes, HDAC3 affects insulin resistance and signaling by regulating the metabolism of the liver, adipose tissue, and muscle. Additionally, HDAC3 plays a key role in diabetic complications such as cardiomyopathy, retinopathy, and nephropathy. Selective inhibition of HDAC3 has the potential to improve insulin sensitivity, reduce chronic inflammation, and enhance pancreatic cell function, offering a promising new therapeutic strategy for diabetes and its complications.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

BACKGROUND:Based on different algorithms of machine learning,how to carry out clinical research on lumbar disc herniation with the help of various algorithmic models has become a trend and hot spot in the development of intelligent medicine at present. OBJECTIVE:To review the characteristics of different algorithmic models of machine learning in the diagnosis and treatment of lumbar disc herniation,and summarize the respective advantages and application strategies of algorithmic models for the same purpose. METHODS:The computer searched PubMed,Web of Science,EMBASE,CNKI,WanFang,VIP and China Biomedical(CBM)databases to extract the relevant articles on machine learning in the diagnosis and treatment of lumbar disc herniation.Finally,96 articles were included for analysis. RESULTS AND CONCLUSION:(1)Different algorithm models of machine learning provide intelligent and accurate application strategies for clinical diagnosis and treatment of lumbar disc herniation.(2)Traditional statistical methods and decision trees in supervised learning are simple and efficient in exploring risk factors and establishing diagnostic and prognostic models.Support vector machine is suitable for small data sets with high-dimensional features.As a nonlinear classifier,it can be applied to the recognition,segmentation and classification of normal or degenerative intervertebral discs,and to establish diagnostic and prognostic models.Ensemble learning can make up for the shortcomings of a single model.It has the ability to deal with high-dimensional data and improve the precision and accuracy of clinical prediction models.Artificial neural network improves the learning ability of the model,and can be applied to intervertebral disc recognition,classification and making clinical prediction models.On the basis of the above uses,deep learning can also optimize images and assist surgical operations.It is the most widely used model with the best performance in the diagnosis and treatment of lumbar disc herniation.The clustering algorithm in unsupervised learning is mainly used for disc segmentation and classification of different herniated segments.However,the clinical application of semi-supervised learning is relatively less.(3)At present,machine learning has certain clinical advantages in the identification and segmentation of lumbar intervertebral discs,classification and grading of the degenerative intervertebral discs,automatic clinical diagnosis and classification,construction of the clinical predictive model and auxiliary operation.(4)In recent years,the research strategy of machine learning has changed to the neural network and deep learning,and the deep learning algorithm with stronger learning ability will be the key to realizing intelligent medical treatment in the future.

Objective To explore the changes of metabonomics in blood of mice after high-voltage electric shock,then screen out the significantly changed differential metabolites and metabolic pathways.Methods The head of C57BL/6J mice was subjected to high-voltage electric shock(electric shock group)or exposed to acoustic and optical stimulation of high-voltage electric(control group),then the whole blood from mice were collected to separate serum.The dual platform combined metabonomic analysis based on gas chromatography-mass spectrometer(GC-MS)and liquid chromatography-mass spectrometer(LC-MS)was performed and orthogonal partial least squares discriminant analysis(OPLS-DA)was used to screen the differential metabolites and related metabolic pathways.Results A total of 415 differential metabolites were screened out in metabonomics in blood of mice after high-voltage electric shock,including 187 up-regulated and 228 down-regulated metabolites.These differentially metabolites were significantly enriched in metabolic pathways including central carbon metabolism in cancer,glucagon signaling pathway,etc.Conclusion By establishing the model of high-voltage electrical injury on experimental mice,this study reveals the significant change of metabolite content and metabolic pathway in blood by high-voltage electrical injury.Which provides a basis for the damage of blood metabolic activity by high-voltage electrical injury,and suggests the potential harm of high-voltage electrical injury to blood metabolic activity in the whole body.

Objective To study the change of lipidomics in chronic cadmium-exposed mice,thereby screening out lipid subclasses,lipid molecules and enriched metabolic pathways with significant differences.Methods Twelve SPF male C57BL/6J mice(8 weeks old)were randomly divided into the control group(normal water feeding)and the experimental group[cadmium water(0.6 mg/L of CdCl2)feeding],with 6 mice in each group.Mice were sacrificed after 6 months of cadmium exposure,and fresh liver tissues were collected immediately.Lipid oil red O staining and lipidomics analysis were performed on liver tissue.Results Compared with the control group,the liver tissue of mice in the experimental group did not appear red after lipid oil red O staining.Seventeen lipid subclasses with significant differences and 144 lipid molecules with significant differences were screened out by lipidomics.These lipid molecules with significant differences were enriched in glycerophospholipid metabolism,linoleic acid metabolism,alpha-linolenic acid metabolism,glycosylphosphati-dylinositol biosynthesis,glycerolipid metabolism and arachidonic acid metabolism by KEGG.Conclusion This study reveals that chronic cadmium exposure can induce the disorder of lipid subclasses and lipid metabolites in the liver of mice,which provides a basis for understanding the non-alcoholic fatty liver disease caused by chronic cadmium exposure.

Objective:To investigate a new method for the reconstruction of hemifacial microsomia by sagittal osteotomy of the affected mandibular outer cortex combined with bone graft of mandibular outer cortex from healthy side.Methods:From March 2006 to March 2023, the clinical data of patients with hemifacial microsomia admitted to the Department of Craniomaxillofacial Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences were analyzed retrospectively. Preoperative diagnosis and surgical design were performed based on clinical manifestations and imaging findings. All cases were operated under general anesthesia. The affected mandibular outer cortex was previously split by an intraoral approach, and then the mandibular outer cortex of appropriate shape and size on the healthy side was harvested and grafted into the split bone space according to the preoperative design, following by internal rigid fixation. Complications, facial appearance improvement, and patient satisfaction were followed up. Photographs were taken preoperative, immediately postoperative and at the long-term(last) postoperative follow-up, and the severity of the deformity was analyzed. CT data from preoperative, immediate postoperative, and long-term follow-up visits were imported into Surgicase Proplan medical three-dimensional image workstation in Dicom format. The mandible was reconstructed using Segmentation, and the thickness of the mandible was measured during pre-operative, immediate post-operative and long-term follow-up visits. Anova with repeated measurement design was used to compare measurements and LSD test was used for multiple comparisons. The Kruskal-Wallis rank sum test were used to statistically analyze malformation severity. P< 0.05 is considered statistically significant. Results:A total of 39 patients were included in this study, including 13 females and 26 males, with an average age of (22.21±4.57) years (15-27 years). All patients were followed up for an average of (45.56±39.41) months (6-153 months) after surgery. The grafted mandibular outer cortex grows well with the adjacent bone tissue, and the mandibular angle and mandibular body are significantly wider. Of the 39 cases, 1 developed an infection 1 year after surgery, the titanium plate was exposed, and the patient healed after debridement and removal of the immobilizing splint. The facial appearance of the other patients improved significantly. Preoperative, immediate postoperative and long term follow up of mandibular thickness measurements were compared in pairs, and the differences were statistically significant (all P<0.05). The patient’s appearance satisfaction score: the preoperative score was [2.0(1.5, 2.0)] points, the immediate postoperative score was [4.0(4.0, 4.0)] points, the score of the last postoperative follow up was [4.0(4.0, 4.0)] points. There was statistical difference in satisfaction among the three groups ( P<0.01). The preoperative scores were compared with the scores of the immediate postoperative and the last postoperative follow-up respectively, and the differences were statistically significant( P<0.01). There was no statistical significance in satisfaction between the immediate postoperative score and the score of the last postoperative follow up ( P>0.05). Conclusion:The sagittal splitting osteotomy of the mandibular outer cortex is consistent with the features of mandibular anatomy, and provides a good condition for the grafting and healing of autogenous bone. Removing the outer cortex of the mandible on the healthy side not only increases the thickness of the affected side, but also decreases the width of the angle of the mandible on the healthy side, so as to effectively correct the asymmetric deformity of the mandible. The method is simple, with few complications and good results, and is one of the ideal treatments to correct hemofacial microsomia.

Objective To explore the mechanism of Zishen Jianpi Huayu Tablets(Corni Fructus,Notoginseng Radix et Rhizoma,Astragali Radix,Puerariae Lobatae Radix,Spatholobi Caulis,Rehmanniae Radix)in the treatment of diabetic retinopathy(DR)by means of network pharmacology and molecular docking technique,and verified by in vitro experiments.Methods The active components of Zishen Jianpi Huayu Tablets and their corresponding target proteins were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and the BATMAN-TCM database.Drug target proteins were converted to their corresponding gene names through the UniProt database.DR-related targets were searched using"diabetic retinopathy"as a keyword in GeneCards,DrugBank,OMIM,and TTD databases.Common targets between the disease and the drug were identified using the Venny tool.These common targets were analyzed using the String database,a protein-protein interaction(PPI)network was constructed.Topological heterogeneity analysis was performed using Cytoscape 3.9.1 to select core targets and create a PPI network diagram.These common targets were entered into the Metascape database for Gene Ontology(GO)function analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis to identify potential action pathways.Molecular docking of the main active components and core targets was performed using Auto Dock tools software,followed by further experimental validation.The CCK-8 assay was used to assess the effect of Zishen Jianpi Huayu Tablet medicated serum on the cell viability of Human Retinal Microvascular Endothelial Cells(HRmECs)under high glucose conditions,and RT-qPCR was used to measure the expression of IL-1β,AKT1,VEGFA,and TP53 mRNA in HRmECs.Results(1)The effective components and corresponding target proteins of Zishen Jianpi Huayu Tablets were screened by Traditional Chinese Medicine System Pharmacology Database and Analysis Platform(TCMSP)and BATMAN-TCM database.The disease-related targets of DR were searched by GeneCards,OMIM and TTD databases.The use of VENNY platform for drug active components target and DR disease-related target to take intersection(common target),that is,Zishen Jianpi Huayu Tablets in the treatment of DR potential target.The network of"drugs-active components-common targets"was constructed to screen out the key active components of Zishen Jianpi Huayu Tablets in the treatment of DR.Import the common target into STRING database,obtain the PPI network relationship,and screen out the core target.Metascape platform was used to analyze the GO function and KEGG pathway enrichment of the common targets.The key active components and core targets were verified by Autodock 4 software for molecular docking.(2)The drug-containing serum and blank serum of Zishen Jianpi Huayu Tablets was prepared.Human retinal microvascular endothelial cells(HRmECs)were randomly divided into 5 groups:the control group(low-sugar DMEM medium+10%blank serum),high-glucose group(high-sugar DMEM medium+10%blank serum)and Zishen Jianpi Huayu Tablets containing low-,medium-and high-dose serum(high-sugar DMEM medium+10%low-,medium-and high-dose drug containing serum)were detected after 48 hours of culture.The proliferative activity of HRmECs cells was detected by CCK-8 method,and the mRNA expressions of IL-1β,AKT1,VEGFA and TP53 in HRmECs cells were detected by RT-qPCR method.Conclusion Zishen Jianpi Huayu Tablets may act on core targets such as IL-1β,IL-6 and VEGFA,as well as key pathways such as NF-κB signaling pathway,AGE-RAGE signaling pathway and PI3K-AKT pathway through various active components such as quercetin,kaempferol and rehmannia flavonoids,so as to play a therapeutic role in DR.