BACKGROUND:Osteoarthritis is now considered a metabolic disease.Previous studies have shown that glycolysis plays an important role in the occurrence and development of osteoarthritis.Compound 3k,as a novel small molecule inhibitor of glycolysis,has anti-inflammatory and anti-tumor effects.Therefore,it can target glycolysis and is expected to provide new ideas for the treatment of osteoarthritis. OBJECTIVE:To explore the role of Compound 3k in osteoarthritis caused by glycolytic overactivity based on the hypoxia-inducible factor 1 alpha(HIF-1α)/reactive oxygen species(ROS)pathway. METHODS:ATDC5 chondroblasts at logarithmic growth phase were taken to induce osteoarthritis in an in vitro cellular model by the action of 10 ng/mL interleukin-1β for 24 hours.The cytotoxicity of Compound 3k at different concentrations(0.25,0.5,1,2.5,5,10,15 &mu;mol/L)was detected by cell counting kit-8 assay,and the appropriate concentrations were selected for the subsequent experiments.The chondrocytes were randomly divided into control,model and treatment groups.The model group was induced with 10 ng/mL interleukin 1β,and the treatment group was pre-stimulated with Compound 3k for 2 hours and then co-cultured with interleukin 1β.The proliferation of the cells in each group was detected by the cell counting kit-8 assay;the inflammatory level of the cells in each group was detected by the ELISA kit;the ROS,extracellular lactate and glucose contents were detected using the kit;qRT-PCR and western blot were used to detect the levels of related inflammatory factors,interleukin-6 and tumor necrosis factor-α,glycolysis-related genes glucose transporter protein-1,glyceraldehyde 3-phosphate dehydrogenase,monocarboxylate transporter protein-1 and HIF-1α. RESULTS AND CONCLUSION:Compared with the control group,the model group showed a decrease in cell proliferative activity,active glycolysis level,manifested by an increase in extracellular lactate content(P<0.001)and a decrease in glucose content(P<0.001),interleukin-6(P<0.000 1)and tumor necrosis factor-α(P<0.001).The expression levels of glycolysis-related genes glucose transporter protein-1(P<0.001),glyceraldehyde 3-phosphate dehydrogenase(P<0.001),monocarboxylic acid transporter protein-1(P<0.001)and HIF-1α(P<0.001)in the model group were all up-regulated,accompanied by oxidative stress and overproduction of ROS.Compared with the model group,Compound 3k treatment effectively increased cell proliferation activity and inhibited the level of overactive glycolysis(P<0.001),while suppressing the expression of genes related to inflammation(P<0.001)and glycolysis in osteoarthritic chondrocytes,inhibiting oxidative stress,downregulating the expression level of HIF-1α(P<0.000 1)and decreasing the content of ROS.To conclude,Compound 3k inhibits interleukin-1β induced chondrocyte inflammation,and its mechanism may be related to glycolysis and HIF-1α/ROS mediated oxidative stress.

PURPOSE: To assess the relationship between dislocation and functional outcomes in supination-external rotation (SER) ankle fractures. METHODS: A retrospective case series study was performed on patients with ankle fractures treated surgically at a large trauma center from January 2015 to December 2021. The inclusion criteria were young and middle-aged patients of 18 - 65 years with SER ankle fractures that can be classified by Lauge-Hansen classification and underwent surgery at our trauma center. Exclusion criteria were serious life-threatening diseases, open fractures, fractures delayed for more than 3 weeks, fracture sites ≥ 2, etc. Then patients were divided into dislocation and no-dislocation groups. Patient demographics, injury characteristics, surgery-related outcomes, and postoperative functional outcomes were collected and analyzed. The functional outcomes of SER ankle fractures were assessed postoperatively at 1-year face-to-face follow-up using the foot and ankle outcome score (FAOS) and American Orthopedic Foot and Ankle Society ankle hindfoot score and by 2 experienced orthopedic physicians. Relevant data were analyzed using SPSS version 22.0 by Chi-square or t-test. RESULTS: During the study period, there were 371 ankle fractures. Among them, 190 (51.2%) were SER patterns with 69 (36.3%) combined with dislocations. Compared with the no-dislocation group, the dislocation group showed no statistically significant differences in gender, age composition, fracture type, diabetes, or smoking history, preoperative waiting time, operation time, and length of hospital stay (all p > 0.05), but a significantly higher Lauge-Hansen injury grade (p < 0.001) and syndesmotic screw fixation rate (p = 0.033). Moreover, the functional recovery was poorer, revealing a significantly lower FAOS in the sport/rec scale (p < 0.001). Subgroup analysis showed that among SER IV ankle fracture patients, FAOS was much lower in pain (p = 0.042) and sport/rec scales (p < 0.001) for those with dislocations. American Orthopedic Foot and Ankle Society ankle hindfoot score revealed no significant difference between dislocation and no-dislocation patients. CONCLUSION Dislocation in SER ankle fractures suggests more severe injury and negatively affects functional recovery, mainly manifested as more pain and poorer motor function, especially in SER IV ankle cases.
Humans ; Ankle Fractures/physiopathology* ; Male ; Female ; Retrospective Studies ; Adult ; Middle Aged ; Supination ; Aged ; Young Adult ; Rotation ; Joint Dislocations/surgery* ; Fracture Fixation, Internal/methods* ; Adolescent ; Recovery of Function ; Treatment Outcome

Esophageal carcinoma is a malignant disease with a high incidence rate and poor prognosis. The mitochondrial apoptosis pathway plays a pivotal role in the regulation of cell death and has become a focal point in current cancer therapeutics research. Various active components from traditional Chinese medicine （TCM） can target the mitochondrial apoptosis pathway to inhibit esophageal carcinoma， presenting as potential therapeutic agents for this disease. This paper summarizes relevant research on the inhibition of esophageal carcinoma by active components in TCM via targeting the mitochondrial apoptosis pathway. It has been found that flavonoids （casticin， icariin， luteolin， kaempferol， hesperetin， deguelin， etc.）， terpenoids （oridonin， Jaridonin， artesunate， ethyl acetate fraction of pleurotus ferulatus triterpenoid， etc.）， alkaloids （matrine， swainsonine， etc.）， polyphenols （curcumin， epigallocatechin-3-gallate， corilagin， etc.）， steroids （α-hederin， polyphyllin Ⅵ， etc.）， phenols （optimized scorpion venom peptide CT-K3K7， gecko active polypeptide， etc.）， volatile oils （cinnamaldehyde， α -asarone， etc.） and other active components from TCM can target the intrinsic mitochondrial apoptosis pathway， induce apoptosis in esophageal carcinoma cells， and inhibit their proliferation， invasion and migration by regulating oxidative stress， blocking the cell cycle， regulating signaling pathways such as PI3K/Akt and MAPK.

ObjectiveTo investigate the possible mechanism of Shufeng Jiedu capsules （SFJD） in alleviating influenza A （H1N1） virus pneumonia and focus on its effect on Toll-like receptor （TLR） signaling pathway in respiratory epithelial cells. MethodsA mouse model of viral pneumonia was established via the A/PR/8/34 （PR8） strain of influenza A virus. Mice were randomly divided into a normal group， a PR8 infection （PR8） group， and an SFJD group （8.4 g·kg^-1）， with 10 mice in each group. The day of infection was designated as day 1. The SFJD group was administered intragastrically at a volume of 20 mL·kg^-1 daily， while the normal and PR8 groups were given an equal volume of deionized water. Micro-computed tomography （Micro-CT） was performed on day 5， and the mice were dissected to collect their lungs， after which the lung index was calculated to verify the therapeutic effect of SFJD. Single-cell sequencing was used to analyze the differentially expressed genes in respiratory epithelial cells. Multiplex fluorescence immunohistochemistry was employed to detect the expression of TLR， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） proteins in epithelial cell adhesion molecule （EpCAM）-positive cells， and the proportion of respiratory epithelial cells expressing TLR pathway proteins was calculated. Respiratory epithelial cells were then sorted by flow cytometry， and Western blot was used to detect the expression of TLR， MyD88， TRAF6， Toll-interleukin receptor domain-containing adaptor inducing interferon-β （TRIF）， inhibitor of κB kinase α （IKKα）， and nuclear factor-κB （NF-κB） in the sorted epithelial cells. Enzyme-linked immunosorbent assay （ELISA） was used to measure the levels of interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α） in lung tissue. ResultsAt the transcriptional level， SFJD reversed the expression of TLR signaling pathway genes in respiratory epithelial cells， downregulating multiple TLR signaling pathway-related genes （P<0.01）. At the protein level， SFJD significantly reduced the proportion of respiratory epithelial cells expressing TLR3 （P<0.05）， the expression levels of TLR2， TLR3， TLR4， TRIF， TRAF6， IKKα， and NF-κB in epithelial cells（P<0.05， P<0.01）， as well as the levels of pro-inflammatory cytokines IL-1β and TNF-α in lung tissue （P<0.01）. ConclusionSFJD may alleviate viral pneumonia by suppressing the expression of TLR in respiratory epithelial cells and their subsequent signaling cascades.

[摘 要] 目的：研究芳香烃受体（AHR）在乳腺癌中的表达及其对乳腺癌细胞增殖、凋亡和药物敏感性的调控机制。方法：通过GEPIA数据库数据分析乳腺癌组织及癌旁组织中AHR的表达水平，探讨其与患者生存期的关联。利用基因敲低和过表达技术构建AHR表达变化的乳腺癌细胞，采用CCK-8实验、细胞计数和流式细胞分析等方法评估AHR对细胞增殖、凋亡和药物敏感性的影响，通过免疫印迹法验证相关分子机制。此外，利用AHR激动剂6-甲酰基吲哚并[3,2-B]咔唑（FICZ）研究外源性激活AHR对乳腺癌细胞多柔比星（DOX）敏感性的影响。结果：GEPIA数据库数据分析结果显示，乳腺癌组织中AHR呈明显低表达（P < 0.05）；对155例乳腺癌患者的生存期进行统计分析也显示AHR低表达与不良预后呈正相关（P < 0.05）。敲低AHR促进细胞增殖（P < 0.05），过表达则能抑制其增殖（P < 0.05）并促进其凋亡（P < 0.05）。外源激活AHR能增强乳腺癌细胞对DOX的敏感性（P < 0.05）。AHR可与MYC基因启动子结合，抑制MYC表达（P < 0.05），从而影响乳腺癌的进展。结论：AHR在乳腺癌中通过调控MYC表达影响细胞增殖和凋亡，外源激活AHR可能成为提高乳腺癌细胞对DOX敏感性的治疗策略。

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.