OBJECTIVE To investigate the mechanism of cordycepin in delaying the transformation from acute kidney injury （AKI） to chronic kidney disease （CKD） （short for “AKI-CKD”）. METHODS Network pharmacology and bioinformatics were used to analyze and predict the signaling pathways of cordycepin in delaying AKI-CKD progression and its relationship with the ferroptosis pathway. Cell experiments were performed to verify the predicted results. Human renal tubular epithelial HK-2 cells were divided into blank group， cordycepin group， model group， and H 2 O 2 +cordycepin group. Except for the blank group and cordycepin group， all other groups were treated with 150 μmol/L H 2 O 2 for 72 h to induce persistent oxidative stress injury in cells. After 72 h of cordycepin （40 μmol/L） intervention， the protein and mRNA expression levels of glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4），nuclear factor-erythroid 2-related factor 2（Nrf2）， and heme oxygenase-1 （HO-1） in cells were detected. Furthermore， the Nrf2 inhibitor ML385 was added on the basis of H 2 O 2 +cordycepin to verify the role of the Nrf2/HO-1 pathway. RESULTS Network pharmacology and bioinformatics analysis showed that there were 42 overlapping genes related to AKI-CKD and ferroptosis that interact with cordycepin ferroptosis， among which 38 were annotated as ferroptosis-related genes. HO-1 and Nrf2 might be important targets for cordycepin to inhibit ferroptosis. The binding energies of cordycepin with Nrf2 and HO-1 proteins were －8.5 and －6.7 kcal/mol， respectively. Cell experiments showed that compared with the model group， the protein and mRNA expression levels of GPX4， Nrf2 and HO-1 were significantly increased （ P ＜0.05），while the protein and mRNA expression levels of ACSL4 were significantly decrease d （ P ＜0.05） in the H 2 O 2 +cordycepin group. After the addition of the Nrf2 inhibitor ML385， the effects of cordycepin on the above proteins and mRNA were significantly reversed （ P ＜0.05）. CONCLUSIONS Cordycepin can inhibit ferroptosis by activating the Nrf2/HO-1 pathway， reduce persistent oxidative stress injury of renal tubular epithelial cells， and delay the progression of AKI-CKD.

This paper summarized the clinical experience of Prof. LI Diangui in treating gastroesophageal reflux disease （GERD） based on the theory of turbidity-toxin in liver. It is believed that internal accumulation of turbidity-toxin and liver depression with stomach counterflow are the main pathogenesis of GERD， and thus the therapeutic methods of resolving turbidity and resolving toxins， regulating the liver and harmonizing the stomach are proposed. In clinical practice， GERD is divided into the early stage， middle stage and late stage. For the early stage， the modified Huazhuo Shugan Hewei Formula （化浊疏肝和胃方） is used to regulate qi and remove turbidity， soothe the liver and harmonize the stomach； for the middle stage， the modified Huazhuo Qingre Zhisuan Formula （化浊清热制酸方） is applied to clear heat， direct the turbid downward， and resolve toxins； for the late stage， the modified Yiwei Decoction （益胃汤） is adopted to replenish qi， nourish yin and simultaneously resolve turbidity-toxin. Throughout the treatment process， attention should be paid to protecting the spleen and stomach， and the medication could be modified according to changes of individual condition.

Objective:To compare the clinical efficacy of ultrasound-guided spinal nerve block (SNB) and paraverteral nerve block (PVB) in treating postherpetic neuralgia.Methods:A total of 52 patients with postherpetic neuralgia who visited the Pain Clinic of the Xiangya Hospital, Central South University from February 2020 to December 2022 were selected and randomly divided into an ultrasound-guided SNB group and a PVB group using a random number table method, with 26 patients in each group. Patients in the SNB group received ultrasound-guided spinal nerve block therapy; The PVB group received ultrasound-guided paraverteral nerve block treatment. Visual Analog Scale (VAS) scores, 36-Item Short Form Survey (SF-36) scores, and total effective rate were observed in two groups of patients before treatment, 2 weeks after treatment, 1 month after treatment, 3 months after treatment, and 6 months after treatment. Complications during treatment were also observed.Results:The total effective rates of SNB group patients at 1, 3, and 6 months after treatment were significantly higher than those of PVB group (all P<0.05). After treatment, the VAS scores of both groups of patients at each time point were significantly reduced compared to before treatment (all P<0.05); The VAS scores of patients in the SNB group were lower than those in the PVB group at 1, 3, and 6 months after treatment, but the difference was not statistically significant (all P>0.05). There was no statistically significant difference in Physical Component Summary (PCS) and Mental Component Summary (MCS) scores between SNB and PVB groups before nerve block treatment (all P>0.05). The MCS and PCS scores of the two groups of patients were significantly higher than before treatment at 2 weeks, 1 month, 3 months, and 6 months after treatment (all P<0.05). The MCS scores of the SNB group were significantly higher than those of the PVB group at 2 weeks, 1 month, 3 months, and 6 months after treatment (all P<0.05), but there was no statistically significant difference in PCS scores between the two groups (all P>0.05). Both groups of patients did not experience any serious complications related to the treatment in this study during the follow-up period. Conclusions:Both ultrasound-guided spinal nerve block and paraverteral nerve block can safely and effectively treat postherpetic neuralgia. The clinical effect of ultrasound-guided spinal nerve block in treating postherpetic neuralgia is better than that of paraverteral nerve block.

Objective To train an automatic recognition and classification model of ulcerative colitis colonoscopy image based on ResNet,and to test its accuracy,in order to help doctors improve the clinical detection rate and classification accuracy of ulcerative colitis.Methods A total of 4000 colonoscopy images were retrospectively collected from the Colonoscopy Center of Hebei Hospital of Traditional Chinese Medicine from January 2018 to October 2023,and were divided into normal group,mild group,moderate group and severe group according to Mayo endoscopic scoring criteria,with 1000 images for each group.After pre-processing such as brightness adjustment and Angle rotation,the number of images was expanded to 20,000,and the data set was randomly divided into training set,verification set and test set according to the ratio of 7∶2∶1.The training set and verification set are input into the ResNet model to learn and test its stability.After all training is completed,the accuracy of the model is recorded through the test set,and the accurate regression curve is made to evaluate the classification effect of the model.Results In the test set,the accuracy of classification of ulcerative colitis was 99.8％in normal group,98.8％in mild group,95.6％in moderate group and 97.8％in severe group.Conclusion ResNet has good performance in image recognition and classification of ulcerative colitis,can improve the clinical accuracy of ulcerative colitis,and can assist doctors to identify and classify the disease,which has a more reliable clinical application value.

Objective To train an automatic recognition and classification model of ulcerative colitis colonoscopy image based on ResNet,and to test its accuracy,in order to help doctors improve the clinical detection rate and classification accuracy of ulcerative colitis.Methods A total of 4000 colonoscopy images were retrospectively collected from the Colonoscopy Center of Hebei Hospital of Traditional Chinese Medicine from January 2018 to October 2023,and were divided into normal group,mild group,moderate group and severe group according to Mayo endoscopic scoring criteria,with 1000 images for each group.After pre-processing such as brightness adjustment and Angle rotation,the number of images was expanded to 20,000,and the data set was randomly divided into training set,verification set and test set according to the ratio of 7∶2∶1.The training set and verification set are input into the ResNet model to learn and test its stability.After all training is completed,the accuracy of the model is recorded through the test set,and the accurate regression curve is made to evaluate the classification effect of the model.Results In the test set,the accuracy of classification of ulcerative colitis was 99.8％in normal group,98.8％in mild group,95.6％in moderate group and 97.8％in severe group.Conclusion ResNet has good performance in image recognition and classification of ulcerative colitis,can improve the clinical accuracy of ulcerative colitis,and can assist doctors to identify and classify the disease,which has a more reliable clinical application value.

Objective:To investigate the effects of Rad50-targeted inhibition on the radiosensitivity of head and neck squamous cell carcinoma cells.Methods:Rad50 in Tca8113 and OSCC-15 cells was down-regulated by siRNA.Then the cells were treated by a small dose of radiation(2 Gy),Western blot was used to detect the expression of Rad50 protein.Comet assay was used to evaluate the DNA double strand breaks(DSBs).Colony survival assay was performed to detect the survival rate of the cells.Telomere FISH was performed to assess the telomere length in the cells.Results:Target siRNA inhibited Rad50 protein expression in Tca8113 and OSCC-15 cells. siRNA combined with the radiation of 2 Gy produced more DSBs,decreased the proliferation and shortened the nucleus telomere length of the cells more than radiation treatment alone.Conclusion:The targeted inhibition of Rad50 may increase the radiosensitivity of Tca8113 and OSCC-15 cells.