Objective:To investigate the effects of baicalin on ferroptosis of mouse fibroblasts (Fbs) under high glucose treatment and its mechanism, and to provide a basis for the treatment of diabetic wounds.Methods:The study was an experimental study. Mouse Fbs were collected and divided into control group with conventional culture, high glucose group treated with glucose at final molarity of 30.0 mmol/L, and low baicalin group and high baicalin group pretreated with baicalin at final molarties of 5 and 10 μmol/L respectively and then treated as that in high glucose group. After 48 h of culture, the cell survival rate was detected by the cell counting kit-8, the reactive oxygen species level in cells was detected by the fluorescent probe method, the levels of malondialdehyde, glutathione, and ferrous ion in cells were detected by colorimetry, and the protein expression levels of solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) in cells and nuclear factor-erythroid 2-related factor 2 (Nrf2) in cytoplasm and nucleus were detected by Western blotting. Another batch of mouse Fbs were collected and divided into control group, high glucose group, high baicalin group, and high baicalin+ML385 group. The cells in the first three groups were treated as before, the cells in the last group were pretreated with baicalin and ML385 of Nrf2 inhibitor at final molarties of 10 μmol/L and then treated as that in high glucose group. After 48 h of culture, the protein expression levels of SLC7A11 and GPX4 in cells and the protein expression level of Nrf2 in cytoplasm and nucleus were detected as before. Except that the sample number in detecting SLC7A11 and GPX4 was 4, the sample number in detecting other indexes was 3.Results:After 48 h of culture, the cell survival rates in control group, high glucose group, low baicalin group, and high baicalin group were (100.0±10.7)%, (70.0±5.0)%, (80.9±3.2)%, and (91.4±1.9)%, respectively. Compared with those in control group, the cell survival rate, the glutathione level, and SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level were significantly decreased in high glucose group ( P<0.05), and the levels of reactive oxygen species, malondialdehyde, and ferrous ion in cells, and cytoplasmic Nrf2 protein expression level were significantly increased in high glucose group ( P<0.05). Compared with those in high glucose group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in low baicalin group and high baicalin group were significantly increased ( P<0.05), the reactive oxygen species and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in low baicalin group and high baicalin group were significantly decreased ( P<0.05), and the malondialdehyde level in cells in high baicalin group was significantly decreased ( P<0.05). Compared with those in low baicalin group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in high baicalin group were significantly increased ( P<0.05), and the reactive oxygen species, malondialdehyde, and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in high baicalin group were significantly decreased ( P<0.05). After 48 h of culture, compared with those in control group, the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased ( P<0.05), and the cytoplasmic Nrf2 protein expression level was significantly increased in high glucose group ( P<0.05); compared with those in high glucose group, the cytoplasmic Nrf2 protein expression level was significantly decreased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly increased in high baicalin group ( P<0.05); compared with those in high baicalin group, the cytoplasmic Nrf2 protein expression level was significantly increased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased in high baicalin+ML385 group ( P<0.05). Conclusions:Baicalin can inhibit the occurrence of ferroptosis in cells by activating the Nrf2 signaling pathway and up-regulating the expressions of proteins related to SLC7A11/GPX4 axis in Fbs in high glucose treatment, thus increasing the cell survival rate.

Objective:To investigate the effects of baicalin on ferroptosis of mouse fibroblasts (Fbs) under high glucose treatment and its mechanism, and to provide a basis for the treatment of diabetic wounds.Methods:The study was an experimental study. Mouse Fbs were collected and divided into control group with conventional culture, high glucose group treated with glucose at final molarity of 30.0 mmol/L, and low baicalin group and high baicalin group pretreated with baicalin at final molarties of 5 and 10 μmol/L respectively and then treated as that in high glucose group. After 48 h of culture, the cell survival rate was detected by the cell counting kit-8, the reactive oxygen species level in cells was detected by the fluorescent probe method, the levels of malondialdehyde, glutathione, and ferrous ion in cells were detected by colorimetry, and the protein expression levels of solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) in cells and nuclear factor-erythroid 2-related factor 2 (Nrf2) in cytoplasm and nucleus were detected by Western blotting. Another batch of mouse Fbs were collected and divided into control group, high glucose group, high baicalin group, and high baicalin+ML385 group. The cells in the first three groups were treated as before, the cells in the last group were pretreated with baicalin and ML385 of Nrf2 inhibitor at final molarties of 10 μmol/L and then treated as that in high glucose group. After 48 h of culture, the protein expression levels of SLC7A11 and GPX4 in cells and the protein expression level of Nrf2 in cytoplasm and nucleus were detected as before. Except that the sample number in detecting SLC7A11 and GPX4 was 4, the sample number in detecting other indexes was 3.Results:After 48 h of culture, the cell survival rates in control group, high glucose group, low baicalin group, and high baicalin group were (100.0±10.7)%, (70.0±5.0)%, (80.9±3.2)%, and (91.4±1.9)%, respectively. Compared with those in control group, the cell survival rate, the glutathione level, and SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level were significantly decreased in high glucose group ( P<0.05), and the levels of reactive oxygen species, malondialdehyde, and ferrous ion in cells, and cytoplasmic Nrf2 protein expression level were significantly increased in high glucose group ( P<0.05). Compared with those in high glucose group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in low baicalin group and high baicalin group were significantly increased ( P<0.05), the reactive oxygen species and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in low baicalin group and high baicalin group were significantly decreased ( P<0.05), and the malondialdehyde level in cells in high baicalin group was significantly decreased ( P<0.05). Compared with those in low baicalin group, the cell survival rate, glutathione level, SLC7A11 and GPX4 protein expression levels in cells, and nuclear Nrf2 protein expression level in high baicalin group were significantly increased ( P<0.05), and the reactive oxygen species, malondialdehyde, and ferrous ion levels in cells, and cytoplasmic Nrf2 protein expression level in high baicalin group were significantly decreased ( P<0.05). After 48 h of culture, compared with those in control group, the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased ( P<0.05), and the cytoplasmic Nrf2 protein expression level was significantly increased in high glucose group ( P<0.05); compared with those in high glucose group, the cytoplasmic Nrf2 protein expression level was significantly decreased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly increased in high baicalin group ( P<0.05); compared with those in high baicalin group, the cytoplasmic Nrf2 protein expression level was significantly increased ( P<0.05), and the nuclear Nrf2 protein expression level and SLC7A11 and GPX4 protein expression levels in cells were significantly decreased in high baicalin+ML385 group ( P<0.05). Conclusions:Baicalin can inhibit the occurrence of ferroptosis in cells by activating the Nrf2 signaling pathway and up-regulating the expressions of proteins related to SLC7A11/GPX4 axis in Fbs in high glucose treatment, thus increasing the cell survival rate.

Objective To systematically retrieve,evaluate and integrate evidences about the assessment and management of perioperative pain in patients with acute aortic dissection.Methods PIPOST model was used to identify themes of assessment and management of perioperative pain.The literatures in the themes was systematically searched through the databases of UpToDate,JBI,BMJ Best Practice,practice guide REgistration for trans RAREncy(PREPARE),Guidelines International Network(GIN),National Guideline Clearinghouse(NGC),National Institute for Health and Care Excellence(NICE),Scottish Intercollegiate Guidelines Network(SIGN),New Zealand Guidelines Group(NZGG),Registered Nurses'Association of Ontario(RNAO),Australian Clinical Practice Guidelines(ACPG),American Heart Association(AHA),European Society of Cardiology(ESC),the Chinese Cochrane Center,Medlive,Cochrane library,PubMed,SinoMed,CNKI,Wangfan Data,and VIP.The retrieved literatures were evaluated and the evidences that met the inclusive criteria were extracted from the literatures by researchers who had trained for evidence-based study.Results A total of 17 studies,including 5 guidelines,3 expert consensus,6 systematic reviews and 3 randomised controlled trials were included in this study.Totally,29 pieces of best evidence were extracted in the assessment and management of pain in perioperative patients with acute aortic dissection,including pain assessment,basic principles of pain management,medication intervention strategies of pain management,non-medication intervention strategies of pain management,pain evaluation,education of pain management and organising pain management.Conclusion Evidences in assessment and management of pain in perioperative patients with acute aortic dissection can provide references and guidance for clinical practice.

Antineoplastic drugs refer to the drugs that act at the cellular and molecular levels to inhibit tumor growth or eliminate tumors through pathways such as cell killing,immune regulation,and endocrine regulation.Antineoplastic drugs generally including chemotherapeutic drugs,molecular targeted therapeutic drugs,immunotherapeutic drugs,and endocrine therapeutic drugs.The management and rational application of antineoplastic drugs in medical institutions are related to the safety of patient treatment.The standard for management of antineoplastic drugs use in clinical is compiled by the Pharmaceutical Affairs Committee of China Hospital Association,which specification requirements 18 key elements in the organizational management and system,medication management,drug monitoring and evaluation of antineoplastic drug management in healthcare institutions.This standard is applicable to all levels and types of healthcare institutions carrying out oncology diagnosis and treatment.This paper describes the methodology and basic content of the standard,hoping to providing a reference for medical institutions to carry out relevant work.

Objective:To develop deep learning models for ulcerative colitis (UC) classification based on Mayo endoscopic score.Methods:A total of 2400 endoscopic images from the Gastrointestinal Endoscopy Centre of the First Affiliated Hospital of Soochow University and the HyperKvasir database were extracted for training classification models, and 200 endoscopic images from Affiliated Jintan Hospital of Jiangsu University were extracted for evaluating the models, both scored by endoscopists according to Mayo endoscopic score (score 0-3). Four deep convolutional neural networks (MobileNetV2, ResNetV2, Xception, EfficientNetV2S), which were pre-trained in the ImageNet database, were used to develop the UC classification models by transfer learning. Models were evaluated in the test set based on the confusion matrix using accuracy, Matthews correlation coefficient (MCC) and Cohen′s kappa, and compared with the performance of senior and junior physicians. Meanwhile, the model was visualized by gradient-weighted class activation mapping.Results:Four deep learning Mayo score models based on UC endoscopic image classification models were successfully developed. In the test set, the accuracy of MobileNetV2, ResNetV2, Xception and EfficientNetV2S was 0.785, 0.800, 0.815, 0.830, respectively (average accuracy 0.808). Amoug them, EfficientNetV2S model was the best, higher than junior physician′s accuracy (accuracy 0.785), and slightly lower than senior physician′s (accuracy 0.870) .Conclusions:The UC endoscopic severity classification models developed by deep learning show good performance, which can be further improved by larger sample size and optimizing the framework.

With persistent breakthrough and maturity of surgical procedures and postoperative immunosuppressive therapy, the survival rate of liver transplant recipients and grafts has been significantly increased. The shortage of donor liver has become the main obstacle for clinical development of liver transplantation. How to expand the source of donor liver has become an urgent issue. Groundbreaking progresses have been made in the use of common marginal donor livers in clinical liver transplantation, such as elderly donor liver, steatosis donor liver, viral hepatitis donor liver and liver from donation after cardiac death. Nevertheless, multiple restrictions still exist regarding the use of marginal donor liver. Consequently, the definition of marginal donor liver and research progress in the application of common marginal donor livers were reviewed, and the opportunities and challenges of mariginal donoor liver were illustrated, aiming to provide reference for expanding the donor pool for clinical liver transplantation and bringing benefits to more patients with end-stage liver disease.

Objective:To develop deep learning models for ulcerative colitis (UC) classification based on Mayo endoscopic score.Methods:A total of 2400 endoscopic images from the Gastrointestinal Endoscopy Centre of the First Affiliated Hospital of Soochow University and the HyperKvasir database were extracted for training classification models, and 200 endoscopic images from Affiliated Jintan Hospital of Jiangsu University were extracted for evaluating the models, both scored by endoscopists according to Mayo endoscopic score (score 0-3). Four deep convolutional neural networks (MobileNetV2, ResNetV2, Xception, EfficientNetV2S), which were pre-trained in the ImageNet database, were used to develop the UC classification models by transfer learning. Models were evaluated in the test set based on the confusion matrix using accuracy, Matthews correlation coefficient (MCC) and Cohen′s kappa, and compared with the performance of senior and junior physicians. Meanwhile, the model was visualized by gradient-weighted class activation mapping.Results:Four deep learning Mayo score models based on UC endoscopic image classification models were successfully developed. In the test set, the accuracy of MobileNetV2, ResNetV2, Xception and EfficientNetV2S was 0.785, 0.800, 0.815, 0.830, respectively (average accuracy 0.808). Amoug them, EfficientNetV2S model was the best, higher than junior physician′s accuracy (accuracy 0.785), and slightly lower than senior physician′s (accuracy 0.870) .Conclusions:The UC endoscopic severity classification models developed by deep learning show good performance, which can be further improved by larger sample size and optimizing the framework.

Acute pancreatitis （AP） is a gastrointestinal disease that requires early intervention， and when it progresses to moderate-severe AP （MSAP） or severe AP （SAP）， there will be a significant increase in the mortality rate of patients. Machine learning （ML） has achieved great success in the early prediction of AP using clinical data with the help of its powerful computational and learning capabilities. This article reviews the research advances in ML in predicting the severity， complications， and death of AP， so as to provide a theoretical basis and new insights for clinical diagnosis and treatment of AP through artificial intelligence.

ObjectiveTo analyze the epidemiological characteristics of varicella in Yangpu District， Shanghai from 2005 to 2022， predict the trend of varicella in Yangpu District in 2023， and provide evidence for prevention and control of varicella outbreaks. MethodsInformation of varicella cases reported in Yangpu District from 2005 to 2022 was obtained from the China Information System for Disease Control and Prevention. Descriptive statistics was used to characterize the varicella epidemiology. An autoregressive integrated moving average （ARIMA） model was established by using the number of cases per month from 2005 to2022 to predict the trend of varicella epidemics in Yangpu District in 2023. The varicella incidence in 2022 was used to evaluate the fitness of the ARIMA model. ResultsFrom January 2005 to December 2021， a total of 11 527 cases of varicella were reported in Yangpu District， Shanghai. After excluding duplicates and clinical diagnoses， 11 413 cases were included into the analysis. The annual average incidence rate was 51.87/10⁵， the age of onset was mainly under 20 years old （66.5%）， and the occupation was mainly students （49.7%）. The ARIMA （1，1，0）×（0，1，1）₁₂ model was constructed and showed a good fitness while using monthly reported varicella cases in 2022 for model fitting. It was predicted that 1 089 cases of varicella would be reported in Yangpu District in 2023. ConclusionIt is predicted that varicella cases in Yangpu District will increase in 2023. It is recommended to continue promoting delayed varicella vaccination to maintain a high level of vaccination rate. Before the peak of the epidemic， health education regarding varicella should be strengthened， and measures for epidemic prevention and control should be reinforced to prevent varicella outbreaks.

Marine microorganisms, especially marine fungi, have historically proven their value as a prolific source for structurally novel and pharmacologically active secondary metabolites (Deshmukh et al., 2018; Carroll et al., 2022). The corals constitute a dominant part of reefs with the highest biodiversity, and harbor highly diverse and abundant microbial symbionts in their tissue, skeleton, and mucus layer, with species-specific core members that are spatially partitioned across coral microhabitats (Wang WQ et al., 2022). The coral-associated fungi were very recently found to be vital producers of structurally diverse compounds, terpenes, alkaloids, peptides, aromatics, lactones, and steroids. They demonstrate a wide range of bioactivity such as anticancer, antimicrobial, and antifouling activity (Chen et al., 2022). The genetically powerful genus Emericella (Ascomycota), which has marine and terrestrial sources, includes over 30 species and is distributed worldwide. It is considered a rich source of diverse secondary metabolites with antimicrobial activity or cytotoxicity (Alburae et al., 2020). Notably, Emericella nidulans, the sexual state of a classic biosynthetic strain Aspergillus nidulans, was recently reported as an important source of highly methylated polyketides (Li et al., 2019) and isoindolone-containing meroterpenoids (Zhou et al., 2016) with unusual skeletons.
Animals ; Aspergillus nidulans ; Polyketides/chemistry* ; Anthozoa/microbiology* ; Anti-Infective Agents/pharmacology* ; Alkaloids