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Background. With the aging of the population, the prevalence of IVDD increases preoperatively. How to better treat IVDD has become an important clinical issue. Deer antlers proved to have a great effect on the treatment of IVDD in many studies, but the molecular mechanism has not been clarified. Objective. To investigate the molecular mechanism and target of deer antlers in the treatment of IVDD. Methods. Compounds from deer antlers were collected and targets were predicted using HERB, TCMSP, TCMID, SwissADME, and SwissTargetPrediction. Collection of disease targets for IVDD was done using GeneCards, TTD, DrugBank, DisGeNET, and OMIM. Cytoscape 3.7.2, AutoDock Vina (v1.1.2), and R software were used for data analysis and the construction of network diagrams. Results. A total of 5 active compounds from deer antlers were screened and 104 therapeutic targets were predicted. A total of 1023 IVDD disease targets were collected. Subsequently, PPI network prediction analysis was performed for disease and treatment targets, and 112 core targets were collected after screening. After obtaining the core target, we used the clusterProfiler software package of R software to carry out GO and KEGG enrichment analyses for the core target and plot the bubble maps. According to the GO enrichment results, the main biological processes of IVDD treatment by deer antlers lie in the rhythmic process, mRNA catabolic process, and G1/S transition of the mitotic cell cycle. KEGG results were mainly related to the PI3K-Akt signaling pathway, thyroid hormone signaling pathway, and Notch signaling pathway. Molecular docking results showed that estrone had the best docking results on ESR1. Conclusion. Deer antlers are rich in various compounds that can prevent the development of IVDD by upregulating the PI3K-Akt signaling pathway and Notch signaling pathway. Its key compounds estradiol and estrone can reduce the inflammatory response and oxidative stress in tissues and organs, thus slowing down the progression of IVDD. Estrone, the active compound in deer antlers, was found by molecular docking to have good results against ESR1, the target of the disease, which may be a potential site for drug therapy.

Chloride intracellular channel 1 (CLIC1) plays an important role in the process of cell epithelial transport, and is also involved in tumor invasion and metastasis. Due to its aberrant expression in cancer, the mechanism of action of CLIC1 in cancer has been carefully studied. In this study, we tried to investigate the relationship between CLIC1 and lung adenocarcinoma (LUAD).The RNA-sequencing data and clinical information of CLIC1 in lung adenocarcinoma were collected from the the cancer genome altas (TCGA) database and analyzed with R software. Paired t test and Mann-Whitney U test were used to detect differences between LUAD tissue and adjacent normal tissue, and the pROC software package performed reactive oxygen species (ROC) curves to detect cutoff values for CLIC1. The expression of CLIC1 in normal human tissues was extracted from the human protein altas (HPA) database, and analyzed clinical proteomic tumor analysis consortium by using UALCAN programme. The relationship between CLIC1 and LUAD was explored by enrichment analysis using gene oncology and Kyoto encyclopedia of genes and genomes. The tumor immunity estimation resource (TIMER) and integrated repository portal for tumor-immune system interactions (TISIDB) databases were used to analyze the correlation between CLIC1 and LUAD immune cell infiltration. Survival analysis of CLIC1 in LUAD was assessed by the PrognoScan database.Compared with normal tissues, both mRNA (messenger Ribose Nucleic Acid) and protein of CLIC1 were overexpressed in LUAD, which was associated with shorter overall survial (OS). In addition, CLIC1 expression was in connection with some clinical-pathological characteristics like tumor node metatasis stages and lymph node metastases. What's more, CLIC1 may play a role in the immune infiltration of LUAD.In summary, CLIC1 is up-regulated in LUAD and is associated with tumor metastasis, tumor staging, and OS. It may be regarded as a novel marker for prognostic judgement in LUAD.

Radiation enteritis (RE) caused by radiation therapy, can seriously affect human health. Recently, studies on RE have been growing rapidly, but there are no bibliometric studies on RE. This study aims to explore the development trends and research hotspots of RE.Academic papers on the Web of Science were retrieved on the topic of "radioactive enteritis" from the establishment of the database to December 2020. Countries, institutions, and subjects selected in this field were visualized using Citespace, HistCite, and Vosviewer. The annual trends in publications, distribution, co-authorship status, and research hotspots were analyzed.The authors ranked first in terms of publication amount were Delaney, Francois, Milliat, and Vozenin-Brotons. The United States had the highest number of posts, followed by China, France, the United Kingdom, and Spain.Future research in the field of RE will focus on double-blind clinical trials of RE, and the related mechanisms, such as oxidative stress and apoptosis.

BACKGROUND: Artificial intelligence (AI) is used to solve the problem of missed diagnosis of polyps in colonoscopy, which has been proved to improve the detection rate of adenomas. The aim of this review was to evaluate the diagnostic performance of AI-assisted detection and classification of polyps in colonoscopy. METHODS: The literature search was undertaken on 4 electronic databases (PubMed, Web of Science, Embase, and Cochrane Library). The inclusion criteria were as follows: studies reporting AI-assisted detection and classification of polyps; studies containing patients, images, or videos receiving AI-assisted diagnosis; studies which included AI-assisted diagnosis and reported classification based on histopathology; and studies providing accurate diagnostic data. Non-English language studies, case-reports, reviews, meeting abstracts and so on were excluded. The Quality Assessment of Diagnostic Accuracy Studies-2 scale was used to evaluate the quality of literature and the Stata 13.0 software was used to perform meta-analysis. RESULTS: Twenty-six articles were included with all of medium quality. Meta-analysis showed none of literature had any obvious publication bias. The application of AI in detection of colorectal polyps achieved a sensitivity of 0.95 [95% confidence interval (CI): 0.89–0.98] and an area under the curve (AUC) of 0.79 (95% CI: 0.79–0.82). In the AI-assisted classification, the sensitivity was 0.92 (95% CI: 0.88–0.95) with a specificity of 0.82 (95% CI: 0.71–0.89) and an AUC of 0.94 (95% CI: 0.92–0.96). For the classification of diminutive polyps, the AI-assisted technique yielded a sensitivity of 0.95 (95% CI: 0.94–0.97), a specificity of 0.88 (95% CI: 0.74–0.95), and an AUC of 0.97 (95% CI: 0.95–0.98). For AI-assisted classification under magnifying endoscopy, the sensitivity was 0.954 (95% CI: 0.92–0.96) with a specificity of 0.95 (95% CI: 0.80–0.99) and an AUC of 0.97 (95% CI: 0.95–0.98). DISCUSSION: The AI-assisted technique demonstrates impressive accuracy for the detection and characterization of colorectal polyps and can be expected to be a novel auxiliary diagnosis method. Our study has inevitable limitations including heterogeneity due to different AI systems and the inability to further analyze the specificity and sensitivity of AI for different types of endoscopes.