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Ulcerative colitis (UC) was a type of inflammatory bowel diseases, which was difficult to cure and even would malignant turn into colon cancer. The specific etiology and molecular mechanism of UC were unclear to date. The purpose of this study was to search for new targets for the diagnosis and treatment of UC.

Firstly, we downloaded the gene expression data of UC from the gene expression omnibus database database (GSE107499), and used multiple bioinformatics methods to find differently expressed genes (DEGs) in UC. Subsequently, we evaluated the lymphocyte infiltration in UC inflamed colon tissue by using the cell type identification by estimating relative subset of known RNA transcripts method.

We obtained 1175 DEGs and 8 hub genes (IL6, TNF, PTPRC, CXCL8, FN1, CD44, IL1B, and MMP9) in this study. Among them, 903 DEGs were up-regulated and 272 DEGs were down-regulated. Compared with non-inflamed colon tissues, the inflamed colon tissues had higher levels of memory B cells, activated memory CD4 T cells, follicular helper T cells, M1 macrophages, resting dendritic cells, activated dendritic cells, activated mast cells, and neutrophils, whereas the proportions of plasma cells, resting memory CD4 T cells, gamma delta T cells, activated NK cells, M2 macrophages and resting mast cells were relatively lower.

The DEGs, hub genes and different lymphatic infiltration conditions can provide new targets for diagnosis and treatment of UC. However, these were just predictions through some theoretical methods, and more basic experiments will be needed to prove in the future.

The DEGs, hub genes and different lymphatic infiltration conditions can provide new targets for diagnosis and treatment of UC. However, these were just predictions through some theoretical methods, and more basic experiments will be needed to prove in the future.It is of significance to evaluate central lymph node status in patients with papillary thyroid carcinoma (PTC), because it can decrease postoperative complications resulting from unnecessary prophylactic central lymph node dissection (CLND). Due to the low sensitivity and specificity of neck ultrasonography in the evaluation of central lymph node metastasis (CLNM), it is urgently required to find alternative biomarkers to predict CLNM in PTC patients, which is the main purpose of this study.RNA-sequencing datasets and clinical data of 506 patients with thyroid carcinoma from the Cancer Genome Atlas (TCGA) database were downloaded and analyzed to identify differentially expressed miRNAs (DEMs), which can independently predict CLNM in PTC. A nomogram predictive of CLNM was developed based on clinical characteristics and the identified miRNAs. Receiver operating characteristics curves were drawn to evaluate the predictive performance of the nomogram. Bioinformatics analyses, including target genes identification, which showed better prediction value than the other three predictors (risk score, age, and ETE) in terms of CLNM identification. Bioinformatics analyses revealed that 5 hub genes, SLC6A1, SYT1, COL19A1, RIMS2, and COL1A2, might involve in pathways including extracellular matrix organization, ion transmembrane transporter activity, axon guidance, and ABC transporters.On the basis of this study, the nomogram including risk score, age, and ETE showed good prediction of CLNM in PTC, which has a potential to facilitate individualized decision for surgical plans.

Xiaoaiping injection, extracted from the Chinese herb Marsdenia tenacissima (Roxb.) Wight et Arn., is a broad-spectrum anti-tumor drug and has been widely used for the treatment of liver cancer in China. The aim of this study is to systematically investigate the efficacy and safety of Xiaoaiping injection for the treatment of liver cancer.

Seven electronic databases including the Cochrane Library, PubMed, Excerpt Medica Database, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, China Scientific Journal Database, and Wanfang Database will be systematically retrieved for data extraction from their inceptions to August 2020. Cochrane Risk of Bias tool will be used to assess the risk of bias of included studies. The RevMan 5.4 and Stata 16.0 software will be applied for statistical analyses. Statistical heterogeneity will be computed by I tests. Sensitivity analysis will be conducted to evaluate the stability of the results. The publication bias will be evaluated by funnel plots and Eggers test. The quality of evidence will be assessed by the GRADE system.

The results of our research will be published in a peer-reviewed journal.

The conclusion of this study will provide helpful evidence of the effect and safety of Xiaoaiping injection for the treatment of liver cancer in clinical practice.

10.17605/OSF.IO/9BD6A.

10.17605/OSF.IO/9BD6A.

Diabetic macular edema (DME) can cause severe vision impairments for patients with diabetes. buy Vorinostat Recently, Conbercept has shown efficacy on DME with 3-monthly loading dose injection and pro re nata (PRN, 3+PRN) thereafter in retrospectivetrials. Furthermore, there are some other approaches have been recommended such as 2mg bimonthly (2q8) after 5 initial doses, or Conbercept 0.5mg treat-and-extend, however, some patients still have recurrence of the disease after treatment. Therefore, in order to identify more efficacy and safety approach on Conbercept inpatients with DME, a randomized controlled trial will be performed with 6-monthly loading dose injection and PRN (6+PRN) compared with 3+PRN treatments.

This study is a multicenter, randomized control trial of Conbecept treating DME in China. Patients with type 2 diabetes suffered from DEM who already planned to receive Conbercept treatment will be recruited. All subjects will be randomized divided into either a study agent treatment group (6+PRN) or a control group (3+PRN), and observes the subjects for 48 weeks after initiation of treatment.

This study will provide a new powerful evidence of the efficacy and safety of Conbecept treating DME.

This RTC study will determine whether multiple treatments of Conbercept provide better effectiveness in patients with DME.

ChiCTR2000032728.

ChiCTR2000032728.

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