TUG1 was highly expressed whereas miR-449b-5p was lowly expressed. TUG1 silencing reduced the inflammation and apoptosis. Dual luciferase reporter assays confirmed that miR-449b-5p was a target of TUG1 as well as HMGB1 and MMP2 were direct targets of miR-449b-5p. Meanwhile, miR-449b-5p mimic presented the same results with TUG1 silencing, which were reversed after TUG1 overexpression. Moreover, MMP2 and HMGB1 expression was decreased after miR-449b-5p overexpression while that of was increased after TUG1 overexpression. These findings demonstrated that TUG1 silencing attenuates I/R-induced inflammation and apoptosis via targeting miR-449b-5p and regulating HMGB1 and MMP2 expression.The diagnosis of breast cancer in early stage is essential for successful treatment. Detection can be performed in several ways, the most common being through mammograms. The projections acquired by this type of examination are directly affected by the composition of the breast, which density can be similar to the suspicious masses, being a challenge the identification of malignant lesions. In this article, we propose a computer-aided detection (CAD) system to aid in the diagnosis of masses in digitized mammograms using a model based in the U-Net, allowing specialists to monitor the lesion over time. Unlike most of the studies, we propose the use of an entire base of digitized mammograms using normal, benign, and malignant cases. Our research is divided into four stages (1) pre-processing, with the removal of irrelevant information, enhancement of the contrast of 7989 images of the Digital Database for Screening Mammography (DDSM), and obtaining regions of interest. (2) Data augmentation, with horizontal mirroring, zooming, and resizing of images; (3) training, with tests of six-based U-Net models, with different characteristics; (4) testing, evaluating four metrics, accuracy, sensitivity, specificity, and Dice Index. The tested models obtained different results regarding the assessed parameters. The best model achieved a sensitivity of 92.32%, specificity of 80.47%, accuracy of 85.95% Dice Index of 79.39%, and AUC of 86.40%. Even using a full base without case selection bias, the results obtained demonstrate that the use of a complete database can provide knowledge to the CAD expert.In the original publication of this article [1], there is a correction in Table 2.BACKGROUND Rice sheath blight (ShB) disease, caused by the pathogenic fungus Rhizoctonia solani, causes significant yield losses globally. US weedy rice populations, which are de-domesticated forms of indica and aus cultivated rice, appear to be more resistant to ShB than local japonica cultivated rice. We mapped quantitative trait loci (QTL) associated with ShB resistance using two F8 recombinant inbred line populations generated from crosses of an indica crop variety, Dee-Geo-Woo-Gen (DGWG), with individuals representing the two major US weed biotypes, straw hull (SH) and black hull awned (BHA). RESULTS We identified nine ShB resistance QTL across both mapping populations. Five were attributable to alleles that affect plant height (PH) and heading date (HD), two growth traits that are known to be highly correlated with ShB resistance. By utilizing an approach that treated growth traits as covariates in the mapping model, we were able to infer that the remaining four QTL are involved in ShB resistance. Two of these, qShB1-2 and qShB4, are different from previously identified ShB QTL and represent new candidates for further study.  https://www.selleckchem.com/products/gdc6036.html  CONCLUSION Our findings suggest that ShB resistance can be improved through favorable plant growth traits and the combined effects of small to moderate-effect resistance QTL. Additionally, we show that including PH and HD as covariates in QTL mapping models is a powerful way to identify new ShB resistance QTL.BACKGROUND Epstein-Barr virus (EBV) is etiologically associated with ~ 10% of all gastric carcinomas. However, the molecular mechanisms and roles of EBV miRNAs in gastric carcinoma oncogenesis are yet to be elucidated. METHODS MicroRNA microarray and TaqMan quantitative real-time RT-PCR were conducted. RT-PCR and luciferase reporter assay for PIAS3, western blotting for 20 proteins, immunofluorescence for STAT3, transfection with miRBART5-5p-plasmid, STAT3-plasmid, miRBART5-5p mimic, or PIAS3-siRNA, and in vitro assays for biological effects of PD-L1 were implemented. In situ hybridization for EBV-encoded small RNAs and immunohistochemistry were performed on gastric carcinoma tissues. RESULTS Transfecting miR-BART5-5p into EBV(-) gastric carcinoma cell lines caused a decrease in PIAS3 3'-UTR reporter activity, PIAS3 downregulation, and subsequent STAT3 activation followed by PIAS3/pSTAT3-dependent PD-L1 upregulation. Interestingly, due to PD-L1 knockdown, apoptosis was increased, while the rate of cell proliferation, invasion capacity, and migration were decreased in miR-BART5-5p-transfected cells. In EBV(+) gastric carcinoma cells, anti-miR-BART5-5p reduced PD-L1 levels through PIAS3/pSTAT3 control. Among 103 patients with EBV-associated gastric carcinomas, overall survival was significantly shortened for those with PD-L1(+) tumors compared to those with PD-L1(-) tumors (P = 0.049). CONCLUSIONS Our findings imply that miR-BART5-5p directly targets PIAS3 and augments PD-L1 through miR-BART5/PIAS3/pSTAT3/PD-L1 axis control. This contributes to antiapoptosis, tumor cell proliferation, invasion and migration, as well as immune escape, furthering gastric carcinoma progression and worsening the clinical outcome, especially in the PD-L1(+) group of patients with EBV-associated gastric carcinomas. miR-BART5-5p may, therefore, be amenable to PD-1/PD-L1 immune checkpoint inhibitor therapy.The objectives of this study are to evaluate the available literature regarding the oncologic effect of neoadjuvant and adjuvant chemotherapy in the treatment of patients with clinically non-metastatic upper tract urothelial carcinoma (UTUC) and locally advanced UTUC. We searched PubMed, Cochrane Library, and Scopus databases in November 2019, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We included studies that compared patients with non-metastatic UTUC who received either neoadjuvant or adjuvant chemotherapy with patients who underwent surgery alone. Subgroup meta-analyses were also performed for studies that investigated only locally advanced UTUC. Overall, 36 studies were included in the review of which 22 studies and 15,378 patients were eligible for the meta-analysis. Neoadjuvant chemotherapy (NAC) was associated with higher rates of pathological downstaging (pDS) (RR 6.48, 95% CI 2.05-20.44, p = 0.001) and pathological complete response (RR 18.