Cummingsmosley0272

566; 95% CI 0.955-6.892; p = 0.0616). Among anti-cancer agents, docetaxel (HR 3.790; 95% CI 1.413-10.167; p = 0.0081) and anti-HER2 therapy (HR 2.507; 95% CI 1.083-5.803; p = 0.0318) were associated with increased risk of lymphedema according to multivariate analysis. Neo-adjuvant chemotherapy did not affect the onset of breast cancer-related lymphedema. Radiotherapy (HR 2.525; 95% CI 1.364-4.676; p = 0.0032) was an important risk factor for breast cancer-related lymphedema. CONCLUSIONS Axillary lymph node dissection, radiotherapy and adjuvant chemotherapy, especially docetaxel, were risk factors for breast cancer-related lymphedema, but BMI and neo-adjuvant chemotherapy were not.BACKGROUND There are conflicting data regarding the role of KRAS mutation on the risk of venous thromboembolism (VTE) in colorectal cancer (CRC) patients. Moreover, the role of other biomarkers such as NRAS or BRAF has not been studied. PURPOSE To analyze the incidence of VTE in a cohort of patients with CRC based on KRAS, NRAS, and BRAF status. METHODS We performed a retrospective review of patients with unresectable locally advanced and metastatic CRC (mCRC) and known KRAS/NRAS/BRAF status, attended in the Medical Oncology Department of the Hospital General Universitario Gregorio Marañón (Madrid, Spain). The primary outcome was VTE defined as any venous thromboembolic event that occurred either 6 months before or at any time after the diagnosis of CRC. The biomarker status (KRAS, NRAS, and BRAF) and other predictors of thrombosis were collected. RESULTS One hundred and ninety-four patients were identified and included in the analysis. Forty-one patients (21.1%) experienced VTE. The incidence was 19.1% in RAS-mutated patients, 28.6% in BRAF-mutated patients and 21% in triple wild-type patients (p = NS). In multivariate analysis, ECOG ≥ 2 was the only independent predictor of VTE (OR 8.73; CI 95% 1.32-57.82; p = 0.025). CONCLUSIONS In our study, biomarkers have not been associated with an increased risk of VTE in CRC patients. A high incidence of VTE in BRAF-mutated patients has been observed and should be explored in further studies.PURPOSE Deep learning has recently shown its outstanding performance in biomedical image semantic segmentation. Most biomedical semantic segmentation frameworks comprise the encoder-decoder architecture directly fusing features of the encoder and the decoder by the way of skip connections. However, the simple fusion operation may neglect the semantic gaps which lie between these features in the decoder and the encoder, hindering the effectiveness of the network. METHODS Dense gate network (DG-Net) is proposed for biomedical image segmentation. In this model, the Gate Aggregate structure is utilized to reduce the semantic gaps between features in the encoder and the corresponding features in the decoder, and the gate unit is used to reduce the categorical ambiguity as well as to guide the low-level high-resolution features to recover semantic information. Through this method, the features could reach a similar semantic level before fusion, which is helpful for reducing semantic gaps, thereby producing accurate results. RESULTS Four medical semantic segmentation experiments, based on CT and microscopy images datasets, were performed to evaluate our model. In the cross-validation experiments, the proposed method achieves IOU scores of 97.953%, 89.569%, 81.870% and 76.486% on these four datasets. Compared with U-Net and MultiResUNet methods, DG-Net yields a higher average score on IOU and Acc. CONCLUSION The DG-Net is competitive with the baseline methods. The experiment results indicate that Gate Aggregate structure and gate unit could improve the performance of the network by aggregating features from different layers and reducing the semantic gaps of features in the encoder and the decoder. This has potential in biomedical image segmentation.Lysine specific demethylase 2B, KDM2B, regulates genes that participate in cellular development, morphogenesis, differentiation and metabolism as a component of the polycomb repressive complex 1 (PRC1). The CxxC finger of KDM2B is responsible for the DNA binding capacity of this epigenetic regulator, acting as a sampling mechanism across chromatin for gene repression OBJECTIVES The molecular determinants of the CxxC-DNA interaction remain largely unknown, revealing a significant knowledge gap to be explored. Our goal was to elucidate the key residues of the CxxC domain that contribute to its function as well as to further elaborate on the significance of this domain in the KDM2B role METHODS By using electrophoresis mobility swift assay, we identified structural elements of CxxC domain that participate in the DNA recognition. We created mouse embryonic fibroblasts overexpressing different truncated and point-mutated mouse KDM2B variants to examine the contribution of the KDM2B domains in replicative senescence bypass RESULTS In this study, we show that only the CxxC finger is essential for the ability of mKDM2B to bypass replicative senescence in primary cells by ink4A-Arf-ink4B locus repression, and that this is mediated by specific interactions of residues R585, K608 and K616 with non-methylated CpG containing DNA CONCLUSIONS These results provide new structural insights into the molecular interactions of CxxC and could serve as a stepping-stone for developing domain-specific inhibitors for KDM2B.Clinical and epidemiological knowledge of 2019 novel coronavirus disease (COVID-19) is limited. We reported a family cluster of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases in Beijing, China. This family comprised three laboratory confirmed cases with clinical symptoms. All three patients had close contact with a relative from Wuhan, Hubei Province. Throat swab samples were all positive for SARS-CoV-2 using real-time reverse transcriptase-polymerase chain reaction assays. Chest computerized tomography revealed ground-glass opacities and consolidation. RRx-001 SARS-CoV-2 infections tend to clusters. Physicians should be aware of contact history so that infected patients can be identified promptly and further spreading prevented.