In areas with a low prevalence of MDR bacteria.

No abstract

In this paper, we propose a unified end-to-end trainable multi-task network that jointly handles lane and road marking detection and recognition that is guided by a vanishing point under adverse weather conditions. We tackle rainy and low illumination conditions, which have not been extensively studied until now due to clear challenges. For example, images taken under rainy days are subject to low illumination, while wet roads cause light reflection and distort the appearance of lane and road markings. At night, color distortion occurs under limited illumination. As a result, no benchmark dataset exists and only a few developed algorithms work under poor weather conditions. To address this shortcoming, we build up a lane and road marking benchmark which consists of about 20,000 images with 17 lane and road marking classes under four different scenarios: no rain, rain, heavy rain, and night. We train and evaluate several versions of the proposed multi-task network and validate the importance of each task. The resulting approach, VPGNet, can detect and classify lanes and road markings, and predict a vanishing point with a single forward pass. Experimental results show that our approach achieves high accuracy and robustness under various conditions in realtime (20 fps). The benchmark and the VPGNet model will be publicly available 1 .

BackgroundWhile vascular endothelial growth factor (VEGF) expression in breast tumors has been correlated with a poor outcome in the pathogenesis of breast cancer, the expression, localization, and function of VEGF receptors VEGFR1 (also known as FLT1) and VEGFR2 (also known as KDR or FLK1), as well as neuropilin 1 (NRP1), in breast cancer are controversial.Methods and FindingsWe investigated the expression and function of VEGF and VEGF receptors in breast cancer cells. We observed that VEGFR1 expression was abundant, VEGFR2 expression was low, and NRP1 expression was variable. MDA-MB-231 and MCF-7 breast cancer cells, transfected with antisense VEGF cDNA or with siVEGF (VEGF-targeted small interfering RNA), showed a significant reduction in VEGF expression and increased apoptosis as compared to the control cells. Additionally, specifically targeted knockdown of VEGFR1 expression by siRNA (siVEGFR1) significantly decreased the survival of breast cancer cells through down-regulation of protein kinase B (AKT) phosphorylation, while targeted knockdown of VEGFR2 or NRP1 expression had no effect on the survival of these cancer cells. Since a VEGFR1-specific ligand, placenta growth factor (PGF), did not, as expected, inhibit the breast cancer cell apoptosis induced by siVEGF, and since VEGFR1 antibody also had no effects on the survival of these cells, we examined VEGFR1 localization. VEGFR1 was predominantly expressed internally in MDA-MB-231 and MCF-7 breast cancer cells. Specifically, VEGFR1 was found to be colocalized with lamin A/C and was expressed mainly in the nuclear envelope in breast cancer cell lines and primary breast cancer tumors. Breast cancer cells treated with siVEGFR1 showed significantly decreased VEGFR1 expression levels and a lack of VEGFR1 expression in the nuclear envelope.ConclusionsThis study provides, to our knowledge for the first time, evidence of a unique survival system in breast cancer cells by which VEGF can act as an internal autocrine (intracrine) survival factor through its binding to VEGFR1. These results may lead to an improved strategy for tumor therapy based on the inhibition of angiogenesis.