A novel protein isoform of the RON tyrosine kinase receptor transforms human pancreatic duct epithelial cells.

The MST1R gene is overexpressed in pancreatic cancer producing elevated levels of the RON tyrosine kinase receptor protein. While mutations in MST1R are rare, alternative splice variants have been previously reported in epithelial cancers. We report the discovery of a novel RON isoform discovered in human pancreatic cancer. Partial splicing of exons 5 and 6 (P5P6) produces a RON isoform that lacks the first extracellular immunoglobulin-plexin-transcription domain. The splice variant is detected in 73% of xenografts derived from pancreatic adenocarcinoma patients and 71% of pancreatic cancer cell lines. Peptides specific to RON P5P6 detected in human pancreatic cancer specimens by mass spectrometry confirm translation of the protein isoform. The P5P6 isoform is found to be constitutively phosphorylated, present in the cytoplasm, and it traffics to the plasma membrane. Expression of P5P6 in immortalized human pancreatic duct epithelial (HPDE) cells activates downstream AKT, and in human pancreatic epithelial nestin-expressing cells, activates both the AKT and MAPK pathways. Inhibiting RON P5P6 in HPDE cells using a small molecule inhibitor BMS-777607 blocked constitutive activation and decreased AKT signaling. P5P6 transforms NIH3T3 cells and induces tumorigenicity in HPDE cells. Resultant HPDE-P5P6 tumors develop a dense stromal compartment similar to that seen in pancreatic cancer. In summary, we have identified a novel and constitutively active isoform of the RON tyrosine kinase receptor that has transforming activity and is expressed in human pancreatic cancer. These findings provide additional insight into the biology of the RON receptor in pancreatic cancer and are clinically relevant to the study of RON as a potential therapeutic target

Decadal changes in summertime reactive oxidized nitrogen and surface ozone over the Southeast United States

Widespread efforts to abate ozone (O3) smog have significantly reduced emissions of nitrogen oxides (NOx) over the past 2 decades in the Southeast US, a place heavily influenced by both anthropogenic and biogenic emissions. How reactive nitrogen speciation responds to the reduction in NOx emissions in this region remains to be elucidated. Here we exploit aircraft measurements from ICARTT (July–August 2004), SENEX (June–July 2013), and SEAC4RS (August–September 2013) and long-term ground measurement networks alongside a global chemistry–climate model to examine decadal changes in summertime reactive oxidized nitrogen (RON) and ozone over the Southeast US. We show that our model can reproduce the mean vertical profiles of major RON species and the total (NOy) in both 2004 and 2013. Among the major RON species, nitric acid (HNO3) is dominant (∼ 42–45%), followed by NOx (31%), total peroxy nitrates (ΣPNs; 14%), and total alkyl nitrates (ΣANs; 9–12%) on a regional scale. We find that most RON species, including NOx, ΣPNs, and HNO3, decline proportionally with decreasing NOx emissions in this region, leading to a similar decline in NOy. This linear response might be in part due to the nearly constant summertime supply of biogenic VOC emissions in this region. Our model captures the observed relative change in RON and surface ozone from 2004 to 2013. Model sensitivity tests indicate that further reductions of NOxemissions will lead to a continued decline in surface ozone and less frequent high-ozone events

Ron Carey Responds

[Excerpt] A New Labor Movement in the Shell of the Old? hits the nail on the head when it says that any hope of reviving the labor movement depends on change at the grassroots, not just in Washington, D.C. In the past five years, we in the Teamsters union have been facing the same challenge that now confronts the AFL-CIO: how to turn the labor bureaucracy into a labor movement again. The reforms we are making—while far from complete—confirm Brecher and Costello\u27s argument that rankand- file involvement and new community coalitions are key to rebuilding labor\u27s strength

RON: Reverse Connection with Objectness Prior Networks for Object Detection

We present RON, an efficient and effective framework for generic object detection. Our motivation is to smartly associate the best of the region-based (e.g., Faster R-CNN) and region-free (e.g., SSD) methodologies. Under fully convolutional architecture, RON mainly focuses on two fundamental problems: (a) multi-scale object localization and (b) negative sample mining. To address (a), we design the reverse connection, which enables the network to detect objects on multi-levels of CNNs. To deal with (b), we propose the objectness prior to significantly reduce the searching space of objects. We optimize the reverse connection, objectness prior and object detector jointly by a multi-task loss function, thus RON can directly predict final detection results from all locations of various feature maps. Extensive experiments on the challenging PASCAL VOC 2007, PASCAL VOC 2012 and MS COCO benchmarks demonstrate the competitive performance of RON. Specifically, with VGG-16 and low resolution 384X384 input size, the network gets 81.3% mAP on PASCAL VOC 2007, 80.7% mAP on PASCAL VOC 2012 datasets. Its superiority increases when datasets become larger and more difficult, as demonstrated by the results on the MS COCO dataset. With 1.5G GPU memory at test phase, the speed of the network is 15 FPS, 3X faster than the Faster R-CNN counterpart.Comment: Project page will be available at https://github.com/taokong/RON, and formal paper will appear in CVPR 201

180nm metal gate, high-k dielectric, implant-free III--V MOSFETs with transconductance of over 425 μS/μm

Abstract: Data is reported from 180 nm gate length GaAs n-MOSFETs with drive current (Ids,sat) of 386 μA/μm (Vg=Vd =1.5 V), extrinsic transconductance (gm) of 426 μS/μm, gate leakage ( jg,limit) of 44 nA/cm2, and on resistance (Ron) of 1640 Ω μm. The gm and Ron metrics are the best values reported to date for III-V MOSFETs, and indicate their potential for scaling to deca-nanometre dimensions

Engaging Students Subtly

Edith Green Professor Ron Mills on the art of teaching

Representations, symbols and embodiment

Response to "Embodied artificial intelligence", a commentary by Ron Chrisley