Soft swimming: Exploiting deformable interfaces for low-Reynolds number locomotion

Reciprocal movement cannot be used for locomotion at low-Reynolds number in an infinite fluid or near a rigid surface. Here we show that this limitation is relaxed for a body performing reciprocal motions near a deformable interface. Using physical arguments and scaling relationships, we show that the nonlinearities arising from reciprocal flow-induced interfacial deformation rectify the periodic motion of the swimmer, leading to locomotion. Such a strategy can be used to move toward, away from, and parallel to any deformable interface as long as the length scales involved are smaller than intrinsic scales, which we identify. A macro-scale experiment of flapping motion near a free surface illustrates this new result

Chronic Ultraviolet Radiation Exposure Does Not Effect Nitric Oxide-Mediated Vasodilation in the Cutaneous Microvasculature

poste

Core Temperature Responses to Compensable vs. Uncompensable Heat Stress in Young Adults (PSU Heat Project)

poste

SkyMapper Southern Survey: First Data Release (DR1)

We present the first data release (DR1) of the SkyMapper Southern Survey, a hemispheric survey carried out with the SkyMapper Telescope at Siding Spring Observatory in Australia. Here, we present the survey strategy, data processing, catalogue construction and database schema. The DR1 dataset includes over 66,000 images from the Shallow Survey component, covering an area of 17,200 deg$^2$ in all six SkyMapper passbands $uvgriz$, while the full area covered by any passband exceeds 20,000 deg$^2$. The catalogues contain over 285 million unique astrophysical objects, complete to roughly 18 mag in all bands. We compare our $griz$ point-source photometry with PanSTARRS1 DR1 and note an RMS scatter of 2%. The internal reproducibility of SkyMapper photometry is on the order of 1%. Astrometric precision is better than 0.2 arcsec based on comparison with Gaia DR1. We describe the end-user database, through which data are presented to the world community, and provide some illustrative science queries.Comment: 31 pages, 19 figures, 10 tables, PASA, accepte

The ecology of exercise: mechanisms underlying Individual variation in behavior, activity, and performance: an introduction to symposium

Wild animals often engage in intense physical activity while performing tasks vital for their survival and reproduction associated with foraging, avoiding predators, fighting, providing parental care, and migrating. In this theme issue we consider how viewing these tasks as “exercise”—analogous to that performed by human athletes—may help provide insight into the mechanisms underlying individual variation in these types of behaviors and the importance of physical activity in an ecological context. In this article and throughout this issue, we focus on four key questions relevant to the study of behavioral ecology that may be addressed by studying wild animal behavior from the perspective of exercise physiology: (1) How hard do individual animals work in response to ecological (or evolutionary) demands?; (2) Do lab-based studies of activity provide good models for understanding activity in free-living animals and individual variation in traits?; (3) Can animals work too hard during “routine” activities?; and (4) Can paradigms of “exercise” and “training” be applied to free-living animals? Attempts to address these issues are currently being facilitated by rapid technological developments associated with physiological measurements and the remote tracking of wild animals, to provide mechanistic insights into the behavior of free-ranging animals at spatial and temporal scales that were previously impossible. We further suggest that viewing the behaviors of non-human animals in terms of the physical exercise performed will allow us to fully take advantage of these technological advances, draw from knowledge and conceptual frameworks already in use by human exercise physiologists, and identify key traits that constrain performance and generate variation in performance among individuals. It is our hope that, by highlighting mechanisms of behavior and performance, the articles in this issue will spur on further synergies between physiologists and ecologists, to take advantage of emerging cross-disciplinary perspectives and technologies

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment