A Monte Carlo Approach to Closing the Reality Gap

We propose a novel approach to the 'reality gap' problem, i.e., modifying a robot simulation so that its performance becomes more similar to observed real world phenomena. This problem arises whether the simulation is being used by human designers or in an automated policy development mechanism. We expect that the program/policy is developed using simulation, and subsequently deployed on a real system. We further assume that the program includes a monitor procedure with scalar output to determine when it is achieving its performance objectives. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate paired roll-outs to identify points of divergence in behavior. These are used to generate {\it state-space kernels} that coerce the simulation into behaving more like observed reality. The method was evaluated using ROS/Gazebo for simulation and a heavily modified Traaxas platform in outdoor deployment. The results support not just that the kernel approach can force the simulation to behave more like reality, but that the modification is such that an improved control policy tested in the modified simulation also performs better in the real world

The Female Athlete's Heart: Facts and Fallacies.

Purpose of the review For many years, competitive sport has been dominated by men. Recent times have witnessed a significant increase in women participating in elite sports. As most studies investigated male athletes, with few reports on female counterparts, it is crucial to have a better understanding on physiological cardiac adaptation to exercise in female athletes, to distinguish normal phenotypes from potentially fatal cardiac diseases. This review reports on cardiac adaptation to exercise in females. Recent findings Recent studies show that electrical, structural, and functional cardiac changes due to physiological adaptation to exercise differ in male and female athletes. Women tend to exhibit eccentric hypertrophy, and while concentric hypertrophy or concentric remodeling may be a normal finding in male athletes, it should be evaluated carefully in female athletes as it may be a sign of pathology. Although few studies on veteran female athletes are available, women seem to be affected by atrial fibrillation, coronary atherosclerosis, and myocardial fibrosis less than male counterparts. Summary Males and females exhibit many biological, anatomical, and hormonal differences, and cardiac adaptation to exercise is no exception. The increasing participation of women in sports should stimulate the scientific community to develop large, longitudinal studies aimed at a better understanding of cardiac adaptation to exercise in female athletes

International criteria for electrocardiographic interpretation in athletes: Consensus statement.

Sudden cardiac death (SCD) is the leading cause of mortality in athletes during sport. A variety of mostly hereditary, structural or electrical cardiac disorders are associated with SCD in young athletes, the majority of which can be identified or suggested by abnormalities on a resting 12-lead electrocardiogram (ECG). Whether used for diagnostic or screening purposes, physicians responsible for the cardiovascular care of athletes should be knowledgeable and competent in ECG interpretation in athletes. However, in most countries a shortage of physician expertise limits wider application of the ECG in the care of the athlete. A critical need exists for physician education in modern ECG interpretation that distinguishes normal physiological adaptations in athletes from distinctly abnormal findings suggestive of underlying pathology. Since the original 2010 European Society of Cardiology recommendations for ECG interpretation in athletes, ECG standards have evolved quickly, advanced by a growing body of scientific data and investigations that both examine proposed criteria sets and establish new evidence to guide refinements. On 26-27 February 2015, an international group of experts in sports cardiology, inherited cardiac disease, and sports medicine convened in Seattle, Washington (USA), to update contemporary standards for ECG interpretation in athletes. The objective of the meeting was to define and revise ECG interpretation standards based on new and emerging research and to develop a clear guide to the proper evaluation of ECG abnormalities in athletes. This statement represents an international consensus for ECG interpretation in athletes and provides expert opinion-based recommendations linking specific ECG abnormalities and the secondary evaluation for conditions associated with SCD

457 KEYNOTE-495/KeyImPaCT: interim analysis of a randomized, biomarker-directed, phase 2 trial of pembrolizumab-based combination therapy for non–small cell lung cancer (NSCLC)

BackgroundT-cell–inflamed gene expression profile (TcellinfGEP) and tumor mutational burden (TMB) are clinically validated biomarkers that independently predict pembrolizumab response. This study investigated prospective TcellinfGEP and TMB assessment in evaluating first-line pembrolizumab-based combination therapies; the different treatment combinations evaluated may provide insight into the unique biology of each biomarker subgroup.MethodsKEYNOTE-495/KeyImPaCT is a group-sequential, adaptively randomized, multisite, open-label, phase 2 study investigating first-line pembrolizumab plus the VEGF/FGFR inhibitor lenvatinib, CTLA-4 inhibitor quavonlimab (MK-1308), or LAG-3 inhibitor favezelimab (MK-4280) in patients with advanced NSCLC. DNA and RNA were extracted from tumor tissue to determine TcellinfGEP and TMB; patients were assigned to one of four biomarker-defined subgroups (TcellinfGEPlowTMBlow, TcellinfGEPlowTMBhigh, TcellinfGEPhighTMBlow, TcellinfGEPhighTMBhigh) and randomly assigned 1:1:1 to receive pembrolizumab (200mg IV Q3W)+lenvatinib (20mg oral QD), pembrolizumab+quavonlimab (75mg IV Q6W), or pembrolizumab+favezelimab (200mg [n=30] or 800mg [n=34] Q3W; the initial prespecified dose was 200mg but changed to 800mg based on emerging data). The primary end point was investigator-assessed ORR per RECIST v1.1. Multiple interim analyses will be performed until the prespecified clinical signal is observed. The first interim analysis for each combination therapy occurred after ≥10 patients had ≥12 weeks of follow-up.ResultsAt the data cutoff (January 11, 2021), 208 patients were treated (pembrolizumab+lenvatinib, n=72; pembrolizumab+quavonlimab, n=72; pembrolizumab+favezelimab 200mg, n=30; pembrolizumab+favezelimab 800mg, n=34). The overall assay success rate for testing and determining TcellinfGEP and TMB was 94%. In patients treated with pembrolizumab+lenvatinib, pembrolizumab+quavonlimab, or pembrolizumab+favezelimab, ORRs were generally highest in the TcellinfGEPhighTMBhigh subgroup (table 1); response rates were similar across combinations within this subgroup. ORR was low across combinations within the TcellinfGEPlowTMBlow subgroup. Treatment-related adverse events (TRAEs) occurred in 88%, 65%, 57%, and 59% of patients in the pembrolizumab+lenvatinib, pembrolizumab+quavonlimab, pembrolizumab+favezelimab 200mg and pembrolizumab+favezelimab 800mg arms, respectively. Consistent with the known TRAEs of these agents, most TRAEs were grade 1 or 2 in severity except in the pembrolizumab+lenvatinib arm (grade 3–5, 63%). Three deaths from TRAEs occurred (pembrolizumab+lenvatinib [n=2], brain hemorrhage and myocardial infarction; pembrolizumab+favezelimab 800 mg [n=1], pneumonitis).Abstract 457 Table 1Confirmed ORR by Therapy and Biomarker StatusConclusionsThese data demonstrate the feasibility and clinical usefulness of prospective TcellinfGEP and TMB assessment to study the clinical activity of three first-line pembrolizumab-based combination therapies in patients with advanced NSCLC. Although sample sizes were small, the TcellinfGEPhighTMBhigh subgroup demonstrated the best response among the biomarker subgroups for all three combination therapies; further validation is needed to determine additional signals and may be addressed as more mature data become available.AcknowledgementsJeanne Fahey, PhD, of Merck & Co., Inc., Kenilworth, New Jersey, USA, provided critical review of the abstract. Elisha Dettman PhD, Mark Ayers MS, and Andrey Loboda PhD of Merck & Co., Inc., Kenilworth, New Jersey, USA, provided critical review of study translational data. Medical writing and/or editorial assistance was provided by Shane Walton, PhD, and Lei Bai, PhD, of ApotheCom (Yardley, PA, USA). This assistance was funded by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.Trial RegistrationClinicalTrials.gov, NCT03516981Ethics ApprovalThe study protocol and all amendments were approved by the relevant institutional review board or ethics committee at each study site. All patients provided written informed consent to participate in the clinical trial

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

Limits on WWZ and WW\gamma couplings from p\bar{p}\to e\nu jj X events at \sqrt{s} = 1.8 TeV

We present limits on anomalous WWZ and WW-gamma couplings from a search for WW and WZ production in p-bar p collisions at sqrt(s)=1.8 TeV. We use p-bar p -> e-nu jjX events recorded with the D0 detector at the Fermilab Tevatron Collider during the 1992-1995 run. The data sample corresponds to an integrated luminosity of 96.0+-5.1 pb^(-1). Assuming identical WWZ and WW-gamma coupling parameters, the 95% CL limits on the CP-conserving couplings are -0.33<lambda<0.36 (Delta-kappa=0) and -0.43<Delta-kappa<0.59 (lambda=0), for a form factor scale Lambda = 2.0 TeV. Limits based on other assumptions are also presented.Comment: 11 pages, 2 figures, 2 table

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

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

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