Comparison between Local Ensemble Transform Kalman Filter and PSAS in the NASA finite volume GCM: perfect model experiments

This paper explores the potential of Local Ensemble Transform Kalman Filter (LETKF) by comparing the performance of LETKF with an operational 3D-Var assimilation system, Physical-Space Statistical Analysis System (PSAS), under a perfect model scenario. The comparison is carried out on the finite volume Global Circulation Model (fvGCM) with 72 grid points zonally, 46 grid points meridionally and 55 vertical levels. With only forty ensemble members, LETKF obtains an analysis and forecasts with lower RMS errors than those from PSAS. The performance of LETKF is further improved, especially over the oceans, by assimilating simulated temperature observations from rawinsondes and conventional surface pressure observations instead of geopotential heights. An initial decrease of the forecast errors in the NH observed in PSAS but not in LETKF suggests that the PSAS analysis is less balanced. The observed advantage of LETKF over PSAS is due to the ability of the forty-member ensemble from LETKF to capture flow-dependent errors and thus create a good estimate of the true background uncertainty. Furthermore, localization makes LETKF highly parallel and efficient, requiring only 5 minutes per analysis in a cluster of 20 PCs with forty ensemble members.Comment: 50 pages, 11 figure

Loss of Trop2 causes ErbB3 activation through a neuregulin-1-dependent mechanism in the mesenchymal subtype of HNSCC

In head and neck squamous cell cancer (HNSCC), four intrinsic subtypes (or groups) have been identified, and each one possesses a unique biology that will require specific treatment strategies. We previously reported that mesenchymal (group 2) tumors exhibit reduced levels of Trop2 expression. In this study, we investigated the functional role of Trop2 in HNSCC and find that loss results in autocrine activation of the EGFR family member ErbB3 via neuregulin-1. Trop2 localizes to both the cell surface and cytosol of HNSCC cells and forms a complex with neuregulin-1, which is predominantly cytosolic. Inactivation of Trop2 increases the concentration of neuregulin-1 at the cell surface where it is cleaved to activate ErbB3. In primary HNSCC, detection of ErbB3 activation was limited to Trop2 negative tumors. An analysis of the Cancer Genome Atlas (TCGA) HNSCC dataset confirms enrichment for ErbB3 activity in mesenchymal tumors. Notably, Trop2 loss triggers sensitivity to anti-ErbB3 antibodies, which results in reduced proliferation and tumorigenic growth of Trop2 negative HNSCC cancer cells. These results uncover a molecular mechanism by which tumor cells control the amount of cell-surface neuregulin-1 available for cleavage and ErbB3 activation. Moreover, we demonstrate that Trop2 is a potential surrogate biomarker to identify tumors with ErbB3 activation and may therefore respond to anti-ErbB3 therapeutics

Measures of outcome for stimulant trials: ACTTION recommendations and research agenda

BACKGROUND: The development and approval of an efficacious pharmacotherapy for stimulant use disorders has been limited by the lack of a meaningful indicator of treatment success, other than sustained abstinence. METHODS: In March, 2015, a meeting sponsored by Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) was convened to discuss the current state of the evidence regarding meaningful outcome measures in clinical trials for stimulant use disorders. Attendees included members of academia, funding and regulatory agencies, pharmaceutical companies, and healthcare organizations. The goal was to establish a research agenda for the development of a meaningful outcome measure that may be used as an endpoint in clinical trials for stimulant use disorders. RESULTS AND CONCLUSIONS: Based on guidelines for the selection of clinical trial endpoints, the lessons learned from prior addiction clinical trials, and the process that led to identification of a meaningful indicator of treatment success for alcohol use disorders, several recommendations for future research were generated. These include a focus on the validation of patient reported outcome measures of functioning, the exploration of patterns of stimulant abstinence that may be associated with physical and/or psychosocial benefits, the role of urine testing for validating self-reported measures of stimulant abstinence, and the operational definitions for reduction-based measures in terms of frequency rather than quantity of stimulant use. These recommendations may be useful for secondary analyses of clinical trial data, and in the design of future clinical trials that may help establish a meaningful indicator of treatment success