Cell Cycle Phase Regulates Glucocorticoid Receptor Function

The glucocorticoid receptor (GR) is a member of the nuclear hormone receptor superfamily of ligand-activated transcription factors. In contrast to many other nuclear receptors, GR is thought to be exclusively cytoplasmic in quiescent cells, and only translocate to the nucleus on ligand binding. We now demonstrate significant nuclear GR in the absence of ligand, which requires nuclear localisation signal 1 (NLS1). Live cell imaging reveals dramatic GR import into the nucleus through interphase and rapid exclusion of the GR from the nucleus at the onset of mitosis, which persists into early G1. This suggests that the heterogeneity in GR distribution is reflective of cell cycle phase

Single-layer graphene modulates neuronal communication and augments membrane ion currents

The use of graphenebased materials to engineer sophisticated biosensing interfaces that can adapt to the central nervous system requires a detailed understanding of how such materials behave in a biological context. Graphene's peculiar properties can cause various cellular changes, but the underlying mechanisms remain unclear. Here, we show that singlelayer graphene increases neuronal firing by altering membraneassociated functions in cultured cells. Graphene tunes the distribution of extracellular ions at the interface with neurons, a key regulator of neuronal excitability. The resulting biophysical changes in the membrane include stronger potassium ion currents, with a shift in the fraction of neuronal firing phenotypes from adapting to tonically firing. By using experimental and theoretical approaches, we hypothesize that the graphene\u2013ion interactions that are maximized when singlelayer graphene is deposited on electrically insulating substrates are crucial to these effects

Rates of Influenza and Pneumococcal Vaccination and Correlation With Survival in Multiple Myeloma Patients

Background Infections are a common reason for hospitalization and death in multiple myeloma (MM). Although pneumococcal vaccination (PV) and influenza vaccination (FV) are recommended for MM patients, data on vaccination status and outcomes are limited in MM. Materials and Methods We utilized data from the global, prospective, observational INSIGHT MM study to analyze FV and PV rates and associated outcomes of patients with MM enrolled 2016-2019. Results Of the 4307 patients enrolled, 2543 and 2500 had study-entry data on FV and PV status. Overall vaccination rates were low (FV 39.6%, PV 30.2%) and varied by region. On separate multivariable analyses of overall survival (OS) by Cox model, FV in the prior 2 years and PV in the prior 5 years impacted OS (vs. no vaccination; FV: HR, 0.73; 95% CI, 0.60-0.90; P = .003; PV: HR, 0.51; 95% CI, 0.42-0.63; P < .0001) when adjusted for age, region, performance status, disease stage, cytogenetics at diagnosis, MM symptoms, disease status, time since diagnosis, and prior transplant. Proportions of deaths due to infections were lower among vaccinated versus non-vaccinated patients (FV: 9.8% vs. 15.3%, P = .142; PV: 9.9% vs. 18.0%, P = .032). Patients with FV had generally lower health resource utilization (HRU) versus patients without FV; patients with PV had higher or similar HRU versus patients without PV. Conclusion Vaccination is important in MM and should be encouraged. Vaccination status should be recorded in prospective clinical trials as it may affect survival. This trial was registered at www.clinicaltrials.gov as #NCT02761187

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard