108 research outputs found

    Nicotinic α7 acetylcholine receptor-mediated currents are not modulated by the tryptophan metabolite kynurenic acid in adult hippocampal interneurons

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    The  tryptophan  metabolite,  kynurenic  acid (KYNA),  is  classically  known  to  be  an antagonist  of ionotropic glutamate receptors. Within the last decade several reports have been published suggesting that KYNA also blocks nicotinic acetylcholine receptors (nAChRs) containing the α7 subunit (α7*). Most of these reports involve either indirect measurements of KYNA effects on α7 nAChR function, or are reports of KYNA effects in complicated in vivo systems.  However, a recent report investigating KYNA interactions with α7 nAChRs failed to detect an interaction using direct measurements of α7 nAChRs function.  Further, it showed that a KYNA blockade of α7 nAChR stimulated GABA release (an indirect measure of α7 nAChR function) was not due to KYNA blockade of the α7 nAChRs. The current study measured the direct effects of KYNA on α7-containing nAChRs expressed on interneurons in the hilar and CA1 stratum radiatum regions of the mouse hippocampus and on interneurons in the CA1 region of the rat hippocampus.  Here we show that KYNA does not block α7* nACHRs using direct patch-­clamp recording of α7 currents in adult brain slices

    Can in vitro studies aid in the development and use of antiseizure therapies? A report of the ILAE/AES Joint Translational Task Force

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    In vitro preparations (defined here as cultured cells, brain slices, and isolated whole brains) offer a variety of approaches to modeling various aspects of seizures and epilepsy. Such models are particularly amenable to the application of anti-seizure compounds, and consequently are a valuable tool to screen the mechanisms of epileptiform activity, mode of action of known anti-seizure medications (ASMs), and the potential efficacy of putative new anti-seizure compounds. Despite these applications, all disease models are a simplification of reality and are therefore subject to limitations. In this review, we summarize the main types of in vitro models that can be used in epilepsy research, describing key methodologies as well as notable advantages and disadvantages of each. We argue that a well-designed battery of in vitro models can form an effective and potentially high-throughput screening platform to predict the clinical usefulness of ASMs, and that in vitro models are particularly useful for interrogating mechanisms of ASMs. To conclude, we offer several key recommendations that maximize the potential value of in vitro models in ASM screening. This includes the use of multiple in vitro tests that can complement each other, carefully combined with in vivo studies, the use of tissues from chronically epileptic (rather than naĂŻve wild-type) animals, and the integration of human cell/tissue-derived preparations

    The Evolutionarily-conserved Polyadenosine RNA Binding Protein, Nab2, Cooperates with Splicing Machinery to Regulate the Fate of pre-mRNA

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    Numerous RNA binding proteins are deposited onto an mRNA transcript to modulate post-transcriptional processing events ensuring proper mRNA maturation. Defining the interplay between RNA binding proteins that couple mRNA biogenesis events is crucial for understanding how gene expression is regulated. To explore how RNA binding proteins control mRNA processing, we investigated a role for the evolutionarily conserved polyadenosine RNA binding protein, Nab2, in mRNA maturation within the nucleus. This work reveals that nab2 mutant cells accumulate intron-containing pre-mRNA in vivo. We extend this analysis to identify genetic interactions between mutant alleles of nab2 and genes encoding the splicing factor, MUD2, and the RNA exosome, RRP6, with in vivo consequences of altered pre-mRNA splicing and poly(A) tail length control. As further evidence linking Nab2 proteins to splicing, an unbiased proteomic analysis of vertebrate Nab2, ZC3H14, identifies physical interactions with numerous components of the spliceosome. We validated the interaction between ZC3H14 and U2AF2/U2AF^(65). Taking all the findings into consideration, we present a model where Nab2/ZC3H14 interacts with spliceosome components to allow proper coupling of splicing with subsequent mRNA processing steps contributing to a kinetic proofreading step that allows properly processed mRNA to exit the nucleus and escape Rrp6-dependent degradation

    The daily association between affect and alcohol use: a meta-analysis of individual participant data

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    Influential psychological theories hypothesize that people consume alcohol in response to the experience of both negative and positive emotions. Despite two decades of daily diary and ecological momentary assessment research, it remains unclear whether people consume more alcohol on days they experience higher negative and positive affect in everyday life. In this preregistered meta-analysis, we synthesized the evidence for these daily associations between affect and alcohol use. We included individual participant data from 69 studies (N = 12,394), which used daily and momentary surveys to assess affect and the number of alcoholic drinks consumed. Results indicate that people are not more likely to drink on days they experience high negative affect, but are more likely to drink and drink heavily on days high in positive affect. People self-reporting a motivational tendency to drink-to-cope and drink-to-enhance consumed more alcohol, but not on days they experienced higher negative and positive affect. Results were robust across different operationalizations of affect, study designs, study populations, and individual characteristics. These findings challenge the long-held belief that people drink more alcohol following increases in negative affect. Integrating these findings under different theoretical models and limitations of this field of research, we collectively propose an agenda for future research to explore open questions surrounding affect and alcohol use.The present study was funded by the Canadian Institutes of Health Research Grant MOP-115104 (Roisin M. O’Connor), Canadian Institutes of Health Research Grant MSH-122803 (Roisin M. O’Connor), John A. Hartford Foundation Grant (Paul Sacco), Loyola University Chicago Research Support Grant (Tracy De Hart), National Institute for Occupational Safety and Health Grant T03OH008435 (Cynthia Mohr), National Institutes of Health (NIH) Grant F31AA023447 (Ryan W. Carpenter), NIH Grant R01AA025936 (Kasey G. Creswell), NIH Grant R01AA025969 (Catharine E. Fairbairn), NIH Grant R21AA024156 (Anne M. Fairlie), NIH Grant F31AA024372 (Fallon Goodman), NIH Grant R01DA047247 (Kevin M. King), NIH Grant K01AA026854 (Ashley N. Linden-Carmichael), NIH Grant K01AA022938 (Jennifer E. Merrill), NIH Grant K23AA024808 (Hayley Treloar Padovano), NIH Grant P60AA11998 (Timothy Trull), NIH Grant MH69472 (Timothy Trull), NIH Grant K01DA035153 (Nisha Gottfredson), NIH Grant P50DA039838 (Ashley N. Linden-Carmichael), NIH Grant K01DA047417 (David M. Lydon-Staley), NIH Grant T32DA037183 (M. Kushner), NIH Grant R21DA038163 (A. Moore), NIH Grant K12DA000167 (M. Potenza, Stephanie S. O’Malley), NIH Grant R01AA025451 (Bruce Bartholow, Thomas M. Piasecki), NIH Grant P50AA03510 (V. Hesselbrock), NIH Grant K01AA13938 (Kristina M. Jackson), NIH Grant K02AA028832 (Kevin M. King), NIH Grant T32AA007455 (M. Larimer), NIH Grant R01AA025037 (Christine M. Lee, M. Patrick), NIH Grant R01AA025611 (Melissa Lewis), NIH Grant R01AA007850 (Robert Miranda), NIH Grant R21AA017273 (Robert Miranda), NIH Grant R03AA014598 (Cynthia Mohr), NIH Grant R29AA09917 (Cynthia Mohr), NIH Grant T32AA07290 (Cynthia Mohr), NIH Grant P01AA019072 (P. Monti), NIH Grant R01AA015553 (J. Morgenstern), NIH Grant R01AA020077 (J. Morgenstern), NIH Grant R21AA017135 (J. Morgenstern), NIH Grant R01AA016621 (Stephanie S. O’Malley), NIH Grant K99AA029459 (Marilyn Piccirillo), NIH Grant F31AA022227 (Nichole Scaglione), NIH Grant R21AA018336 (Katie Witkiewitz), Portuguese State Budget Foundation for Science and Technology Grant UIDB/PSI/01662/2020 (Teresa Freire), University of Washington Population Health COVID-19 Rapid Response Grant (J. Kanter, Adam M. Kuczynski), U.S. Department of Defense Grant W81XWH-13-2-0020 (Cynthia Mohr), SANPSY Laboratory Core Support Grant CNRS USR 3413 (Marc Auriacombe), Social Sciences and Humanities Research Council of Canada Grant (N. Galambos), and Social Sciences and Humanities Research Council of Canada Grant (Andrea L. Howard)

    THE NEEDLE in the 100 deg<sup>2</sup> HAYSTACK: UNCOVERING AFTERGLOWS of FERMI GRB<inf>s</inf> with the PALOMAR TRANSIENT FACTORY

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    The Fermi Gamma-ray Space Telescope has greatly expanded the number and energy window of observations of gamma-ray bursts (GRBs). However, the coarse localizations of tens to a hundred square degrees provided by the Fermi GRB Monitor instrument have posed a formidable obstacle to locating the bursts' host galaxies, measuring their redshifts, and tracking their panchromatic afterglows. We have built a target-of-opportunity mode for the intermediate Palomar Transient Factory in order to perform targeted searches for Fermi afterglows. Here, we present the results of one year of this program: 8 afterglow discoveries out of 35 searches. Two of the bursts with detected afterglows (GRBs 130702A and 140606B) were at low redshift (z = 0.145 and 0.384, respectively) and had spectroscopically confirmed broad-line Type Ic supernovae. We present our broadband follow-up including spectroscopy as well as X-ray, UV, optical, millimeter, and radio observations. We study possible selection effects in the context of the total Fermi and Swift GRB samples. We identify one new outlier on the Amati relation. We find that two bursts are consistent with a mildly relativistic shock breaking out from the progenitor star rather than the ultra-relativistic internal shock mechanism that powers standard cosmological bursts. Finally, in the context of the Zwicky Transient Facility, we discuss how we will continue to expand this effort to find optical counterparts of binary neutron star mergers that may soon be detected by Advanced LIGO and Virgo. © 2015. The American Astronomical Society. All rights reserved
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