Evidence map›Paper›PMID 38116240›Full record

ArticleAdvances in drug and alcohol research2023

miR-9 utilizes precursor pathways in adaptation to alcohol in mouse striatal neurons.

Edward Andrew Mead, Yongping Wang, Sunali Patel, Austin P Thekkumthala, Rebecca Kepich, Elizabeth Benn-Hirsch, Victoria Lee, Azra Basaly, Susan Bergeson, Hava T Siegelmann and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Advances in drug and alcohol research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Edward Andrew MeadLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Yongping WangLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Sunali PatelThermo Fisher Scientific Inc., Austin, TX, United States.
Austin P ThekkumthalaLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Rebecca KepichLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Elizabeth Benn-HirschLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Victoria LeeLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Azra BasalyLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Susan BergesonDepartment of Cell Biology and Biochemistry, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, United States.
Hava T SiegelmannDepartment of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates.
Andrzej Zbigniew PietrzykowskiLaboratory of Adaptation, Reward and Addiction, Department of Animal Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States.
Rutgers, The State University of New Jersey · USDynamic Systems (United States) · USTexas Tech University · USThermo Fisher Scientific (United States) · US

Funding

miRNA Regulation of Gene Expression in Alcohol Tolerance and WithdrawalR01AA017920 · NIAAA · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI PIETRZYKOWSKI, ANDRZEJ ZBIGNIEW, TREISTMAN, STEVEN N · 2009 to 2013
$2.0M
NIAAA NIH HHS R01 AA017920
6 · The paper itself

Abstract

microRNA-9 (miR-9) is one of the most abundant microRNAs in the mammalian brain, essential for its development and normal function. In neurons, it regulates the expression of several key molecules, ranging from ion channels to enzymes, to transcription factors broadly affecting the expression of many genes. The neuronal effects of alcohol, one of the most abused drugs in the world, seem to be at least partially dependent on regulating the expression of miR-9. We previously observed that molecular mechanisms of the development of alcohol tolerance are miR-9 dependent. Since a critical feature of alcohol action is temporal exposure to the drug, we decided to better understand the time dependence of alcohol regulation of miR-9 biogenesis and expression. We measured the effect of intoxicating concentration of alcohol (20 mM ethanol) on the expression of all major elements of miR-9 biogenesis: three pri-precursors (pri-mir-9-1, pri-mir-9-2, pri-mir-9-3), three pre-precursors (pre-mir-9-1, pre-mir-9-2, pre-mir-9-3), and two mature microRNAs: miR-9-5p and miR-9-3p, using digital PCR and RT-qPCR, and murine primary medium spiny neurons (MSN) cultures. We subjected the neurons to alcohol based on an exposure/withdrawal matrix of different exposure times (from 15 min to 24 h) followed by different withdrawal times (from 0 h to 24 h). We observed that a short exposure increased mature miR-9-5p expression, which was followed by a gradual decrease and subsequent increase of the expression, returning to pre-exposure levels within 24 h. Temporal changes of miR-9-3p expression were complementing miR-9-5p changes. Interestingly, an extended, continuous presence of the drug caused a similar pattern. These results suggest the presence of the adaptive mechanisms of miR-9 expression in the presence and absence of alcohol. Measurement of miR-9 pre- and pri-precursors showed further that the primary effect of alcohol on miR-9 is through the mir-9-2 precursor pathway with a smaller contribution of mir-9-1 and mir-9-3 precursors. Our results provide new insight into the adaptive mechanisms of neurons to alcohol exposure. It would be of interest to determine next which microRNA-based mechanisms are involved in a transition from the acute, intoxicating effects of alcohol to the chronic, addictive effects of the drug.

Indexed as

addictionalcohol adaptationdigital PCRmedium spiny neuronsmicroRNA miR-9

Identifiers

PMID38116240
PMCPMC10730111
OpenAlexW4379512076

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.