Evidence map›Paper›PMID 33309017›Full record

ArticleBiological psychiatry2021

Computational Analysis of Multidimensional Behavioral Alterations After Chronic Social Defeat Stress.

Zachary S Lorsch, Alberto Ambesi-Impiombato, Rebecca Zenowich, Irene Morganstern, Emer Leahy, Mukesh Bansal, Eric J Nestler, Taleen Hanania

Open access · greenAbstract read
In one paragraph

Article in Biological psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Characterization of a novel female chronic social defeat stress (femCSDS) model utilizing persistently aggressive CD1 parous females.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Advancing preclinical chronic stress models to promote therapeutic discovery for human stress disorders.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  8. Article
  9. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Zachary S LorschNash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Alberto Ambesi-ImpiombatoPsychoGenics Inc., Paramus, New Jersey.
Rebecca ZenowichPsychoGenics Inc., Paramus, New Jersey.
Irene MorgansternPsychoGenics Inc., Paramus, New Jersey.
Emer LeahyPsychoGenics Inc., Paramus, New Jersey.
Mukesh BansalPsychoGenics Inc., Paramus, New Jersey.
Eric J NestlerNash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York. Electronic address: eric.nestler@mssm.edu.
Taleen HananiaPsychoGenics Inc., Paramus, New Jersey. Electronic address: taleen.hanania@psychogenics.com.
Psychogenics (United States) · USAllen Institute for Brain Science · US

Funding

MOUNT SINAI MEDICAL SCIENTIST TRAINING PROGRAMT32GM007280 · NIGMS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI BARON, MARGARET H · 1985 to 2021
$22.8M
REPRESSIVE HISTONE AND DNA METHYLATION IN RODENT DEPRESSION MODELSP50MH096890 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI NESTLER, ERIC J. · 2012 to 2021
$20.2M
Using neuroeconomics to disentangle the transcriptional mechanisms underlying resilience versus susceptibility to stressR01MH051399 · NIMH · YALE UNIVERSITY · PI NESTLER, ERIC J. · 1994 to 2023
$10.2M
Training Program in Mental Health ResearchT32MH096678 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SALTON, STEPHEN R, SHAPIRO, MATTHEW L · 2012 to 2016
$1.1M
Transcriptional networks of resilience in a mouse model of depressionF30MH110073 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI LORSCH, ZACHARY SPENCER · 2016 to 2018
$125k
NIGMS NIH HHS T32 GM007280NIMH NIH HHS F30 MH110073NIMH NIH HHS P50 MH096890NIMH NIH HHS R01 MH051399NIMH NIH HHS T32 MH096678
6 · The paper itself

Abstract

backgroundThe study of depression in humans depends on animal models that attempt to mimic specific features of the human syndrome. Most studies focus on one or a few behavioral domains, with time and practical considerations prohibiting a comprehensive evaluation. Although machine learning has enabled unbiased analysis of behavior in animals, this has not yet been applied to animal models of psychiatric disease.

methodsWe performed chronic social defeat stress (CSDS) in mice and evaluated behavior with PsychoGenics' SmartCube, a high-throughput unbiased automated phenotyping platform that collects >2000 behavioral features based on machine learning. We evaluated group differences at several times post-CSDS and after administration of the antidepressant medication imipramine.

resultsSmartCube analysis after CSDS successfully separated control and defeated-susceptible mice, and defeated-resilient mice more resembled control mice. We observed a potentiation of CSDS effects over time. Treatment of susceptible mice with imipramine induced a 40.2% recovery of the defeated-susceptible phenotype as assessed by SmartCube.

conclusionsHigh-throughput analysis can simultaneously evaluate multiple behavioral alterations in an animal model for the study of depression, which provides a more unbiased and holistic approach to evaluating group differences after CSDS and perhaps can be applied to other mouse models of psychiatric disease.

Indexed as

Behavior, AnimalStress, PsychologicalAnimalsDisease Models, AnimalMiceMice, Inbred C57BLSocial BehaviorSocial DefeatAntidepressantsBehaviorBioinformaticsChronic social defeat stressDepressionTranslational models

Identifiers

PMID33309017
PMCPMC8052271
OpenAlexW3094584865

What OpenQuestion holds

Textmetadata
LicenceTDM
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.