Evidence map›Paper›PMID 27544423›Full record

ReviewBrain research2017

Cell-based therapies for the treatment of schizophrenia.

Jennifer J Donegan, Daniel J Lodge

Abstract readReview
In one paragraph

Review in Brain research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Hippocampal α5-GABABiological psychiatry global open science · 2023
    Article
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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

2 authors at 1 institution in 1 country.

Jennifer J DoneganDepartment of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX 78229, USA. Electronic address: Noy@uthscsa.edu.
Daniel J LodgeDepartment of Pharmacology and Center for Biomedical Neuroscience, University of Texas Health Science Center, San Antonio, TX 78229, USA.
The University of Texas Health Science Center at San Antonio · US

Funding

Regulation of ventral hippocampal system functionR01MH090067 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI LODGE, DANIEL · 2010 to 2019
$3.5M
NIMH NIH HHS R01 MH090067
6 · The paper itself

Abstract

Schizophrenia is a devastating psychiatric disorder characterized by positive, negative and cognitive symptoms. While aberrant dopamine system function is typically associated with the positive symptoms of the disease, it is thought that this is secondary to pathology in afferent regions. Indeed, schizophrenia patients show dysregulated activity in the hippocampus and prefrontal cortex, two regions known to regulate dopamine neuron activity. These deficits in hippocampal and prefrontal cortical function are thought to result, in part, from reductions in inhibitory interneuron function in these brain regions. Therefore, it has been hypothesized that restoring interneuron function in the hippocampus and/or prefrontal cortex may be an effective treatment strategy for schizophrenia. In this article, we will discuss the evidence for interneuron pathology in schizophrenia and review recent advances in our understanding of interneuron development. Finally, we will explore how these advances have allowed us to test the therapeutic value of interneuron transplants in multiple preclinical models of schizophrenia. This article is part of a Special Issue entitled SI:StemsCellsinPsychiatry.

Indexed as

Cell TransplantationAnimalsBrainHumansInterneuronsSchizophreniaDopamineInterneuronsPrefrontal cortexSchizophreniaStem cellsVentral hippocampus

Identifiers

PMID27544423
PMCPMC5474910
OpenAlexW2517217264

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.