Evidence map›Paper›PMID 31495451›Full record

ReviewTrends in neurosciences2019

Intergenerational Metabolic Syndrome and Neuronal Network Hyperexcitability in Autism.

Aileen Rivell, Mark P Mattson

Open access · greenAbstract readReview
In one paragraph

Review in Trends in neurosciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

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  20. Development of prefrontal cortex.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022
    Review
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.

Aileen RivellLaboratory of Neurosciences, National Institute on Aging Intramural Research Program, Baltimore, MD, USA.
Mark P MattsonLaboratory of Neurosciences, National Institute on Aging Intramural Research Program, Baltimore, MD, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: mmattso2@jhmi.edu.
National Institute on Aging · US

Funding

Dietary Modification Of Brain Aging And Neurodegenerative DisordersZIAAG000315 · NIA · NATIONAL INSTITUTE ON AGING · PI MATTSON, MARK · 2009 to 2018
$5.0M
Intramural NIH HHS ZIA AG000315
6 · The paper itself

Abstract

We review evidence that suggests a role for excessive consumption of energy-dense foods, particularly fructose, and consequent obesity and insulin resistance (metabolic syndrome) in the recent increase in prevalence of autism spectrum disorders (ASD). Maternal insulin resistance, obesity, and diabetes may predispose offspring to ASD by mechanisms involving chronic activation of anabolic cellular pathways and a lack of metabolic switching to ketosis resulting in a deficit in GABAergic signaling and neuronal network hyperexcitability. Metabolic reprogramming by epigenetic DNA and chromatin modifications may contribute to alterations in gene expression that result in ASD. These mechanistic insights suggest that interventions that improve metabolic health such as intermittent fasting and exercise may ameliorate developmental neuronal network abnormalities and consequent behavioral manifestations in ASD.

Indexed as

AnimalsAutistic DisorderBrainEnergy MetabolismEpigenesis, GeneticHumansNerve NetNeuronsacetylomeautism spectrum disorderdiabetesGABAhigh fructose corn syrupketone bodiesmTORobesitysociality

Identifiers

PMID31495451
PMCPMC6779523
OpenAlexW2972003441

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.