Evidence map›Paper›PMID 37110185›Full record

ArticleMetabolites2023

Longitudinal Evaluation Using Preclinical 7T-Magnetic Resonance Imaging/Spectroscopy on Prenatally Dose-Dependent Alcohol-Exposed Rats.

Tensei Nakano, Tomohiro Natsuyama, Naoki Tsuji, Nanami Katayama, Junpei Ueda, Shigeyoshi Saito

Abstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

6 authors.

Tensei NakanoDepartment of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 560-0871, Japan.
Tomohiro NatsuyamaCourse of Medical Physics and Engineering, School of Allied Health Sciences, Osaka University, Osaka 565-0871, Japan.
Naoki TsujiCourse of Medical Physics and Engineering, School of Allied Health Sciences, Osaka University, Osaka 565-0871, Japan.
Nanami KatayamaCourse of Medical Physics and Engineering, School of Allied Health Sciences, Osaka University, Osaka 565-0871, Japan.
Junpei UedaDepartment of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 560-0871, Japan.
Shigeyoshi SaitoDepartment of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka 560-0871, Japan.ORCID 0000-0002-5100-9561

Funding

Ministry of Education, Culture, Sports, Science and Technology JPMXS0450400022
6 · The paper itself

Abstract

Prenatal alcohol exposure causes many detrimental alcohol-induced defects in children, collectively known as fetal alcohol spectrum disorders (FASD). This study aimed to evaluate a rat model of FASD, in which alcohol was administered at progressively increasing doses during late pregnancy, using preclinical magnetic resonance (MR) imaging (MRI) and MR spectroscopy (MRS). Wistar rats were orally administered 2.5 mL/day of ethanol (25% concentration) on gestational day 15, and postnatal fetuses were used as FASD models. Four groups were used: a control group (non-treatment group) and three groups of FASD model rats that received one, two, or four doses of ethanol, respectively, during the embryonic period. Body weight was measured every other week until eight weeks of age. MRI and MRS were performed at 4 and 8 weeks of age. The volume of each brain region was measured using acquired T

Indexed as

fetal alcohol spectrum disorderpreclinical 7T-MRI/MRSprenatally alcohol-exposed

Identifiers

PMID37110185
PMCPMC10142287

What OpenQuestion holds

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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.