Evidence map›Paper›PMID 35815018›Full record

ReviewFrontiers in psychiatry2022

A Role for Data Science in Precision Nutrition and Early Brain Development.

Sarah U Morton, Brian J Leyshon, Eleonora Tamilia, Rutvi Vyas, Michaela Sisitsky, Imran Ladha, John B Lasekan, Matthew J Kuchan, P Ellen Grant, Yangming Ou

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. 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

10 authors at 2 institutions in 1 country.

Sarah U MortonDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Brian J LeyshonAbbott, Columbus, OH, United States.
Eleonora TamiliaDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Rutvi VyasDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Michaela SisitskyDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Imran LadhaDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
John B LasekanAbbott, Columbus, OH, United States.
Matthew J KuchanAbbott, Columbus, OH, United States.
P Ellen GrantDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Yangming OuDivision of Newborn Medicine, Boston Children's Hospital, Boston, MA, United States.
Boston Children's Hospital · USAbbott (United States) · US

Funding

Genetic Analysis and Manipulation Core (GAEC)P50HD105351 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI Hisashi Umemori · 2021 to 2026
$9.4M
Multi-site Data for Nutrition Studies in Healthy Early ChildhoodR03HD107124 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI OU, YANGMING · 2022 to 2023
$177k
NICHD NIH HHS P50 HD105351NICHD NIH HHS R03 HD107124
6 · The paper itself

Abstract

Multimodal brain magnetic resonance imaging (MRI) can provide biomarkers of early influences on neurodevelopment such as nutrition, environmental and genetic factors. As the exposure to early influences can be separated from neurodevelopmental outcomes by many months or years, MRI markers can serve as an important intermediate outcome in multivariate analyses of neurodevelopmental determinants. Key to the success of such work are recent advances in data science as well as the growth of relevant data resources. Multimodal MRI assessment of neurodevelopment can be supplemented with other biomarkers of neurodevelopment such as electroencephalograms, magnetoencephalogram, and non-imaging biomarkers. This review focuses on how maternal nutrition impacts infant brain development, with three purposes: (1) to summarize the current knowledge about how nutrition in stages of pregnancy and breastfeeding impact infant brain development; (2) to discuss multimodal MRI and other measures of early neurodevelopment; and (3) to discuss potential opportunities for data science and artificial intelligence to advance precision nutrition. We hope this review can facilitate the collaborative march toward precision nutrition during pregnancy and the first year of life.

Indexed as

brain developmentdata sciencemagnetic resonance imageneonatenutrition

Identifiers

PMID35815018
PMCPMC9259898
OpenAlexW4283312776

What Socratic holds

Textmetadata
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 Socratic graph.