Evidence map›Paper›PMID 33668810›Full record

ReviewGenes2021

Quantifying Fetal Reprogramming for Biomarker Development in the Era of High-Throughput Sequencing.

Fu-Sheng Chou, Krystel Newton, Pei-Shan Wang

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Fu-Sheng ChouDivision of Neonatology, Department of Pediatrics, Loma Linda University School of Medicine, Loma Linda, CA 92350, USA.ORCID 0000-0002-5770-0580
Krystel NewtonDivision of Neonatology, Department of Pediatrics, Loma Linda University School of Medicine, Loma Linda, CA 92350, USA.
Pei-Shan WangPXT Research & Data Analytics, LLC, Rancho Cucamonga, CA 91739, USA.
Loma Linda University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gestational hypertensive disorders continue to threaten the well-being of pregnant women and their offspring. The only current definitive treatment for gestational hypertensive disorders is delivery of the fetus. The optimal timing of delivery remains controversial. Currently, the available clinical tools do not allow for assessment of fetal stress in its early stages. Placental insufficiency and fetal growth restriction secondary to gestational hypertensive disorders have been shown to have long-term impacts on offspring health even into their adulthood, becoming one of the major focuses of research in the field of developmental origins of health and disease. Fetal reprogramming was introduced to describe the long-lasting effects of the toxic intrauterine environment on the growing fetus. With the advent of high-throughput sequencing, there have been major advances in research attempting to quantify fetal reprogramming. Moreover, genes that are found to be differentially expressed as a result of fetal reprogramming show promise in the development of transcriptional biomarkers for clinical use in detecting fetal response to placental insufficiency. In this review, we will review key pathophysiology in the development of placental insufficiency, existing literature on high-throughput sequencing in the study of fetal reprogramming, and considerations regarding research design from our own experience.

Indexed as

Genetic MarkersFemaleFetal DevelopmentFetal Growth RetardationGene Expression RegulationHigh-Throughput Nucleotide SequencingHumansPlacental InsufficiencyPregnancySequence Analysis, DNAGenetic Markersplacental insufficiencypreeclampsiatranscriptional biomarker

Identifiers

PMID33668810
PMCPMC7996299
OpenAlexW3130481973

What OpenQuestion 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 OpenQuestion graph.