MétaCan
Menu
Back to cohort
Record W2768805139 · doi:10.1098/rsbl.2017.0643

Associations between imprinted gene expression in the placenta, human fetal growth and preeclampsia

2017· article· en· W2768805139 on OpenAlexaff
Julian K. Christians, Katherine Leavey, Brian Cox

Bibliographic record

VenueBiology Letters · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsUniversity of TorontoSimon Fraser University
Fundersnot available
KeywordsGenomic imprintingImprinting (psychology)BiologyGenePlacentaPreeclampsiaGeneticsMicroarrayFetusMicroarray analysis techniquesGene expressionGene expression profilingPregnancyDNA methylation

Abstract

fetched live from OpenAlex

Genomic imprinting is essential for normal placental and fetal growth. One theory to explain the evolution of imprinting is the kinship theory (KT), which predicts that genes that are paternally expressed will promote fetal growth, whereas maternally expressed genes will suppress growth. We investigated the expression of imprinted genes using microarray measurements of expression in term placentae. Correlations between birthweight and the expression levels of imprinted genes were more significant than for non-imprinted genes, but did not tend to be positive for paternally expressed genes and negative for maternally expressed genes. Imprinted genes were more dysregulated in preeclampsia (a disorder associated with placental insufficiency) than randomly selected genes, and we observed an excess of patterns of dysregulation in preeclampsia that would be expected to reduce nutrient allocation to the fetus, given the predictions of the KT. However, we found no evidence of coordinated regulation among these imprinted genes. A few imprinted genes have previously been shown to be associated with fetal growth and preeclampsia, and our results indicate that this is true for a broader set of imprinted genes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.275
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBiology LettersSame topicGenetic Syndromes and ImprintingFrench-language works237,207