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Record W4412654671 · doi:10.3390/cells14141097

Role of Cellular Senescence in IUGR: Impact on Fetal Morbidity and Development

2025· review· en· W4412654671 on OpenAlexafffund
Aliabbas Zia, Faezeh Sahebdel, Yosra Er‐Reguyeg, Michel Desjarlais, Jean-Clément Mars, Gregory A. Lodygensky, Sylvain Chemtob

Bibliographic record

VenueCells · 2025
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversité LavalHôpital Maisonneuve-RosemontUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health ResearchUniversité de MontréalMitacs
KeywordsSenescenceInflammationIntrauterine growth restrictionOxidative stressPathologicalPlacentaFetusMechanism (biology)MedicineBiologyBioinformaticsImmunologyPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Intrauterine growth restriction (IUGR) is a critical challenge in perinatal medicine and is associated with significant morbidity and mortality. This review explores the intricate involvement of early developmental senescence in IUGR. We highlight the dual role of cellular senescence in both normal development and pathological conditions, emphasizing the need for further research to elucidate these mechanisms and develop targeted interventions. We discuss how oxidative stress and mitochondrial dysfunction affect senescence determinants. We present emerging therapeutic strategies aimed at targeting senescence and inflammation in the placenta. We also introduce Rytvela, an interleukin-1 (IL-1) receptor modulator developed in our laboratory, which selectively attenuates pro-inflammatory signaling while preserving essential immune responses, which in turn mitigate senescence. By addressing senescence-related dysfunctions, such interventions may improve placental performance and fetal outcomes, opening up new directions for the clinical management of IUGR.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.040
GPT teacher head0.343
Teacher spread0.303 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes2
Has abstractyes

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