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Record W4377220106 · doi:10.1177/10738584231176233

Critical Windows: Exploring the Association Between Perinatal Trauma, Epigenetics, and Chronic Pain

2023· review· en· W4377220106 on OpenAlexaff
Zoe N. Kodila, Sandy R. Shultz, Glenn R. Yamakawa, Richelle Mychasiuk

Bibliographic record

VenueThe Neuroscientist · 2023
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsVancouver Island University
FundersNational Health and Medical Research Council
KeywordsEpigeneticsChronic painOffspringMedicineNeuroscienceBioinformaticsPsychologyPsychiatryPregnancyBiologyGenetics

Abstract

fetched live from OpenAlex

Chronic pain is highly prevalent and burdensome, affecting millions of people worldwide. Although it emerges at any point in life, it often manifests in adolescence. Given that adolescence is a unique developmental period, additional strains associated with persistent and often idiopathic pain lead to significant long-term consequences. While there is no singular cause for the chronification of pain, epigenetic modifications that lead to neural reorganization may underpin central sensitization and subsequent manifestation of pain hypersensitivity. Epigenetic processes are particularly active during the prenatal and early postnatal years. We demonstrate how exposure to various traumas, such as intimate partner violence while in utero or adverse childhood experiences, can significantly influence epigenetic regulation within the brain and in turn modify pain-related processes. We provide compelling evidence that the burden of chronic pain is likely initiated early in life, often being transmitted from mother to offspring. We also highlight two promising prophylactic strategies, oxytocin administration and probiotic use, that have the potential to attenuate the epigenetic consequences of early adversity. Overall, we advance understanding of the causal relationship between trauma and adolescent chronic pain by highlighting epigenetic mechanisms that underlie this transmission of risk, ultimately informing how to prevent this rising epidemic.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.112
GPT teacher head0.364
Teacher spread0.252 · 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 designNot applicable
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

Citations22
Published2023
Admission routes1
Has abstractyes

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