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Record W2951361109 · doi:10.82308/24583

The effects of early life adversity on hypothalamic- pituitary-adrenal axis, sympathetic, and parasympathetic responses to the Montreal Imaging Stress Task

2017· article· en· W2951361109 on OpenAlexaboutno aff
Alexander Barton

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyReactivity (psychology)Autonomic nervous systemVagal toneParasympathetic nervous systemSympathetic nervous systemHypothalamic–pituitary–adrenal axisDevelopmental psychologyNeuroscienceInternal medicineMedicineHeart rateHormonePathology

Abstract

fetched live from OpenAlex

Early life adversity (ELA) has been shown to be associated with emergences of psycho- andother pathologies later in life. These physiological and psychological effects are hypothesizedto be mediated by changes in stress physiology, namely the hypothalamic-pituitary-adrenal(HPA) axis, and the autonomic nervous system (ANS). Numerous studies have shown effectsof ELA on HPA-axis response. However, findings have been mixed with some researchersreporting potentiating effects of ELA on HPA-reactivity, while others have found bluntingeffects of ELA. Importantly, the majority of studies so far have focused on HPA-reactivity,neglecting to incorporate measures of the independent branches of the ANS. This thesis hypothesizedthat inter-individual differences in the relationship between HPA-reactivity andELA could be explained via a moderating effect of ANS reactivity. The thesis incorporatedheart rate variability (HRV), specifically respiratory sinus arrhythmia (RSA) — an index ofparasympathetic nervous system (PSNS) activity — as well as salivary α-amylase (sAA) —a marker of the ANS but with prominent sympathetic nervous system (SNS) components —to obtain a more thorough and complete picture of stress reactivity. Results found no effectsof ELA on stress reactivity in the PSNS and HPA-axis. However, when controlling for thePSNS we found a difference in reactivity of sAA between those high in ELA and those lowin ELA, providing initial evidence of observable effects of ELA on the SNS in sAA measures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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