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Record W2989069730 · doi:10.7554/elife.46797

The effects of psychosocial stress on dopaminergic function and the acute stress response

2019· article· en· W2989069730 on OpenAlexaboutno aff
Michael Bloomfield, Robert A. McCutcheon, Matthew J. Kempton, Tom P. Freeman, Oliver Howes

Bibliographic record

VenueeLife · 2019
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
FundersMedical Research CouncilNational Institute for Health and Care ResearchUniversity College LondonWellcome TrustWellcome
KeywordsPsychosocialDopaminergicPsychologyDopamineVulnerability (computing)MedicineClinical psychologyInternal medicinePsychiatryNeuroscience

Abstract

fetched live from OpenAlex

Chronic psychosocial adversity induces vulnerability to mental illnesses. Animal studies demonstrate that this may be mediated by dopaminergic dysfunction. We therefore investigated whether long-term exposure to psychosocial adversity was associated with dopamine dysfunction and its relationship to psychological and physiological responses to acute stress. Using 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine ([18F]-DOPA) positron emission tomography (PET), we compared dopamine synthesis capacity in n = 17 human participants with high cumulative exposure to psychosocial adversity with n = 17 age- and sex-matched participants with low cumulative exposure. The PET scan took place 2 hr after the induction of acute psychosocial stress using the Montréal Imaging Stress Task to induce acute psychosocial stress. We found that dopamine synthesis correlated with subjective threat and physiological response to acute psychosocial stress in the low exposure group. Long-term exposure to psychosocial adversity was associated with dampened striatal dopaminergic function (p=0.03, d = 0.80) and that psychosocial adversity blunted physiological yet potentiated subjective responses to acute psychosocial stress. Future studies should investigate the roles of these changes in vulnerability to mental illnesses.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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 designBench or experimental
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

Citations117
Published2019
Admission routes1
Has abstractyes

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