MétaCan
Menu
Back to cohort
Record W1968588368 · doi:10.1155/2012/917901

Progesterone and Cerebral Function during Emotion Processing in Men and Women with Schizophrenia

2012· article· en· W1968588368 on OpenAlexafffund
Julie Champagne, Nadia Lakis, Josiane Bourque, Émmanuel Stip, Olivier Lipp, Adrianna Mendrek

Bibliographic record

VenueSchizophrenia Research and Treatment · 2012
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversité de MontréalInstitut universitaire en santé mentale de Montréal
FundersInstitute of Gender and HealthCanadian Institutes of Health ResearchEli Lilly and Company
KeywordsSchizophrenia (object-oriented programming)EstrogenMedicineHormoneTestosterone (patch)Internal medicineAffect (linguistics)Sex hormone-binding globulinClinical psychologyEndocrinologyPhysiologyPsychologyPsychiatryAndrogen

Abstract

fetched live from OpenAlex

Schizophrenia has been associated with disturbed levels of sex-steroid hormones, including estrogen and testosterone. In the present study we have examined the implication of a less studied hormone progesterone. Forty-three patients with schizophrenia (21 women) and 43 control participants (21 women) underwent functional MRI while viewing emotionally positive, negative, and neutral images. Blood samples were taken prior to the scanning session to evaluate progesterone levels. Simple regression analyses between levels of progesterone and brain activations associated with emotion processing were performed using SPM5. A positive correlation was found between progesterone levels and brain activations during processing of emotionally charged images in both healthy and schizophrenia men, but no significant relationship was revealed in women. These preliminary results indicate that progesterone is significantly associated with brain activations during processing of positive and negative affect in healthy and schizophrenia men, but not in women. Further investigation is warranted.

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 score0.753
Threshold uncertainty score0.552

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 communication0.0000.001
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 head0.045
GPT teacher head0.301
Teacher spread0.256 · 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

Citations22
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueSchizophrenia Research and TreatmentSame topicStress Responses and CortisolFrench-language works237,207