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Pituitary gland volume in adolescent and young adult bipolar and unipolar depression

2008· article· en· W2107738325 on OpenAlexafffund
Frank P. MacMaster, Ronald A. Leslie, David R. Rosenberg, Vivek Kusumakar

Bibliographic record

VenueBipolar Disorders · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsDalhousie University
FundersNova Scotia Health Research Foundation
KeywordsDepression (economics)Internal medicinePituitary glandBipolar disorderMoodMood disordersEndocrinologyPsychologyMedicinePsychiatryHormoneAnxiety

Abstract

fetched live from OpenAlex

OBJECTIVES: Few studies have examined pituitary gland size in mood disorders, particularly in adolescents. We hypothesized increase in the pituitary gland size in early-onset mood disorders. METHODS: Thirty subjects between the ages of 13 and 20 years participated in the study. Three groups (control, bipolar I depression and unipolar depression) of 10 subjects each (4 male, 6 female) underwent volumetric magnetic resonance imaging at 1.5 T. RESULTS: Analysis of covariance (covarying for age, sex and intracranial volume) revealed a significant difference in pituitary gland volume amongst the groups [F(2,24) = 7.092, p = 0.014]. Post hoc analysis revealed that controls had a significantly smaller pituitary gland volume than both bipolar patients (p = 0.019) and depressed patients (p = 0.049). Bipolar and depressed subjects did not differ significantly from each other with regard to pituitary gland volume (p = 0.653). Control females had larger pituitary glands than control males [F(1,8) = 10.523, p = 0.012], but no sex differences were noted in the mood disorder groups. CONCLUSIONS: Pituitary glands are enlarged in adolescents with mood disorders compared to controls. Healthy young females have larger pituitary glands than males, but such a difference is not evident in individuals with unipolar depression or bipolar disorder. These findings provide new evidence of abnormalities of the pituitary in early onset mood disorders, and are consistent with neuroendocrine dysfunction in early stages of such 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.882

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 communication0.0000.000
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 head0.015
GPT teacher head0.231
Teacher spread0.217 · 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

Citations66
Published2008
Admission routes2
Has abstractyes

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