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Record W7149222556

Hypersomatotropism and Hypercortisolism Caused by a Plurihormonal Pituitary Adenoma in a Dog

2025· article· en· W7149222556 on OpenAlexaboutno aff
Elber Alberto Soler Arias, Ricardo Rodas Elvir, Adrian F Daly, H.S. Kooistra, Interne geneeskunde GD, Welfare & Emerging Diseases, CS_Welfare & emerging diseases

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2025
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsCabergolineAcromegalyPituitary adenomaLabrador RetrieverPituitary glandPituitary disorderSupine positionAdenomaDexamethasoneCushing syndrome
DOInot available

Abstract

fetched live from OpenAlex

A 12-year-old, male Labrador Retriever was presented because of polyuria, polydipsia, polyphagia, joint pain, and physical features consistent with acromegaly. Circulating insulin-like growth factor-1 (IGF-1) concentration was increased (> 1000 ng/mL; reference interval [RI], 42-449), suggestive of hypersomatotropism. An abnormal low-dose dexamethasone suppression test and increased circulating adrenocorticotropic (ACTH) concentration indicated pituitary-dependent hypercortisolism. Computed tomography identified an enlarged pituitary gland. Treatment with cabergoline initially decreased circulating IGF-1 and ACTH concentrations and urinary cortisol-to-creatinine ratio (UCCR), with a notable reduction in acromegalic physical features. However, 7 months after the start of cabergoline treatment, IGF-1, ACTH, and UCCR had increased again, although pituitary gland size remained stable. Because of worsening joint pain, euthanasia was performed. On necropsy, double immunohistochemistry identified pituitary tumor cells with cytoplasmic co-expression of both growth hormone (GH) and ACTH, consistent with a monomorphic plurihormonal macroadenoma. This case shows that concurrent hypersomatotropism and hypercortisolism can occur in dogs caused by a plurihormonal pituitary adenoma.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueUtrecht University Repository (Utrecht University)Same topicVeterinary Medicine and SurgeryFrench-language works237,207