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Record W2087605678 · doi:10.3171/jns.2003.99.2.0402

Gonadotropic pituitary carcinoma: HER-2/neu expression and gene amplification

2003· article· en· W2087605678 on OpenAlexaff
Federico Roncaroli, Vânia Nosé, Bernd W. Scheithauer, Kálmán Kovács, Éva Horváth, William F. Young, Ricardo V. Lloyd, Mary C. Bishop, Bradley Hsi, Jonathan A. Fletcher

Bibliographic record

VenueJournal of neurosurgery · 2003
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsInstitute of Nutrition, Metabolism and Diabetes
Fundersnot available
KeywordsMedicinePathologyMetastasisCarcinomaPituitary adenomaAdenomaInternal medicineCancer

Abstract

fetched live from OpenAlex

The authors report on two gonadotropic carcinomas of the adenohypophysis that occurred in a55-year-old man (Case 1) and a 53-year-old woman (Case 2), with signs of mass effect and amenorrhea, respectively. Both lesions were macroadenomas. The tumor in Case 1 metastasized to dura mater, skull, nasal sinus, and larynx 2 years after patient presentation, whereas that in Case 2 spread to vertebral bodies and ribs after a 19-year latency. Histologically, the primary, recurrent, and metastatic lesions in Case 1 featured brisk mitotic activity and high MIB-1 levels as well as p53 labeling indices. Immunoreactivity for HER-2/neu was assessable only in rare neoplastic cells of the second recurrence and in 80% of cells of the dural metastasis. Low-level HER-2/neu gene amplification was evident in the recurrent tumors and metastasis. The sellar and metastatic tumors in Case 2 resembled benign gonadotropic adenoma with oncocytic change; p53 accumulation, HER-2/neu overexpression, and HER-2/neu gene amplification were not present. The results indicate that low-level amplification of the HER-2/neu gene might be associated with pituitary carcinomas in which more aggressive behavior is seen. Further studies are needed to determine whether HER-2/neu plays a role in the pathogenesis of pituitary carcinoma.

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 score0.072
Threshold uncertainty score0.335

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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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

Citations43
Published2003
Admission routes1
Has abstractyes

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