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Record W3176819348 · doi:10.1096/fasebj.20.4.a637-b

nestin: immunohistochemical expression in vessels during the development and progression of pituitary infarction

2006· article· en· W3176819348 on OpenAlexaff
Fateme Salehi, Kálmán Kovács, Michael D. Cusimano, C. David Bell, Fabio Rotondo, Bernd W Sheithauer

Bibliographic record

VenueThe FASEB Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsNestinPathologyImmunohistochemistryNeovascularizationAngiogenesisBiologyInfarctionMedicineInternal medicineStem cellCell biologyCancer researchMyocardial infarction

Abstract

fetched live from OpenAlex

The aim of our work was to investigate immunohistochemical expression of nestin, a member of the intermediate filament family, in the adenohypophysial vasculature during the development and progression of pituitary infarction. Non‐tumorous adenohypopheses (45 cases) and pituitary adenomas (34 cases) of various types, all exhibiting acute or healing infarcts were examined. The streptavidin‐biotin‐peroxidase complex method was applied. In areas of adenohypophyses and pituitary adenomas with no infarction, nestin was expressed in scattered capillaries and endothelial cells. In acute infarcts, no nestin was demonstrable in the necrotic capillaries (50 cases). Where newly formed capillaries spread into necrotic zones, nestin expression was noted in all capillaries (25 cases). In the hypocellular, fibrotic scar phase, only few vessels were apparent and immunoreactivity was focal and mild (4 cases). In conclusion, nestin is strongly expressed in newly formed capillaries and is downregulated when infarcts transform to fibrous tissue. Nestin expression may provide valuable insight into the process of pituitary angiogenesis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.252
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

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