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Record W2958100444 · doi:10.1002/hed.25871

VEGFR‐2 is downregulated in sestamibi‐negative parathyroid adenomas

2019· article· en· W2958100444 on OpenAlexaff
Boban M. Erovic, David P. Goldstein, L. Sylvia, Stefan Janik, Özgür Mete, Jonathan C. Irish

Bibliographic record

VenueHead & Neck · 2019
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAngiogenesisVascular endothelial growth factorPathologyWnt signaling pathwayInternal medicineCancer researchEndocrinologySignal transductionBiologyVEGF receptorsCell biology

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this study was to determine the expression profile of several biomarkers in sestamibi-positive (n = 23) and sestamibi-negative (n = 6) parathyroid adenomas. METHODS: A tissue microarray of parathyroid adenomas from 29 patients was constructed and slides were stained for several proteins involved in angiogenesis, inflammation, cell adhesion, cell cycle, apoptosis, and with markers of the sonic hedgehog, mTOR, Forkhead box O and WNT signal transduction pathways. Protein expression was determined using an image-analysis software (Spectrum Plus©, 38 Aperio). RESULTS: Protein expression analysis revealed that the vascular endothelial growth factor receptor 2 (VEGFR2) score was significantly higher in the sestamibi-positive cohort compared to sestamibi-negative adenomas (P = .038). Other proteins were not differentially expressed between sestamibi-positive and sestamibi-negative adenomas. CONCLUSION: It is hypothesized that VEGFR-2 overexpression in parathyroid adenomas increases vascular permeability resulting in a higher uptake of sestamibi.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.998

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)0.0000.003

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 head0.292
Teacher spread0.278 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

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