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Record W2606474317

Differential responses of choroidal melanocytes and uveal melanoma cells to low oxygen conditions.

2017· article· en· W2606474317 on OpenAlexaff
Cindy Weidmann, Jade Pomerleau, Laurence Trudel-Vandal, Solange Landreville

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de QuébecCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMelaninMelanocyteMelanomaHyperoxiaChoroidMicrophthalmia-associated transcription factorBiologyCell growthRetinalOxygen tensionGLUT3Cell biologyAndrologyChemistryCancer researchEndocrinologyOxygenRetinaGlucose transporterGeneGLUT1MedicineGeneticsBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: Tissue culture is traditionally performed at atmospheric oxygen concentration (21%), which induces hyperoxic stress, as endogenous physiologic oxygen tension found in tissues varies between 2% and 9%. This discrepancy may lead to misinterpretation of results and may explain why effects observed in vitro cannot always be reproduced in vivo and vice versa. Only a few studies have been conducted in low physiologic oxygen conditions to understand the development and differentiation of cells from the eye. METHODS: The aim of this study was to investigate the growth and gene expression profile of melanocytes from the choroid permanently exposed to 21% (hyperoxic) or 3% (physiologic) oxygen with proliferation assays and DNA microarray. The cellular behavior of the melanocytes was then compared to that of cancer cells. RESULTS: . CONCLUSIONS: This study showed that the oxygen concentration must be tightly controlled in experimental settings, because it influences the subsequent cellular behavior of human choroidal melanocytes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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 designBench or experimental
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

Citations12
Published2017
Admission routes1
Has abstractyes

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Same venuePubMedSame topicOcular Oncology and TreatmentsFrench-language works237,207