MétaCan
Menu
Back to cohort
Record W2062878015 · doi:10.1007/s10227-002-0108-3

UV Induces GADD45 in a p53-Dependent and -Independent Manner in Human Keratinocytes

2003· article· en· W2062878015 on OpenAlexaff
Tomoko Maeda, Adrian B. Sim, Duane A. Leedel, Prescillia Chua, Eugene G. Chomey, Le Luong, Victor A. Tron

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2003
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGadd45DNA damageWestern blotDNA repairMessenger RNAMolecular biologyCell cycleHuman skinMedicineCell biologyApoptosisCell cycle checkpointCancer researchBiologyDNAGeneBiochemistryGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: GADD45 is a multifunctional protein involved in DNA repair and in cell cycle checkpoint control. p53 plays an important role in regulating DNA repair and in response to UVB in keratinocytes. OBJECTIVE: GADD45 and p53 expression was examined and compared at the mRNA and protein level after exposure to UV irradiation. METHODS: Human keratinocytes were exposed to increasing doses of UVB, and an RNA protection assay and a Western blot analysis were performed. RESULTS: The RNase protection assays using human keratinocytes showed that GADD45 mRNA increases after 4 h and remains elevated for 24 h in cells irradiated at 100, 300, or 600 J/m2 UVB. The level of GADD45 protein increases after 8 h and remains elevated for 48 h, with maximal induction at 300 J/m2. p53 mRNA did not rise in concert with GADD45 at any dose used, and p53 protein was not up-regulated at the lower dose of 100 J/m2. CONCLUSION: GADD45 is regulated in both a p53-dependent and a p53-independent manner in keratinocytes after UV exposure.

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 score0.004

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicCancer-related Molecular PathwaysFrench-language works237,207