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Record W4366520880 · doi:10.1016/j.stemcr.2023.03.013

IRX5 promotes DNA damage repair and activation of hair follicle stem cells

2023· article· en· W4366520880 on OpenAlexaff
Jefferson K. Chen, Julie Wiedemann, Ly Thi Huong Nguyen, Zhongqi Lin, Mahum Tahir, Chi‐chung Hui, Maksim V. Plikus, Bogi Andersen

Bibliographic record

VenueStem Cell Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of General Medical SciencesNational Institutes of Health
KeywordsBiologyHair follicleStem cellDNA damageCell biologyDNA repairDNAAndrologyGenetics

Abstract

fetched live from OpenAlex

The molecular mechanisms allowing hair follicles to periodically activate their stem cells (HFSCs) are incompletely characterized. Here, we identify the transcription factor IRX5 as a promoter of HFSC activation. Irx5 −/− mice have delayed anagen onset, with increased DNA damage and diminished HFSC proliferation. Open chromatin regions form near cell cycle progression and DNA damage repair genes in Irx5 −/− HFSCs. DNA damage repair factor BRCA1 is an IRX5 downstream target. Inhibition of FGF kinase signaling partially rescues the anagen delay in Irx5 −/− mice, suggesting that the Irx5 −/− HFSC quiescent phenotype is partly due to failure to suppress Fgf18 expression. Interfollicular epidermal stem cells also show decreased proliferation and increased DNA damage in Irx5 −/− mice. Consistent with a role for IRX5 as a promoter of DNA damage repair, we find that IRX genes are upregulated in many cancer types and that there is a correlation between IRX5 and BRCA1 expression in breast cancer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.470

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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