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Record W4406027519 · doi:10.1371/journal.pone.0316134

The involvement of Elf5 in regulating keratinocyte proliferation and differentiation processes in skin

2025· article· en· W4406027519 on OpenAlexfundno aff
Anhua Hu, Maximilian E. Pickup, Maryam A. Lawal, Hetal J. Patel, Mohammed I. Ahmed

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsHair follicleStem cellCell biologyKeratinocyteBiologyCellular differentiationProgenitor cellTranscription factorEpidermis (zoology)Gene silencingCell cultureAnatomyGenetics

Abstract

fetched live from OpenAlex

Skin and hair development is regulated by multitude of programs of activation and silencing of gene expression to maintain normal skin and hair follicle (HF) development, homeostasis, and cycling. Here, we have identified E74-like factor 5 (Elf5) transcription factor, as a novel regulator of keratinocyte proliferation and differentiation processes in skin. Expression analysis has revealed that Elf5 expression was localised and elevated in stem/progenitor cell populations of both the epidermis (basal and suprabasal) and in HF bulge and hair germ stem cell (SCs) compartments during skin and hair development and cycling. Expressional and functional analysis using RT-qPCR, western blot and colony forming assays, revealed that Elf5 plays an important role in regulating keratinocyte proliferation and differentiation processes as well as potentially determining cell fate by regulating the stem/progenitor cell populations in skin and HFs. These data will provide a platform for pharmacological manipulation of Elf5 in skin, leading to advancements in many areas of research, including stem cell, regenerative medicine, and ageing.

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 head0.022
GPT teacher head0.242
Teacher spread0.220 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicHair Growth and DisordersFrench-language works237,207