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Record W4392699094 · doi:10.7554/elife.94995.1.sa2

Reviewer #1 (Public Review): Damage-induced basal epithelial cell migration modulates the spatial organization of redox signaling and sensory neuron regeneration

2024· peer-review· en· W4392699094 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRedox biology and oxidative stress
Canadian institutionsnot available
FundersUniversity of California, Los AngelesGeorg-August-Universität GöttingenYork UniversityUniversity of Wisconsin-Madison
KeywordsRegeneration (biology)NeuronNeuroscienceSensory systemCell biologyBiologyBasal (medicine)Sensory neuronBiotechnology

Abstract

fetched live from OpenAlex

Epithelial damage leads to early reactive oxygen species (ROS) signaling, which regulates sensory neuron regeneration and tissue repair. How the initial type of tissue injury influences early damage signaling and regenerative growth of sensory axons remains unclear. Previously we reported that thermal injury triggers distinct early tissue responses in larval zebrafish. Here, we found that thermal but not mechanical injury impairs sensory axon regeneration and function. Real-time imaging revealed an immediate tissue response to thermal injury characterized by the rapid Arp2/3-dependent migration of keratinocytes, which was associated with tissue-scale ROS production and sustained sensory axon damage. Osmotic regulation induced by isotonic treatment was sufficient to limit keratinocyte movement, spatially-restrict ROS production and rescue sensory function. These results suggest that early keratinocyte dynamics regulate the spatial and temporal pattern of long-term signaling in the wound microenvironment during tissue repair.

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)0.034
metaresearch head score (Gemma)0.219
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.107
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.219
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.003
Science and technology studies0.0040.002
Scholarly communication0.0090.006
Open science0.0050.005
Research integrity0.0160.007
Insufficient payload (model declined to judge)0.1070.052

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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