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Record W3016056304 · doi:10.1172/jci136162

(H)Elping nerve growth factor: Elp1 inhibits TrkA’s phosphatase to maintain retrograde signaling

2020· letter· en· W3016056304 on OpenAlexaff
David R. Kaplan, William C. Mobley

Bibliographic record

VenueJournal of Clinical Investigation · 2020
Typeletter
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsNerve growth factorTropomyosin receptor kinase ACell biologyNeuroscienceNeurotrophinBiologyLow-affinity nerve growth factor receptorSignal transductionReceptorGenetics

Abstract

fetched live from OpenAlex

Nerve growth factor (NGF) regulates many aspects of neuronal biology by retrogradely propagating signals along axons to the targets of those axons. How this occurs when axons contain a plethora of proteins that can silence those signals has long perplexed the neurotrophin field. In this issue of the JCI, Li et al. suggest an answer to this vexing problem, while exploring why the Elp1 gene that is mutated in familial dysautonomia (FD) causes peripheral neuropathy. They describe a distinctive function of Elp1 as a protein that is required to sustain NGF signaling by blocking the activity of its phosphatase that shuts off those signals. This finding helps explain the innervation deficits prominent in FD and reveals a unique role for Elp1 in the regulation of NGF-dependent TrkA activity.

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)0.001
metaresearch head score (Gemma)0.053
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.008
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 head0.174
GPT teacher head0.361
Teacher spread0.187 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2020
Admission routes1
Has abstractyes

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