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Record W2737152634 · doi:10.4103/1673-5374.211176

Targeting 14-3-3 adaptor protein-protein interactions to stimulate central nervous system repair

2017· review· en· W2737152634 on OpenAlex
Andrew H. Kaplan, Alyson E. Fournier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeural Regeneration Research · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topic14-3-3 protein interactions
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsSignal transducing adaptor proteinAxonNeuroscienceAxon guidanceNeuroregenerationFusicoccinBiologyRegeneration (biology)Central nervous systemSmall moleculeComputational biologyCell biologyNervous systemSignal transductionGeneticsBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The goal of developing treatments for central nervous system (CNS) injuries is becoming more attainable with the recent identification of various drugs that can repair damaged axons. These discoveries have stemmed from screening efforts, large expression datasets and an improved understanding of the cellular and molecular biology underlying axon growth. It will be important to continue searching for new compounds that can induce axon repair. Here we describe how a family of adaptor proteins called 14-3-3s can be targeted using small molecule drugs to enhance axon outgrowth and regeneration. 14-3-3s bind to many functionally diverse client proteins to regulate their functions. We highlight the recent discovery of the axon-growth promoting activity of fusicoccin-A, a fungus-derived small molecule that stabilizes 14-3-3 interactions with their client proteins. Here we discuss how fusicoccin-A could serve as a starting point for the development of drugs to induce CNS 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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.192
GPT teacher head0.463
Teacher spread0.271 · 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