MétaCan
Menu
Back to cohort
Record W2528563507 · doi:10.1073/pnas.1614047113

eIF2α phosphorylation controls thermal nociception

2016· article· en· W2528563507 on OpenAlexafffund
Arkady Khoutorsky, Robert E. Sorge, Masha Prager‐Khoutorsky, Sophie Anne Pawlowski, Geraldine Longo, Seyed Mehdi Jafarnejad, Soroush Tahmasebi, Loren J. Martin, Mark H. Pitcher, Christos G. Gkogkas, Reza Sharif‐Naeini, Alfredo Ribeiro‐da‐Silva, Charles W. Bourque, Fernando Cerveró, Jeffrey S. Mogil, Nahum Sonenberg

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsMontreal General HospitalMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health ResearchLouise and Alan Edwards FoundationGovernment of CanadaMcGill University
KeywordsPhosphorylationIntegrated stress responseeIF2Cell biologyBiologyChemistryTranslation (biology)BiochemistryMessenger RNAGene

Abstract

fetched live from OpenAlex

) exhibit reduced responses to noxious heat. Pharmacological attenuation of eIF2α phosphorylation decreases thermal, but not mechanical, pain sensitivity, whereas increasing eIF2α phosphorylation has the opposite effect on thermal nociception. The impact of eIF2α phosphorylation (p-eIF2α) on thermal thresholds is dependent on the transient receptor potential vanilloid 1. Moreover, we show that induction of eIF2α phosphorylation in primary sensory neurons in a chronic inflammation pain model contributes to thermal hypersensitivity. Our results demonstrate that the cellular stress response pathway, mediated via p-eIF2α, represents a mechanism that could be used to alleviate pathological heat sensation.

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 score0.004
Threshold uncertainty score0.012

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)0.0040.001

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 head0.039
GPT teacher head0.312
Teacher spread0.274 · 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

Citations54
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPain Mechanisms and TreatmentsFrench-language works237,207