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An Ion Channel Essential for Sensing Chemical Damage

2007· article· en· W2014185236 on OpenAlexfundno aff
Lindsey J. Macpherson, Bailong Xiao, Kelvin Y. Kwan, Matt Petrus, Adrienne E. Dubin, Sun Wook Hwang, Benjamin F. Cravatt, David P. Corey, Ardem Patapoutian

Bibliographic record

VenueJournal of Neuroscience · 2007
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial ResearchCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Neurological Disorders and StrokeFondation pour la Recherche Médicale
KeywordsIodoacetamideIon channelCysteineChemistryOxidative stressFormaldehydeIn vitroBiophysicsBiochemistryCell biologyBiologyReceptorEnzyme

Abstract

fetched live from OpenAlex

Tissue damage and its downstream consequences are experimentally assayed by formaldehyde application, which indiscriminately modifies proteins and is presumed to cause pain through broadly acting mechanisms. Here we show that formaldehyde activates the ion channel TRPA1 and that TRPA1-deficient mice exhibit dramatically reduced formaldehyde-induced pain responses. 4-Hydroxynonenal, a reactive chemical produced endogenously during oxidative stress, and other related aldehydes also activate TRPA1 in vitro. Furthermore, painful responses to iodoacetamide, a nonspecific cysteine-alkylating compound, are abolished in TRPA1-deficient mice. Therefore, although these reactive chemicals modify many proteins, the associated pain appears mainly dependent on a single ion channel.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.323
Teacher spread0.282 · 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

Citations288
Published2007
Admission routes1
Has abstractyes

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