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Record W2148132100 · doi:10.2174/138161209788186263

Acid Sensing Ion Channels and Acid Nociception

2009· review· en· W2148132100 on OpenAlexaff
Gilles Dubé, A. Elagoz, Halinder S. Mangat

Bibliographic record

VenueCurrent Pharmaceutical Design · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon Transport and Channel Regulation
Canadian institutionsCelluForce (Canada)
Fundersnot available
KeywordsAcid-sensing ion channelNociceptionIon channelNeuroscienceSensory systemNociceptorMedicineChemistryBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Acid Sensing Ion Channels (ASICs) are a family of cation channels expressed principally in neurons and that are activated by protons. The sensitivity of ASICs to acidosis and their distribution in primary sensory neurons points to a significant role of these channels in acid nociception. However, despite the fact that the first ASIC was identified more than 10 years ago the physiological and pathophysiological role of this channel family remains poorly understood. In this paper, the available body of data (genetic, pharmacological, and other) on ASICs will be reviewed and the role of ASIC in normal nociception and other pain sensations will be discussed. Some of the recent drug discovery and development activities ongoing in our laboratory, which point to ASICs being a relevant target for pain modulation, will also be summarized.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.005

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 head0.140
GPT teacher head0.398
Teacher spread0.258 · 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
GenreReview

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

Citations49
Published2009
Admission routes1
Has abstractyes

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