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Record W2014438108 · doi:10.1152/jn.00096.2004

Opioid-Like Actions of Neuropeptide Y in Rat Substantia Gelatinosa: Y1 Suppression of Inhibition and Y2 Suppression of Excitation

2004· article· en· W2014438108 on OpenAlexaff
Timothy D. Moran, William F. Colmers, Peter A. Smith

Bibliographic record

VenueJournal of Neurophysiology · 2004
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExcitatory postsynaptic potentialInhibitory postsynaptic potentialNeurosciencePostsynaptic potentialNeuropathic painGABAergicGlycine receptorChemistryNeuropeptide Y receptorOpioidAnalgesicSpinal cordNociceptionReceptorNeuropeptidePharmacologyBiologyGlycine

Abstract

fetched live from OpenAlex

Neuropathic pain that results from injury to the peripheral or CNS responds poorly to opioid analgesics. Y1 and Y2 receptors for neuropeptide Y (NPY) may, however, serve as targets for analgesics that retain their effectiveness in neuropathic pain states. In substantia gelatinosa neurons in spinal cord slices from adult rats, we find that NPY acts via presynaptic Y2 receptors to attenuate excitatory postsynaptic currents (EPSCs) and predominantly on presynaptic Y1 receptors to attenuate glycinergic and GABAergic inhibitory postsynaptic currents (IPSCs). Because NPY attenuates the frequency of TTX-resistant miniature EPSCs and IPSCs, perturbation of the neurotransmitter release process contributes to its actions at both excitatory and inhibitory synapses. These effects, which are reminiscent of those produced by analgesic opioids, provide a cellular basis for previously documented spinal analgesic actions mediated via Y1 and Y2 receptors in neuropathic pain paradigms. They also underline the importance of suppression of inhibition in spinal analgesic mechanisms.

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 score0.003
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.286
Teacher spread0.262 · 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

Citations63
Published2004
Admission routes1
Has abstractyes

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