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Record W2469928227 · doi:10.1021/acschemneuro.6b00097

Identification of 2-({[1-(4-Fluorophenyl)-5-(2-methoxyphenyl)-1<i>H</i>-pyrazol-3-yl]carbonyl}amino)tricyclo[3.3.1.13,7]decane-2-carboxylic Acid (NTRC-844) as a Selective Antagonist for the Rat Neurotensin Receptor Type 2

2016· article· en· W2469928227 on OpenAlexafffund
James B. Thomas, Mélanie Vivancos, Angela M. Giddings, Robert W. Wiethe, Keith R. Warner, Alexandre Murza, Élie Besserer‐Offroy, Jean‐Michel Longpré, Scott P. Runyon, Ann M. Decker, Brian P. Gilmour, Philippe Sarret

Bibliographic record

VenueACS Chemical Neuroscience · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute on Drug AbuseNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsAgonistAntagonistIn vivoNeurotensinChemistryPharmacologyReceptorCarboxylic acidStereochemistryAnalgesicMedicineBiochemistryNeuropeptideBiology

Abstract

fetched live from OpenAlex

Neurotensin receptor type 2 (NTS2) compounds display analgesic activity in animal pain models. We have identified the first high-affinity NTS2-selective antagonist (8) that is active in vivo. This study also revealed that the NTS2 FLIPR assay designation for a compound, agonist, partial agonist, and so forth, did not correlate with its in vivo activity as observed in the thermal tail-flick acute model of pain. This suggests that calcium mobilization is not the signaling pathway involved in NTS2-mediated analgesia as assessed by the thermal tail-flick model. Finally, we found a significant bias between rat and human for compound 9 in the NTS2 binding assay.

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 score0.008

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)0.0030.001

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 head0.027
GPT teacher head0.280
Teacher spread0.252 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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Same venueACS Chemical NeuroscienceSame topicNeuropeptides and Animal PhysiologyFrench-language works237,207