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Record W6929120492 · doi:10.48336/z0h5-h409

Trace amine-associated receptor 1 as a novel immunomodulatory target in multiple sclerosis

2023· article· en· W6929120492 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMultiple sclerosisImmune systemCytokineReceptorPathophysiologySignal transduction

Abstract

fetched live from OpenAlex

TAAR1 is a previously established neuroregulator with emerging evidence suggesting a role in modulation of the immune response. Multiple sclerosis is an immune-mediated demyelinating disease of the central nervous system (CNS). This study investigated expression of TAAR1 in immune cells relevant to MS pathophysiology in both the periphery and CNS of MS patients. RT-qPCR analyses of TAAR1 mRNA levels in peripheral immune cells from MS patients shared a statistically significant decrease in TAAR1 mRNA in MS patient monocytes compared to controls. TAAR1 expression at the protein-level was visualized in both peripherally-derived and CNS-resident macrophages bordering an MS lesion. Additionally, this study attempted to characterize a function of TAAR1 within the immune system that is relevant to MS neuroinflammation. Effects of TAAR1 agonist treatment on cytokine secretion and on the metabolic profile of pro-inflammatory macrophages from the periphery indicated a potential anti-inflammatory function, however, TAAR1 agonists had no effect on cytokine secretion from macrophages resident to the CNS. This study effectively demonstrates the potential for a novel link between TAAR1 and MS pathophysiology and establishes critical preliminary research towards elucidating the function of TAAR1 in peripheral and CNS-resident macrophages.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.029
GPT teacher head0.232
Teacher spread0.203 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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