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Record W4399730261 · doi:10.1186/s13041-024-01106-5

Inhibition of cortical synaptic transmission, behavioral nociceptive, and anxiodepressive-like responses by arecoline in adult mice

2024· article· en· W4399730261 on OpenAlexafffund
Qi‐Yu Chen, Yuxiang Zhang, Yujie Ma, Min Zhuo

Bibliographic record

VenueMolecular Brain · 2024
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsCanada Research Chairs
FundersCanadian Institutes of Health Research
KeywordsPsychopharmacologyNeuroscienceArecolineNociceptionNeurotransmissionPsychologyMedicinePsychiatryInternal medicineMuscarinic acetylcholine receptor

Abstract

fetched live from OpenAlex

Areca nut, the seed of Areca catechu L., is one of the most widely consumed addictive substances in the world after nicotine, ethanol, and caffeine. The major effective constituent of A. catechu, arecoline, has been reported to affect the central nervous system. Less is known if it may affect pain and its related emotional responses. In this study, we found that oral application of arecoline alleviated the inflammatory pain and its induced anxiolytic and anti-depressive-like behavior. Arecoline also increased the mechanical nociceptive threshold and alleviated depression-like behavior in naïve mice. In the anterior cingulate cortex (ACC), which acts as a hinge of nociception and its related anxiety and depression, by using the multi-electrode field potential recording and whole-cell patch-clamp recording, we found that the evoked postsynaptic transmission in the ACC of adult mice has been inhibited by the application of arecoline. The muscarinic receptor is the major receptor of the arecoline in the ACC. Our results suggest that arecoline alleviates pain, anxiety, and depression-like behavior in both physiological and pathological conditions, and this new mechanism may help to treat patients with chronic pain and its related anxiety and disorder in the future.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.487

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.041
GPT teacher head0.287
Teacher spread0.246 · 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 teacher head, 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

Citations13
Published2024
Admission routes2
Has abstractyes

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