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Record W2887874827 · doi:10.1177/1744806918798406

Heterosynaptic long-term potentiation from the anterior cingulate cortex to spinal cord in adult rats

2018· article· en· W2887874827 on OpenAlexafffund
Qi‐Yu Chen, Tao Chen, Li‐Jun Zhou, Xian‐Guo Liu, Min Zhuo

Bibliographic record

VenueMolecular Pain · 2018
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceLong-term potentiationAnterior cingulate cortexSpinal cordNMDA receptorNociceptionNeurotransmissionMedicinePsychologyReceptorInternal medicine

Abstract

fetched live from OpenAlex

Spinal nociceptive transmission receives biphasic modulation from supraspinal structures. Recent studies demonstrate that the anterior cingulate cortex facilitates spinal excitatory synaptic transmission and nociceptive reflex. However, whether the top-down descending facilitation can cause long-term synaptic changes in spinal cord remains unclear. In the present study, we recorded C-fiber-evoked field potentials in spinal dorsal horn and found that the anterior cingulate cortex stimulation caused enhancement of C-fiber-mediated responses. The enhancement lasted for more than a few hours. Spinal application of N-methyl-D-aspartate (NMDA) receptor antagonist D-AP5 abolished this enhancement, suggesting that the activation of the NMDA receptor is required. Furthermore, spinal application of methysergide, a serotonin receptor antagonist, also blocked the anterior cingulate cortex-induced spinal long-term potentiation. Our results suggest that the anterior cingulate cortex stimulation can produce heterosynaptic form of long-term potentiation at the spinal cord dorsal horn, and this novel form of long-term potentiation may contribute to top-down long-term facilitation in chronic pain conditions.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.280
Teacher spread0.270 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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