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Record W4396883109 · doi:10.1177/17448069241258110

Recruitment of cortical silent responses by forskolin in the anterior cingulate cortex of adult mice

2024· article· en· W4396883109 on OpenAlexafffund
Yujie Ma, Jinjin Wan, Shun Hao, Qi‐Yu Chen, Min Zhuo

Bibliographic record

VenueMolecular Pain · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsLong-term potentiationAMPA receptorNeurosciencePostsynaptic potentialAnterior cingulate cortexSilent synapseForskolinExcitatory postsynaptic potentialBiologyNMDA receptorInternal medicineReceptorMedicineStimulationInhibitory postsynaptic potential

Abstract

fetched live from OpenAlex

Recent studies using different experimental approaches demonstrate that silent synapses may exist in the adult cortex including the sensory cortex and anterior cingulate cortex (ACC). The postsynaptic form of long-term potentiation (LTP) in the ACC recruits some of these silent synapses and the activity of calcium-stimulated adenylyl cyclases (ACs) is required for such recruitment. It is unknown if the chemical activation of ACs may recruit silent synapses. In this study, we found that activation of ACs contributed to synaptic potentiation in the ACC of adult mice. Forskolin, a selective activator of ACs, recruited silent responses in the ACC of adult mice. The recruitment was long-lasting. Interestingly, the effect of forskolin was not universal, some silent synapses did not undergo potentiation or recruitment. These findings suggest that these adult cortical synapses are not homogenous. The application of a selective calcium-permeable AMPA receptor inhibitor 1-naphthyl acetyl spermine (NASPM) reversed the potentiation and the recruitment of silent responses, indicating that the AMPA receptor is required. Our results strongly suggest that the AC-dependent postsynaptic AMPA receptor contributes to the recruitment of silent responses at cortical LTP.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.052
GPT teacher head0.374
Teacher spread0.321 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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