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Record W2007298657 · doi:10.1016/s0924-9338(09)70318-9

Cortical Mechanisms for Emotional Fear and Chronic Pain

2009· article· en· W2007298657 on OpenAlexaff
Min Zhuo

Bibliographic record

VenueEuropean Psychiatry · 2009
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNeuroscienceChronic painAnterior cingulate cortexLong-term potentiationPsychologySynaptic plasticityPrefrontal cortexCognitionNeuroplasticityMedicineReceptor

Abstract

fetched live from OpenAlex

Investigation of molecular and cellular mechanisms of synaptic plasticity is the major focus of many neuroscientists. There are two major reasons for searching new genes and molecules contributing to central plasticity: first, it provides basic neural mechanism for learning and memory, a key function of the brain; second, it provides new targets for treating brain-related disease. Here, I propose that LTP in the anterior cingulate cortex (ACC) as a synaptic model for emotional fear and chronic pain in the brain. Integrative approaches including genetic, neurobiological and physiological methods are used to investigate the roles of cortical neurons and microglia in synaptic LTP, fear and chronic pain. We have identified several key calcium-stimulated signaling molecules including AC1, CaMKIV and FMRP for AMPA receptor mediated cingulate LTP, trace fear memory, and chronic pain. By contrast, microglia only contributes to changes in spinal dorsal horn, but not in the cortex. Our findings strongly suggest that ACC LTP may serve as a cellular model for studying central sensitization that related to fear and chronic pain, as well as pain-related cognitive emotional disorders.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.622
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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 designTheoretical or conceptual
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
Published2009
Admission routes1
Has abstractyes

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