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Record W1966351672 · doi:10.1126/science.1191792

Alleviating Neuropathic Pain Hypersensitivity by Inhibiting PKMζ in the Anterior Cingulate Cortex

2010· article· en· W1966351672 on OpenAlexafffund
Xiang‐Yao Li, Hyoung‐Gon Ko, Tao Chen, Giannina Descalzi, Kohei Koga, Hansen Wang, Susan S. Kim, Yuze Shang, Chuljung Kwak, Soowon Park, Jaehoon Shim, Kyungmin Lee, Graham L. Collingridge, Bong‐Kiun Kaang, Min Zhuo

Bibliographic record

VenueScience · 2010
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNeuropathic painLong-term potentiationAnterior cingulate cortexNerve injuryPeripheral nerve injuryChronic painMedicineNeuroscienceAMPA receptorAnesthesiaGlutamate receptorReceptorSciatic nervePsychologyInternal medicineCognition

Abstract

fetched live from OpenAlex

Synaptic plasticity is a key mechanism for chronic pain. It occurs at different levels of the central nervous system, including spinal cord and cortex. Studies have mainly focused on signaling proteins that trigger these plastic changes, whereas few have addressed the maintenance of plastic changes related to chronic pain. We found that protein kinase M zeta (PKMζ) maintains pain-induced persistent changes in the mouse anterior cingulate cortex (ACC). Peripheral nerve injury caused activation of PKMζ in the ACC, and inhibiting PKMζ by a selective inhibitor, ζ-pseudosubstrate inhibitory peptide (ZIP), erased synaptic potentiation. Microinjection of ZIP into the ACC blocked behavioral sensitization. These results suggest that PKMζ in the ACC acts to maintain neuropathic pain. PKMζ could thus be a new therapeutic target for treating chronic pain.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
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 head0.010
GPT teacher head0.264
Teacher spread0.254 · 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

Citations407
Published2010
Admission routes2
Has abstractyes

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