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Record W1683401737 · doi:10.1016/j.celrep.2015.07.001

Role of Prelimbic GABAergic Circuits in Sensory and Emotional Aspects of Neuropathic Pain

2015· article· en· W1683401737 on OpenAlexafffund
Zizhen Zhang, Vinícius M. Gadotti, Lina Chen, Ivana A. Souza, Patrick L. Stemkowski, Gerald W. Zamponi

Bibliographic record

VenueCell Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesMitacsCanada Research ChairsCanadian Diabetes Association
KeywordsOptogeneticsNeuroscienceGABAergicChannelrhodopsinInhibitory postsynaptic potentialExcitatory postsynaptic potentialNociceptorSensory systemNeuropathic painNociceptionParvalbuminInfralimbic cortexPrefrontal cortexPsychologyMedicineInternal medicineReceptor

Abstract

fetched live from OpenAlex

Noxious stimuli are detected by peripheral nociceptors and then transmitted to higher CNS centers, where they are perceived as an unpleasant sensation. The mechanisms that govern the emotional component associated with pain are still incompletely understood. Here, we used optogenetic approaches both in vitro and in vivo to address this issue. We found that peripheral nerve injury inhibits pyramidal cell firing in the prelimbic area of the prefrontal cortex as a result of feed-forward inhibition mediated by parvalbumin-expressing GABAergic interneurons. In addition, activation of inhibitory archaerhodopsin or excitatory channelrhodopsin-2 in these neurons decreased and increased pain responses, respectively, in freely moving mice and accordingly modulated conditioned place preference scores and place escape/avoidance behavior. Our findings thus demonstrate an important role of the prelimbic area in sensory and emotional aspects of pain and identify GABAergic circuits in this region as a potential target for pain therapeutics.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.234
Teacher spread0.215 · 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

Citations231
Published2015
Admission routes2
Has abstractyes

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