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Spinal microglia are required for long-term maintenance of neuropathic pain

2017· article· en· W2715463416 on OpenAlexaff
Stefania Echeverry, Xiang Shi, Mu Yang, Hao Huang, Yichen Wu, Louis-Étienne Lorenzo, Jimena Pérez-Sánchez, Robert P. Bonin, Yves De Koninck, Ji Zhang

Bibliographic record

VenuePain · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de QuébecMcGill University
Fundersnot available
KeywordsMicrogliaMedicineNeuropathic painNerve injuryChronic painSpinal cordNeurosciencePeripheral nerve injurySaporinNeurotrophic factorsNociceptorNociceptionAnesthesiaSciatic nerveInflammationImmunologyReceptorInternal medicineImmunotoxinBiologyPhysical therapy

Abstract

fetched live from OpenAlex

While spinal microglia play a role in early stages of neuropathic pain etiology, whether they are useful targets to reverse chronic pain at late stages remains unknown. Here, we show that microglia activation in the spinal cord persists for >3 months following nerve injury in rodents, beyond involvement of proinflammatory cytokine and chemokine signalling. In this chronic phase, selective depletion of spinal microglia in male rats with the targeted immunotoxin Mac1-saporin and blockade of brain-derived neurotrophic factor-TrkB signalling with intrathecal TrkB Fc chimera, but not cytokine inhibition, almost completely reversed pain hypersensitivity. By contrast, local spinal administration of Mac1-saporin did not affect nociceptive withdrawal threshold in control animals nor did it affect the strength of afferent-evoked synaptic activity in the spinal dorsal horn in normal conditions. These findings show that the long-term, chronic phase of nerve injury-induced pain hypersensitivity is maintained by microglia-neuron interactions. The findings also effectively separate the central signalling pathways underlying the maintenance phase of the pathology from the early and peripheral inflammatory reactions to injury, pointing to different targets for the treatment of acute vs chronic injury-induced 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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
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 head0.039
GPT teacher head0.311
Teacher spread0.272 · 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 designObservational
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

Citations118
Published2017
Admission routes1
Has abstractyes

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