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Record W2131156766 · doi:10.4049/jimmunol.1001241

Painful Pathways Induced by TLR Stimulation of Dorsal Root Ganglion Neurons

2011· article· en· W2131156766 on OpenAlexaff
Qi Jia, Krisztina Buzás, Huiting Fan, Jeffrey I. Cohen, Kening Wang, Erik K. Mont, Dennis M. Klinman, Joost J. Oppenheim, O. M. Zack Howard

Bibliographic record

VenueThe Journal of Immunology · 2011
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsNova Scotia Hospital
FundersNational Cancer InstituteNational Institutes of Health
KeywordsTRPV1Dorsal root ganglionStimulationCXCL10Transient receptor potential channelChemokineCell biologyProinflammatory cytokineReceptorNociceptionChemistryNociceptorNeuroscienceBiologyImmunologyInflammationSensory system

Abstract

fetched live from OpenAlex

We hypothesize that innate immune signals from infectious organisms and/or injured tissues may activate peripheral neuronal pain signals. In this study, we demonstrated that TLRs 3, 7, and 9 are expressed by human dorsal root ganglion neurons (DRGNs) and in cultures of primary mouse DRGNs. Stimulation of murine DRGNs with TLR ligands induced expression and production of proinflammatory chemokines and cytokines CCL5 (RANTES), CXCL10 (IP-10), IL-1α, IL-1β, and PGE(2), which have previously been shown to augment pain. Further, TLR ligands upregulated the expression of a nociceptive receptor, transient receptor potential vanilloid type 1 (TRPV1), and enhanced calcium flux by TRPV1-expressing DRGNs. Using a tumor-induced temperature sensitivity model, we showed that in vivo administration of a TLR9 antagonist, known as a suppressive oligodeoxynucleotide, blocked tumor-induced temperature sensitivity. Taken together, these data indicate that stimulation of peripheral neurons by TLR ligands can induce nerve 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.037
GPT teacher head0.255
Teacher spread0.218 · 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

Citations166
Published2011
Admission routes1
Has abstractyes

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