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Excitatory and inhibitory responses in the brain to experimental pain: A systematic review of MR spectroscopy studies

2020· review· en· W3015276615 on OpenAlexafffund
Jessica Archibald, Erin L. MacMillan, Alinda Enzler, Catherine R. Jutzeler, Petra Schweinhardt, John L. K. Kramer

Bibliographic record

VenueNeuroImage · 2020
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsPhilips (Canada)University of British Columbia HospitalSimon Fraser UniversityUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesCARE Canada
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología, ParaguayNational Science FoundationConsejo Nacional de Ciencia y TecnologíaCraig H. Neilsen FoundationPhilipsSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsGlutamineGlutamate receptorContext (archaeology)Chronic painMedicineInhibitory postsynaptic potentialNoxious stimulusNeuroscienceMetaboliteAnesthesiaInternal medicineChemistryPsychologyNociceptionBiochemistryBiologyAmino acid

Abstract

fetched live from OpenAlex

BACKGROUND: H-MRS). The advantage of MRS compared to other techniques is the capacity to non-invasively examine metabolites involved in neurotransmission of pain, including glutamate, γ-aminobutyric acid (GABA), glutamate ​+ ​glutamine (Glx), and glutamine. OBJECTIVE: To systematically review MRS studies used in the context of studying experimental pain in healthy human participants. DATA SOURCES: PubMed, Ovid Medline, and Embase databases were searched using pre-specified search terms. ELIGIBILITY CRITERIA: Studies investigating glutamate, GABA, Glx and/or glutamine in relation to experimental pain (e.g., heat) in healthy participants via MRS. APPRAISAL CRITERIA: Each study was evaluated with a modified quality criterion (used in previous imaging systematic reviews) as well as a risk of bias assessment. RESULTS: From 5275 studies, 14 met the selection criteria. Studies fell into two general categories, those examining changes in metabolites triggered by noxious stimulation or examining the relationship between sensitivity to pain and resting metabolite levels. In five (out of ten) studies, glutamate, Glx and/or glutamine increased significantly in response to experimental pain (compared to baseline) in three different brain areas. To date, there is no evidence to suggest Glx, glutamate or glutamine levels decrease, suggesting an overall effect in favour of increased excitation to pain. In addition to no changes, both increases and decreases were reported for levels of GABA+ (=GABA ​+ ​macromolecules). A positive correlation between pain sensitivity and resting glutamate and Glx levels were reported across three studies (out of three). Further research is needed to examine the relationship of GABA+ and pain sensitivity. LIMITATIONS: A major limitation of our review was a limited number of studies that used MRS to examine experimental pain. In light of this and major differences in study design, we did not attempt to aggregate results in a meta-analysis. As for the studies we reviewed, there was a limited number of brain areas were examined by studies included in our review. Moreover, the majority of studies included lacked an adequate control condition (i.e., non-noxious stimulation) or blinding, which represent a major source of potential bias. CONCLUSION: MRS represents a promising tool to examine the brain in pain, functionally, and at rest with support for increased glutamate, glutamine and Glx levels in relation to pain. IMPLICATIONS: Resting and functional MRS should be viewed as complementary to existing neuroimaging techniques, and serve to investigate the brain in pain. Systematic review registration number- CRD42018112917.

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)0.011
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0150.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.087
GPT teacher head0.411
Teacher spread0.324 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations23
Published2020
Admission routes2
Has abstractyes

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