Evidence map›Paper›PMID 36156899›Full record

ArticleJournal of pain research2022

Activation of Neuroinflammation via mTOR Pathway is Disparately Regulated by Differential Target Multiplexed and Traditional Low-Rate Spinal Cord Stimulation in a Neuropathic Pain Model.

Dana M Tilley, Ricardo Vallejo, Francesco Vetri, David C Platt, David L Cedeno

Abstract read
In one paragraph

Article in Journal of pain research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Dana M TilleyResearch and Development, SGX Medical, Bloomington, IL, USA.ORCID 0000-0003-1884-1927
Ricardo VallejoResearch and Development, SGX Medical, Bloomington, IL, USA.
Francesco VetriResearch Department, National Spine and Pain Centers, Bloomington, IL, USA.
David C PlattResearch and Development, SGX Medical, Bloomington, IL, USA.
David L CedenoResearch and Development, SGX Medical, Bloomington, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Spinal cord stimulation (SCS) has been used for decades to treat neuropathic pain conditions with limited understanding of its mechanisms of action. The mTOR pathway is a well-known co-factor in chronic pain and has not been previously linked to SCS therapy. Proteomic and phosphorylation analyses allow capturing a broad view of tissue response to an injury model and subsequent therapies such as SCS. Here, we evaluated the effect of differential target multiplexed SCS programming (DTMP) and traditional low-rate spinal cord stimulation (LR-SCS) on the mTOR pathway using proteomic and phosphoproteomic analyses. Methods: The spared nerve injury (SNI) model of neuropathic pain in animals was established followed by continuous treatment with either DTMP or LR-SCS for 48 hours. Control groups included sham-stimulated (No-SCS) and uninjured animals (No-SNI). Proteins were extracted from spinal cord tissue removed post-stimulation and subjected to liquid chromatography/tandem mass spectrometry to assess changes in protein expression and states of phosphorylation. Bioinformatics tools and literature were used to identify mTOR-related proteins in the various groups. Results: Over 7000 proteins were identified and filtered to find 1451 and 705 proteins significantly affected by DTMP and LR-SCS (p < 0.05), respectively, relative to No-SCS. Literature and bioinformatic tools yielded 192 mTOR-related proteins that were cross-referenced to the list of DTMP and LR-SCS affected proteins. Of these proteins, 49 were found in the proteomic dataset. Eight of these proteins showed a significant response to the pain model, 25 were significantly modulated by DTMP, and 8 by LR-SCS. Phosphoproteomic analyses yielded 119 mTOR-related phosphoproteins affected by the injury model with a 66% reversal following DTMP versus a 58% reversal by LR-SCS. Conclusion: Proteomic and phosphoproteomic analyses support the hypothesis that DTMP, and to a lesser extent LR-SCS, reverse injury induced changes of the mTOR pathway while treating neuropathic pain.

Indexed as

central sensitizationinflammationnerve injuryphosphoproteomic analysisproteomic analysis

Identifiers

PMID36156899
PMCPMC9507284

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.