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Record W3123082989 · doi:10.1097/oi9.0000000000000011

Compartment syndrome-induced muscle injury is diminished by the neutralization of pro-inflammatory cytokines

2018· article· en· W3123082989 on OpenAlexaff
Erin Donohoe, Aurelia Bihari, Emil H. Schemitsch, David Sanders, Abdel‐Rahman Lawendy

Bibliographic record

VenueOTA International The Open Access Journal of Orthopaedic Trauma · 2018
Typearticle
Languageen
FieldMedicine
TopicMuscle and Compartmental Disorders
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineMicrocirculationCytokineProinflammatory cytokineChemokineTumor necrosis factor alphaIntravital microscopyInflammationIschemiaCremaster muscleImmunologyNecrosisInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Objectives: Compartment syndrome (CS) is one of the most devastating consequences of musculoskeletal trauma. The pathophysiology of CS includes elevation of intracompartmental pressure (ICP), causing damage to the microcirculation, decreased oxygen delivery, tissue anoxia, and cell death. CS is a combined ischemic and inflammatory condition that induces the systemic inflammatory cascade. In complete ischemia, within the first hour of reperfusion, a peak in the pro-inflammatory cytokine, tumor necrosis factor alpha (TNF-α) has been previously reported. The purpose of this study was to examine the suspected systemic inflammatory cytokine/chemokine release in response to CS, and to evaluate the microvascular dysfunction, tissue injury, and inflammatory response following the neutralization of pro-inflammatory cytokines TNF-α and/or interleukin-1 beta (IL-1β). Methods: Twenty-eight male Wistar rats were randomly assigned into 5 groups: Sham (no CS), CS (with isotype control), CS+TNF-α neutralizing antibody (NA), CS+IL-1β NA, CS+Combo (both TNF-α and IL-1β NA). CS was induced by elevation of ICP above 30 mm Hg through an infusion of isotonic saline into the anterior compartment of the hind limb for 2 hours; NA were administered just prior to fasciotomy. Microvascular perfusion, cellular tissue injury, and inflammatory response within the extensor digitorum longus muscle were assessed using intravital video microscopy for 45 minutes after fasciotomy. Systemic levels of 24 different cytokines/chemokines were also measured, using the xMAP Luminex technology. Results: Of the 24 cytokines/chemokines sampled, 6 were significantly elevated from their baseline levels, and included the pro-inflammatory cytokines TNF-α, IL-1β, growth-related oncogene/keratinocyte chemoattractant (GRO/KC), monocyte chemoattractant protein 1 (MCP-1), macrophage inflammatory protein 1 alpha (MIP-1α), and the anti-inflammatory cytokine IL-10. CS resulted in a significant decrease in microvascular perfusion, from 75 ± 2% continuously perfused capillaries in the sham to 31 ± 4% in CS ( P < .001), a significant increase in tissue injury (0.33 ± 0.4 versus 0.04 ± 0.01 in sham) and leukocyte activation (14 ± 2 adherent leukocytes/1000 μm 2 versus 2 ± 1 adherent leukocytes/100 μm 2 in sham, P < .001). CS-associated tissue injury was significantly decreased with TNF-α neutralization ( P < .05), both when administered alone or in combination with IL-1β ( P < .05). Additionally, TNF-α neutralization blocked CS-associated leukocyte activation ( P < .05); IL-1β neutralization also diminished leukocyte adhesion ( P < .05). Perfusion remained virtually unchanged in CS animals treated with NA (36 ± 4%, 32 ± 3% and 30 ± 2% in CS+TNF-α, CS+IL-1β and CS+Combo groups, respectively). Conclusion: The results of this study indicate that CS induces a systemic inflammation, as evidenced by upregulation of inflammatory cytokines/chemokines in circulation. Neutralization of TNF-α led to a significant reduction in tissue injury; however, it had no effect on the CS-induced microvascular dysfunction. This suggests a distinct role of TNF-α in the pathophysiology of muscle injury in CS.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.392
Teacher spread0.322 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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