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Record W4318913464 · doi:10.1161/strokeaha.122.041422

Rapid Activation of Neuroinflammation in Stroke: Plasma and Extracellular Vesicles Obtained on a Mobile Stroke Unit

2023· article· en· W4318913464 on OpenAlexaff
Robert G. Kowalski, Aurélie Ledreux, John Violette, Robert Neumann, David Ornelas, Xiaoli Yu, Steven G. Griffiths, Scott Lewis, Priscilla Nash, Andrew A. Monte, Christina Coughlan, Clayton Deighan, James C. Grotta, William Jones, Michael W. Graner

Bibliographic record

VenueStroke · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsInternational Game Technology (Canada)Université de Moncton
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical Sciences
KeywordsMedicineNeuroinflammationModified Rankin ScaleStroke (engine)BiomarkerInternal medicineInterquartile rangeGlial fibrillary acidic proteinThrombolysisTissue plasminogen activatorInflammationIschemiaIschemic strokeImmunohistochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Neuroinflammation is ubiquitous in acute stroke and worsens outcome. However, the precise timing of the inflammatory response is unknown, hindering the design of acute anti-inflammatory therapeutic interventions. We sought to identify the onset of the neuroinflammatory cascade using a mobile stroke unit. METHODS: The study is a proof-of-concept, cohort investigation of ultra-early blood- and extracellular vesicle-derived markers of neuroinflammation and outcome in acute stroke. Blood was obtained, prehospital, on an mobile stroke unit. Outcomes were biomarker concentrations, modified Rankin Scale score, and National Institutes of Health Stroke Scale score. RESULTS: Forty-one adults were analyzed, including 15 patients treated on the mobile stroke unit between August 2021 and April 2022, and 26 healthy controls to establish biomarker reference levels. Median patient age was 74 (range, 36-97) years, 60% were female, and 80% White. Ten (67%) were diagnosed as stroke, with 8 (53%) confirmed and 2 likely transient ischemic attack or stroke averted by thrombolysis; 5 were stroke mimics. For strokes, median initial National Institutes of Health Stroke Scale score was 11 (range, 4-19) and 6 (75%) received tPA (tissue-type plasminogen activator). Blood was obtained a median of 58 (range, 36-133) minutes after symptom onset. Within 36 minutes after stroke, plasma IL-6 (interleukin-6), neurofilament light chain, UCH-L1 (ubiquitin C-terminal hydrolase L1), and GFAP (glial fibrillary acidic protein) were elevated by as much as 10 times normal. In EVs, MMP-9 (matrix metalloproteinase-9), CXCL4 (chemokine (C-X-C motif) ligand 4), CRP (C-reactive protein), IL-6, OPN (osteopontin), and PECAM1 (platelet and endothelial cell adhesion molecule 1) were elevated. Inflammatory markers increased rapidly in the first 2 hours and continued rising for 24 hours. CONCLUSIONS: The neuroinflammatory cascade was found to be activated within 36 to 133 minutes after stroke and progresses rapidly. This is earlier than observed previously in humans and suggests injury from neuroinflammation occurs faster than had been surmised. These findings could inform development of acute immunomodulatory stroke therapies and lead to new diagnostic tools and improved outcomes.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.260
Teacher spread0.221 · 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 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

Citations40
Published2023
Admission routes1
Has abstractyes

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