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Record W1988868629 · doi:10.1093/brain/awl296

The cellular inflammatory response in human spinal cords after injury

2006· article· en· W1988868629 on OpenAlexafffund
Judith C. Fleming, M. D. Norenberg, David A. Ramsay, Gregory A. Dekaban, Alex E. Marcillo, Alvaro D. Saenz, Melissa A. Pasquale‐Styles, W. Dalton Dietrich, Lynne C. Weaver

Bibliographic record

VenueBrain · 2006
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsWestern UniversityRobarts Clinical TrialsLondon Health Sciences Centre
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Neurological Disorders and StrokeOntario Neurotrauma FoundationLondon Health Sciences Centre
KeywordsExtravasationMicrogliaInflammationSpinal cord injuryMedicinePathologySpinal cordPathologicalWallerian degenerationCD68NecrosisImmunohistochemistryImmunology

Abstract

fetched live from OpenAlex

Spinal cord injury (SCI) provokes an inflammatory response that generates substantial secondary damage within the cord but also may contribute to its repair. Anti-inflammatory treatment of human SCI and its timing must be based on knowledge of the types of cells participating in the inflammatory response, the time after injury when they appear and then decrease in number, and the nature of their actions. Using post-mortem spinal cords, we evaluated the time course and distribution of pathological change, infiltrating neutrophils, monocytes/macrophages and lymphocytes, and microglial activation in injured spinal cords from patients who were 'dead at the scene' or who survived for intervals up to 1 year after SCI. SCI caused zones of pathological change, including areas of inflammation and necrosis in the acute cases, and cystic cavities with longer survival (Zone 1), mantles of less severe change, including axonal swellings, inflammation and Wallerian degeneration (Zone 2) and histologically intact areas (Zone 3). Zone 1 areas increased in size with time after injury whereas the overall injury (size of the Zones 1 and 2 combined) remained relatively constant from the time (1-3 days) when damage was first visible. The distribution of inflammatory cells correlated well with the location of Zone 1, and sometimes of Zone 2. Neutrophils, visualized by their expression of human neutrophil alpha-defensins (defensin), entered the spinal cord by haemorrhage or extravasation, were most numerous 1-3 days after SCI, and were detectable for up to 10 days after SCI. Significant numbers of activated CD68-immunoreactive ramified microglia and a few monocytes/macrophages were in injured tissue within 1-3 days of SCI. Activated microglia, a few monocytes/macrophages and numerous phagocytic macrophages were present for weeks to months after SCI. A few CD8(+) lymphocytes were in the injured cords throughout the sampling intervals. Expression by the inflammatory cells of the oxidative enzymes myeloperoxidase (MPO) and nicotinamide adenine dinucleotide phosphate oxidase (gp91(phox)), and of the pro-inflammatory matrix metalloproteinase (MMP)-9, was analysed to determine their potential to cause oxidative and proteolytic damage. Oxidative activity, inferred from MPO and gp91(phox) immunoreactivity, was primarily associated with neutrophils and activated microglia. Phagocytic macrophages had weak or no expression of MPO or gp91(phox). Only neutrophils expressed MMP-9. These data indicate that potentially destructive neutrophils and activated microglia, replete with oxidative and proteolytic enzymes, appear within the first few days of SCI, suggesting that anti-inflammatory 'neuroprotective' strategies should be directed at preventing early neutrophil influx and modifying microglial activation.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.344
Teacher spread0.328 · 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

Citations863
Published2006
Admission routes2
Has abstractyes

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