Bacterial lipopolysaccharide is associated with stroke
Bibliographic record
Abstract
We aimed to determine if plasma levels of bacterial lipopolysaccharide (LPS) and lipoteichoic acid (LTA) are associated with different causes of stroke and correlate with C-reactive protein (CRP), LPS-binding protein (LBP), and the NIH stroke scale (NIHSS). Ischemic stroke (cardioembolic (CE), large artery atherosclerosis (LAA), small vessel occlusion (SVO)), intracerebral hemorrhage (ICH), transient ischemic attack (TIA) and control subjects were compared (n = 205). Plasma LPS, LTA, CRP, and LBP levels were quantified by ELISA. LPS and CRP levels were elevated in ischemic strokes (CE, LAA, SVO) and ICH compared to controls. LBP levels were elevated in ischemic strokes (CE, LAA) and ICH. LTA levels were increased in SVO stroke compared to TIA but not controls. LPS levels correlated with CRP and LBP levels in stroke and TIA. LPS, LBP and CRP levels positively correlated with the NIHSS and WBC count but negatively correlated with total cholesterol. Plasma LPS and LBP associate with major causes of ischemic stroke and with ICH, whereas LPS/LBP do not associate with TIAs. LTA only associated with SVO stroke. LPS positively correlated with CRP, LBP, and WBC but negatively correlated with cholesterol. Higher LPS levels were associated with worse stroke outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".