The Relationship between Protein C, Protein S and Cytokines in Acute Ischemic Stroke
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The role of inflammation in the pathogenesis of acute ischemic stroke is well known, but its association with the clinical picture is as yet unclear. MATERIAL AND METHODS: In our study, we measured the serum levels of the proinflammatory cytokines interleukin-1beta (IL-1beta), tumor necrosis factor alpha (TNFalpha) and interleukin-6 (IL-6) within the first 50 h of stroke in 60 acute stroke patients, and examined the association with the natural anticoagulants protein C and free protein S. We compared the results with a control group that consisted of 30 volunteers. We also correlated their levels with the clinical outcomes by using the Canadian Neurological Scale (CNS). RESULTS: Neither stroke patients nor the control group had any elevations in IL-1beta serum levels. However, the levels of serum IL-6 were significantly higher in stroke patients (13.7 +/- 19.46 vs. 4.3 +/- 15.88, p = 0.002). In addition, the protein S levels of patients were lower than those of the controls (84.36 +/- 27.97 vs. 95.9 +/- 25.64, p = 0.007). Although IL-6 showed negative correlation with protein S (r = -0.504, p = 0.000), the other studied cytokines TNFalpha and IL-1beta did not correlate with these natural anticoagulants. Another negative correlation was found between IL-6 and CNS scores (r = -0.451, p = 0.000). In addition, both protein C and protein S positively correlated with CNS (r = 0.263, p = 0.042; r = 0.381, p = 0.003). There was also a positive correlation between protein C and protein S (r = 0.408, p = 0.001). CONCLUSIONS: Our results suggest that TNFalpha and IL1beta serum levels are not elevated in the acute phase of stroke and have no correlation with the natural anticoagulants protein C and protein S. However, a decrease in free protein S may be related to elevated IL-6 levels. In addition, increased levels of IL-6 and reduced levels of protein C and protein S may play a role in acute ischemic stroke severity.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it