CXCL1/CXCL8 (GROα/IL-8) in human diabetic ketoacidosis plasma facilitates leukocyte recruitment to cerebrovascular endothelium in vitro
Bibliographic record
Abstract
Diabetic ketoacidosis (DKA) in children is associated with intracranial vascular complications, possibly due to leukocyte-endothelial interactions. Our aim was to determine whether DKA-induced inflammation promoted leukocyte adhesion to activated human cerebrovascular endothelium. Plasma was obtained from children with type 1 diabetes either in acute DKA or in an insulin-controlled state (CON). Plasma concentrations of 21 inflammatory analytes were compared between groups. DKA was associated with altered circulating levels of ↑CXCL1 (GROα), ↑CXCL8 (IL-8), ↑IL-6, ↑IFNα2, and ↓CXCL10 (IP-10) compared with CON. These plasma analyte measurements were then used to create physiologically relevant cytokine mixtures (CM). Human cerebral microvascular endothelial cells (hCMEC/D3) were stimulated with either plasma (DKA-P or CON-P) or CM (DKA-CM or CON-CM) and assessed for polymorphonuclear leukocyte (PMN) adhesion. Stimulation of hCMEC/D3 with DKA-P or DKA-CM increased PMN adhesion to hCMEC/D3 under "flow" conditions. PMN adhesion to hCMEC/D3 was suppressed with neutralizing antibodies to CXCL1/CXCL8 or their hCMEC/D3 receptors CXCR1/CXCR2. DKA-P, but not DKA-CM, initiated oxidative stress in hCMEC/D3. Expression of ICAM-1, VCAM-1, and E-selectin were unaltered on hCMEC/D3 by either DKA-P or DKA-CM. In summary, DKA elicits inflammation in children associated with changes in circulating cytokines/chemokines. Increased CXCL1/CXCL8 instigated PMN adhesion to hCMEC/D3, possibly contributing to DKA-associated intracranial vascular complications.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".