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 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 | 0.000 |
| 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) | 0.002 | 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".