The Acute Effect of Clamped Hyperglycemia on the Urinary Excretion of Inflammatory Cytokines/Chemokines in Uncomplicated Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Acute glycemic variability contributes to diabetic complications potentially through induction of inflammation. Our objective was to determine whether acute hyperglycemia affects urinary secretion of inflammatory cytokines/chemokines in humans with uncomplicated type 1 diabetes. RESEARCH DESIGN AND METHODS: Blood pressure, renal hemodynamics (inulin and paraaminohippurate clearances), and urine samples were obtained after 6 h of clamped euglycemia (4-6 mmol/l) and hyperglycemia (9-11 mmol/l) on two consecutive days in subjects with type 1 diabetes (n = 25). Forty-two urinary cytokines/chemokines were measured using a Luminex platform. RESULTS: Clamped hyperglycemia produced an expected increase in glomerular filtration rate (131 ± 4 to 148 ± 8 ml/min/1.73 m²). Clamped hyperglycemia was associated with significant increases in urinary eotaxin, fibroblast growth factor-2, granulocyte-macrophage colony-stimulating factor, interferon-α 2, interleukin-2 and -12, monocyte chemoattractant protein-3, macrophage-derived chemokine, macrophage inflammatory protein-1α, platelet-derived growth factor, tumor necrosis factor-α, and CD40 ligand (P < 0.05). CONCLUSIONS: Acute hyperglycemia results in increased urinary excretion of inflammatory cytokines/chemokines in humans with uncomplicated type 1 diabetes, and this may contribute to kidney injury.
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 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 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".