Peripheral Blood Mononuclear Cells from Patients with Type 1 Diabetes and Diabetic Retinopathy Produce Higher Levels of IL-17A, IL-10 and IL-6 and Lower Levels of IFN-γ—A Pilot Study
Bibliographic record
Abstract
Inflammation is key to the pathogenesis of diabetic retinopathy (DR). This prospective study investigated alterations in inflammatory cytokines in peripheral blood mononuclear cells (PBMCs) in 41 people with type 1 diabetes (T1D), sub-grouped into mild non-proliferative DR (mNPDR; n = 13) and active and inactive (each n = 14) PDR. Age/gender-matched healthy controls (n = 13) were included. PBMCs were isolated from blood samples. Intracellular cytokine expression by PBMCs after 16-h stimulation (either E. coli lipopolysaccharide (LPS), phorbol 12-myristate 13-acetate plus ionomycin, D-glucose or D-mannitol) were assessed by flow cytometry. Cytokine production in plasma, non-stimulated and LPS-stimulated PBMC supernatant was also assessed. Increased BMC IL-10 secretion and reduced expression of IL-6 and IFN-γ in CD3+ cells were observed in mNPDR. Reduced IL-6 and IL-10 secretion, and higher levels of intracellular IL-6 expression, especially in CD11b+ PBMCs, was detected in aPDR; levels were positively correlated with DR duration. Patients with T1D demonstrated increased intracellular expression of IL-17A in myeloid cells and reduced IFN-γ expression in CD3+ cells. Plasma levels of IL-1R1 were increased in mNPDR compared with controls. Results suggest that elevated PBMC-released IL-10, IL-6, in particular myeloid-produced IL-17A, may be involved in early stages of DR. IL-6-producing myeloid cells may play a role in PDR development.
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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) | 0.003 | 0.001 |
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".