Dysfunctional crosstalk between macrophages and fibroblasts under LPS-infected and hyperglycemic environment in diabetic wounds
Bibliographic record
Abstract
Diabetic wounds, especially diabetic foot ulcers, present a major clinical challenge due to delayed healing and prolonged inflammation. Macrophage-fibroblast interactions are essential for wound repair, yet this crosstalk is disrupted in diabetic wounds due to hyperglycemia and bacterial infection. This study investigates the dysfunctional communication between macrophages and fibroblasts, focusing on autocrine, paracrine, and juxtacrine signaling in simulated diabetic environments. Using monoculture and co-culture models of THP-1-derived macrophages and primary human dermal fibroblasts, we simulated conditions of normal glucose, LPS-induced infection, high glucose (with AGEs), and combined high glucose (with AGEs) and LPS. Macrophages in hyperglycemic and LPS-infected environments exhibited a pro-inflammatory M1 phenotype with elevated expression of CD80, and STAT1 and increased production of IL-1β, TNF-α, and MMP9. Fibroblast migration was significantly impaired under high glucose conditions, particularly in paracrine model. Secretome profiling showed heightened pro-inflammatory cytokines and proteases, with reduced anti-inflammatory markers (IL-10 and VEGF-A) under hyperglycemic conditions. Paracrine signaling exacerbated the inflammatory response, while juxtacrine signaling showed more moderate effects, conducive to healing. These findings highlight the pathological macrophage-fibroblast crosstalk in diabetic wounds, particularly under hyperglycemic and LPS-infected conditions, offering insights for potential immunomodulatory therapies aimed at restoring effective signaling and improving wound healing outcomes.
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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 | 0.001 | 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".