Therapeutic Insulin Analogue Concentrations at Infusion Sites Enhanced the Pro-Inflammatory Response and Apoptosis in an In Vitro Macrophage-Material Interaction Model
Bibliographic record
Abstract
Continuous subcutaneous insulin infusion for Type 1 diabetes relies upon insulin infusion sets (IIS) to reliably deliver insulin to a subcutaneous depot, where it is absorbed into systemic circulation. However, IIS are plagued by short wear times and high failure rates, due in part to inconsistent insulin absorption that can arise over time. While emerging evidence suggests that the local inflammatory response to the IIS cannula may impact both wear times and unreliable insulin adsorption, the mechanisms are poorly understood. Here, we investigated the effects of local infused insulin concentrations on the biomaterial host response to better understand the underlying factors that limit the IIS performance. We first modeled the insulin concentration for a constant basal infusion rate to select a relevant insulin concentration range of 0.1-10 U/mL within the infusion site. We then examined the influence of a commercial insulin analogue (Humulin-N) using an in vitro macrophage-material model, which uses adsorbed fibroblast lysate (containing damage-associated molecular patterns) to activate macrophages and recapitulates macrophage responses on implanted biomaterials. RAW-Blue macrophages cultured on lysate-adsorbed surfaces had increased nuclear factor-κB (NF-κB) and activating protein 1 (AP-1) activity and intracellular reactive oxygen species (ROS) accumulation compared to control surfaces. Humulin-N concentration (0.5-10 U/mL) enhanced the NF-κB/AP-1 activity and ROS accumulation in macrophages on lysate-adsorbed surfaces. However, Humulin-N had no effect on NF-κB/AP-1 or ROS in the absence of the inflammatory stimulus. Additionally, high insulin concentrations arising from therapeutic doses induced macrophage apoptosis with and without adsorbed lysate. This study contributes to emerging evidence that infused insulin affects the tissue response to IIS.
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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 | 0.001 |
| 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".