Biodistribution of Native and Nanoformulated Innate Defense Regulator Peptide 1002
Bibliographic record
Abstract
Innate defense regulator-1002 (IDR-1002) is a synthetic peptide with promising immunomodulatory and antibiofilm properties. An appreciable body of work exists around its mechanism of action at the cellular and molecular level, along with its efficacy across several infection and inflammation models. However, little is known about its absorption, distribution, and excretion in live organisms. Here, we performed a comprehensive biodistribution assessment with a gallium-67 radiolabeled derivative of IDR-1002 using nuclear tracing techniques. Various dose levels of the radiotracer (2-40 mg/kg) were administered into the blood, peritoneal cavity, and subcutaneous tissue, or instilled into the lungs. The peptide was well tolerated at all subcutaneous and intraperitoneal doses, although higher levels were associated with delayed absorption kinetics and precipitation of the peptide within the tissues. Low intratracheal doses were rapidly absorbed systemically, and small increases in the dose level were lethal. Intravenous doses were rapidly cleared from the blood at lower levels, and upon escalation, were toxic with a high proportion of the dose accumulating within the lung tissue. To improve biocompatibility and prolong its circulation within the blood, IDR-1002 was further formulated onto high molecular weight hyperbranched polyglycerol (HPG) polymers. Constructs prepared at 5:1 and 10:1 peptide-to-polymer ratios were colloidally stable, maintained the biological profile of the peptide payload and helped reduce red blood cell lysis. The 5:1 construct circulated well in the blood, but higher peptide loading was associated with rapid clearance by the reticuloendothelial system. Many peptides face pharmacokinetic and biocompatibility challenges, but formulations such as those with HPG have the potential to overcome these limitations.
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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) | 0.000 | 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 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".