Progesterone-binding modified hyperbranched polyglycerols : synthesis, characterization and biological assessment
Bibliographic record
Abstract
Traumatic brain injury (TBI) has been proven as an established risk factor of Alzheimer’s disease (AD). Historically, progesterone (Pro) has been found to promote recovery from moderate TBI. However, the utility of this drug as a TBI treatment is severely hampered by its near total insolubility in water due to its hydrophobicity, which contributes to an inability to rapidly administer the drug after injury. The present work describes the synthesis, characterization, development and in vitro evaluation of nanoparticulate formulations of Pro for treatment of TBI. The nanoparticles developed for Pro consist of a library of hyperbranched polyglycerols (HPGs), which were hydrophobically modified with alkyl chains (C₆,₈,₁₀,₁₂,₁₄,₁₈) to enable loading the hydrophobic drug, and were further modified with MPEG chains to increase the solubility and stability of the formulations. Hydrophobically derivatized HPGs (HPG-Cn-MPEG), also known as dHPG(Cn), were characterized by GPC and NMR methods. Pro encapsulation by and release from the drug-binding pocket was determined through a reverse-phase UPLC method. Combination of binding, release and kinetic studies of the dHPG(Cn)/Pro library presented a relatively high number of drug molecules encapsulated, slow release and stable formulations. In vitro assays, including blood biocompatibility, cytotoxicity and cellular uptake, were performed on dHPG(Cn)/Pro. Blood biocompatibility studies demonstrated that the polymer-drug formulations do not cause significant changes in blood coagulation time (APTT assay), nor have they significant effects on red blood cell aggregation, lysis or platelet aggregation. There was no platelet activation observed in this study. Study of viability of human cortical microvascular endothelial cells and human astrocytoma cells in the presence of dHPG(Cn)/Pro demonstrated no toxicity. Studies on the same cells presented significant uptake with relatively even distribution of the formulation inside the cells. Further investigations indicated no degradation pathway for dHPG(Cn) over short periods of time (~ 8 h). Overall, the in vitro studies suggest that dHPG(Cn) are compatible and harmless to cells, suitable for carrying hydrophobic drugs and molecules, such as Pro, to the target tissues.
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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".