Acid-Labile mPEG–Vinyl Ether–1,2-Dioleylglycerol Lipids with Tunable pH Sensitivity: Synthesis and Structural Effects on Hydrolysis Rates, DOPE Liposome Release Performance, and Pharmacokinetics
Bibliographic record
Abstract
A family of 3-methoxypoly(ethylene glycol)-vinyl ether-1,2-dioleylglycerol (mPEG-VE-DOG) lipopolymer conjugates, designed on the basis of DFT calculations to possess a wide range of proton affinities, was synthesized and tested for their hydrolysis kinetics in neutral and acidic buffers. Extruded ∼100 nm liposomes containing these constructs in ≥90 mol % 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) produced dispersions that retained their calcein cargo for more than 2 days at pH 7.5, but released the encapsulated contents over a wide range of time scales as a function of the electronic properties of the vinyl ether linkage, the solution pH, and the mPEG-VE-DOG composition in the membrane. The in vivo performance of two different 90:10 DOPE:mPEG-VE-DOG compositions was also evaluated for blood circulation time and biodistribution in mice, using (125)I-tyraminylinulin as a label. The pharmacokinetic profiles gave a t(1/2) of 7 and 3 h for 90:10 DOPE:ST302 and 90:10 DOPE:ST502, respectively, with the liposomes being cleared predominantly by liver and spleen uptake. The behavior of these DOPE:mPEG-VE-DOG formulations is consistent with their relative rates of vinyl ether hydrolysis, i.e., the more acid-sensitive mPEG-VE-DOG derivatives produced faster leakage rates from DOPE:mPEG-VE-DOG liposomes, but decreased the blood circulation times in mice. These findings suggest that the vinyl ether-based PEG-lipid derivatives are promising agents for stabilizing acid-sensitive DOPE liposomes to produce formulations with a priori control over their pH responsiveness in vitro. Our data also suggest, however, that the same factors that contribute to enhanced acid sensitivity of the DOPE:mPEG-VE-DOG dispersions are also likely responsible for their reduced pharmacokinetic profiles.
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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".