Rapid structural transformation of ionizable lipid nanoparticles involving Omega-3 polyunsaturated fatty acids enhances antioxidant defense and mitochondrial proteins activity in pH-responsive drug delivery
Bibliographic record
Abstract
Inefficient intracellular delivery remains a major bottleneck in the development of nanomedicines targeting brain disorders. To address this challenge, we present a dynamic structural nanomedicine platform based on ionizable liquid crystalline lipid nanoparticles (LC-LNPs) incorporating omega-3 polyunsaturated fatty acids (PUFAs), enabling pH-responsive transformation and neuroprotective drug delivery. The created multidrug-loaded nonlamellar LC-LNP co-encapsulated the antioxidants ginkgolide B and quercetin and were functionalized with the bioactive cell-penetrating pituitary adenylate cyclase-activating polypeptide (PACAP) for targeted neuronal delivery. The time-resolved synchrotron SAXS study revealed that the PUFA-LNPs exploit the inherent pH-sensitivity of DHA and EPA to undergo a rapid, millisecond-timescale pH-dependent structural transformation from a hexagonal mesophase (lattice parameter shrinkage from 6.14 nm to ∼5.57 nm within 200 ms). This dynamic mechanism, triggered by acidic pH, induces a more compact LNP nanostructure that promotes the efficient release of poorly soluble antioxidant compounds. The in vivo safety study following intranasal administration in C57BL/6 J mice established excellent biocompatibility for nose-to-brain drug delivery. The multidrug-loaded LC-LNPs induced significant neuroprotective transcriptomic changes, including the upregulation of mitochondrial, antioxidant, and neurotrophic markers alongside suppression of pro-apoptotic genes. The in vitro studies confirmed that PUFA-LNPs effectively modulate mitochondrial protein activity (e.g., a 1.5-fold increase in ATP synthase expression), enhance mitochondrial resilience, antioxidant enzyme function (GSH-Px), and positively influence ROS-associated signaling pathways. Thanks to the ionizable carboxyl groups of PUFAs, which confer their intrinsic pH-sensitive properties, we achieved precisely characterized, pH-responsive structural reorganization of the LNPs, enabling enhanced intracellular drug delivery and synergistic neuroprotection of neuronal cells.
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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 | 0.000 | 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 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".