Design of block-copolymer-based micelles for active and passive targeting
Bibliographic record
Abstract
A self-consistent field study is presented on the design of active and passive targeting block-copolymeric micelles. These micelles form in water by self-assembly of triblock copolymers with a hydrophilic middle block and two hydrophobic outer blocks. A minority amount of diblock copolymers with the same chemistry is taken to coassemble into these micelles. At the end of the hydrophilic block of the diblock copolymers, a targeting moiety (TM) is present. Assuming that the rotation of the micelle towards the target is sufficiently fast, we can elaborate a single gradient cell model, wherein the micelle is in the center and the receptor (R) substrate exists on the outer plane of the spherical coordinate system. The distribution function of the targeting moiety corresponds to a Landau free energy with local minima and corresponding maxima. The lowest minimum, which is the ground state, shifts from within the micelle to the adsorbing state upon bringing the substrate closer to the micelle, implying a jumplike translocation of the targeting moiety. Equally deep minima represent the binodal of the phase transition, which is, due to the finite chain length, first-order like. The maximum in-between the two relevant minima implies that there is an activation barrier for the targeting moiety to reach the receptor surface. We localize the parameter space wherein the targeting moiety is (when the micelle is far from the target) preferably hidden in the stealthy hydrophilic corona of the micelle, which is desirable to avoid undesired immune responses, and still can jump out of the corona to reach the target quick enough, that is, when the barrier height is sufficiently low. The latter requirement may be identified by a spinodal condition. We found that such hidden TMs can still establish a TM-R contact at distances up to twice the corona size. The translocation transition will work best when the affinity of the TM for the core is avoided and when hydrophilic TMs are selected.
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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".