Cellular uptake and targeting of low dispersity, dual emissive, segmented block copolymer nanofibers
Bibliographic record
Abstract
), with a crystallizable PDHF core-forming block and a 'stealth' PEG corona-forming block with different end-group functionalities. Segmented C-B-A-B-C pentablock 1D nanofibers with varied spatially-defined coronal chemistries and a selected length (95 nm) were prepared using the living crystallization-driven self-assembly (CDSA) seeded-growth method. As the blue fluorescence of PDHF is often subject to environment-related quenching, a far-red BODIPY (BD) fluorophore was attached to the PEG end-group of the coronal B segments to provide additional tracking capability. Folic acid (FA) was also incorporated as a targeting group in the terminal C segments. These dual-emissive pentablock nanofibers exhibited uptake into >97% of folate receptor positive HeLa cells by flow cytometry. In the absence of FA, no significant uptake was detected and nanofibers with either FA or BD coronal groups showed no significant toxicity. Correlative light and electron microscopy (CLEM) studies revealed receptor-mediated endocytosis as an uptake pathway, with subsequent localization to the perinuclear region. A significant proportion of the nanofibers also appeared to interact with the cell membrane in an end-on fashion, which was coupled with fluorescence quenching of the PDHF core. These results provide new insights into the cellular uptake of polymer-based nanofibers and suggest their potential use in targeted therapies and diagnostics.
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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".