Cell-surface proteoglycans as molecular portals for cationic peptide and polymer entry into cells
Bibliographic record
Abstract
Polycationic macromolecules and cationic peptides acting as PTDs (protein transduction domains) and CPPs (cell-penetrating peptides) represent important classes of agents used for the import and delivery of a wide range of molecular cargoes into cells. Their entry into cells is typically initiated through interaction with cell-surface HS (heparan sulfate) molecules via electrostatic interactions, followed by endocytosis of the resulting complexes. However, the endocytic mechanism employed (clathrin-mediated endocytosis, caveolar uptake or macropinocytosis), defining the migration of these peptides into cells, depends on parameters such as the nature of the cationic agent itself and complex formation with cargo, as well as the nature and distribution of proteoglycans expressed on the cell surface. Moreover, a survey of the literature suggests that endocytic pathways should not be considered as mutually exclusive, as more than one entry mechanism may be operational for a given cationic complex in a particular cell type. Specifically, the observed import may best be explained by the distribution and uptake of cell-surface HSPGs (heparan sulfate proteoglycans), such as syndecans and glypicans, which have been shown to mediate the uptake of many ligands besides cationic polymers. A brief overview of the roles of HSPGs in ligand internalization is presented, as well as mechanistic hypotheses based on the known properties of these cell-surface markers. The identification and investigation of interactions made by glycosaminoglycans and core proteins of HSPGs with PTDs and cationic polymers will be crucial in defining their uptake by cells.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".