Antibody Conjugation Methods for Active Targeting of Liposomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Liposomes are useful drug delivery vehicles since they may protect encapsulated drugs from enzymatic degradation and rapid clearance in vivo, or alter biodistribution, potentially leading to reduced toxicities (1,2). A major limitation to the development of many specialized applications is the problem of directing liposomes to tissues where they would not normally accumulate. Consequently, a great deal of effort has been made over the years to develop liposomes that have targeting vectors attached to the bilayer surface. These vectors have included ligands such as oligosaccharides (3,4), peptides (5,6), proteins (7,8) and vitamins (9). Most studies have focused on antibody conjugates since procedures for producing highly specific monoclonal antibodies (MAbs) are well established. In principle it should be possible to deliver liposomes to any cell type as long as the cells are accessible to the carrier. In practice it is usually not this simple since access to tissue, competition, and rapid clearance are formidable obstacles. It has also been shown that antibodies become immunogenic when coupled to liposomes (10,11), although in similar experiments with ovalbumin we have demonstrated that immunogenicity can be suppressed by formulating the liposomes with the cytotoxic drug doxorubi-cin (12). Such issues as these suggest that the development of antibody-targeted liposomes for in vivo applications will present difficult challenges.
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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 it