Engineering Cell Surfaces via Liposome Fusion
Bibliographic record
Abstract
In this study, we have rewired cell surfaces with ketone and oxyamine molecules based on liposome fusion for applications in cell-surface engineering. Lipid vesicles, functionalized with ketone and oxyamine molecules, display complementary chemistry and undergo recognition, docking, and subsequent fusion upon covalent oxime bond formation. Liposome fusion was characterized by several techniques including matrix-assisted laser-desorption/ionization mass spectrometry (MALDI-MS), light scattering, fluorescence resonance energy transfer (FRET), and transmission electron microscopy (TEM). When cultured with cells, ketone- and oxyamine-containing liposomes undergo spontaneous membrane fusion to present the respective molecules from cell surfaces. Ketone-functionalized cell surfaces serve as sites for chemoselective ligation with oxyamine-conjugated molecules. We tailored and fluorescently labeled cell surfaces with an oxyamine-conjugated rhodamine dye. As an application of this cell-surface engineering strategy, ketone- and oxyamine-functionalized cells were patterned on oxyamine- and ketone-presenting surfaces, respectively. Cells adhered, spread, and proliferated in the patterned regions via interfacial oxime linkage. The number of ketone molecules on the cell surface was also quantified by flow cytometry.
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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) | 0.001 | 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".