A Dual Receptor and Reporter for Multi-Modal Cell Surface Engineering
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
The rapid development of new small molecule drugs, nanomaterials, and genetic tools to modulate cellular function through cell surface manipulation has revolutionized the diagnosis, study, and treatment of disorders in human health. Since the cell membrane is a selective gateway barrier that serves as the first line of defense/offense and communication to its environment, new approaches that molecularly engineer or tailor cell membrane surfaces would allow for a new era in therapeutic design, therapeutic delivery, complex coculture tissue construction, and in situ imaging probe tracking technologies. In order to develop the next generation of multimodal therapies, cell behavior studies, and biotechnologies that focus on cell membrane biology, new tools that intersect the fields of chemistry, biology, and engineering are required. Herein, we develop a liposome fusion and delivery strategy to present a novel dual receptor and reporter system at cell surfaces without the use of molecular biology or metabolic biosynthesis. The cell surface receptor is based on bio-orthogonal functional groups that can conjugate a range of ligands while simultaneously reporting the conjugation through the emission of fluorescence. We demonstrate this dual receptor and reporter system by conjugating and tracking various cell surface ligands for temporal control of cell fluorescent signaling, cell-cell interaction, and tissue assembly construction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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