Producing highly effective extracellular vesicles using IBAR and talin F3 domain fusion
Bibliographic record
Abstract
Extracellular vesicles (EVs), transporting diverse cellular components, play a crucial role in intercellular communication in numerous physiological and pathological processes. EVs have also been recognized as a drug delivery platform for therapeutic purposes and cell-free regenerative medicine. While various approaches have focused on increasing EV production for efficient use therapeutic use of EVs, enhancing the quality of EVs, such as ensuring efficient uptake by their target cells, has not been widely explored. In this study, we linked a negative membrane curvature-forming inverse BAR (IBAR) domain with an integrin β tail-binding talin F3 domain to create the IBAR-F3 fusion protein. We observed that IBAR-F3 can trigger filopodia-like membrane protrusions and attract integrins to those protrusion-rich regions, when expressed in Chinese hamster ovary cells expressing integrin αIIbβ3. Surprisingly, the expression of IBAR-F3 also induced a robust production of EVs, which were then efficiently taken up by nearby cells in an integrin-dependent manner. Moreover, IBAR triggered integrin activation, presumably by inducing negative membrane curvature that likely disrupts the interaction between the integrin α and β transmembrane domain. Therefore, we suggest that IBAR-F3 should be utilized to promote both EV production and efficient uptake mediated by integrins. Furthermore, the negative curvature-inducing integrin activation suggests that integrins on EVs can be activated by the nanoscale change in the curvature of the EV without the need for conventional machinery to activate integrin inside the EVs.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".