Large-scale generation of cell-derived nanovesicles
Bibliographic record
Abstract
Exosomes are enclosed compartments that are released from cells and that can transport biological contents for the purpose of intercellular communications. Research into exosomes is hindered by their rarity. In this article, we introduce a device that uses centrifugal force and a filter with micro-sized pores to generate a large quantity of cell-derived nanovesicles. The device has a simple polycarbonate structure to hold the filter, and operates in a common centrifuge. Nanovesicles are similar in size and membrane structure to exosomes. Nanovesicles contain intracellular RNAs ranging from microRNA to mRNA, intracellular proteins, and plasma membrane proteins. The quantity of nanovesicles produced using the device is 250 times the quantity of naturally secreted exosomes. Also, the quantity of intracellular contents in nanovesicles is twice that in exosomes. Nanovesicles generated from murine embryonic stem cells can transfer RNAs to target cells. Therefore, this novel device and the nanovesicles that it generates are expected to be used in exosome-related research, and can be applied in various applications such as drug delivery and cell-based therapy.
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.
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".