Role of Exosomes/Microvesicles in the Nervous System and Use in Emerging Therapies
Bibliographic record
Abstract
Extracellular membrane vesicles (EMVs) are nanometer sized vesicles, including exosomes and microvesicles capable of transferring DNAs, mRNAs, microRNAs, non-coding RNAs, proteins, and lipids among cells without direct cell-to-cell contact, thereby representing a novel form of intercellular communication. Many cells in the nervous system have been shown to release EMVs, implicating their active roles in development, function, and pathologies of this system. While substantial progress has been made in understanding the biogenesis, biophysical properties, and involvement of EMVs in diseases, relatively less information is known about their biological function in the normal nervous system. In addition, since EMVs are endogenous vehicles with low immunogenicity, they have also been actively investigated for the delivery of therapeutic genes/molecules in treatment of cancer and neurological diseases. The present review summarizes current knowledge about EMV functions in the nervous system under both physiological and pathological conditions, as well as emerging EMV-based therapies that could be applied to the nervous system in the foreseeable future.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".