Darwin’s gemmules and extracellular vesicles: A striking resemblance
Bibliographic record
Abstract
We read with great interest the recent review article pertaining to extracellular vesicles (EVs) by Davies. 1 Davies O.G. Extracellular vesicles: from bone development to regenerative orthopedics. Mol. Ther. 2023; 31: 1251-1274 Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar This review article is highly appreciated and summarizes a large body of experimental data and many new study results. It is of great interest and importance in regenerative medicine. However, this review article contains a minor point that needs a rethink. In the brief historical context, Davies correctly states that Charles Darwin pioneered the study of molecular transfer from cell to cell. But he insists that EVs only contain a mixture of RNAs, proteins, lipids, and metabolites, without mentioning the DNA content in them. In his opinion, EVs, unlike Darwin’s hypothetical gemmules, do not mediate the transfer of genetic information. This seems to be an outdated view that needs to be updated. Here we would like to point out that EVs also contain DNA as well, thus bearing a striking resemblance to Darwin’s gemmules. Response to a letter to the editor on Darwin’s gemmules and extracellular vesicles: A striking resemblanceOwen G. DaviesMolecular TherapyAugust 3, 2023In BriefI would like to thank the authors of this letter for providing an interesting perspective and for publishing many thought-provoking articles on the topic of Darwin’s pangenesis over the years. Full-Text PDF
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".