Gut Microbiota Extracellular Vesicles as Signaling Molecules Mediating Host-Microbiota Communications
Bibliographic record
Abstract
Over the past decade, gut microbiota dysbiosis has been linked to many health disorders; however, the detailed mechanism of this correlation remains unclear. Gut microbiota can communicate with the host through immunological or metabolic signalling. Recently, microbiota-released extracellular vesicles (MEVs) have emerged as significant mediators in the intercellular signalling mechanism that could be an integral part of microbiota-host communications. MEVs are small membrane-bound vesicles that encase a broad spectrum of biologically active compounds (i.e., proteins, mRNA, miRNA, DNA, carbohydrates, and lipids), thus mediating the horizontal transfer of their cargo across intra- and intercellular space. In this study, we provide a comprehensive and in-depth discussion of the biogenesis of microbial-derived EVs, their classification and routes of production, as well as their role in inter-bacterial and inter-kingdom signaling.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".