Immune Cell-Derived Extracellular Vesicles in the Face of Pathogenic Infections
Bibliographic record
Abstract
Extracellular Vesicles (EVs) are a collection of vesicles released from cells that play an important role in intercellular communication. Microbial infections are known as one of the major problems in the medical field. Considering the increasing resistance of strains to routine drug treatments, the need for new therapies seems to be more than ever. Recent studies have shown that the EVs released from immune cells during microbial infections had anti-microbial effects or were able to induce neighbouring cells to display anti-microbial effects. This mini-review aimed to explore the latest studies on immune cell-derived EVs in viral, bacterial, fungal, and parasitic infections. Review of the literature demonstrated that specific cargos in EVs were involved in the fight against pathogenic infections. Additionally, the transport of appropriate bioactive molecules including miRNAs, mRNAs, and proteins via EVs could mediate the anti-microbial process. Thus, it could be a proof-of-principle that therapeutic approaches based on EVs derived from immune cells could offer a promising path forward, which is still in early stages and needs further assessments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".