Stem Cell-Derived Exosome as Potential Therapeutics for Microbial Diseases
Bibliographic record
Abstract
Exosomes, as the smallest extracellular vesicles that carry a cargo of nucleic acids, lipids, and proteins and mediate intercellular communication, have attracted much attention in diagnosis and treatment in the field of medicine. The contents of exosomes vary depending on the cell type and physiological conditions. Among exosomes derived from several cell types, stem cell-derived exosomes (stem cell-Exo) are increasingly being explored due to their immunomodulatory properties, regenerative capacity, anti-inflammatory and anti-microbial functions. Administration of stem cell-Exo, as a cell-free therapy for various diseases, has gained great promise. Indeed, the advantages of exosomes secreted from stem cells outweigh those of their parent cells owing to their small size, high stability, less immunogenicity, no risk of tumorigenesis, and easier condition for storage. Recently, the use of stem cell-Exo has been proposed in the field of microbial diseases. Pathogens including bacteria, viruses, fungi, and parasites can cause various diseases in humans with acute and chronic complications, sometimes resulting in mortality. On the other hand, treatments based on antibiotics and other chemical compounds have many side effects and the strains become resistant to drugs in some cases. Hence, this review aimed to highlight the effect of stem cell-derived extracellular vesicles including stem cell-Exo on microbial diseases. Although most published studies are preclinical, the avenue of clinical application of stem cell-Exo is under way to reach clinical applications. The challenges ahead of this cell-free treatment that might be applied as a therapeutic alternative to stem cells for translation from bench to bed were emphasized, as well.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".