<i>Trichomonas vaginalis</i> exosome‐like vesicles modify the cytokine profile and reduce inflammation in parasite‐infected mice
Bibliographic record
Abstract
Trichomonas vaginalis (Tv) is a flagellated parasite commonly spread through sexual transmission. This protozoan initiates a severe inflammatory process, inducing nitric oxide, interleukin-6 (IL-6), IL-8, IL-10, IL-17 and IL-22 production by host immune cells. The parasites elicit these responses by releasing surface lipophosphoglycan, small extracellular vesicles (exosomes) and other factors. Tv exosomes are similar to mammalian exosomes and have been implicated in the modulation of IL-8 secretion by epithelial cells. Here, we report that exosome-like vesicles from T. vaginalis (Tv-ELVs) induced a more than 15-fold increase in IL-10 expression in RAW264.7 macrophages but only a two fold increase in IL-6 and TNF-α expression levels measured by RT-PCR. Because Tv-ELVs modulated the macrophage response, we also explored the effect of Tv-ELVs in a murine model of infection. Pretreatment with Tv-ELVs significantly increased IL-10 production as measured in vaginal washes by days 8 and 16 post-infection. Remarkably, Tv-ELVs-pretreated mice exhibited a decrease in IL-17 production and a significant decrease in vulvar inflammation. In addition, IL-6 and IL-13 were decreased during infection. Our results suggest that Tv-ELVs have an immunomodulatory role on the cytokine profile induced by the parasite and promote a decrease in the inflammatory process in mice infected with T. vaginalis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".