Bibliographic record
Abstract
Successful endoparasites of mammals must outwit the sophisticated immune systems of their hosts that have evolved to detect and destroy/eradicate them. Many species of helminth parasite can directly or indirectly manipulate host immunity: helminth-derived molecules can suppress or skew activity of many immune cell phenotypes, and mobilization of regulatory cells in response to infection can inhibit immune cell activation. Moreover, many investigations, principally in laboratory-based rodent-helminth systems, demonstrate that infection with helminths (trematode, cestode or nematode) can ameliorate the severity of concomitant disease that model diabetes, inflammatory bowel disease and multiple sclerosis. Ongoing analyses in these model systems may uncover novel approaches to the management and cure of inflammatory diseases that are major global health issues. However, the potential of environmentally or experimentally (i.e. 'therapeutically') acquired infection with helminth parasites to exaggerate the severity immunopathologies in the host should not be overlooked. Here, examples of infection with helminth parasites exacerbating concomitant disease and commentary on possible adverse effects of helminth therapy are provided--the intent is not to undermine the development of helminth therapy, but to illustrate caveats that may need to be considered should helminth therapy be utilized as a treatment for inflammatory disease.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".