Adoptive transfer of helminth antigen‐pulsed dendritic cells protects against the development of experimental colitis in mice
Bibliographic record
Abstract
Infection with helminth parasites and treatment with worm extracts can suppress inflammatory disease, including colitis. Postulating that dendritic cells (DCs) participated in the suppression of inflammation and seeking to move beyond the use of helminths per se, we tested the ability of Hymenolepis diminuta antigen-pulsed DCs to suppress colitis as a novel cell-based immunotherapy. Bone marrow derived DCs pulsed with H. diminuta antigen (HD-DCs), or PBS-, BSA-, or LPS-DCs as controls, were transferred into wild-type (WT), interleukin-10 (IL-10) knock-out (KO), and RAG-1 KO mice, and the impact on dinitrobenzene sulphonic acid (DNBS)-induced colitis and splenic cytokine production assessed 72 h later. Mice receiving HD-DCs were significantly protected from DNBS-induced colitis and of the experimental groups only these mice displayed increased Th2 cytokines and IL-10 production. Adoptive transfer of HD-DCs protected neither RAG-1 nor IL-10 KO mice from DNBS-colitis. Furthermore, the transfer of CD4(+) splenocytes from recipients of HD-DCs protected naïve mice against DNBS-colitis, in an IL-10 dependent manner. Thus, HD-DCs are a novel anti-colitic immunotherapy that can educate anti-colitic CD4(+) T cells: mechanistically, the anti-colitic effect of HD-DCs requires that the host has an adaptive immune response and the ability to mobilize IL-10.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".