Th1-Mediated Immunity against Helicobacter pylori Can Compensate for Lack of Th17 Cells and Can Protect Mice in the Absence of Immunization
Bibliographic record
Abstract
Helicobacter pylori (H. pylori) infection can be significantly reduced by immunization in mice. Th17 cells play an essential role in the protective immune response. Th1 immunity has also been demonstrated to play a role in the protective immune response and can compensate in the absence of IL-17. To further address the potential of Th1 immunity, we investigated the efficacy of immunization in mice deficient in IL-23p19, a cytokine that promotes Th17 cell development. We also examined the course of Helicobacter infection in unimmunized mice treated with Th1 promoting cytokine IL-12. C57BL/6, IL-12 p35 KO, and IL-23 p19 KO mice were immunized and challenged with H. pylori. Protective immunity was evaluated by CFU determination and QPCR on gastric biopsies. Gastric and splenic IL-17 and IFNγ levels were determined by PCR or by ELISA. Balb/c mice were infected with H. felis and treated with IL-12 therapy and the resulting gastric bacterial load and inflammatory response were assessed by histologic evaluation. Vaccine induced reductions in bacterial load that were comparable to wild type mice were observed in both IL-12 p35 and IL-23 p19 KO mice. In the absence of IL-23 p19, IL-17 levels remained low but IFNγ levels increased significantly in both immunized challenged and unimmunized/challenged mice. Additionally, treatment of H. felis-infected Balb/c mice with IL-12 resulted in increased gastric inflammation and the eradication of bacteria in most mice. These data suggest that Th1 immunity can compensate for the lack of IL-23 mediated Th17 responses, and that protective Th1 immunity can be induced in the absence of immunization through cytokine therapy of the infected host.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".