Translating Observations From Leishmanization Into Non-Living Vaccines: The Potential of Dendritic Cell-Based Vaccination Strategies Against Leishmania
Bibliographic record
Abstract
Leishmaniasis is a health-threatening vector-borne disease in almost 90 different countries. While a prophylactic human vaccine is not yet available, the fact that recovery from leishmaniasis establishes lifelong immunity against secondary infection suggests that a vaccine is attainable. In the past, deliberate infection with virulent parasites, termed Leishmanization, was used as a live-vaccine against cutaneous leishmaniasis and effectively protected against vector-transmitted disease in endemic areas. However, the practice was discontinued due to major complications including non-healing skin lesions, exacerbation of skin diseases, and the potential impact of immunosuppression. Instead, tremendous effort has been made to develop killed, live attenuated and nonliving subunit formulations. Many of these formulations produce promising experimental results but have failed in field trials or against experimental challenge with infected sand flies. Recently, experimental models of leishmanization have unraveled the critical role of parasite persistence in maintaining the circulating CD4+ effector T cells responsible for mitigating the inflammatory response early after sand fly challenge and mediating protective immunity. Here, we put forward the notion that for effective vaccine design (especially non-living vaccines), the role of antigen persistence and pre-existing effector CD4+ T cells should be taken into consideration. We propose that dendritic cell (DC) based vaccination strategies warrant greater attention because of their potential to act as long-term antigen depots, thereby emulating this critical requirement of naturally acquired protective immunity against infected sand fly challenge.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".