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Record W2152769327 · doi:10.4161/hv.5.5.7607

Vaccines and vaccination strategies against human cutaneous leishmaniasis

2009· review· en· W2152769327 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Vaccines · 2009
Typereview
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsVaccinationCutaneous leishmaniasisImmunologyLeishmaniasisImmunityLeishmaniaLeishmania majorImmune systemMedicineVirologyAttenuated vaccineDiseaseBiologyVirulence

Abstract

fetched live from OpenAlex

One might think that the development of a vaccine against cutaneous leishmaniasis would be relatively straightforward because the type of immune response required for protection is known and natural immunity occurs following recovery from primary infection. However, there is as yet no effective vaccine against the disease in humans. Although vaccination in murine studies has yielded promising results, these vaccines have failed miserably when tested in primates or humans. The reasons behind these failures are unknown and remain a major hurdle for vaccine design and development against cutaneous leishmaniasis. In contrast, recovery from natural, deliberate or experimental infections results in development of long-lasting immunity to re-infection. This so called infection-induced resistance is the strongest anti-Leishmania immunity known. Here, we briefly review the different approaches to vaccination against cutaneous leishmaniasis and argue that vaccines composed of genetically modified (attenuated) parasites, which induce immunity akin to infection-induced resistance, may provide best protection against cutaneous leishmaniasis in humans.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.389
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it