Lessons Learned from Protective Immune Responses to Optimize Vaccines against Cryptosporidiosis
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.
Bibliographic record
Abstract
In developing countries, cryptosporidiosis causes moderate-to-severe diarrhea and kills thousands of infants and toddlers annually. Drinking and recreational water contaminated with Cryptosporidium spp. oocysts has led to waterborne outbreaks in developed countries. A competent immune system is necessary to clear this parasitic infection. A better understanding of the immune responses required to prevent or limit infection by this protozoan parasite is the cornerstone of development of an effective vaccine. In this light, lessons learned from previously developed vaccines against Cryptosporidium spp. are at the foundation for development of better next-generation vaccines. In this review, we summarize the immune responses elicited by naturally and experimentally-induced Cryptosporidium spp. infection and by several experimental vaccines in various animal models. Our aim is to increase awareness about the immune responses that underlie protection against cryptosporidiosis and to encourage promotion of these immune responses as a key strategy for vaccine development. Innate and mucosal immunity will be addressed as well as adaptive immunity, with an emphasis on the balance between TH1/TH2 immune responses. Development of more effective vaccines against cryptosporidiosis is needed to prevent Cryptosporidium spp.-related deaths in infants and toddlers in developing countries.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 it