Vector microbiota manipulation by host antibodies: the forgotten strategy to develop transmission-blocking vaccines
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
Human and animal pathogens that are transmitted by arthropods are a global concern, particularly those vectored by ticks (e.g. Borrelia burgdorferi and tick-borne encephalitis virus) and mosquitoes (e.g. malaria and dengue virus). Breaking the circulation of pathogens in permanent foci by controlling vectors using acaricide-based approaches is threatened by the selection of acaricide resistance in vector populations, poor management practices and relaxing of control measures. Alternative strategies that can reduce vector populations and/or vector-mediated transmission are encouraged worldwide. In recent years, it has become clear that arthropod-associated microbiota are involved in many aspects of host physiology and vector competence, prompting research into vector microbiota manipulation. Here, we review how increased knowledge of microbial ecology and vector-host interactions is driving the emergence of new concepts and tools for vector and pathogen control. We focus on the immune functions of host antibodies taken in the blood meal as they can target pathogens and microbiota bacteria within hematophagous arthropods. Anti-microbiota vaccines are presented as a tool to manipulate the vector microbiota and interfere with the development of pathogens within their vectors. Since the importance of some bacterial taxa for colonization of vector-borne pathogens is well known, the disruption of the vector microbiota by host antibodies opens the possibility to develop novel transmission-blocking vaccines.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it