Profiling lipidomic changes in dengue-resistant and dengue-susceptible strains of Colombian Aedes aegypti after dengue virus challenge
Bibliographic record
Abstract
The mosquito Aedes aegypti is the primary vector for all four serotypes of dengue viruses (DENV1-4), which infect millions across the globe each year. Traditional insecticide programs have been transiently effective at minimizing cases; however, insecticide resistance and habitat expansion have caused cases of DENV to surge over the last decade. There is an urgent need to develop novel vector control measures, but these are contingent on a detailed understanding of host-parasite interactions. Here, we have utilized lipidomics to survey the profiles of naturally DENV-resistant (Cali-MIB) or susceptible (Cali-S) populations of Ae. aegypti, isolated from Cali, Colombia, when fed on blood meals containing DENV. Control insects were fed on a DENV-free blood meal. Midguts were dissected from Cali-MIB and Cali-S females at three time points post-infectious blood meal, 18, 24 and 36h, to identify changes in the lipidome at key times associated with the entry, replication and exit of DENV from midgut cells. We used principal component analysis to visualize broad patterns in lipidomic profiles between the treatment groups, and significance analysis of microarray to determine lipids that were altered in response to viral challenge. These data can be used to identify molecules or metabolic pathways particular to the susceptible or refractory phenotypes, and possibly lead to the generation of stable, DENV-resistant strains of Ae. aegypti.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".