Molecular approaches for blood meal analysis and species identification of mosquitoes (Insecta: Diptera: Culicidae) in rural locations in southern England, United Kingdom
Bibliographic record
Abstract
Thirty-four species of Culicidae are present in the UK, of which 15 have been implicated as potential vectors of arthropod-borne viruses such as West Nile virus. Identification of mosquito feeding preferences is paramount to the understanding of vector-host-pathogen interactions which, in turn, would assist in the control of disease outbreaks. Results are presented on the application of DNA barcoding for vertebrate species identification in blood-fed female mosquitoes in rural locations. Blood-fed females (n = 134) were collected in southern England from rural sites and identified based on morphological criteria. Blood meals from 59 specimens (44%) were identified as feeding on eight hosts: European rabbit, cow, human, barn swallow, dog, great tit, magpie and blackbird. Analysis of the cytochrome c oxidase subunit I mtDNA barcoding region and the internal transcribed spacer 2 rDNA region of the specimens morphologically identified as Anopheles maculipennis s.l. revealed the presence of An. atroparvus and An. messeae. A similar analysis of specimens morphologically identified as Culex pipiens/Cx. torrentium showed all specimens to be Cx. pipiens (typical form). This study demonstrates the importance of using molecular techniques to support species-level identification in blood-fed mosquitoes to maximize the information obtained in studies investigating host feeding patterns.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".