DNA barcodes corroborating identification of mosquito species and multiplex real-time PCR differentiating Culex pipiens complex and Culex torrentium in Iran
Bibliographic record
Abstract
Identifying mosquito species is a fundamental step in risk assessment and implementation of preventative strategies. Moreover, Culex pipiens is the most widespread mosquito vector in several regions of Iran and is the main vector for transmission of West Nile virus (WNV). Mosquitoes were collected at 14 sites in northern regions of Iran in 2015 and 2016. A subset of mosquito specimens was selected for identification confirmation using a DNA-barcoding technique. Construction of a phylogenetic tree showed clustering of mosquito sequences into three main genera: Aedes, Anopheles and Culex with individuals of a single species clustered closely together, regardless of where and when they were collected. Cx. pipiens complex and Cx. torrentium were identified and differentiated using multiplex real-time PCR targeting the gene locus for acetylcholinesterase 2 (ace2) to discriminate between Cx. pipiens pipiens and Cx. torrentium. The CQ11 microsatellite locus was used for discrimination between Cpp. biotypes. The predominant mosquito species in investigated regions were Cx. pipiens pipiens biotype pipiens, but we also detected Culex pipiens pipiens biotype molestus and hybrids of the two pipiens biotypes, as well as Cx. torrentium. The results of this study represent the first certain evidence of the presence of Cx. pipiens pipiens biotype molestus and hybrids between pipiens and molestus forms, and Cx. torrentium in Iran through a molecular identification approach. This report of a potentially important bridge vector for WNV might have key influence in the risk projections for WNV in Iran.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".