Genetic diversity and phylogeographic structure of Anopheles kochi, Anopheles maculatus, and Anopheles vagus: ITS2-based analysis of highland transboundary populations in the Menoreh Hills, Java, Indonesia
Bibliographic record
Abstract
Baseline genetic characterization of malaria vector populations provides critical data for evidence-based surveillance in persistent transmission foci. This pilot study generated preliminary genetic baseline data for Anopheles populations in the Menoreh Hills border region between Central Java and Yogyakarta provinces, Indonesia, addressing a key geographic gap in regional vector research. Adult female mosquitoes were collected from 3 houses with reported malaria cases in Ngadirejo Village using standardized entomological methods, including human landing, animal landing, and resting collections. Specimens were morphologically identified and molecularly characterized via ITS2 gene sequencing. Phylogenetic analyses were assessed using maximum likelihood methods, and genetic diversity indices were calculated to examine population structure. A total of 62 specimens representing 3 species were collected exclusively through animal landing collections: Anopheles vagus (48 specimens, 77.4%), Anopheles maculatus (9 specimens, 14.5%), and Anopheles kochi (5 specimens, 8.1%). An. kochi exhibited high haplotype diversity (Hd=0.709) with low nucleotide diversity (π=0.004), while An. maculatus showed lower haplotype diversity (Hd=0.480) and higher nucleotide diversity (π=0.026). Phylogenetic analysis revealed Purworejo specimens clustered with regional populations: An. kochi grouped within Clade I with Indonesian isolates; An. maculatus distributed across multiple clades; An. vagus formed a cohesive unit with other Indonesian populations. The exclusive success of animal landing collections in the Menoreh Hills highlands provides key methodological insights. This study offers essential baseline reference data, validates cost-effective genetic surveillance approaches, and supports future large-scale population connectivity studies across the Menoreh Hills malaria transmission complex.
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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 | 0.001 | 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".