Genetic diversity of Plasmodium vivax in clinical isolates from Bangladesh
Bibliographic record
Abstract
BACKGROUND: Plasmodium vivax is the second most prevalent human malaria parasite in Bangladesh; however, there are no data of its genetic diversity. Several molecular markers are available where Pvcsp, Pvmsp 1 and Pvmsp 3α are most commonly used for P. vivax genotyping studies. The aim of the study was to investigate the population structure of P. vivax in Bangladesh. METHODS: A total of 102 P. vivax-positive blood samples were collected from different malaria-endemic areas in Bangladesh and subsequently analysed for those three genotyping markers. Nested PCR was performed for diagnosis and genotyping analysis followed by PCR-RFLP to detect genetic diversity using Pvcsp, Pvmsp 1 and Pvmsp 3α markers. RESULTS: Analysis of Pvcsp showed that the VK210 repeat type was highly prevalent (64.7%, 66/102) compared to VK247 (35.3%, 36/102), although the prevalence of VK247 was higher than other Southeast Asian countries. Analysis of these three genes revealed a diverse, circulating population of P. vivax where a total of ten, 56 and 35 distinct genotypes were detected for Pvcsp, Pvmsp 1 and Pvmsp 3α, respectively. CONCLUSION: This genotyping observation of P. vivax is the first report from Bangladesh and will provide valuable information for establishing the genotyping methods and circulating genetic variants of these three markers available in Bangladesh.
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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 | 0.000 |
| 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 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".