Mutations in Plasmodium falciparum K13 propeller gene from Bangladesh (2009–2013)
Bibliographic record
Abstract
BACKGROUND: Bangladesh is a malaria hypo-endemic country sharing borders with India and Myanmar. Artemisinin combination therapy (ACT) remains successful in Bangladesh. An increase of artemisinin-resistant malaria parasites on the Thai-Cambodia and Thai-Myanmar borders is worrisome. K13 propeller gene (PF3D7_1343700 or PF13_0238) mutations have been linked to both in vitro artemisinin resistance and in vivo slow parasite clearance rates. This group undertook to evaluate if mutations seen in Cambodia have emerged in Bangladesh where ACT use is now standard for a decade. METHODS: Samples were obtained from Plasmodium falciparum-infected malaria patients from Upazila health complexes (UHC) between 2009 and 2013 in seven endemic districts of Bangladesh. These districts included Khagrachari (Matiranga UHC), Rangamati (Rajasthali UHC), Cox's Bazar (Ramu and Ukhia UHC), Bandarban (Lama UHC), Mymensingh (Haluaghat UHC), Netrokona (Durgapur and Kalmakanda UHC), and Moulvibazar (Sreemangal and Kamalganj UHC). RESULTS: Out of 296 microscopically positive P. falciparum samples, 271 (91.6%) were confirmed as mono-infections by both real-time PCR and nested PCR. The K13 propeller gene from 253 (93.4%) samples was sequenced bi-directionally. One non-synonymous mutation (A578S) was found in Bangladeshi clinical isolates. The A578S mutation was confirmed and lies adjacent to the C580Y mutation, the major mutation causing delayed parasite clearance in Cambodia. Based on computational modeling A578S should have a significant effect on tertiary structure of the protein. CONCLUSION: The data suggest that P. falciparum in Bangladesh remains free of the C580Y mutation linked to delayed parasite clearance. However, the mutation A578S is present and based on structural analysis could affect K13 gene function. Further in vivo clinical studies are required to validate the effect of this mutation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".