DNA aptamers for the recognition of HMGB1 from Plasmodium falciparum
Bibliographic record
Abstract
Rapid Diagnostic Tests (RDTs) for malaria are restricted to a few biomarkers and antibody-mediated detection. However, the expression of commonly used biomarkers varies geographically and the sensibility of immunodetection can be affected by batch-to-batch differences or limited thermal stability. In this study we aimed to overcome these limitations by identifying a potential biomarker and by developing molecular sensors based on aptamer technology. Using gene expression databases, ribosome profiling analysis, and structural modeling, we find that the High Mobility Group Box 1 protein (HMGB1) of Plasmodium falciparum is highly expressed, structurally stable, and present along all blood-stages of P. falciparum infection. To develop biosensors, we used in vitro evolution techniques to produce DNA aptamers for the recombinantly expressed HMG-box, the conserved domain of HMGB1. An evolutionary approach for evaluating the dynamics of aptamer populations suggested three predominant aptamer motifs. Representatives of the aptamer families were tested for binding parameters to the HMG-box domain using microscale thermophoresis and rapid kinetics. Dissociation constants of the aptamers varied over two orders of magnitude between nano- and micromolar ranges while the aptamer-HMG-box interaction occurred in a few seconds. The specificity of aptamer binding to the HMG-box of P. falciparum compared to its human homolog depended on pH conditions. Altogether, our study proposes HMGB1 as a candidate biomarker and a set of sensing aptamers that can be further developed into rapid diagnostic tests for P. falciparum detection.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".