Microfluidic cell-phoresis enabling high-throughput analysis of red blood cell deformability and biophysical screening of antimalarial drugs
Bibliographic record
Abstract
Changes in red blood cell (RBC) deformability are associated with the pathology of many diseases and could potentially be used to evaluate disease status and treatment efficacy. We developed a simple, sensitive, and multiplexed RBC deformability assay based on the spatial dispersion of single cells in structured microchannels. This mechanism is analogous to gel electrophoresis, but instead of transporting molecules through nano-structured material to measure their length, RBCs are transported through micro-structured material to measure their deformability. After transport, the spatial distribution of cells provides a readout similar to intensity bands in gel electrophoresis, enabling simultaneous measurement on multiple samples. We used this approach to study the biophysical signatures of falciparum malaria, for which we demonstrate label-free and calibration-free detection of ring-stage infection, as well as in vitro assessment of antimalarial drug efficacy. We show that clinical antimalarial drugs universally reduce the deformability of RBCs infected by Plasmodium falciparum and that recently discovered PfATP4 inhibitors, known to induce host-mediated parasite clearance, display a distinct biophysical signature. Our process captures key advantages from gel electrophoresis, including image-based readout and multiplexing, to provide a functional screen for new antimalarials and adjunctive agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".