Optical Interferometric Device for Rapid and Specific Detection of Biological Cells
Bibliographic record
Abstract
Here, we report a rapid and accurate optical method for detecting cells from liquid samples in a label-free manner. The working principle of the method is based on the interference of parts of a conical laser beam, coming from a single-mode optical fiber directly, and reflected from a flat glass surface. The glass is functionalized by antibodies against the cells to be detected from the liquid sample. Cells bound to that surface modify the reflected beam, and hence, change the resulting interference pattern, too. By registering and interpreting the variation in the image, the presence of cells from the sample can be detected. As for a demonstration, cell suspensions from a U937 cell line were used in glass chambers functionalized by antibodies (TMG6-5 (mIgG1)) to which the cells specifically bind. The limit of detection (LOD) of the method was also estimated. This proof-of-concept setup offers a cost-effective and easy-to-use way of rapid and specific detection of any type of cells (including pathogens) from suspensions (e.g., body fluids). The possible portability of the device predicts its applicability as a rapid test in clinical diagnostics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".