Can temporal analysis of optical coherence tomography statistics report on dextrorotatory-glucose levels in blood?
Bibliographic record
Abstract
We report the use of optical coherence tomography (OCT) for measuring dextrorotatory-glucose (D-glucose) in liquid phantoms and in drawn blood based on temporal dynamics of light scattering. The presence of D-glucose alters the medium viscosity, thus affecting the Brownian motion of the scatterers (polystyrene microspheres (PMS) in phantoms, red blood cells (RBCs) in blood) as measured by OCT. To quantify the effect, the signal autocorrelation functions were measured from M-mode OCT data and exponentially fit to obtain the decorrelation times. These were then related to translational (and rotational, in case of asymmetric scatterers) diffusion coefficients which enabled the determination of D-glucose-controlled medium viscosity. Obtained viscosily values agreed well with the literature, and showed expected increase with D-glucose concentrations. Whole blood smears were imaged with microscope and another effect of added glucose, that of red blood cell deformation, was also observed. This phantom and blood OCT study demonstrates the technique’s ability to detect and quantify D-glucose presence in non-flowing liquid suspensions, and suggests several additional research routes necessary to determine its potential for in vivo applications.
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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 | 0.003 | 0.020 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".