Minimally invasive method for the point-of-care quantification of lymphatic vessel function
Bibliographic record
Abstract
Current clinical methods for the evaluation of lymphatic vessel function, crucial for early diagnosis and evaluation of treatment response of several pathological conditions, in particular of postsurgical lymphedema, are based on complex and mainly qualitative imaging techniques. To address this unmet medical need, we established a simple strategy for the painless and quantitative assessment of cutaneous lymphatic function. We prepared a lymphatic-specific tracer formulation, consisting of the clinically approved near-infrared fluorescent dye, indocyanine green, and the solubilizing surfactant Kolliphor HS15. The tracer was noninvasively delivered to the dermal layer of the skin using MicronJet600 hollow microneedles, and the fluorescence signal decay at the injection site was measured over time using a custom-made, portable detection device. The decay rate of fluorescence signal in the skin was used as a direct measure of lymphatic vessel drainage function. With this method, we could quantify impaired lymphatic clearance in transgenic mice lacking dermal lymphatics and distinguish distinct lymphatic clearance patterns in pigs in different body locations and under manual stimulus. Overall, this method has the potential for becoming a noninvasive and quantitative clinical "office test" for lymphatic function assessment.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".