UAS™—A Urine Preservative for Oncology Applications
Bibliographic record
Abstract
Liquid biopsy is a revolutionary tool that is gaining momentum in the field of cancer research. As a body fluid, urine can be used in non-invasive diagnostics for various types of cancer. We investigated the performance of UAS™ as a preservative for urinary analytes. Firstly, the need for urine preservation was investigated using urine samples from healthy volunteers. Secondly, the performance of UAS™ was assessed for cell-free DNA (cfDNA) and host cell integrity during storage at room temperature (RT) and after freeze-thaw cycling. Finally, UAS™ was used in a clinical setting on samples from breast and prostate cancer patients. In the absence of a preservative, urinary cfDNA was degraded, and bacterial overgrowth occurred at RT. In urine samples stored in UAS™, no microbial growth was seen, and cfDNA and cellular integrity were maintained for up to 14 days at RT. After freeze-thaw cycling, the preservation of host cell integrity and cfDNA showed significant improvements when using UAS™ compared to unpreserved urine samples. Additionally, UAS™ was found to be compatible with several commercially available isolation methods.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".