Investigation of a correlation between taxane‐based chemotherapy and the ultrasonic time‐of‐flight of human fingernails
Bibliographic record
Abstract
BACKGROUND: Medical practitioners have long associated the physical appearance of human fingernails with certain underlying health conditions due to their direct connection to the vascular system. The objective of this study was to demonstrate how human fingernails can potentially be used as a biomarker to determine the severity of a patient's reaction to chemotherapy. METHODS: Quantitative investigation of fingernails in patients undergoing taxane-based chemotherapy was conducted using a high-frequency 50 MHz ultrasound device in B-mode in the form of a pilot study. Time-of-Flight (TOF) ultrasonic signal measurements were recorded longitudinally across fingernails over three time intervals; (before treatment, in the middle of treatment, and on the last day of treatment); a neuropathy assessment and photographs were also taken for comparison. RESULTS: A total of 17 patients were examined in this study with ages ranging from 35-69 years old with both weekly and biweekly chemotherapy regimens. Onycholysis and fingernail discoloration were observed in 8 of the 17 patients. White transverse lines and white lunula were observed on 4 of the 17 patients. Quantitative assessment revealed a TOF median decrease in fingernails during the first half of chemotherapy treatment; conversely, TOF median was found to have increased during the second half. Median TOF measurements at the end of treatment were found to return to approximately that of the baseline value. CONCLUSION: This was a novel application of ultrasound in fingernails as chemotherapy biomarkers and further studies should be considered to verify and expand on the results obtained in this study.
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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 | 0.000 | 0.001 |
| 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".