Assessment of X-ray fluorescence capabilities for nail and hair matrices through zinc measurement in keratin reference materials
Bibliographic record
Abstract
BACKGROUND: Novel and emerging biomarkers of zinc status are being developed to help study and address zinc deficiency around the world. Two potential biomarkers, nail and hair, involve the measurement of zinc from easily accessible keratin-based components of the body. Portable X-ray fluorescence (XRF) is a relatively new approach to the assessment of zinc in nail or hair, and has a number of compelling advantages compared with other techniques. The aim of the current study was to test the ability of XRF to measure zinc in keratinized reference materials (RMs) designed to simulate nail and hair. METHODS: Four Keratin Matrix RMs were prepared and characterized for numerous trace elements by the New York State Department of Health's Wadsworth Center. The Keratin Matrix RMs consisted of powdered samples of caprine (goat) horns pooled from several animals. Concentrations of zinc, as assessed by inductively coupled plasma mass spectrometry (ICP-MS), were similar to what would be expected from human nail or hair tissues. Repeat measurements of the RMs were made using a portable XRF system. The XRF zinc results were compared with the ICP-MS zinc concentrations. Three different approaches to quantifying the zinc content by XRF were performed: (1) zinc signal to total signal ratio, (2) zinc signal to sulfur signal ratio, and (3) system output zinc concentration. RESULTS: The portable XRF results from a given RM were found to be consistent across repeat trials under all three approaches to XRF quantitation. Precision, calculated as the relative standard deviation of repeat measurements ranged from an average result of 0.8 % (using the system output zinc concentration method) to 6.1 % (using the zinc signal to sulfur signal ratio method). Measurement of the RMs provided XRF zinc results which scaled well with ICP-MS zinc concentration, particularly when using the XRF zinc to total and system zinc concentration methods. A Bland-Altman plot showed that the XRF system zinc concentration output exceeded the ICP-MS zinc concentration by, on average, 10.2 % ± 1.2 %. CONCLUSION: Overall, both accuracy and precision of measurement were found to be promising for portable XRF, provided appropriate conversions to concentration are introduced. The results of this study indicate that portable XRF is an effective and dependable method of assessing zinc concentration in keratinized tissue RMs. This will have implications for the future use of portable XRF to monitor zinc status in humans through measurements of nail and hair.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".