Single hair analysis by X-ray fluorescence spectrometry detects small changes in dietary zinc intake: A nested randomized controlled trial
Bibliographic record
Abstract
The aim of this study was to determine whether X-ray fluorescence spectrometry (XRF) could be used to detect changes in hair zinc concentration in response to a modest daily increase in zinc from the consumption of zinc biofortified wheat flour. This study was conducted as part of an effectiveness trial (BiZiFED2) exploring the potential for zinc biofortified wheat to alleviate zinc deficiency in adolescent girls aged 10–16 years in Pakistan (trial registration ID ISRCTN17107812). A randomized controlled design was used. Participants received either control flour or zinc biofortified flour for 6 months. Consumption of biofortified flour resulted in an average daily increase in dietary zinc intake of 1.5 mg per day above that of the control flour. At baseline and at the end of the intervention, individual hair samples (control:n= 59, intervention:n= 64) were analyzed for zinc and sulfur content by XRF. Data were analyzed using linear mixed effects models to contrast between trial groups the changes from baseline to end point and also to compare baseline and end point values within each trial group. Increases from baseline to endpoint in both sulfur and zinc were significantly greater in the intervention group compared to control (sulfur counts. Control: baseline = 119.87 ± 20.33 and endpoint = 121.58 ± 23.58/intervention: baseline = 122.67 ± 24.19 and endpoint = 131.60 ± 21.34); (Zinc counts. Control: baseline = 50.88 ± 14.33 and endpoint = 54.82 ± 14.61/intervention: baseline = 49.61 ± 10.77 and endpoint = 58.79 ± 12.20). For these parameters, there were also significant increases from baseline to endpoint in the intervention group but not in control. Furthermore, for Zn:S count ratio there were no differences in terms of the magnitude of the change from baseline to endpoint in the control group, although significant increases from baseline to endpoint were evident in the intervention group (Zn:S count ratio. Control: baseline = 0.42 ± 0.10 and endpoint = 0.45 ± 0.08/intervention: baseline = 0.41 ± 0.08 and endpoint = 0.45 ± 0.08). A modest increase in dietary zinc over 6 months resulted in a detectable increase in both sulfur and zinc counts in individual hairs measured using XRF. This offers a sensitive, non-invasive method to monitor changes within subjects in response to dietary zinc interventions.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".