Improvements in an<i>in vivo</i>neutron activation analysis (NAA) method for the measurement of fluorine in human bone
Bibliographic record
Abstract
We previously published a method for the in vivo measurement of bone fluoride using neutron activation analysis (NAA) and demonstrated the utility of the technique in a pilot study of environmentally exposed people. The method involved activation of the hand in an irradiation cavity at the McMaster University Accelerator Laboratory and acquisition of the resultant γ-ray signals in a '4π' NaI(Tl) detector array of nine detectors. In this paper we describe a series of improvements to the method. This was investigated via measurement of hand simulating phantoms doped with varying levels of fluorine and fixed amounts of sodium, chlorine and calcium. Four improvements to the technique were tested since our first publication. The previously published detection limit for phantom measurements using this system was 0.66 mg F/g Ca. The accelerator irradiation and detection facilities were relocated to a new section of the laboratory and one more detector was added to the detection system. This was found to reduce the detection limit (possibly because of better detection shielding and additional detector) to 0.59 mg F/g Ca, a factor of 1.12. A new set of phantoms was developed and in this work we show that they improved the minimum detectable limit for fluoride in phantoms irradiated using neutrons produced by 2.15 MeV protons on lithium by a factor of 1.55. We compared the detection limits previously obtained using a summed signal from the nine detectors with the detection limit obtained by acquiring the spectra in anticoincidence mode for reduction of the disturbing signal from chlorine in bone. This was found to improve the ratio of the detection of fluorine to chlorine (an interfering signal) by a factor of 2.8 and the resultant minimum detection limit was found to be reduced by a factor of 1.2. We studied the effects of changing the timing of γ-ray acquisition. Our previously published data used a series of three 10 s acquisitions followed by a 300 s count. Changing the acquisition to a series of six 5 s acquisitions was found to further improve the detection limit by a factor of 1.4. We also present data showing that if the neutron dose is delivered to the phantom in a shorter time period, i.e. the dose rate is increased and irradiation shortened then the detection limit can be reduced by a further factor of 1.35.The overall improvement in detection limit by employing all of these changes was found to be a factor of 3.9. The technique now has an in phantom detection limit of 0.17 mg F/g Ca compared to a previous detection limit of 0.66 mg F/g Ca. The system can now be tested on human volunteers to see if individuals with diagnosed fluorosis can be distinguished from the general Canadian population using this technique.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".