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Record W2990960682 · doi:10.7717/peerj-achem.1

Analysis of copper, selenium, and zinc in newborn dried bloodspots using total reflection X-ray fluorescence (TXRF) spectroscopy

2019· article· en· W2990960682 on OpenAlexafffundabout
Jessica Pawly, Richard L. Neitzel, Niladri Basu

Bibliographic record

VenuePeerJ Analytical Chemistry · 2019
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsSeleniumX-ray fluorescenceZincCopperLinearityAnalytical Chemistry (journal)Accuracy and precisionMaterials scienceChemistryFluorescenceChromatographyMathematicsPhysicsStatisticsMetallurgyOptics

Abstract

fetched live from OpenAlex

Background There exists great interest in using dried bloodspots across the clinical, public health, and nutritional sciences to characterize circulating levels of essential elements yet current methods face several challenges related to instrumentation, quality control, and matrix effects. Elemental analysis via total X-ray fluorescence (TXRF) may help overcome these challenges. The objective of this study was to develop and apply a novel TXRF-based analytical method to quantify essential elements (copper, selenium, zinc) in dried bloodspots. Methods Analytical methods were developed with human whole blood standard reference materials from the Institut National de Santé Publique du Québec (INSPQ). The method was developed in careful consideration of several quality control parameters (e.g., analytical accuracy, precision, linearity, and assay range) which were iteratively investigated to help refine and realize a robust method. The developed method was then applied to a quantitative descriptive survey of punches ( n = 675) taken from residual dried bloodspots from a newborn screening biobank program (Michigan BioTrust for Health). Results The analytical method developed to quantify the three target elements in dried bloodspots fared well against a priori quality control criteria (i.e., analytical accuracy, precision, linearity and range). In applying this new method, the average (±SD) blood copper, selenium, and zinc levels in the newborn samples were 1,117.0 ± 627.1 µg/L, 193.1 ± 49.1 µg/L, and 4,485 ± 2,275 µg/L respectively. All the elements were normally distributed in the sample population, and the measured concentrations fall within an expected range. Conclusions This study developed and applied a novel and robust method to simultaneously quantify three essential elements. The method helps overcome challenges in the field concerning elemental analysis in dried bloodspots and the findings help increase understanding of nutritional status in newborns.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.326
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations4
Published2019
Admission routes3
Has abstractyes

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