Elemental analysis of dried blood spots using total reflection X-ray fluorescence spectroscopy
Notice bibliographique
Résumé
Introduction: Essential elements are required for the proper functioning of the human body and are critical to growth and development. Dried blood spots (DBS), capillary blood collected on specialized filter paper by pricking an individual's finger or heel, are a minimally invasive and cost-effective alternative to venipuncture for multi-element analysis. Nutritional assessments using DBS can help overcome logistical challenges faced by researchers, particularly in terms of data collection efforts in resource-limited regions and newborn screening programs. Although previous studies have used DBS for elemental measurements, technological and practical hurdles remain, such as detection limits and sample volume requirements. In addition, there is currently no widely accepted standard method of analysis.Objectives: The primary objective of this research was to develop a method for quantifying select essential elements (copper, selenium and zinc) in DBS using Total Reflection X-Ray Fluorescence Spectroscopy (TXRF) and apply this method to a cohort of newborns from the Michigan BioTrust for Health Program. Methods: The study was conducted in two phases. In Phase 1, method development and validation was established using human whole blood standard reference material (SRM) of known elemental concentrations from the Institut National de Santé Publique du Québec (INSPQ; n=7). The selected protocol on 3mm diameter DBS sub-samples was subsequently used in Phase 2 to analyze essential elements in sub-sampled human DBS from a cohort of newborns from the Michigan BioTrust for Health Project (n=675). Three of the SRMs were selected for inter-assay accuracy (n=38 batches) and precision analysis. The generalized extreme studentized deviate (ESD) test was applied to detect outliers in the cohort. Descriptive statistics, accuracy and precision measures were first calculated, followed by Student's t-tests and one-way analysis of variance (ANOVA) to measure inter-assay variation, variation in punch type and storage temperature. All analyses were conducted using JMP®Pro 13.0.0 and Microsoft Excel 15.4.Results: Accuracy was measured by comparing TXRF DBS concentrations to corresponding whole blood SRM concentrations. Accuracy (mean±SD) for triplicate measurements of copper (Cu), selenium (Se), and zinc (Zn) using a 3mm diameter SRM DBS sub-sample were 99.5±3.4%, 100.2±6.9%, 102.6±4.4%, respectively. Accuracy of the selected SRMs (n=3) analyzed in the Michigan BioTrust Cohort for Cu was 107.8 ± 16.3%, 93.7 ± 14.2% for Se, and 109.0 ± 15.7%for Zn. The coefficient of variation, a measure of precision, of the SRMs across all batches was 13.3% for Cu, 17.3% for Se, and 13.7% for Zn. The Michigan BioTrust Cohort population values for Cu, Se, and Zn in the DBS were 1018.1 ± 269.9 mg/L, 241.0 ±58.2 mg/L, and 4250.0 ±1314.9 mg/L, respectively. High concentrations and high variability of Cu, 818.0 ± 1413.9 g/L, and Zn, 2005.3 ± 1622.2 g/L, were detected in the blank filter paper and are a barrier to quantitative analysis of DBS. Implications: These results imply that elemental analysis of DBS using TXRF provide a semi-quantitative method for measuring select essential elements in sub-sampled DBS. The values obtained are for Cu and Se are comparable to human adult population reference values whereas the Zn values are lower, reflecting physiologically lower Zn concentrations in newborns. Given present limitations in the quantitative analysis of DBS, this method has the potential to be used as a screening tool in the evaluation of essential elements in nutritional research, overcoming many of the challenges associated with venipuncture and current analytical methods–potentially leading to informed health policies and interventions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».