Cost-Effective HPLC-UV Method for Quantification of Vitamin D<sub>2</sub> and D<sub>3</sub> in Dried Blood Spot: A Potential Adjunct to Newborn Screening for Prophylaxis of Intractable Paediatric Seizures
Bibliographic record
Abstract
25-Hydroxyvitamin D (25-(OH)D) deficiency is recently been described as one of the multiple factors responsible for pediatric seizures. 25-Hydroxyvitamin D3 and 25-Hydroxyvitamin D2 are the well-known markers to determine Vitamin D status. In this work we report the development of a sensitive and cost effective HPLC technique for the quantification of the vitamin D metabolites from dried blood spot samples (DBS). The metabolites were extracted using acetonitrile–methanol–0.1% formic acid (60 : 20 : 20 (v/v)) and analyzed on an Acclaim C18 column (150 × 4.6 mm i.d., 3 µm) at a flow rate of 1 mL/min. The method was linear in the range of 10–80 ng/mL. Limit of detection and limit of quantification (LOQ) of the method were 5 and 10 ng/mL respectively. Extensive stability studies demonstrated the analytes to be stable in stock and matrix with a percent change within the acceptable range of ±15%. Comparison of the newly developed HPLC-DBS method with the reported LC-MS-DBS and electrochemiluminescence immunoassay (ECLIA) methods followed by Bland–Altman analysis demonstrated a bias of 0.08 and −0.14, respectively proving the methods are comparable. Application of the developed method to a pediatric seizure cohort depicted 46.6% of cases as deficient and 26.6% as insufficient for 25-(OH)D. Among deficient cases 8 samples were below 10 ng/mL and exact amount was not calculated since these were below the LOQ levels. The mean ± standard deviation (S.D.) in the remaining 6 deficient cases was 13.22 ± 2.80 ng/mL. The levels in healthy infants were 33.9 ± 6.11 ng/mL. The method can be used routinely for assessing 25-(OH)D deficiency in newborn.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".