MALDI-MS in first-line screening of newborns for sickle cell disease: results from a prospective study in comparison to HPLC.

Objectives: Newborn screening (NBS) for sickle cell disease (SCD) requires a robust, high-throughput method to detect hemoglobin S (HbS). Screening for SCD is performed by qualitative methods, such as isoelectric focusing (IEF), and both qualitative and quantitative methods such as high performance liquid chromatography (HPLC), capillary electrophoresis (CE), and tandem mass spectrometry (MS/MS). All these methods detect HbS, as well as low-level or absent HbA, and also other variants of hemoglobin.

The Reliable, Automatic Classification of Neonates in First-Tier MALDI-MS Screening for Sickle Cell Disease.

Previous research has shown that a MALDI-MS technique can be used to screen for sickle cell disease (SCD), and that a system combining automated sample preparation, MALDI-MS analysis and classification software is a relevant approach for first-line, high-throughput SCD screening. In order to achieve a high-throughput "plug and play" approach while detecting "non-standard" profiles that might prompt the misclassification of a sample, we have incorporated various sets of alerts into the decision support software. These included "biological alert" indicators of a newborn's clinical status (e.

A Multicentre Pilot Study of a Two-Tier Newborn Sickle Cell Disease Screening Procedure with a First Tier Based on a Fully Automated MALDI-TOF MS Platform.

The reference methods used for sickle cell disease (SCD) screening usually include two analytical steps: a first tier for differentiating haemoglobin S (HbS) heterozygotes, HbS homozygotes and β-thalassemia from other samples, and a confirmatory second tier. Here, we evaluated a first-tier approach based on a fully automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform with automated sample processing, a laboratory information management system and NeoSickle software for automatic data interpretation. A total of 6701 samples (with high proportions of phenotypes homozygous (FS) or heterozygous (FAS) for the inherited genes for sickle haemoglobin and samples from premature newborns) were screened.

eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems.

Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations.