Non-invasive prenatal screening (NIPS) is a test for the detection of major fetal chromosomal abnormalities in maternal blood during pregnancy. The purpose of this study was to assess the performance of NIPS implemented within the framework of the Screening Program for Congenital Abnormalities of the Andalusian Health System.
A retrospective observational study was undertaken to determine the number of NIPS tests performed since its introduction. The number of invasive diagnostic tests done after the implementation of NIPS in the patients included in the program between March 2016 and August 2017 was also quantified.
A total of 6,258 combined first- and second trimester screening tests were performed, covering 95% of the population. In total, 250 subjects were identified as high risk, of whom 200 underwent NIPS after loss to follow-up. NIPS showed a sensitivity of 100% (95% CI: 76.84–100%) and a specificity of 99.46% (95% CI: 97.04–99.99%).
This test has proven to have a very high sensitivity and specificity. The results obtained demonstrate that the incorporation of NIPS in clinical practice minimizes the rate of miscarriages and reduces the frequency of invasive procedures by 70%.
Studies on the assessment of indoor air pollutants in terms of concentration and characterization in the Gulf Cooperation Council (GCC) countries have been recently carried out. This review assesses the health effects associated with indoor air pollution exposures in GCC, including other air pollutants (siloxanes, flame retardants, synthetic phenolic antioxidants) which were not explored in a previous study. In addition, the influence of ventilation conditions due to different indoor environments was also investigated. It was revealed that there is a lack of human health assessment studies on most indoor air pollutants in almost all GCC countries, except the United Arab Emirates, Kingdom of Saudi Arabia and Kuwait, where few attempts were made for some specific pollutants. Commonly reported plausible health effects potentially associated with indoor air pollution were related to respiratory symptoms and sick building syndrome (SBS). Many of the current health assessment studies in GCC countries were based on predictions and/or estimates of exposures rather than clinically based observational studies. Measured ventilation levels and indoor air velocities in most buildings failed to meet the American Society of Heating, Refrigerating and Air-conditioning Engineers (ASHRAE) threshold limits of 8 L/s/p and 0.18–0.25 m/s, respectively. Additionally, limited studies have investigated respiratory symptoms and SBS potentially attributable to poor ventilation in the region. It is highly recommended that future indoor air quality (IAQ) studies in GCC should focus more on epidemiologic and intervention studies.
In recent years, mass spectrometry (MS) has been applied to clinical microbial biotyping, exploiting the speed of matrix-assisted laser desorption/ionization (MALDI) in recording microbe-specific MS profiles. More recently, liquid atmospheric pressure (AP) MALDI has been shown to produce extremely stable ion flux from homogenous samples and ‘electrospray ionization (ESI)-like’ multiply charged ions for larger biomolecules, whilst maintaining the benefits of traditional MALDI including high tolerance to contaminants, low analyte consumption and rapid analysis. These and other advantages of liquid AP-MALDI MS have been explored in this study to investigate its potential in microbial biotyping.
Genetically diverse bacterial strains were analyzed using liquid AP-MALDI MS, including clinically relevant species such as Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae. Bacterial cultures were subjected to a simple and fast extraction protocol using ethanol and formic acid. Extracts were spotted with a liquid support matrix (LSM) and analyzed using a Synapt G2-Si mass spectrometer with an in-house built AP-MALDI source.
Each species produces a unique lipid profile in the m/z range of 400–1100, allowing species discrimination. Traditional (solid) MALDI MS produced spectra containing a high abundance of matrix-related clusters and an absence of lipid peaks. The MS profiles of the bacterial species tested form distinct clusters using principle component analysis (PCA) with a classification accuracy of 98.63% using a PCA-based prediction model.
Liquid AP-MALDI MS profiles can be sufficient to distinguish clinically relevant bacterial pathogens and other bacteria, based on their unique lipid profiles. The analysis of the lipid MS profiles is typically excluded from commercial instruments approved for clinical diagnostics.