Analysis of serum homocysteine in the laboratory practice - comparison of the direct chemiluminescence immunoassay and high performance liquid chromatography coupled with fluorescent detection

Introduction: Effective diagnosis of cardiovascular diseases requires the right tools to be used enabling selective and sensitive analysis of their biomarkers. One of them is homocysteine (Hcy), nowadays determined by immunoassays and chromatographic methods. This study aims to compare the results obtained by direct chemiluminescence immunoassay (CLIA) and high performance liquid chromatography with fluorescent detection (HPLC-FD) using commercial kits. Materials and methods: Homocysteine concentration was determined in serum samples obtained from 101 individuals, using Atellica IM HCY (Siemens Healthineers, Erlangen, Germany) and HCY in plasma/serum – HPLC-FD (Chromsystems Instruments & Chemicals GmbH, Gräfelfing, Germany) tests validated for routine analysis. The latter was applied as a reference method. The comparability and agreement between the tested methods were evaluated using the Passing-Bablok (PB) regression analysis and the Bland-Altman (BA) method of the differences analysis. Results: Studies showed that CLIA gives higher Hcy concentrations (15.7 ± 4.14 μmol/L). Passing-Bablok regression analysis of the results obtained with CLIA (y) compared with HPLC-FD (x) yielded an intercept of 0.22 (95%CI: - 2.16 to 2.46) and slope of 1.58 (95%CI: 1.33 to 1.87). Bland-Altman analysis demonstrated a systematic positive bias for CLIA of 5.85 ± 2.77 μmol/L. Conclusions: Methods disagreement precludes their interchangeability. Lower Hcy values by HPLC-FD result from its greater selectivity. High performance liquid chromatography with fluorescent detection should be considered as preferential method for analysing Hcy in blood serum as well as the recommended reference method for routine clinical analysis. This fact, however, imposes the need to establish new reference ranges

Influence of Post-Flowering Climate Conditions on Anthocyanin Profile of Strawberry Cultivars Grown from North to South Europe

The effect of cultivar and environmental variations and their interaction on anthocyanin components of strawberry were assessed for six cultivars grown in five locations from North to South of Europe in two different years. To evaluate the impact of latitude- and altitude-related factors, daily mean (Tmean), maximum (Tmax) and minimum (Tmin) temperature and global radiation accumulated for 3, 5, 10 and 15 days before fruit sampling, was analyzed. In general, fruits grown in the south were more enriched in total anthocyanin and pelargonidin-3-glucoside (pel-3-glc), the most abundant anthocyanin in strawberry. Principal component analysis (PCA) provided a separation of the growing locations within a cultivar due to latitudinal climatic differences, temporary weather changes before fruit collection and cultivation technique. PCA also depicted different patterns for anthocyanin distribution indicating a cultivar specific reaction on the environmental factors. The linear regression analysis showed that pel-3-glc was relatively less affected by these factors, while the minor anthocyanins cyanidin-3-glucoside, cyanidin-3-(6-O-malonyl)-glucoside, pelargonidin-3-rutinoside and pelargonidin-3-(6-O-malonoyl)-glucoside were sensitive to Tmax. The global radiation strongly increased cya-3-mal-glc in ‘Frida’ and pel-3-rut in ‘Frida’ and ‘Florence’. ‘Candonga’ accumulated less pel-3-glc and total anthocyanin with increased global radiation. The anthocyanin profiles of ‘Gariguette’ and ‘Clery’ were unaffected by environmental conditions.publishedVersio

Machine learning in the diagnosis of asthma phenotypes during coronavirus disease 2019 pandemic

BACKGROUND: During the coronavirus disease 2019 (COVID‐19) pandemic, it has become a pressing need to be able to diagnose aspirin hypersensitivity in patients with asthma without the need to use oral aspirin challenge (OAC) testing. OAC is time consuming and is associated with the risk of severe hypersensitive reactions. In this study, we sought to investigate whether machine learning (ML) based on some clinical and laboratory procedures performed during the pandemic might be used for discriminating between patients with aspirin hypersensitivity and those with aspirin‐tolerant asthma. METHODS: We used a prospective database of 135 patients with non‐steroidal anti‐inflammatory drug (NSAID)–exacerbated respiratory disease (NERD) and 81 NSAID‐tolerant (NTA) patients with asthma who underwent OAC. Clinical characteristics, inflammatory phenotypes based on sputum cells, as well as eicosanoid levels in induced sputum supernatant and urine were extracted for the purpose of applying ML techniques. RESULTS: The overall best ML model, neural network (NN), trained on a set of best features, achieved a sensitivity of 95% and a specificity of 76% for diagnosing NERD. The 3 promising models (i.e., multiple logistic regression, support vector machine, and NN) trained on a set of easy‐to‐obtain features including only clinical characteristics and laboratory data achieved a sensitivity of 97% and a specificity of 67%. CONCLUSIONS: ML techniques are becoming a promising tool for discriminating between patients with NERD and NTA. The models are easy to use, safe, and achieve very good results, which is particularly important during the COVID‐19 pandemic

Influence of Post-Flowering Climate Conditions on Anthocyanin Profile of Strawberry Cultivars Grown from North to South Europe

The effect of cultivar and environmental variations and their interaction on anthocyanin components of strawberry were assessed for six cultivars grown in five locations from North to South of Europe in two different years. To evaluate the impact of latitude- and altitude-related factors, daily mean (Tmean), maximum (Tmax) and minimum (Tmin) temperature and global radiation accumulated for 3, 5, 10 and 15 days before fruit sampling, was analyzed. In general, fruits grown in the south were more enriched in total anthocyanin and pelargonidin-3-glucoside (pel-3-glc), the most abundant anthocyanin in strawberry. Principal component analysis (PCA) provided a separation of the growing locations within a cultivar due to latitudinal climatic differences, temporary weather changes before fruit collection and cultivation technique. PCA also depicted different patterns for anthocyanin distribution indicating a cultivar specific reaction on the environmental factors. The linear regression analysis showed that pel-3-glc was relatively less affected by these factors, while the minor anthocyanins cyanidin-3-glucoside, cyanidin-3-(6-O-malonyl)-glucoside, pelargonidin-3-rutinoside and pelargonidin-3-(6-O-malonoyl)-glucoside were sensitive to Tmax. The global radiation strongly increased cya-3-mal-glc in ‘Frida’ and pel-3-rut in ‘Frida’ and ‘Florence’. ‘Candonga’ accumulated less pel-3-glc and total anthocyanin with increased global radiation. The anthocyanin profiles of ‘Gariguette’ and ‘Clery’ were unaffected by environmental conditions

Exploring Genotype-by-Environment Interactions of Chemical Composition of Raspberry by Using a Metabolomics Approach

Promoting the consumption of fruits is a key objective of nutrition policy campaigns due to their associated health benefits. Raspberries are well appreciated for their remarkable flavor and nutritional value attributable to their antioxidant properties. Consequently, one of the objectives of present-day raspberry breeding programs is to improve the fruit’s sensory and nutritive characteristics. However, developing new genotypes with enhanced quality traits is a complex task due to the intricate impacts genetic and environmental factors have on these attributes, and the difficulty to phenotype them. We used a multi-platform metabolomic approach to compare flavor- and nutritional-related metabolite profiles of four raspberry cultivars (‘Glen Ample’, ‘Schönemann’, ‘Tulameen’ and ‘Veten’) grown in different European climates. Although the cultivars appear to be better adapted to high latitudes, for their content in soluble solids and acidity, multivariate statistical analyses allowed us to underscore important genotypic differences based on the profiles of important metabolites. ‘Schönemann’ and ‘Veten’ were characterized by high levels of anthocyanins and ellagitannins, respectively, ‘Tulameen’ by its acidity, and ‘Glen Ample’ for its content of sucrose and β-ionone, two main flavor contributors. Our results confirmed the value of metabolomic-driven approaches, which may foster the development of cultivars with enhanced health properties and flavor