MicroRNA Profiling of B Cell Subsets from Systemic Lupus Erythematosus Patients Reveals Promising Novel Biomarkers

MicroRNAs control the differentiation and function of B cells, which are considered key elements in the pathogenesis of systemic lupus erythematosus (SLE). However, a common micro(mi)RNA signature has not emerged since published data includes patients of variable ethnic background, type of disease, and organ involvement, as well as heterogeneous cell populations. Here, we aimed at identifying a miRNA signature of purified B cells from renal and non-renal severe SLE patients of Latin American background, a population known to express severe disease. Genome-wide miRNA expression analyses were performed on naive and memory B cells and revealed two categories of miRNA signatures. The first signature represents B cell subset-specific miRNAs deregulated in SLE: 11 and six miRNAs discriminating naive and memory B cells of SLE patients from healthy controls (HC), respectively. Whether the miRNA was up or down-regulated in memory B cells as compared with naive B cells in HC, this difference was abolished in SLE patients, and vice versa. The second signature identifies six miRNAs associated with specific pathologic features affecting renal outcome, providing a further understanding for SLE pathogenesis. Overall, the present work provided promising biomarkers in molecular diagnostics for disease severity as well as potential new targets for therapeutic intervention in SLE.     

New Biofuel Alternatives: Integrating Waste Management and Single Cell Oil Production

Concerns about greenhouse gas emissions have increased research efforts into alternatives in bio-based processes. With regard to transport fuel, bioethanol and biodiesel are still the main biofuels used. It is expected that future production of these biofuels will be based on processes using either non-food competing biomasses, or characterised by low CO₂ emissions. Many microorganisms, such as microalgae, yeast, bacteria and fungi, have the ability to accumulate oils under special culture conditions. Microbial oils might become one of the potential feed-stocks for biodiesel production in the near future. The use of these oils is currently under extensive research in order to reduce production costs associated with the fermentation process, which is a crucial factor to increase economic feasibility. An important way to reduce processing costs is the use of wastes as carbon sources. The aim of the present review is to describe the main aspects related to the use of different oleaginous microorganisms for lipid production and their performance when using bio-wastes. The possibilities for combining hydrogen (H₂) and lipid production are also explored in an attempt for improving the economic feasibility of the process.     

Physicochemical and bioactive compounds at edible ripeness of eleven varieties of avocado (Persea americana) cultivated in the Andean Region of Peru

This work aimed evaluating some physicochemical compounds, hydrophilic (H-AC) and lipophilic (L-AC) antioxidant capacity of eleven avocado genotypes grown in the Andes. The results show great variability in physical and chemical properties, dry matter (DM) and lipid contents with ranges of 18.4–39.3% and 10.1–23.2%, respectively. All genotypes had high oleic acid content (50.4–69.9%) and a high unsaturated fatty acid/saturated fatty acid ratio (UFA/SFA, from 3.05 to 6.05), while the unsaponifiable fraction contained mainly β-sitosterol (140.83–235.51 mg/100 g DM) and α-tocopherol (17.44–71.29 µg/g DM). Total phenolic compounds (TPC), H-AC and L-AC ranged from 0.48 to 0.88 mg EAG/g DM, 5.37 to 14.00 and 1.87 to 6.71 μmol ET/g DM, respectively. Although the genotype influences avocado characteristics, climatic conditions in the Andean region seem to be important for the biosynthesis of metabolites of interest and should be considered in future studies.     

Yoghurt‐type beverage with partial substitution of milk by a chickpea extract: Effect on physicochemical and flow properties

The objective of this study was to determine the evolution of physicochemical and flow properties of a yoghurt‐type beverage partially replaced with a chickpea extract over a period of 22 days. From two chickpea extracts, Blanco Noroeste was selected for its higher protein content. Six yoghurt‐type formulations were prepared, stored at 4 °C and analysed on days 1, 8, 15 and 22. pH was 4.24–4.75, while brightness was 81.7–94.5. Flow properties of the yoghurt‐type exhibited a non‐Newtonian behaviour. From three formulations that underwent sensory evaluation, the 30:70 mix obtained the highest acceptation. This yoghurt‐type beverage exhibited characteristics similar to natural yoghurt.     

Evaluation of physiological workload assessment methods using heart rate and accelerometry for a smart wearable system

Work metabolism (WM) can be accurately estimated by oxygen consumption (VO₂), which is commonly assessed by heart rate (HR) in field studies. However, the VO₂–HR relationship is influenced by individual capacity and activity characteristics. The purpose of this study was to evaluate three models for estimating WM compared with indirect calorimetry, during simulated work activities. The techniques were: the HR-Flex model; HR branched model, combining HR with hip-worn accelerometers (ACC); and HR?+?arm-leg ACC model, combining HR with wrist- and thigh-worn ACC. Twelve participants performed five simulated work activities and three submaximal tests. The HR?+?arm-leg ACC model had the overall best performance with limits of agreement (LoA) of ?3.94 and 2.00?mL/min/kg, while the HR-Flex model had ?5.01 and 5.36?mL/min/kg and the branched model, ?6.71 and 1.52?mL/min/kg. In conclusion, the HR?+?arm-leg ACC model should, when feasible, be preferred in wearable systems for WM estimation.

Practitioner Summary: Work with high energy demand can impair employees’ health and life quality. Three models were evaluated for estimating work metabolism during simulated tasks. The model combining heart rate, wrist- and thigh-worn accelerometers showed the best accuracy. This is, when feasible, suggested for wearable systems to assess work metabolism.