Nature and Lability of Northern Adriatic Macroaggregates

The key organic constituents of marine macroaggregates (macrogels) of prevalently phytoplankton origin, periodically occurring in the northern Adriatic Sea, are proteins, lipids and especially polysaccharides. In this article, the reactivity of various macroaggregate fractions in relation to their composition in order to decode the potentially »bioavailable« fractions is summarized and discussed. The enzymatic hydrolysis of the macroaggregate matrix, using α-amylase, β-glucosidase, protease, proteinase and lipase, revealed the simultaneous degradation of polysaccharides and proteins, while lipids seem largely preserved. In the fresh surface macroaggregate samples, a pronounced degradation of the α-glycosidic bond compared to β-linkages. Degradation of the colloidal fraction proceeded faster in the higher molecular weight (MW) fractions. N-containing polysaccharides can be important constituents of the higher MW fraction while the lower MW constituents can mostly be composed of poly- and oligosaccharides. Since the polysaccharide component in the higher MW fraction is more degradable compared to N-containing polysaccharides, the higher MW fraction represents a possible path of organic nitrogen preservation. Enzymatic hydrolysis, using α-amylase and β-glucosidase, revealed the presence of α- and β-glycosidic linkages in all fractions with similar decomposition kinetics. Our results indicate that different fractions of macroaggregates are subjected to compositional selective reactivity with important implications for macroaggregate persistence in the seawater column and deposition

A HepG2 Cell-Based Biosensor That Uses Stainless Steel Electrodes for Hepatotoxin Detection

Humans are frequently exposed to environmental hepatotoxins, which can lead to liver failure. Biosensors may be the best candidate for the detection of hepatotoxins because of their high sensitivity and specificity, convenience, time-saving, low cost, and extremely low detection limit. To investigate suitability of HepG2 cells for biosensor use, different methods of adhesion on stainless steel surfaces were investigated, with three groups of experiments performed in vitro. Cytotoxicity assays, which include the resazurin assay, the neutral red assay (NR), and the Coomassie Brilliant Blue (CBB) assay, were used to determine the viability of HepG2 cells exposed to various concentrations of aflatoxin B1 (AFB1) and isoniazid (INH) in parallel. The viability of the HepG2 cells on the stainless steel surface was quantitatively and qualitatively examined with different microscopy techniques. A simple cell-based electrochemical biosensor was developed by evaluating the viability of the HepG2 cells on the stainless steel surface when exposed to various concentrations of AFB1 and INH by using electrochemical impedance spectroscopy (EIS). The results showed that HepG2 cells can adhere to the metal surface and could be used as part of the biosensor to determine simple hepatotoxic samples

Nature and lability of northern Adriatic macroaggregates

The key organic constituents of marine macroaggregates (makrogels) of prevalently phytoplankton origin, periodically occurring in the northern Adriatic Sea, are proteins, lipids and especially polysaccharides. In this article, the reactivity of various macroaggregate fractions in relation to their composition in order to decode the potentially "bioavailabe" fractions id summarized and discussed..

Immunophenotypes of anti-SARS-CoV-2 responses associated with fatal COVID-19

Background The relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood. Methods A longitudinal prospective cohort of hospitalised patients with COVID-19 (n=254) was followed up to 35 days after admission (median, 8 days). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T-, B- and natural killer lymphocyte subsets and serum interleukin-6 (IL-6) response. We used machine learning to identify patterns of the immune response and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors. Results Overall, 45 (18%) patients died within 28 days after hospitalisation. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR 3.36–21.69; 95% CI 1.51–163.61 and HR 8.39–10.79; 95% CI 1.20–82.67; p≤0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterised by a very low risk of mortality. Conclusions By employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6-mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice