Effects of hydrogen peroxide on the content of major volatile halogenated compounds in the red alga Asparagopsis taxiformis (Bonnemaisoniaceae)

The genus Asparagopsis is a prolific source of halogenated metabolites. Due to its commercial applications, it has been intensively cultivated in southern Portugal. In the present study, we assess if the internal levels of the major halogenated metabolites (bromoform and dibromoacetic acid) in Asparagopsis taxiformis can be increased with hydrogen peroxide (H2O2) addition. Previous studies with red algae showed that the production/release of bromoform can be enhanced by exogenously supplying H2O2. However, no study has assessed if H2O2 supply enhances the content of secondary metabolites within the biomass. This detail is important as the objective of the proposed research is to enhance the content of these valuable metabolites in the produced biomass. Both the activity of the haloperoxidase enzyme and the metabolite content were assessed on short-term and long-term incubation periods to H2O2. To determine the susceptibility of A. taxiformis photosynthetic performance to the imposed oxidative stress, the in vivo fluorescence of photosystem II was monitored. A. taxiformis was shown to be physiologically vulnerable to H2O2, given the observed decrease of the maximum quantum yield of photosynthesis (F v/F m). Contrary to what was expected, the presence of H2O2 inhibited the activity of the iodoperoxidase enzyme. Nevertheless, the extracted halogenated metabolites were higher over the first hours of exposure to H2O2, decreasing after 48 h. These results are probably related to the prosthetic group of the halogenated enzyme in A. taxiformis and the long-term oxidative stress damage of H2O2 exposure. Considering the objective of the proposed research, addition of H2O2 to the cultures, prior (3 h) to biomass harvesting, increases the metabolite content

Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network.

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke

Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network.

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P&lt;0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke