Hematologic and hepatic responses of the freshwater fish Hoplias malabaricus after saxitoxin exposure.

The bioaccumulation of saxitoxins (STX) in the trophic chain, mainly in freshwater, are not completely known. This work aimed to elucidate the effects of STX on Hoplias malabaricus through trophic bioassay. The fish were fed once every five days with Astyanax sp. before being subjected to an intraperitoneal inoculation with the lysate of Cylindrospermopsis raciborskii culture containing 97% STX and 3% by neosaxitoxin and gonyautoxin during 20 days. The animal?s liver was assessed using biomarkers as activities of superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), and glutathione peroxidase (GPx), and concentrations of reduced glutathione (GSH) and lipoperoxidation (LPO) and protein carbonylation (PCO). In the blood was analyzed the genotoxic and hematological parameters. The hepatosomatic index and the relative condition factor did not show a significant difference between the exposed and control groups. The values of mean corpuscular hemoglobin concentration and mean corpuscular hemoglobin increased in the STX group. The hepatic tissue from both groups exhibited a typical pattern that have been already described for most teleost fish. The results suggested the generation of reactive oxygen species, with increased activity of GPx and concentrations of LPO and GSH; whereas the specific activity of SOD decreased. However, no changes were observed in the CAT, PCO, and DNA damage. Although the STX effects are known as neurotoxic, this cyanotoxin caused liver biochemical alterations that can be considered ecologically relevant

Effects of COVID-19 Lockdown on Melanoma Diagnosis in Switzerland: Increased Tumor Thickness in Elderly Females and Shift towards Stage IV Melanoma during Lockdown.

At the early stages of the COVID-19 outbreak in 2020, Switzerland was among the countries with the highest number of SARS-CoV2-infections per capita in the world. Lockdowns had a remarkable impact on primary care access and resulted in postponed cancer screenings. The aim of this study was to investigate the effects of the COVID-19 lockdown on the diagnosis of melanomas and stage of melanomas at diagnosis. In this retrospective, exploratory cohort study, 1240 patients with a new diagnosis of melanoma were analyzed at five tertiary care hospitals in German-speaking Switzerland over a period of two years and three months. We compared the pre-lockdown (01/FEB/19-15/MAR/20, n = 655) with the lockdown (16/MAR/20-22/JUN/20, n = 148) and post-lockdown period (23/JUN/20-30/APR/21, n = 437) by evaluating patients' demographics and prognostic features using Breslow thickness, ulceration, subtype, and stages. We observed a short-term, two-week rise in melanoma diagnoses after the major lift of social lockdown restrictions. The difference of mean Breslow thicknesses was significantly greater in older females during the lockdown compared to the pre-lockdown (1.9 ± 1.3 mm, p = 0.03) and post-lockdown period (1.9 ± 1.3 mm, p = 0.048). Thickness increase was driven by nodular melanomas (2.9 ± 1.3 mm, p = 0.0021; resp. 2.6 ± 1.3 mm, p = 0.008). A proportional rise of advanced melanomas was observed during lockdown (p = 0.047). The findings provide clinically relevant insights into lockdown-related gender- and age-dependent effects on melanoma diagnosis. Our data highlight a stable course in new melanomas with a lower-than-expected increase in the post-lockdown period. The lockdown period led to a greater thickness in elderly women driven by nodular melanomas and a proportional shift towards stage IV melanoma. We intend to raise awareness for individual cancer care in future pandemic management strategies

Lifespan extension and the doctrine of double effect

Recent developments in biogerontology—the study of the biology of ageing—suggest that it may eventually be possible to intervene in the human ageing process. This, in turn, offers the prospect of significantly postponing the onset of age-related diseases. The biogerontological project, however, has met with strong resistance, especially by deontologists. They consider the act of intervening in the ageing process impermissible on the grounds that it would (most probably) bring about an extended maximum lifespan—a state of affairs that they deem intrinsically bad. In a bid to convince their deontological opponents of the permissibility of this act, proponents of biogerontology invoke an argument which is grounded in the doctrine of double effect. Surprisingly, their argument, which we refer to as the ‘double effect argument’, has gone unnoticed. This article exposes and critically evaluates this ‘double effect argument’. To this end, we first review a series of excerpts from the ethical debate on biogerontology in order to substantiate the presence of double effect reasoning. Next, we attempt to determine the role that the ‘double effect argument’ is meant to fulfil within this debate. Finally, we assess whether the act of intervening in ageing actually can be justified using double effect reasoning

OTIMIZAÇÃO DE PORTFÓLIOS: ANÁLISE DE EFICIÊNCIA

This article aims to analyze the behavior of a portfolio of assets selected by Data Envelopment Analysis (DEA), optimized by the Sharpe approach, and compare it to portfolios of assets obtained only by DEA or the Sharpe approach. To do that, we used the DEA model to assess the efficiency of shares of the São Paulo Stock Exchange (Bovespa), employing return, variance and other indicators such as input and output variables. Also, we used the Sharpe approach to optimize the portfolio composition. In the comparison of portfolios, we noted that the resulting combination of both models performed better than the portfolios optimized by only one of the models

Feeding into old age: long-term effects of dietary fatty acid supplementation on tissue composition and life span in mice

Smaller mammals, such as mice, possess tissues containing more polyunsaturated fatty acids (PUFAs) than larger mammals, while at the same time live shorter lives. These relationships have been combined in the ‘membrane pacemaker hypothesis of aging’. It suggests that membrane PUFA content might determine an animal’s life span. PUFAs in general and certain long-chain PUFAs in particular, are highly prone to lipid peroxidation which brings about a high rate of reactive oxygen species (ROS) production. We hypothesized that dietary supplementation of either n-3 or n-6 PUFAs might affect (1) membrane phospholipid composition of heart and liver tissues and (2) life span of the animals due to the altered membrane composition, and subsequent effects on lipid peroxidation. Therefore, we kept female laboratory mice from the C57BL/6 strain on three diets (n-3 PUFA rich, n-6 PUFA rich, control) and assessed body weights, life span, heart, and liver phospholipid composition after the animals had died. We found that while membrane phospholipid composition clearly differed between feeding groups, life span was not directly affected. However, we were able to observe a positive correlation between monounsaturated fatty acids in cardiac muscle and life span

Identification of FasL as a crucial host factor driving COVID-19 pathology and lethality

The dysregulated immune response and inflammation resulting in severe COVID-19 are still incompletely understood. Having recently determined that aberrant death-ligand-induced cell death can cause lethal inflammation, we hypothesized that this process might also cause or contribute to inflammatory disease and lung failure following SARS-CoV-2 infection. To test this hypothesis, we developed a novel mouse-adapted SARS-CoV-2 model (MA20) that recapitulates key pathological features of COVID-19. Concomitantly with occurrence of cell death and inflammation, FasL expression was significantly increased on inflammatory monocytic macrophages and NK cells in the lungs of MA20-infected mice. Importantly, therapeutic FasL inhibition markedly increased survival of both, young and old MA20-infected mice coincident with substantially reduced cell death and inflammation in their lungs. Intriguingly, FasL was also increased in the bronchoalveolar lavage fluid of critically-ill COVID-19 patients. Together, these results identify FasL as a crucial host factor driving the immuno-pathology that underlies COVID-19 severity and lethality, and imply that patients with severe COVID-19 may significantly benefit from therapeutic inhibition of FasL

Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance

Prediction of metabolic clusters in early lactation dairy cows using models based on 2 milk biomarkers

The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and beta-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immuno-gamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbalanced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the "balanced" group (n = 43) and were compared with cows in what was referred to as the "other balanced" group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the "imbalanced" group (n = 19) and compared with cows in what was referred to as the "other imbalanced" group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids arid BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-beta-D-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, parity, milk yield featurs) were used to create predictive models for the metabolic clusters. Accuracy for prediction of balanced (80%) and imbalanced (88%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning