Differential Immune Response to Bioprosthetic Heart Valve Tissues in the α1,3Galactosyltransferase-Knockout Mouse Model

Structural valve deterioration (SVD) of bioprosthetic heart valves (BHVs) has great clinical and economic consequences. Notably, immunity against BHVs plays a major role in SVD, especially when implanted in young and middle-aged patients. However, the complex pathogenesis of SVD remains to be fully characterized, and analyses of commercial BHVs in standardized-preclinical settings are needed for further advancement. Here, we studied the immune response to commercial BHV tissue of bovine, porcine, and equine origin after subcutaneous implantation into adult a1,3-galactosyltransferase-knockout (Gal KO) mice. The levels of serum anti-galactose a1,3-galactose (Gal) and -non-Gal IgM and IgG antibodies were determined up to 2 months post-implantation. Based on histological analyses, all BHV tissues studied triggered distinct infiltrating cellular immune responses that related to tissue degeneration. Increased anti-Gal antibody levels were found in serum after ATS 3f and Freedom/Solo implantation but not for Crown or Hancock II grafts. Overall, there were no correlations between cellular-immunity scores and post-implantation antibodies, suggesting these are independent factors differentially affecting the outcome of distinct commercial BHVs. These findings provide further insights into the understanding of SVD immunopathogenesis and highlight the need to evaluate immune responses as a confounding factor

Reviewing the use of resilience concepts in forest sciences

Purpose of the review Resilience is a key concept to deal with an uncertain future in forestry. In recent years, it has received increasing attention from both research and practice. However, a common understanding of what resilience means in a forestry context, and how to operationalise it is lacking. Here, we conducted a systematic review of the recent forest science literature on resilience in the forestry context, synthesising how resilience is defined and assessed. Recent findings Based on a detailed review of 255 studies, we analysed how the concepts of engineering resilience, ecological resilience, and social-ecological resilience are used in forest sciences. A clear majority of the studies applied the concept of engineering resilience, quantifying resilience as the recovery time after a disturbance. The two most used indicators for engineering resilience were basal area increment and vegetation cover, whereas ecological resilience studies frequently focus on vegetation cover and tree density. In contrast, important social-ecological resilience indicators used in the literature are socio-economic diversity and stock of natural resources. In the context of global change, we expected an increase in studies adopting the more holistic social-ecological resilience concept, but this was not the observed trend. Summary Our analysis points to the nestedness of these three resilience concepts, suggesting that they are complementary rather than contradictory. It also means that the variety of resilience approaches does not need to be an obstacle for operationalisation of the concept. We provide guidance for choosing the most suitable resilience concept and indicators based on the management, disturbance and application context

Screening Human Embryos for Polygenic Traits Has Limited Utility

The increasing proportion of variance in human complex traits explained by polygenic scores, along with progress in preimplantation genetic diagnosis, suggests the possibility of screening embryos for traits such as height or cognitive ability. However, the expected outcomes of embryo screening are unclear, which undermines discussion of associated ethical concerns. Here, we use theory, simulations, and real data to evaluate the potential gain of embryo screening, defined as the difference in trait value between the top-scoring embryo and the average embryo. The gain increases very slowly with the number of embryos but more rapidly with the variance explained by the score. Given current technology, the average gain due to screening would be ≈2.5 cm for height and ≈2.5 IQ points for cognitive ability. These mean values are accompanied by wide prediction intervals, and indeed, in large nuclear families, the majority of children top-scoring for height are not the tallest. © 2019 Elsevier Inc. Recent progress in genetic testing of embryos has made it technically feasible to profile IVF embryos for polygenic traits such as height or IQ, but simulations, models, and empirical data show that the gain in trait value when selecting the top-scoring embryo is currently limited and uncertain. © 2019 Elsevier Inc

LC–MS Analysis of Polyclonal Human Anti-Neu5Gc Xeno-Autoantibodies Immunoglobulin G Subclass and Partial Sequence Using Multistep Intravenous Immunoglobulin Affinity Purification and Multienzymatic Digestion

Human polyclonal IgG antibodies directly against the non-human sialic acid N-glycolylneuraminic acid (Neu5Gc) are potential biomarkers and mechanistic contributors to cancer and other diseases associated with chronic inflammation. Using a sialoglycan microarray, we screened the binding pattern of such antibodies (anti-Neu5Gc IgG) in several samples of clinically-approved human IVIG (IgG). These results were used to select an appropriate sample for a multi-step affinity purification of the xeno-autoantibody fraction. The sample was then analyzed via our multi-enzyme digestion procedure followed by nanoLC coupled to LTQ-FTMS. We used characteristic and unique peptide sequences to determine the IgG subclass distribution and thus provided direct evidence that all four IgG subclasses can be generated during a xeno-autoantibody immune response to carbohydrate Neu5Gc-antigens. Furthermore, we obtained a significant amount of sequence coverage of both the constant and variable regions. The approach described here, therefore, provides a way to characterize these clinically significant antibodies, helping to understand their origins and significance

Clinical stability and propensity score matching in Cardiac Surgery: Is the clinical evaluation of treatment efficacy algorithm-dependent in small sample size settings?

Background: Propensity score matching represents one of the most popular techniques to deal with treatment allocation bias in observational studies. However, when the number of enrolled patients is very low, the creation of matched set of subjects may highly depend on the model used to estimate individual propensity scores, undermining the stability of consequential clinical findings. In this study, we investigate the potential issues related to the stability of the matched sets created by different propensity score models and we propose some diagnostic tools to evaluate them. Methods: Matched groups of patients were created using five different methods: Logistic Regression, Classification and Regression Trees, Bagging, Random Forest and Generalized Boosted Model. Differences between subjects in the matched sets were evaluated by comparing both pre-treatment covariates and propensity score distributions. We applied our proposal to a cardio-surgical observational study that aims to compare two different procedures of cardiac valve replacement. Results: Both baseline characteristics and propensity score distributions were systematically different across matched samples of patients created with different models used to estimate propensity score. The most relevant differences were observed for the matched set created by estimating individual propensity scores with Classification and Regression Trees algorithm. Conclusion: Clinical stability of matched samples created with different statistical methods should always be evaluated to ensure reliability of final estimates. This work opens the door for future investigations that fully assess the implications of this finding