Defining "Development".

Is it possible, and in the first place is it even desirable, to define what "development" means and to determine the scope of the field called "developmental biology"? Though these questions appeared crucial for the founders of "developmental biology" in the 1950s, there seems to be no consensus today about the need to address them. Here, in a combined biological, philosophical, and historical approach, we ask whether it is possible and useful to define biological development, and, if such a definition is indeed possible and useful, which definition(s) can be considered as the most satisfactory

Social epigenetics: a science of social science?

Epigenetics has considerable potential to transform social science by embedding mutually regulative reciprocal connections between biological and social processes within the human activities it studies. This paper highlights common epigenetic methods and outlines practical considerations in the design of ‘social epigenetics’ research addressing the identification of biomolecular pathways, statistical inference of causality, conceptualization of the environment as a biochemical event, heritability of epigenetic alterations and intergenerational accountability, and concept of time implied by attempts to capture complex, non‐linear gene‐environment interactions. Finally, we reflect on the social epigenome as a conceptual space and try to identify barriers to translation, and practical and ethical issues raised by epigenetics research. In order for social epigenetics and social science to contribute to the emergence of this putative ‘science of social science’ and to capture meaningful human experience they will both need to change significantly

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

The Chitin Connection

Chitin, a polymer of N-acetylglucosamine, is an essential component of the fungal cell wall. Chitosan, a deacetylated form of chitin, is also important in maintaining cell wall integrity and is essential for Cryptococcus neoformans virulence. In their article, Gilbert et al. [N. M. Gilbert, L. G. Baker, C. A. Specht, and J. K. Lodge, mBio 3(1):e00007-12, 2012] demonstrate that the enzyme responsible for chitosan synthesis, chitin deacetylase (CDA), is differentially attached to the cell membrane and wall. Bioactivity is localized to the cell membrane, where it is covalently linked via a glycosylphosphatidylinositol (GPI) anchor. Findings from this study significantly enhance our understanding of cryptococcal cell wall biology. Besides the role of chitin in supporting structural stability, chitin and host enzymes with chitinase activity have an important role in host defense and modifying the inflammatory response. Thus, chitin appears to provide a link between the fungus and host that involves both innate and adaptive immune responses. Recently, there has been increased attention to the role of chitinases in the pathogenesis of allergic inflammation, especially asthma. We review these findings and explore the possible connection between fungal infections, the induction of chitinases, and asthma

The emerging structure of the Extended Evolutionary Synthesis: where does Evo-Devo fit in?

The Extended Evolutionary Synthesis (EES) debate is gaining ground in contemporary evolutionary biology. In parallel, a number of philosophical standpoints have emerged in an attempt to clarify what exactly is represented by the EES. For Massimo Pigliucci, we are in the wake of the newest instantiation of a persisting Kuhnian paradigm; in contrast, Telmo Pievani has contended that the transition to an EES could be best represented as a progressive reformation of a prior Lakatosian scientific research program, with the extension of its Neo-Darwinian core and the addition of a brand-new protective belt of assumptions and auxiliary hypotheses. Here, we argue that those philosophical vantage points are not the only ways to interpret what current proposals to ‘extend’ the Modern Synthesis-derived ‘standard evolutionary theory’ (SET) entail in terms of theoretical change in evolutionary biology. We specifically propose the image of the emergent EES as a vast network of models and interweaved representations that, instantiated in diverse practices, are connected and related in multiple ways. Under that assumption, the EES could be articulated around a paraconsistent network of evolutionary theories (including some elements of the SET), as well as models, practices and representation systems of contemporary evolutionary biology, with edges and nodes that change their position and centrality as a consequence of the co-construction and stabilization of facts and historical discussions revolving around the epistemic goals of this area of the life sciences. We then critically examine the purported structure of the EES—published by Laland and collaborators in 2015—in light of our own network-based proposal. Finally, we consider which epistemic units of Evo-Devo are present or still missing from the EES, in preparation for further analyses of the topic of explanatory integration in this conceptual framework

Intermittent pair-housing, pair relationship qualities, and HPA activity in adult female rhesus macaques

Laboratory rhesus macaques are often housed in pairs and may be temporarily or permanently separated for research, health, or management reasons. While both long-term social separations and introductions can stimulate a stress response that impacts inflammation and immune function, the effects of short-term overnight separations and whether qualities of the pair relationship mediate these effects are unknown. In this study, we investigated the effects of overnight separations on the urinary cortisol concentration of 20 differentially paired adult female rhesus macaques (Macaca mulatta) at the California National Primate Research Center. These females were initially kept in either continuous (no overnight separation) or intermittent (with overnight separation) pair-housing and then switched to the alternate pair-housing condition partway through the study. Each study subject was observed for 5 weeks, during which we collected measures of affiliative, aggressive, anxious, abnormal, and activity-state behaviors in both pair-housing conditions. Additionally, up to three urine samples were collected from each subject per week and assayed for urinary free cortisol and creatinine. Lastly, the behavioral observer scored each pair on four relationship quality attributes (“Anxious,” “Tense,” “Well-meshed,” and “Friendly”) using a seven-point scale. Data were analyzed using a generalized linear model with gamma distribution and an information theoretic approach to determine the best model set. An interaction between the intermittent pairing condition and tense pair adjective rating was in the top three models of the best model set. Dominance and rates of affiliation were also important for explaining urinary cortisol variation. Our results suggest that to prevent significant changes in HPA-axis activation in rhesus macaque females, which could have unintended effects on research outcomes, pairs with “Tense” relationships and overnight separations preventing tactile contact should be avoided