Fast assessment of long axis strain with standard cardiovascular magnetic resonance: a validation study of a novel parameter with reference values

Background: Assessment of longitudinal function with cardiovascular magnetic resonance (CMR) is limited to measurement of systolic excursion of the mitral annulus (MAPSE) or elaborate strain imaging modalities. The aim of this study was to develop a fast assessable parameter for the measurement of long axis strain (LAS) with CMR. Methods: 40 healthy volunteers and 125 patients with different forms of cardiomyopathy were retrospectively analyzed. Four different approaches for the assessment of LAS with CMR measuring the distance between the LV apex and a line connecting the origins of the mitral valve leaflets in enddiastole and endsystole were evaluated. Values for LAS were calculated according to the strain formula. Results: LAS derived from the distance of the epicardial apical border to the midpoint of the line connecting the mitral valve insertion points (LAS-epi/mid) proved to be the most reliable parameter for the assessment of LAS among the different approaches. LAS-epi/mid displayed the highest sensitivity (81.6 %) and specificity (97.5 %), furthermore showing the best correlation with feature tracking (FTI) derived transmural longitudinal strain (r = 0.85). Moreover, LAS-epi/mid was non-inferior to FTI in discriminating controls from patients (Area under the curve (AUC) = 0.95 vs. 0.94, p = NS). The time required for analysis of LAS-epi/mid was significantly shorter than for FTI (67 ± 8 s vs. 180 ± 14 s, p < 0.0001). Additionally, LAS-epi/mid performed significantly better than MAPSE (Delta AUC = 0.09; p < 0.005) and the ejection fraction (Delta AUC = 0.11; p = 0.0002). Reference values were derived from 234 selected healthy volunteers. Mean value for LAS-epi/mid was −17.1 ± 2.3 %. Mean values for men were significantly lower compared to women (−16.5 ± 2.2 vs. -17.9 ± 2.1 %; p < 0.0001), while LAS decreased with age. Conclusions: LAS-epi/mid is a novel and fast assessable parameter for the analysis of global longitudinal function with non-inferiority compared to transmural longitudinal strain

Adaptive Evolution of the Myo6 Gene in Old World Fruit Bats (Family: Pteropodidae)

PMCID: PMC3631194This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

A mathematical model of aging-related and cortisol induced hippocampal dysfunction

<p>Abstract</p> <p>Background</p> <p>The hippocampus is essential for declarative memory synthesis and is a core pathological substrate for Alzheimer's disease (AD), the most common aging-related dementing disease. Acute increases in plasma cortisol are associated with transient hippocampal inhibition and retrograde amnesia, while chronic cortisol elevation is associated with hippocampal atrophy. Thus, cortisol levels could be monitored and managed in older people, to decrease their risk of AD type hippocampal dysfunction. We generated an in silico<it/>model of the chronic effects of elevated plasma cortisol on hippocampal activity and atrophy, using the systems biology mark-up language (SBML). We further challenged the model with biologically based interventions to ascertain if cortisol associated hippocampal dysfunction could be abrogated.</p> <p>Results</p> <p>The in silico<it/>SBML model reflected the in vivo<it/>aging of the hippocampus and increased plasma cortisol and negative feedback to the hypothalamic pituitary axis. Aging induced a 12% decrease in hippocampus activity (HA), increased to 30% by acute and 40% by chronic elevations in cortisol. The biological intervention attenuated the cortisol associated decrease in HA by 2% in the acute cortisol simulation and by 8% in the chronic simulation.</p> <p>Conclusion</p> <p>Both acute and chronic elevations in cortisol secretion increased aging-associated hippocampal atrophy and a loss of HA in the model. We suggest that this first SMBL model, in tandem with in vitro<it/>and in vivo<it/>studies, may provide a backbone to further frame computational cortisol and brain aging models, which may help predict aging-related brain changes in vulnerable older people.</p

Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

New Episodic Learning Interferes with the Reconsolidation of Autobiographical Memories

It is commonly assumed that, with time, an initially labile memory is transformed into a permanent one via a process of consolidation. Yet, recent evidence indicates that memories can return to a fragile state again when reactivated, requiring a period of reconsolidation. In the study described here, we found that participants who memorized a story immediately after they had recalled neutral and emotional experiences from their past were impaired in their memory for the neutral (but not for the emotional) experiences one week later. The effect of learning the story depended critically on the preceding reactivation of the autobiographical memories since learning without reactivation had no effect. These results suggest that new learning impedes the reconsolidation of neutral autobiographical memories

Differences in Cell Division Rates Drive the Evolution of Terminal Differentiation in Microbes

Multicellular differentiated organisms are composed of cells that begin by developing from a single pluripotent germ cell. In many organisms, a proportion of cells differentiate into specialized somatic cells. Whether these cells lose their pluripotency or are able to reverse their differentiated state has important consequences. Reversibly differentiated cells can potentially regenerate parts of an organism and allow reproduction through fragmentation. In many organisms, however, somatic differentiation is terminal, thereby restricting the developmental paths to reproduction. The reason why terminal differentiation is a common developmental strategy remains unexplored. To understand the conditions that affect the evolution of terminal versus reversible differentiation, we developed a computational model inspired by differentiating cyanobacteria. We simulated the evolution of a population of two cell types –nitrogen fixing or photosynthetic– that exchange resources. The traits that control differentiation rates between cell types are allowed to evolve in the model. Although the topology of cell interactions and differentiation costs play a role in the evolution of terminal and reversible differentiation, the most important factor is the difference in division rates between cell types. Faster dividing cells always evolve to become the germ line. Our results explain why most multicellular differentiated cyanobacteria have terminally differentiated cells, while some have reversibly differentiated cells. We further observed that symbioses involving two cooperating lineages can evolve under conditions where aggregate size, connectivity, and differentiation costs are high. This may explain why plants engage in symbiotic interactions with diazotrophic bacteria

Digital Well-Being and Manipulation Online

Social media use is soaring globally. Existing research of its ethical implications predominantly focuses on the relationships amongst human users online, and their effects. The nature of the software-to-human relationship and its impact on digital well-being, however, has not been sufficiently addressed yet. This paper aims to close the gap. I argue that some intelligent software agents, such as newsfeed curator algorithms in social media, manipulate human users because they do not intend their means of influence to reveal the user’s reasons. I support this claim by defending a novel account of manipulation and by showing that some intelligent software agents are manipulative in this sense. Apart from revealing a priori reason for thinking that some intelligent software agents are manipulative, the paper offers a framework for further empirical investigation of manipulation online

Development of a Management Algorithm for Post-operative Pain (MAPP) after total knee and total hip replacement: study rationale and design.

BACKGROUND: Evidence from clinical practice and the extant literature suggests that post-operative pain assessment and treatment is often suboptimal. Poor pain management is likely to persist until pain management practices become consistent with guidelines developed from the best available scientific evidence. This work will address the priority in healthcare of improving the quality of pain management by standardising evidence-based care processes through the incorporation of an algorithm derived from best evidence into clinical practice. In this paper, the methodology for the creation and implementation of such an algorithm that will focus, in the first instance, on patients who have undergone total hip or knee replacement is described. METHODS: In partnership with clinicians, and based on best available evidence, the aim of the Management Algorithm for Post-operative Pain (MAPP) project is to develop, implement, and evaluate an algorithm designed to support pain management decision-making for patients after orthopaedic surgery. The algorithm will provide guidance for the prescription and administration of multimodal analgesics in the post-operative period, and the treatment of breakthrough pain. The MAPP project is a multisite study with one coordinating hospital and two supporting (rollout) hospitals. The design of this project is a pre-implementation-post-implementation evaluation and will be conducted over three phases. The Promoting Action on Research Implementation in Health Services (PARiHS) framework will be used to guide implementation. Outcome measurements will be taken 10 weeks post-implementation of the MAPP. The primary outcomes are: proportion of patients prescribed multimodal analgesics in accordance with the MAPP; and proportion of patients with moderate to severe pain intensity at rest. These data will be compared to the pre-implementation analgesic prescribing practices and pain outcome measures. A secondary outcome, the efficacy of the MAPP, will be measured by comparing pain intensity scores of patients where the MAPP guidelines were or were not followed. DISCUSSION: The outcomes of this study have relevance for nursing and medical professionals as well as informing health service evaluation. In establishing a framework for the sustainable implementation and evaluation of a standardised approach to post-operative pain management, the findings have implications for clinicians and patients within multiple surgical contexts