Interactomics: Dozens of Viruses, Co-evolving With Humans, Including the Influenza A Virus, may Actively Distort Human Aging.

Some viruses (e.g., human immunodeficiency virus 1 and severe acute respiratory syndrome coronavirus 2) have been experimentally proposed to accelerate features of human aging and of cellular senescence. These observations, along with evolutionary considerations on viral fitness, raised the more general puzzling hypothesis that, beyond documented sources in human genetics, aging in our species may also depend on virally encoded interactions distorting our aging to the benefits of diverse viruses. Accordingly, we designed systematic network-based analyses of the human and viral protein interactomes, which unraveled dozens of viruses encoding proteins experimentally demonstrated to interact with proteins from pathways associated with human aging, including cellular senescence. We further corroborated our predictions that specific viruses interfere with human aging using published experimental evidence and transcriptomic data; identifying influenza A virus (subtype H1N1) as a major candidate age distorter, notably through manipulation of cellular senescence. By providing original evidence that viruses may convergently contribute to the evolution of numerous age-associated pathways through co-evolution, our network-based and bipartite network-based methodologies support an ecosystemic study of aging, also searching for genetic causes of aging outside a focal aging species. Our findings, predicting age distorters and targets for anti-aging therapies among human viruses, could have fundamental and practical implications for evolutionary biology, aging study, virology, medicine, and demography.

Network analyses unveil ageing-associated pathways evolutionarily conserved from fungi to animals.

The genetic roots of the diverse paces and shapes of ageing and of the large variations in longevity observed across the tree of life are poorly understood. Indeed, pathways associated with ageing/longevity are incompletely known, both in terms of their constitutive genes/proteins and of their molecular interactions. Moreover, there is limited overlap between the genes constituting these pathways across mammals. Yet, dedicated comparative analyses might still unravel evolutionarily conserved, important pathways associated with longevity or ageing. Here, we used an original strategy with a double evolutionary and systemic focus to analyse protein interactions associated with ageing or longevity during the evolution of five species of Opisthokonta. We ranked these proteins and interactions based on their evolutionary conservation and centrality in past and present protein-protein interaction (PPI) networks, providing a big systemic picture of the evolution of ageing and longevity pathways that identified which pathways emerged in which Opisthokonta lineages, were conserved, and/or central. We confirmed that longevity/ageing-associated proteins (LAPs), be they pro- or anti-longevity, are highly central in extant PPI, consistently with the antagonistic pleiotropy theory of ageing, and identified key antagonistic regulators of ageing/longevity, 52 of which with homologues in humans. While some highly central LAPs were evolutionarily conserved for over a billion years, we report a clear transition in the functionally important components of ageing/longevity within bilaterians. We also predicted 487 novel evolutionarily conserved LAPs in humans, 54% of which are more central than mTOR, and 138 of which are druggable, defining new potential targets for anti-ageing treatments in humans.

Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia.

Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.

Influence of contrast agent dispersion on bolus-based MRI myocardial perfusion measurements: A computational fluid dynamics study.

PURPOSE: Bolus-based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in-silico model of the coronary arteries down to the pre-arteriolar vessels has been developed. METHODS: In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre-arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification. RESULTS: Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are -28% ± 16% and -8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree. CONCLUSION: Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus-based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.

Hamilton meets causal decision theory.

In this paper, I contrast two mathematically equivalent ways of modeling the evolution of altruism, namely the classical inclusive fitness approach and a more recent, "direct fitness" approach. Though both are usually considered by evolutionists as mere different ways of representing the same causal process (i.e. that of kin selection), I argue that this consensus is misleading, for there is a fundamental ambiguity concerning the causal interpretation of the DF approach. Drawing on an analogy between the structure of inclusive fitness theory and that of causal decision theory (Stalnaker, 1972), I show that only the inclusive fitness framework can provide us with a proper, and unambiguous causal partition of the relevant variables involved in the evolution of altruism.

The behavioural ecology of irrational behaviours.

Natural selection is often envisaged as the ultimate cause of the apparent rationality exhibited by organisms in their specific habitat. Given the equivalence between selection and rationality as maximizing processes, one would indeed expect organisms to implement rational decision-makers. Yet, many violations of the clauses of rationality have been witnessed in various species such as starlings, hummingbirds, amoebas and honeybees. This paper attempts to interpret such discrepancies between economic rationality (defined by the main axioms of rational choice theory) and biological rationality (defined by natural selection). After having distinguished two kinds of rationality we introduce irrationality as a negation of economic rationality by biologically rational decision-makers. Focusing mainly on those instances of irrationalities that can be understood as exhibiting inconsistency in making choices, i.e. as non-conformity of a given behaviour to axioms such as transitivity or independence of irrelevant alternatives, we propose two possible families of Darwinian explanations that may account for these apparent irrationalities. First, we consider cases where natural selection may have been an indirect cause of irrationality. Second, we consider putative cases where violations of rationality axioms may have been directly favored by natural selection. Though the latter cases (prima facie) seem to clearly contradict our intuitive representation of natural selection as a process that maximizes fitness, we argue that they are actually unproblematic; for often, they can be redescribed as cases where no rationality axiom is violated, or as situations where no adaptive solution exists in the first place.

The causal meaning of Hamilton's rule.

Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'.

Magnetic flimmers: 'light in the electromagnetic darkness'.

Transcranial magnetic stimulation has become an important field for both research in neuroscience and for therapy since Barker in 1985 showed that it was possible to stimulate the human motor cortex with an electromagnet. Today for instance, transcranial magnetic stimulation can be used to measure nerve conduction velocities and to create virtual lesions in the brain. The latter option creates the possibility to inactivate parts of the brain temporarily without permanent damage. In 2008, the American Food and Drugs Administration approved repetitive transcranial magnetic stimulation as a therapy for major depression under strict conditions. Repetitive transcranial magnetic stimulation has not yet been cleared for treatment of other diseases, including schizophrenia, anxiety disorders, obesity and Parkinson's disease, but results seem promising. Transcranial magnetic stimulation, however, was not invented at the end of the 20th century. The discovery of electromagnetism, the enthusiasm for electricity and electrotherapy, and the interest in Beard's concept of neurasthenia already resulted in the first electromagnetic treatments in the late 19th and early 20th century. In this article, we provide a history of electromagnetic stimulation circa 1900. From the data, we conclude that Mesmer's late 18th century ideas of 'animal magnetism' and the 19th century absence of physiological proof had a negative influence on the acceptance of this therapy during the first decades of the 20th century. Electromagnetism disappeared from neurological textbooks in the early 20th century to recur at the end of that century.

Organisms in evolution.

Organisms constitute one of the most remarkable features of our living world. However, they have not yet received any accepted characterization within the framework of the evolutionary theory. The reasons for this contrast between the saliency of organisms in the biological landscape and their theoretical status are multiple and they are analyzed in the first part of this paper. Starting from this contrast, I argue for a theoretically grounded concept of organism within the framework of evolutionary theory itself. To this effect I argue that the theory of major transitions in evolution (Maynard Smith and Szathmáry 1995; Michod 1999) provides us with the theoretical basis for an understanding of the individuality of organisms and I propose a first characterization of organisms as evolutionary units structured by a division of reproductive labor among their parts. I also discuss one of the most important implications of this definition, namely that some colonial entities are to be counted as superorganisms. Finally, I show that though theoretically satisfying, this definition does not suffice in order fully to individuate the organisms and superorganisms in practice. To this end, physiology is needed, because it offers us some criteria for their individuation in ecological space. These criteria, however, are not immune to errors through misidentification and their shortcomings are discussed in the last section. In conclusion, I emphasize the positive implications of these criteria concerning the ecological significance of organisms.

Pherogram normalization in capillary electrophoresis and micellar electrokinetic chromatography analyses in cases of sample matrix-induced migration time shifts.

When analyzing bio-matrix samples using capillary electrophoresis (CE) or micellar electrokinetic chromatography (MEKC), unwanted shifts in the time axis are often observed, both between samples and standards and between samples, thus hampering identification. These shifts are caused by either or both of two sample matrix-induced effects: variations in stacking conditions (effective field strength or migration length) and variations in electroosmotic flow. Based on elementary CE principles and provided that any two peaks in the pherograms can be linked, these variations can be separately accounted and quantitatively corrected for, so that perfectly overlapping pherograms of standards and samples can be obtained after normalization. The method was validated using samples of a DNA ladder, separated in a sieving polymer. In addition, a number of data files from CE and MEKC analyses (steroids, opioids, beta-blockers, amines, and inorganic anions) previously published by other authors were successfully normalized. A freeware computer programme, CEqualizer, for normalizing ASCII files of detector signals using the method described, is available to the CE community from http: //www.ceyork.f2s.com.