Hungarian Academy of Sciences

About: Hungarian Academy of Sciences is a government organization based out in Budapest, Hungary. It is known for research contribution in the topics: Catalysis & Population. The organization has 21510 authors who have published 56712 publications receiving 1612286 citations. The organization is also known as: Magyar Tudományos Akadémia & MTA.

Population genomics of Bronze Age Eurasia

Abstract: The Bronze Age of Eurasia (around 3000-1000 BC) was a period of major cultural changes. However, there is debate about whether these changes resulted from the circulation of ideas or from human migrations, potentially also facilitating the spread of languages and certain phenotypic traits. We investigated this by using new, improved methods to sequence low-coverage genomes from 101 ancient humans from across Eurasia. We show that the Bronze Age was a highly dynamic period involving large-scale population migrations and replacements, responsible for shaping major parts of present-day demographic structure in both Europe and Asia. Our findings are consistent with the hypothesized spread of Indo-European languages during the Early Bronze Age. We also demonstrate that light skin pigmentation in Europeans was already present at high frequency in the Bronze Age, but not lactose tolerance, indicating a more recent onset of positive selection on lactose tolerance than previously thought.

Prediction of transmembrane alpha-helices in prokaryotic membrane proteins: the dense alignment surface method.

Abstract: Prediction of transmembrane α-helices in prokaryotic membrane proteins : the dense alignment surface method

Evolutionary dynamics of group interactions on structured populations: a review.

Abstract: Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory.

Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation

Abstract: Cellular electrophysiology experiments, important for understanding cardiac arrhythmia mechanisms, are usually performed with channels expressed in non myocytes, or with non-human myocytes. Differences between cell types and species affect results. Thus, an accurate model for the undiseased human ventricular action potential (AP) which reproduces a broad range of physiological behaviors is needed. Such a model requires extensive experimental data, but essential elements have been unavailable. Here, we develop a human ventricular AP model using new undiseased human ventricular data: Ca2+ versus voltage dependent inactivation of L-type Ca2+ current (ICaL); kinetics for the transient outward, rapid delayed rectifier (IKr), Na+/Ca2+ exchange (INaCa), and inward rectifier currents; AP recordings at all physiological cycle lengths; and rate dependence and restitution of AP duration (APD) with and without a variety of specific channel blockers. Simulated APs reproduced the experimental AP morphology, APD rate dependence, and restitution. Using undiseased human mRNA and protein data, models for different transmural cell types were developed. Experiments for rate dependence of Ca2+ (including peak and decay) and intracellular sodium ([Na+]i) in undiseased human myocytes were quantitatively reproduced by the model. Early afterdepolarizations were induced by IKr block during slow pacing, and AP and Ca2+ alternans appeared at rates >200 bpm, as observed in the nonfailing human ventricle. Ca2+/calmodulin-dependent protein kinase II (CaMK) modulated rate dependence of Ca2+ cycling. INaCa linked Ca2+ alternation to AP alternans. CaMK suppression or SERCA upregulation eliminated alternans. Steady state APD rate dependence was caused primarily by changes in [Na+]i, via its modulation of the electrogenic Na+/K+ ATPase current. At fast pacing rates, late Na+ current and ICaL were also contributors. APD shortening during restitution was primarily dependent on reduced late Na+ and ICaL currents due to inactivation at short diastolic intervals, with additional contribution from elevated IKr due to incomplete deactivation.

The CNN paradigm

Abstract: A concise tutorial description of the cellular neural network (CNN) paradigm is given, along with a precise taxonomy. The CNN is defined, and the canonical equations are described. The importance of many independent input signal arrays, adaptive templates, and the multilayer capability is emphasized and motivated by examples. It is shown how simply a wave-type partial differential equation can be generated. >