Destacados

Cada año, un comité de expertos debe acometer una ardua tarea: de entre todas las publicaciones de ICREA, debe escoger unas cuantas que destaquen del resto. Es todo un reto: a veces los debates se acaloran, y siempre son difíciles, pero acaba saliendo una lista con las mejors publicaciones del año. No se concede ningún premio, y el único reconocimiento adicional es el honor de ser resaltado en la web de ICREA. Cada publicación tiene algo especial, ya sea una solución especialmente elegante, un éxito espectacular en los medios de comunicación o la simple fascinación por una idea del todo nueva. Independientemente de la razón, se trata de los mejores de los mejores y, como tales, nos complace compartirlos aquí.

LIST OF SCIENTIFIC HIGHLIGHTS

Format: yyyy
  • RNA molecules attract proteins causing disease (2018)

    Tartaglia, Gian Gaetano (CRG)

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    RNA molecules attract proteins causing disease

    We analyzed protein-RNA networks and identified properties of RNA attracting proteins in large assemblies. We found that trinucleotide repeats in the FMR1 gene attract several proteins including the splicing factor TRA2A that aggregates in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).

     

  • What gamma-ray pulsars are X-ray bright, and why? (2018)

    Torres, Diego F. (CSIC - ICE)

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    What gamma-ray pulsars are X-ray bright, and why?

    Pulsars are dense, magnetic relics of massive stars, and are amongst the most extreme objects in the Universe. Originally detected through their radio emission, pulsars are now known to also emit other types of radiation. Some of this emission is standard thermal radiation – the type that everything with a temperature above absolute zero emits. But in pulsars, non-thermal radiation can also be created by synchrotron emission and curvature emission. Both processes involve charged particles being accelerated along magnetic field lines, causing them to radiate light that can vary in wavelength from radio waves to gamma-rays.

    This year, Torres developed a model that combined synchrotron and curvature radiation to predict whether pulsars detected in gamma-rays could also be expected to appear in X-rays.

    Despite the extreme precision of the observations, and the underlying complexity of the processes involved, just four physical parameters suffice in his model to fit the spectrum of all gamma and/or X-ray pulsars known, disregarding whether they are normal or millisecond pulsars, detected in X-rays or gamma-rays or both.

    When analyzing the fits for all pulsars, relevant correlations of the model parameters appear, explaining the different observational behaviors.

    This model answers at once what process is behind the emission spectra and how the spectral variety arises. It explains intricacies such as why we have detected flat spectra at low and high energies. And it provides a predictive tool by which to identify new X-ray pulsars.

    Torres also partnered with a team led by his former postdoc Jian Li, to select three gamma-ray emitting pulsars that they expected, based on the model, to shine in X-rays. Not only did they detect X-ray pulsations from all three of the pulsars searched, but they also found that the spectrum of X-rays was as predicted.

    This discovery already represented a significant increase in the total number of pulsars known to emit non-thermal X-rays and help us better comprehend the interaction between particles and magnetic fields in pulsars and beyond.

    This text is based on ESA, ICE, Athena, INTEGRAL, and CSIC press releases.

     

  • Super-stretchy cells (2018)

    Trepat, Xavier (IBEC)

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    Super-stretchy cells

    One of the most enviable features of superheroes is their ability to stretch their bodies beyond imaginable limits. In this study we discovered that our cells can do just that.

    Together with the team led by Marino Arroyo (UPC), we developed a new approach to subject epithelial tissues – the thin cellular layers that cover internal and external surfaces of the body – to very large deformations, up to four times their original size. These cellular layers are fundamental to life, as they protect the body from radiation, pollutants and pathogens. They’re also responsible for gas exchange in the lungs, absorption of nutrients in the gut, and excretion of urine in the kidneys.

    Most materials are unhappy during stretching. As they become progressively deformed, they’ll want to go back to their unstretched state, like a rubber band, or may even break as the tension increases. We found that epithelial sheets have a different and unusual mechanical behavior. To our surprise, tissues did not break during stretching, and they were able to recover their initial size in a fully reversible way when unstretched. Even more surprisingly, some cells in the tissue barely stretched, while others became ‘superstretched’, increasing their area more than ten times.

    We identified the molecular mechanisms that explain this physical behavior, which we call ‘active superelasticity’ as an analogy with the behavior of some high-tech metal alloys used in medical technologies. As cells become stretched, they become equally happy in an unstretched state or in a super-stretched state. As a result, these cell sheets can deal with increasing stretch by progressively switching cells into their super-stretched state without increasing tension, which would otherwise compromise integrity or cohesion. Understanding this surprising mechanical behavior in epithelial tissues could help us build better artificial organs or new bionic technologies such as organs-on-a-chip.

  • Proximity-induced spin-orbit coupling in graphene unambiguously demonstrated (2018)

    Valenzuela, Sergio O. (ICN2)

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    Proximity-induced spin-orbit coupling in graphene unambiguously demonstrated

    Spin is the intrinsic angular momentum of subatomic particles. Although with no real equivalent in classical physics, it can be used much like charge to store, manipulate and transport information. Graphene is known to transport electron spins very effectively over large distances. However, manipulating these spins is made difficult by the lack of any means of controlling them externally. The spin-orbit coupling (SOC) interaction offers just such a means, though in graphene this must be ‘borrowed’ from other materials via the proximity effect.

    ICN2 researchers have unambiguously demonstrated that SOC can be induced in graphene by proximity to transition metal dichalcogenides (TMDC). Using an experimental approach developed over the last two years by the ICN2 group, it was observed that spins behaved differently upon reaching the graphene/TMDC bilayer depending on their orientation. In-plane spins were found to be very sensitive to the proximity-induced SOC, relaxing and losing their orientation as much as 10 times faster than out-of-plane spins. This strongly anisotropic spin relaxation was further observed to be a consequence of the spin-valley coupling also imprinted onto the graphene from the TMDC.

    Crucially, all observations were carried out at room temperature, making them of direct relevance to future technological applications.

    These results suggest that a graphene/TMDC system could be used as a spin filter, allowing the detection of small orientation changes. They also represent the first step to achieving external control over the propagation of spins in graphene, and offer an interesting starting point for the exploration of coupled spin-valley phenomena and topological and spin-valleytronics device concepts.

  • Low-carbon energy transition requires more renewables than projected (2018)

    van den Bergh, Jeroen (UAB)

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    Low-carbon energy transition requires more renewables than projected

    Following the Paris Agreement, global energy transition scenarios have been presented. While these tend to be analysed in terms of gross energy, precise accounting requires assessing net energy. To this end, the notion of ‘energy return on investment’ (EROI) is useful. It signifies the amount of useful energy yielded from investing a unit of energy into obtaining that energy. Coal and hydroelectricity have high, nuclear, oil and gas medium, and solar and wind power medium to low EROIs.

    The importance of low versus high EROI energy sources for the economy, welfare and lifestyles is illustrated in the scheme. To improve lifestyles, the low-EROI society has three options: increase gross energy production, improve end use energy efficiency in production and consumption of goods/services, or improve average EROI considerably through technological improvements and investment in higher-EROI energy sources.

    We develop a dynamic model to analyse net energy supplied to society, considering operational and investment costs. The model is used to undertake three exercises: (1) simulate a low-carbon transition consistent with >66% probability of limiting warming to 2°C, using a basic scenario of the International Energy Agency as a reference; (2) simulate a ‘business as usual´ scenario based on current trends; and (3) optimise a transition to maintain current levels of net energy per capita by maximizing net energy within the 2°C carbon budget.

    The findings (see graphs) indicate that without substantial investments in energy efficiency, net energy per capita is likely to decline in the future between 24% and 31% from 2014 levels. To maintain current net energy per capita, renewable energy sources would have to grow at a rate 2-3 times that of current projections. The results further indicate a prioritization in phasing out fossil fuels, namely first coal then oil and finally gas. This can be achieved by implementing a carbon price, as it discourages coal more than oil, and oil more than gas. Finally, we propose an ‘energy return on carbon’ (EROC) indicator, a metric of net energy per tCO2, to assist in maximizing net energy within the 2 ºC carbon budget.

  • All you need to know to build an artificial body and brain summarized in a unique new Handbook of Living Machines. (2018)

    Verschure, Paul FMJ (IBEC)

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    All you need to know to build an artificial body and brain summarized in a unique new Handbook of Living Machines.

    Contemporary technology is still far removed from the versatility, scalability, and
    sustainability of living systems. Harnessing natural principles could render a radically new
    class of technology that is renewable, adaptive, robust, self-repairing, social, potentially
    moral, perhaps even conscious. This is the realm of “living machines”. Within the domain of
    living machines we distinguish two classes of entities—biomimetic systems that harness the
    principles discovered in nature and embody them in new artifacts, and biohybrid systems
    that couple biological entities with synthetic ones in a rich and close interaction so forming a
    new hybrid bio-artificial entity.
    Research in biomimetic and biohybrid systems is flourishing at the moment and this
    handbook surveys the state-of-the-art and points to the opportunities ahead. Promising
    areas in biomimetics include self-organization and co-operativity, biologically-inspired active materials, self-assembly and self-repair, learning, memory, control architectures and self-regulation, locomotion in the air, on land or in water, perception, cognition, control, and communication. In all of these areas, the potential of biomimetics is being shown through the
    construction of a wide range of different biomimetic devices and animal-like robots.
    Biohybrid systems is a relatively new field, with exciting and largely unknown potential, but
    one that is likely to shape the future of humanity. Examples of current research include
    brain-machine interfaces—where neurons are connected to microscopic sensors and
    actuators—and various forms of intelligent prostheses from sensory devices like artificial
    retinas, to life-like artificial limbs, brain implants, and virtual reality-based rehabilitation
    approaches.
    This Handbook includes contributions from leading international researchers drawing ideas
    from science, engineering, and the humanities. Their contributions explore the potential of
    many kinds of Living Machine technology, and also consider their possible future impacts
    both on society and on how we see and understand ourselves.