Highlights

Every year, a committee of experts sits down with a tough job to do: from among all ICREA publications, they must find a handful that stand out from all the others. This is indeed a challenge. The debates are sometimes heated and always difficult but, in the end, a shortlist of  the most outstanding publications of the year is produced. No prize is awarded, and the only additional acknowledge is the honour of being chosen and highlighted by ICREA. Each piece has something unique about it, whether it be a particularly elegant solution, the huge impact it has in the media or the sheer fascination it generates as a truly new idea. For whatever the reason, these are the best of the best and, as such, we are proud to share them here.

LIST OF SCIENTIFIC HIGHLIGHTS

Format: yyyy
  • A common mechanism regulates inflammation in opposing directions in tissue regeneration and cancer (2019)

    Postigo, Antonio (FRCB-IDIBAPS)

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    A common mechanism regulates inflammation in opposing directions in tissue regeneration and cancer

    Inflammation is a normal response of the body to infections and injury. The migration into the inflamed tissue of some cells of our immune system known as macrophages is a requisite for the elimination of cell debris and the subsequent regeneration of injured tissues. Tissue regeneration most often involves the activation of “stem cells” that are normally in a quiescent stage. We found that a protein named ZEB1 both protects skeletal muscle from damage and is required for its regeneration. ZEB1 promotes the transition of macrophages toward an anti-inflammatory and pro-regenerative status in acute and chronic (muscular dystrophies) injured skeletal muscles. ZEB1 is also required for muscle stem cells to maintain their quiescent status. These results established ZEB1 as an important factor in the regulation of inflammatory response and in improving the regenerative capacity of stem cells, opening new avenues in the treatment of muscular dystrophies (Siles et al., 2019).

    However, continuous inflammation is at the root of many diseases. Thus, chronic inflammation of some tissues, such as the liver, pancreas or colon, is a known risk factor for the development of cancer. We found that ZEB1 is required for the inflammation of the colon. We found that, contrary to what occurs in skeletal muscle, ZEB1 promotes (rather than inhibits) chronic inflammation and its progression toward cancer. ZEB1 causes the inflammation of the epithelial cells in the colon (a disease known as ulcerative colitis) and contributes to their subsequent transformation into cancer cells. ZEB1 triggers inflammation by inducing lesions in the DNA of the cell but also by inhibiting our body's self-repair mechanisms as it prevents the repair of DNA lesions through the inhibition of an enzyme called MPG. This work unveils a new mechanism in the link between inflammation and cancer and can help to develop new strategies in the treatment of ulcerative colitis and of other chronic inflammatory conditions that are risk factors in cancer development (de Barrios et al 2019).

  • Towards Data-Integrated Cell (2019)

    Przulj, Natasa (BSC-CNS)

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    Towards Data-Integrated Cell

    We propose a novel, data-driven concept of an integrated cell, iCell, that integrates several types of systems-level genomic data. We construct iCells of cancers and the corresponding healty tissues. We identify new genes involved in cancer, many of which have previously been of unknown function and cannot be identified as different in cancer in any specific data type in isolation from others. We biologically validate that they have a role in cancer and find additional support via retrospective survival analyses of thousands of patients. Our methodology is universal and enables integrative comparisons of diverse molecular data over cells and tissues.

  • Bad fats in the brain (2019)

    Pujol Onofre, Aurora (IDIBELL)

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    Bad fats in the brain

    Genomic Medicine approach identifies a novel brain disease and its potential treatment. Leukodystrophies are rare inherited disorders that affect the white matter of the brain, the myelin sheath, resulting in a range of severe and often lethal neurological presentations. Several leukodystrophy-associated genes have been identified; however, the etiology of many cases remains unsolved. The use of whole exome sequencing and novel platforms for international data exchange (GeneMatcher) led to the identification of  mutations in the endoplasmic reticulum lipid desaturase DEGS1 as the underlying cause of a new ultrarare disease in 19 patients from 13 unrelated families, spread over four continents. The novel disease is called Hypomyelinating Leukodystrophy 18 (HLD18 OMIM: # 618404).

    Mutations in DEGS1 caused  imbalance of the DEGS1 substrate dihydroceramides, and its product, the ceramides. In a DEGS1 knockdown zebrafish model, treatment with a drug in use for multiple sclerosis, fingolimod, reduced the imbalance between dihydroceramides and ceramides, restored locomotor deficits, and increased the numbers of oligodendrocytes, the cells producing myelin,  suggesting this strategy be explored for DEGS1 patients. An international pilot clinical trial for DEGS1 patients is in progress.

    The work has been prized as  Best Late-Breaking Talk at the International Society for Inherited Errors of Metabolism congress, SSIEM, Amsterdam, September 5th 2019.

  • Revealing the Universal Behavior of Spin Transport in Polycrystalline Graphene Devices (2019)

    Roche, Stephan (ICN2)

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    Revealing the Universal Behavior of Spin Transport in Polycrystalline Graphene Devices

    Graphene is a material that has been gaining fame in recent years due to its magnificent properties. In particular, for spintronics, graphene is a valuable material because the spins of the electrons used remain unaltered for unprecedented distances. However, graphene needs to be produced on a large scale in order to be used in future devices. With that respect, chemical vapour deposition (CVD) is the most promising fabrication method. CVD involves growing graphene on a metallic substrate at high temperatures. In this process, the generation of graphene starts at different points of the substrate simultaneously. This produces different single-crystal domains of graphene separated from one another through grain boundaries, consisting of arrays of five-, seven- or even eight-member carbon rings. The final product is, thus, polycrystalline graphene. A critical question for developing graphene-based spintronic technologies is to assess the impact of polycrystalline morphology with respect to the single-crystal situation. Using first-principles simulations and efficient quantum transport methodplogies, the impact of grain boundaries on spin transport in polycrystalline graphene has been fully clarified.

    Indeed we found that the spin diffusion length in polycrystalline graphene, supported on dielectric substrates, turns put to be insensitive to the grain size but only depends on the strength of the substrate-induced spin-orbit coupling. Moreover, this is valid not only for the diffusive regime of transport, but also for the weakly localized one, in which quantum phenomena prevail. This is the first quantum mechanical simulation confirming that the same expression for spin diffusion length holds in both regimes.

    Such research highlights the fact that single-domain graphene may not be a requirement for spintronics applications, and that polycrystalline CVD-grown graphene may work just as well. This puts the focus on other aspects to enhance in graphene production, such as the elimination of magnetic impurities, and should accelerate the integration of scalable graphene onto memory or spin logics technologies

  • Musical Pleasure is mediated by Dopamine (2019)

    Rodríguez Fornells, Antoni (UB)

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    Musical Pleasure is mediated by Dopamine

    The present study shows for the first time a causal role of dopamine (a neurotransmiter involved in the regularion of reward experiences) in musical pleasure and motivation: enjoying a piece of music, deriving pleasure from it, wanting to listen to it again and be willing to spend money for it. Researchers manipulated the dopaminergic synaptic availability for the participants (27 volunteers) using a pharmacological design. In three different sessions, separated by one week at least, reserchers orally administrated to each participant a dopamine precursor (levodopa, which increases dopaminergic availability), a dopamine antagonist (risperidone; to reduce dopaminergic signaling), and placebo (lactose; as a control). The authors indirectly measured changes in pleasure using electrodermal activity, which is a very sensitive technique to evaluate emotional changes (i.e., in this case, the hedonic impact of music). Participants provided subjective ratings of the experienced pleasure (real time ratings and general pleasure ratings provided after each song). Importantly, motivational responses were measured by asking participants how much of their own money they were willing to spend for each song.

    The results showed that while the dopamine precursor levodopa increased the hedonic experience to music and motivational responses, such as willingness to purchase a song, the dopamine antagonist risperidone led to a reduction of both.

    These results shed new light on the neurochemistry underpinning music reward, contributing to the fervid and open debate on the nature of abstract human pleasures. These findings challenge previous evidence conducted in animal models, where dopaminergic manipulations showed a clear role of dopamine in motivation and learning, but a controversial function in regulating hedonic responses in primary rewards (e.g. food), which has been mainly related to opioids release. These results indicate that dopaminergic transmission in humans might play different or additive roles than the ones postulated in affective processing, particularly in abstract cognitive activities such as music listening.

  • A new model predicts key characteristics of major earthquakes and associated tsunamis   (2019)

    Rodríguez Ranero, César (CSIC - ICM)

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    A new model predicts key characteristics of major earthquakes and associated tsunamis  

    The study allows explaining the behaviour of large earthquakes, predicting their potential to generate tsunamis more accurately than any previous method. The model explains why some moderate seismic events in the past generated anomalously large tsunamis and solves physical paradoxes of previous models.

    After decades of research there is no conventional model that explains earthquake’s behaviour, so that understanding seismic rupture is still one of the major open questions in Earth Sciences. For instance, there is no explanation for the systematic variation of properties of seismic rupture progressing from deep to shallow depth along faults. This uncertainty has led to underestimate earthquake capacity to generate tsunamis, making it difficult to forecast their associated risks. For instance, the Sanriku event (Japan) in 1896 caused a tsunami up to 38 meters high, devastating several coastal towns and causing more than 22,000 victims. The arrival of the tsunami took local residents by surprise, because the intensity of the earthquake that preceded it was moderate. Similarly tragic examples are tsunamis generated by recent giant earthquakes, like Banda-Aceh in Indonesia (2004) and Tohoku-Oki in Japan  (2011), with tsunamis larger than expected, leading to unforeseen catastrophic situations such as flooding of Fukushima nuclear power plant.

    We ​​propose a new conceptual model that explains various essential characteristics of earthquakes and predicts their tsunamigenic potential. Changes in earthquake rupture behaviour with depth are not understood and are attributed to local variations in the physical mechanism operating when a fault is seismically slipping. In contrast, we show that they are due to systematic changes in the rigidity of the rocks that rest on the mega-faults that generate the earthquakes, and that fracture and deform during the seismic rupture. Measuring changes in rigidity with depth allows to explain the speed of propagation and duration of seismic ruptures, the amount of slip on faults, changes in amplitude of the generated seismic vibration, and earthquake magnitude.