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 24 publications 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
  • Connector Tensor Networks: A Renormalization-Type Approach to Quantum Certification (2020)

    Acín Dal Maschio, Antonio (ICFO)

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    Connector Tensor Networks: A Renormalization-Type Approach to Quantum Certification

    Certain quantum features with no classical counterpart, such as entanglement and the violation of Bell inequalities, arise as collective properties of systems with several components and cannot be detected by looking at the individual parts. Recognizing whether a given system exhibits such features is central in the study of quantum fundamentals and quantum information science but is generally a very complicated problem, often even intractable. In our work, we propose a novel method to detect quantum properties. While existing methods can address systems with just a few components, our approach is scalable and can be applied to systems with hundreds of parts.

    Our approach exploits an important insight from statistical physics: A large system can often be coarse grained to a smaller one in ways that leave important global properties intact while discarding small-scale details. We develop new classes of coarse-graining transformations, called connectors, which preserve the feature of interest. The net result of these transformations is to map the original problem of detecting quantum properties to a simpler one with a tractable number of components.

    While we showcase our method by constructing specific classes of connectors for detecting entanglement and Bell nonlocality, the formalism is remarkably general: It can be applied to identify collective global properties in any system’s network. We therefore expect that connector theory will find application in other areas of quantum theory.

  • Bioactivity descriptors for drug-like compounds (2020)

    Aloy Calaf, Patrick (IRB Barcelona)

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    Bioactivity descriptors for drug-like compounds

    Small molecules are an excellent tool to probe biological functions and, indeed, they are the main asset of pharmaceutical companies. However, they have received a limited attention by academic researchers during the ‘omics revolution’ since, contrary to gene and protein knowledge, compound data are scattered and diverse, making them inaccessible to most researchers and not suited to standard statistical analyses. Often, the only way to approach the characterization of a compound is to assume it will have the same activity as compounds with similar chemical properties (i.e. the so-called ‘similarity principle’).

    The broad release of bioactivity data has led to the realization that the similarity principle applies beyond chemical properties (i.e. molecules eliciting similar side-effects tend to share the mechanism of action, even when their chemical structures appear to be unrelated), suggesting that ‘biological’ similarities offer an alternative means to functionally characterize small molecules. Unfortunately, there is no blueprint to compare the biological profiles of small molecules, since bioactivity data come expressed in formats that are not adapted to common similarity metrics. The Chemical Checker (CC) provides processed, harmonized and integrated bioactivity data on ~1M small molecules. The CC divides data into five levels of increasing complexity, from the chemical properties of compounds to their clinical outcomes. In between, it includes targets, off-targets, networks and cell-level information, such as omics data, growth inhibition and morphology. Bioactivity data are expressed in a vector format, extending the concept of chemical similarity to similarity between bioactivity signatures. We show how CC signatures can aid drug discovery tasks, including target identification and library characterization. We also demonstrate the discovery of compounds that reverse and mimic biological signatures of disease models and genetic perturbations in cases that could not be addressed using chemical information alone. Overall, the CC signatures facilitate the conversion of bioactivity data to a format that is readily amenable for modern machine learning.

  • A novel theoretical framework for analyzing environmental justice in green cities  (2020)

    Anguelovski, Isabelle (UAB)

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    A novel theoretical framework for analyzing environmental justice in green cities 

    It is increasingly orthodox practice for cities to deploy urban greening interventions to address diverse socio-environmental challenges, from protecting urban ecosystems to enhancing built environments and climate resilience or improving health outcomes. In a recent article, myself and colleagues have proposed to expand the theoretical boundaries used to challenge this growing orthodoxy by laying out a nuanced framework that advances critical urban environmental justice scholarship. Beginning from the now well-supported assumption that urban greening is a deeply political project often framed by technocratic principles and promotional claims that this project will result in more just and prosperous cities, our work identifies existing contributions and limits when examining urban green inequities through the traditional lenses of distributional, recognition, and procedural justice. We also lay out a different framework for analyzing justice in urban greening. Here, our argument highlights the need to uncover how persistent domination and subordination prevents green interventions from becoming an emancipatory anti-subordination, intersectional, and relational project that consider the needs, identities, and everyday lives of marginalized groups. We also illustrate our framework’s usefulness by applying it to the analysis of urban residents’ (lack of) access to urban greening and by applying it to two different planning and policy domains: (a) greening for wellbeing, care, and health and (b) greening for recreation and play. This final analysis serves to provide critical questions and strategies that can hopefully guide new urban green planning and practice approaches.

  • Infections Contribute to More Than Half of Child Deaths in Developing Countries (2020)

    Bassat Orellana, Quique (ISGlobal)

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    Infections Contribute to More Than Half of Child Deaths in Developing Countries

    The Child Health and Mortality Prevention Surveillance (CHAMPS) network published in 2020 its initial scientific findings, providing reliable data on the causes of death in children under five years of age and stillborn foetuses in five settings in Africa and Asia. The study was co-led by the Barcelona Institute for Global Health (ISGlobal), together with Emory University in Atlanta and the US Centers for Disease Control and Prevention.

    Minimally invasive autopsies were performed on 933 deceased neonates, children <5 years of age and stillborn foetuses at five sites in Bangladesh, Kenya, Mali, Mozambique and South Africa. This autopsy method, developed several years ago by ISGlobal, allows the cause of death to be determined with high precision through the analysis of postmortem tissue samples.

    Notably, the authors of the study were able to describe the entire chain of events leading to death. Two or more conditions were identified in the causal chain for 63% of cases and infection contributed to death in 54% of cases. One of the key features of this study is the granularity of the data we obtained. We were able to identify the infectious pathogens involved and associate them with the histopathological abnormalities observed in the organ tissue. This gave us an almost three-dimensional picture of the processes that led to death, and in a less invasive way than conventional autopsy techniques.

    The high prevalence of Klebsiella pneumoniae in a considerable number of cases of pneumonia, sepsis and meningitis was a key finding of the study. This information could drive the development of new tools and strategies for the prevention or treatment of this pathogen.

    A detailed understanding of all the factors involved in child deaths is essential to estimate the burden of disease, track global progress and develop efficient, cost-effective and, most importantly, evidence-based policies to combat child mortality. The CHAMPS studies will mark a turning point in these efforts, since they provide crucial information for the design and implementation of life-saving health interventions.

  • COLORECTAL CANCER EXPANDS FROM BIOSYNTHETIC CELL NICHES (2020)

    Batlle Gómez, Eduard (IRB Barcelona)

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    COLORECTAL CANCER EXPANDS FROM BIOSYNTHETIC CELL NICHES

    Tissue homeostasis requires controlled protein synthesis rates, and distinct cell types in healthy tissues exhibit different biosynthetic capabilities. In tumors, this regulation is disrupted by oncogenic alterations, many of which enhance the cell biosynthetic machinery, including ribosomal DNA transcription, ribosomal biogenesis, and protein production rates. We however discovered that the vast majority of ribosomal RNA and proteins synthesized in colorectal cancer (CRCs) are contributed by a limited subset of cells positioned immediately adjacent to the stroma. We showed that tumor cells that reside in these biosynthetic niches function as cancer stem cells although often they do not express LGR5 or other stem cell marker genes. In contrast, tumor cell differentiation is characterized by pervasive and permanent loss of biosynthetic capacities. To investigate the role of biosynthetic cells in CRC, we developed a methodology based on the use of CRISPR/Cas9 to edit the genomes of patient-derived organoids to introduce cell-specific ablation cassettes. Using this strategy in CRC models, we showed that lack of the biosynthetic cell compartment irreversibly halts tumor growth and induces tumor differentiation. We propose that zonation patterns of ribosomal DNA transcription and protein synthesis in CRC reflect the existence of a simple stem cell-like hierarchy based on the differential biosynthetic capacity of tumor cells. This model challenges some widely accepted views on the identity and features of stem cells in CRC and may inspire new therapeutic approaches.

  • Bottom-up effects from phytoplankton on fish production in lakes (2020)

    Brucet, Sandra (UVIC)

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    Bottom-up effects from phytoplankton on fish production in lakes

    All ecosystems, and aquatic ones are no exception, are made up of different trophic levels. Predator-prey relationships that are established between more than two of these levels are called trophic cascades and can significantly alter the functioning of ecosystems. These cascades, one of the most studied concepts in ecology, are the topic of the article Energy-based top-down and bottom-up relationships between fish community energy demand or production and phytoplankton across lakes at a continental scale, published by our group.

    Our work analyzes the magnitude of trophic cascades from an energy point of view in lakes using samples from 227 European lakes. The results suggest that bottom-up effects have more effect on ecosystems than top-down effects. That is, the observed effects of primary producers (i.e., those that are food for other species but do not feed on any of them) on the fish that inhabit the lakes are substantially stronger than the effects that fish can produce on these primary producers.

    To reach these conclusions, we used the Metabolic Theory of Ecology to estimate the metabolic metrics of each fish community, as well as to calculate the energy demand and production of each community. From each of the lakes analyzed, we quantified the magnitude of the trophic cascades and established in which direction they have the greatest impact on the ecosystem. In addition, for the first time, generally neglected effects have been taken into account in the comparison of trophic cascades between ponds, such as the metabolic activity of fish. The results are important for the management of the ecological status of European lakes.

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