ORCID Profile
0000-0001-7702-6098
Current Organisation
Institute of Aquaculture Torre de la Sal (CSIC)
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Publisher: MDPI AG
Date: 03-02-2021
Abstract: The evolutionary aspects of cystatins are greatly underexplored in early-emerging metazoans. Thus, we surveyed the gene organization, protein architecture, and phylogeny of cystatin homologues mined from 110 genomes and the transcriptomes of 58 basal metazoan species, encompassing free-living and parasite taxa of Porifera, Placozoa, Cnidaria (including Myxozoa), and Ctenophora. We found that the cystatin gene repertoire significantly differs among phyla, with stefins present in most of the investigated lineages but with type 2 cystatins missing in several basal metazoan groups. Similar to liver and intestinal flukes, myxozoan parasites possess atypical stefins with chimeric structure that combine motifs of classical stefins and type 2 cystatins. Other early metazoan taxa regardless of lifestyle have only the classical representation of cystatins and lack multi-domain ones. Our comprehensive phylogenetic analyses revealed that stefins and type 2 cystatins clustered into taxonomically defined clades with multiple independent paralogous groups, which probably arose due to gene duplications. The stefin clade split between the subclades of classical stefins and the atypical stefins of myxozoans and flukes. Atypical stefins represent key evolutionary innovations of the two parasite groups for which their origin might have been linked with ancestral gene chimerization, obligate parasitism, life cycle complexity, genome reduction, and host immunity.
Publisher: Springer Science and Business Media LLC
Date: 25-05-2023
Publisher: IOP Publishing
Date: 24-08-2023
Abstract: Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding its scale up. In particular, there is an emerging body of work which suggests that generic, data agnostic quantum machine learning (QML) architectures may suffer from severe trainability issues, with the gradient of typical variational parameters vanishing exponentially in the number of qubits. Additionally, the high expressibility of QML models can lead to overfitting on training data and poor generalisation performance. A promising strategy to combat both of these difficulties is to construct models which explicitly respect the symmetries inherent in their data, so-called geometric quantum machine learning (GQML). In this work, we utilise the techniques of GQML for the task of image classification, building new QML models which are equivariant with respect to reflections of the images. We find that these networks are capable of consistently and significantly outperforming generic ansatze on complicated real-world image datasets, bringing high-resolution image classification via quantum computers closer to reality. Our work highlights a potential pathway for the future development and implementation of powerful QML models which directly exploit the symmetries of data.
Publisher: American Physical Society (APS)
Date: 25-02-2022
Publisher: Wiley
Date: 17-05-2019
DOI: 10.1111/MEC.15068
Abstract: Bacteroidetes is one of the dominant phyla of ocean bacterioplankton, yet its ersity and population structure is poorly understood. To advance in the delineation of ecologically meaningful units within this group, we constructed near full-length 16S rRNA gene clone libraries from contrasting marine environments in the NW Mediterranean. Based on phylogeny and the associated ecological variables (depth and season), 24 different Bacteroidetes clades were delineated. By considering their relative abundance (from iTag licon sequencing studies), we described the distribution patterns of each of these clades, delimiting them as Ecologically Significant Taxonomic Units (ESTUs). Spatially, there was almost no overlap among ESTUs at different depths. In deep waters there was predominance of Owenweeksia, Leeuwenhoekiella, Muricauda-related genera, and some depth-associated ESTUs within the NS5 and NS2b marine clades. Seasonally, multi-annual dynamics of recurring ESTUs were present with dominance of some ESTUs within the NS4, NS5 and NS2b marine clades along most of the year, but with variable relative frequencies between months. A drastic change towards the predominance of Formosa-related ESTUs and one ESTU from the NS5 marine clade was typically present after the spring bloom. Even though there are no isolates available for these ESTUs to determine their physiology, correlation analyses identified the environmental preference of some of them. Overall, our results suggest that there is a high degree of niche specialisation within these closely related clades. This work constitutes a step forward in disentangling the ecology of marine Bacteroidetes, which are essential players in organic matter processing in the oceans.
Publisher: Royal Society of Chemistry (RSC)
Date: 2021
DOI: 10.1039/D1NR04858A
Abstract: Scanning tunnelling microscopy (STM) images are shown to depend on the momentum space features of s le electronic states, with important implications for material design and characterisation, and applications in quantum computing, quantum sensing and photonics.
Publisher: American Physical Society (APS)
Date: 23-06-2023
No related grants have been discovered for Oswaldo Palenzuela.