CEA Grenoble

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTLow Molecular Mass Gelators of Organic Liquids and the Properties of Their GelsPierre Terech and Richard G. WeissView Author Information Laboratoire Physico-Chimie Moléculaire, UMR 585, Département de Recherche Fondamentale sur la Matière Condensée, C.E.A.-Grenoble, 17, Rue des Martyrs, 38054 Grenoble Cédex 09, France, and Department of Chemistry, Georgetown University, Washington, DC 20057-1227 Cite this: Chem. Rev. 1997, 97, 8, 3133–3160Publication Date (Web):December 18, 1997Publication History Received10 March 1997Revised2 July 1997Published online18 December 1997Published inissue 1 December 1997https://pubs.acs.org/doi/10.1021/cr9700282https://doi.org/10.1021/cr9700282research-articleACS PublicationsCopyright © 1997 American Chemical SocietyRequest reuse permissionsArticle Views17869Altmetric-Citations2857LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Aggregation,Gelation,Gels,Liquids,Molecules Get e-Alerts

Spintronics utilizing antiferromagnetic materials has potential for the next generation of applications and offers opportunities for new ideas. Ultimately, antiferromagnets could replace ferromagnets as the active spin-dependent element on which spintronic devices are based. Central to this endeavor is the need for predictive models, relevant disruptive materials, and new experimental designs. This paper reviews spintronic effects described based on theoretical and experimental analysis of antiferromagnetic materials.

JASPAR (http://jaspar.genereg.net/) is an open-access database containing manually curated, non-redundant transcription factor (TF) binding profiles for TFs across six taxonomic groups. In this 9th release, we expanded the CORE collection with 341 new profiles (148 for plants, 101 for vertebrates, 85 for urochordates, and 7 for insects), which corresponds to a 19% expansion over the previous release. We added 298 new profiles to the Unvalidated collection when no orthogonal evidence was found in the literature. All the profiles were clustered to provide familial binding profiles for each taxonomic group. Moreover, we revised the structural classification of DNA binding domains to consider plant-specific TFs. This release introduces word clouds to represent the scientific knowledge associated with each TF. We updated the genome tracks of TFBSs predicted with JASPAR profiles in eight organisms; the human and mouse TFBS predictions can be visualized as native tracks in the UCSC Genome Browser. Finally, we provide a new tool to perform JASPAR TFBS enrichment analysis in user-provided genomic regions. All the data is accessible through the JASPAR website, its associated RESTful API, the R/Bioconductor data package, and a new Python package, pyJASPAR, that facilitates serverless access to the data.

Colloidal core/shell nanocrystals contain at least two semiconductor materials in an onionlike structure. The possibility to tune the basic optical properties of the core nanocrystals, for example, their fluorescence wavelength, quantum yield, and lifetime, by growing an epitaxial-type shell of another semiconductor has fueled significant progress on the chemical synthesis of these systems. In such core/shell nanocrystals, the shell provides a physical barrier between the optically active core and the surrounding medium, thus making the nanocrystals less sensitive to environmental changes, surface chemistry, and photo-oxidation. The shell further provides an efficient passivation of the surface trap states, giving rise to a strongly enhanced fluorescence quantum yield. This effect is a fundamental prerequisite for the use of nanocrystals in applications such as biological labeling and light-emitting devices, which rely on their emission properties. Focusing on recent advances, this Review discusses the fundamental properties and synthesis methods of core/shell and core/multiple shell structures of II-VI, IV-VI, and III-V semiconductors.

JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.

The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.

JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTOccurrence, Classification, and Biological Function of Hydrogenases: An OverviewPaulette M. Vignais and Bernard BilloudView Author Information CEA Grenoble, Laboratoire de Biochimie et Biophysique des Systèmes Intégrés, UMR CEA/CNRS/UJF 5092, Institut de Recherches en Technologies et Sciences pour le Vivant (iRTSV), 17 rue des Martyrs, 38054 Grenoble cedex 9, France, and Atelier de BioInformatique Université Pierre et Marie Curie (Paris 6), 12 rue Cuvier, 75005 Paris, France Cite this: Chem. Rev. 2007, 107, 10, 4206–4272Publication Date (Web):October 10, 2007Publication History Received26 February 2007Published online10 October 2007Published inissue 1 October 2007https://pubs.acs.org/doi/10.1021/cr050196rhttps://doi.org/10.1021/cr050196rresearch-articleACS PublicationsCopyright © 2007 American Chemical SocietyRequest reuse permissionsArticle Views13248Altmetric-Citations1283LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Bacteria,Cluster chemistry,Iron-sulfur clusters,Monomers,Peptides and proteins Get e-Alerts

The 12th generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2014 by the Working Group V-MOD appointed by the International Association of Geomagnetism and Aeronomy (IAGA). It updates the previous IGRF generation with a definitive main field model for epoch 2010.0, a main field model for epoch 2015.0, and a linear annual predictive secular variation model for 2015.0-2020.0. Here, we present the equations defining the IGRF model, provide the spherical harmonic coefficients, and provide maps of the magnetic declination, inclination, and total intensity for epoch 2015.0 and their predicted rates of change for 2015.0-2020.0. We also update the magnetic pole positions and discuss briefly the latest changes and possible future trends of the Earth’s magnetic field.

Spintronics is one of the emerging fields for the next-generation nanoelectronic devices to reduce their power consumption and to increase their memory and processing capabilities. Such devices utilise the spin degree of freedom of electrons and/or holes, which can also interact with their orbital moments. In these devices, the spin polarisation is controlled either by magnetic layers used as spin-polarisers or analysers or via spin–orbit coupling. Spin waves can also be used to carry spin current. In this review, the fundamental physics of these phenomena is described first with respect to the spin generation methods as detailed in Sections 2 ~ 9. The recent development in their device applications then follows in Sections 10 and 11. Future perspectives are provided at the end.

The future of energy supply depends on innovative breakthroughs regarding the design of cheap, sustainable, and efficient systems for the conversion and storage of renewable energy sources, such as solar energy. The production of hydrogen, a fuel with remarkable properties, through sunlight-driven water splitting appears to be a promising and appealing solution. While the active sites of enzymes involved in the overall water-splitting process in natural systems, namely hydrogenases and photosystem II, use iron, nickel, and manganese ions, cobalt has emerged in the past five years as the most versatile non-noble metal for the development of synthetic H(2)- and O(2)-evolving catalysts. Such catalysts can be further coupled with photosensitizers to generate photocatalytic systems for light-induced hydrogen evolution from water.

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Industries such as the automotive, aerospace or military, as well as environmental and biological research have promoted the development of ultraviolet (UV) photodetectors capable of operating at high temperatures and in hostile environments. UV-enhanced Si photodiodes are hence giving way to a new generation of UV detectors fabricated from wide-bandgap semiconductors, such as SiC, diamond, III-nitrides, ZnS, ZnO, or ZnSe. This paper provides a general review of latest progresses in wide-bandgap semiconductor photodetectors.

In this paper, a new dual descriptor for nucleophilicity and electrophilicity is introduced. The new index is defined in terms of the variation of hardness with respect to the external potential, and it is written as the difference between nucleophilic and electrophilic Fukui functions, thus being able to characterize both reactive behaviors. It is shown that the new descriptor correctly predicts the site reactivity induced by different donor and acceptor groups in substituted phenyl molecules. Also, the Dunitz-Burgi attack on ketones and aldehydes has been revisited to illustrate the stereoselective capability of this new index. Finally, its predictive ability has been tested successfully on different series of conjugated and nonconjugated carbonyl compounds.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTADDITION / CORRECTIONThis article has been corrected. View the notice.Structure/Function Relationships of [NiFe]- and [FeFe]-HydrogenasesJuan C. Fontecilla-Camps, Anne Volbeda, Christine Cavazza, and Yvain NicoletView Author Information Laboratoire de Cristallographie et Cristallogenèse des Proteines, Institut de Biologie Structurale J. P. Ebel, CEA, CNRS, Universitè Joseph Fourier, 41 rue J. Horowitz, 38027 Grenoble Cedex 1, France Cite this: Chem. Rev. 2007, 107, 10, 4273–4303Publication Date (Web):September 13, 2007Publication History Received26 March 2007Published online13 September 2007Published inissue 1 October 2007https://pubs.acs.org/doi/10.1021/cr050195zhttps://doi.org/10.1021/cr050195zresearch-articleACS PublicationsCopyright © 2007 American Chemical SocietyRequest reuse permissionsArticle Views11789Altmetric-Citations1185LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Cluster chemistry,Ligands,Monomers,Peptides and proteins,Redox reactions Get e-Alerts

Silicon photonics research can be dated back to the 1980s. However, the previous decade has witnessed an explosive growth in the field. Silicon photonics is a disruptive technology that is poised to revolutionize a number of application areas, for example, data centers, high-performance computing and sensing. The key driving force behind silicon photonics is the ability to use CMOS-like fabrication resulting in high-volume production at low cost. This is a key enabling factor for bringing photonics to a range of technology areas where the costs of implementation using traditional photonic elements such as those used for the telecommunications industry would be prohibitive. Silicon does however have a number of shortcomings as a photonic material. In its basic form it is not an ideal material in which to produce light sources, optical modulators or photodetectors for example. A wealth of research effort from both academia and industry in recent years has fueled the demonstration of multiple solutions to these and other problems, and as time progresses new approaches are increasingly being conceived. It is clear that silicon photonics has a bright future. However, with a growing number of approaches available, what will the silicon photonic integrated circuit of the future look like? This roadmap on silicon photonics delves into the different technology and application areas of the field giving an insight into the state-of-the-art as well as current and future challenges faced by researchers worldwide. Contributions authored by experts from both industry and academia provide an overview and outlook for the silicon waveguide platform, optical sources, optical modulators, photodetectors, integration approaches, packaging, applications of silicon photonics and approaches required to satisfy applications at mid-infrared wavelengths. Advances in science and technology required to meet challenges faced by the field in each of these areas are also addressed together with predictions of where the field is destined to reach.

Gallium nitride (GaN) is a compound semiconductor that has tremendous potential to facilitate economic growth in a semiconductor industry that is silicon-based and currently faced with diminishing returns of performance versus cost of investment. At a material level, its high electric field strength and electron mobility have already shown tremendous potential for high frequency communications and photonic applications. Advances in growth on commercially viable large area substrates are now at the point where power conversion applications of GaN are at the cusp of commercialisation. The future for building on the work described here in ways driven by specific challenges emerging from entirely new markets and applications is very exciting. This collection of GaN technology developments is therefore not itself a road map but a valuable collection of global state-of-the-art GaN research that will inform the next phase of the technology as market driven requirements evolve. First generation production devices are igniting large new markets and applications that can only be achieved using the advantages of higher speed, low specific resistivity and low saturation switching transistors. Major investments are being made by industrial companies in a wide variety of markets exploring the use of the technology in new circuit topologies, packaging solutions and system architectures that are required to achieve and optimise the system advantages offered by GaN transistors. It is this momentum that will drive priorities for the next stages of device research gathered here.

Abstract Kwant is a Python package for numerical quantum transport calculations. It aims to be a user-friendly, universal, and high-performance toolbox for the simulation of physical systems of any dimensionality and geometry that can be described by a tight-binding model. Kwant has been designed such that the natural concepts of the theory of quantum transport (lattices, symmetries, electrodes, orbital/spin/electron-hole degrees of freedom) are exposed in a simple and transparent way. Defining a new simulation setup is very similar to describing the corresponding mathematical model. Kwant offers direct support for calculations of transport properties (conductance, noise, scattering matrix), dispersion relations, modes, wave functions, various Greenʼs functions, and out-of-equilibrium local quantities. Other computations involving tight-binding Hamiltonians can be implemented easily thanks to its extensible and modular nature. Kwant is free software available at http://kwant-project.org/ .

Colloidal nanocrystals (NCs, i.e., crystalline nanoparticles) have become an important class of materials with great potential for applications ranging from medicine to electronic and optoelectronic devices. Today's strong research focus on NCs has been prompted by the tremendous progress in their synthesis. Impressively narrow size distributions of just a few percent, rational shape-engineering, compositional modulation, electronic doping, and tailored surface chemistries are now feasible for a broad range of inorganic compounds. The performance of inorganic NC-based photovoltaic and light-emitting devices has become competitive to other state-of-the-art materials. Semiconductor NCs hold unique promise for near- and mid-infrared technologies, where very few semiconductor materials are available. On a purely fundamental side, new insights into NC growth, chemical transformations, and self-organization can be gained from rapidly progressing in situ characterization and direct imaging techniques. New phenomena are constantly being discovered in the photophysics of NCs and in the electronic properties of NC solids. In this Nano Focus, we review the state of the art in research on colloidal NCs focusing on the most recent works published in the last 2 years.