Showing papers by "North Carolina State University published in 2020"
National Institutes of Health1, Delft University of Technology2, Humboldt University of Berlin3, DuPont4, Laval University5, University of Alicante6, University of Copenhagen7, Vilnius University8, University of Georgia9, University of St Andrews10, Bangor University11, University of Toronto12, University of Freiburg13, Wageningen University and Research Centre14, North Carolina State University15
TL;DR: An updated evolutionary classification of CRISPR–Cas systems and cas genes is provided, with an emphasis on the major developments that have occurred since the publication of the latest classification, in 2015, which includes 2 classes, 6 types and 33 subtypes.
Abstract: The number and diversity of known CRISPR-Cas systems have substantially increased in recent years. Here, we provide an updated evolutionary classification of CRISPR-Cas systems and cas genes, with an emphasis on the major developments that have occurred since the publication of the latest classification, in 2015. The new classification includes 2 classes, 6 types and 33 subtypes, compared with 5 types and 16 subtypes in 2015. A key development is the ongoing discovery of multiple, novel class 2 CRISPR-Cas systems, which now include 3 types and 17 subtypes. A second major novelty is the discovery of numerous derived CRISPR-Cas variants, often associated with mobile genetic elements that lack the nucleases required for interference. Some of these variants are involved in RNA-guided transposition, whereas others are predicted to perform functions distinct from adaptive immunity that remain to be characterized experimentally. The third highlight is the discovery of numerous families of ancillary CRISPR-linked genes, often implicated in signal transduction. Together, these findings substantially clarify the functional diversity and evolutionary history of CRISPR-Cas.
1,153 citations
TL;DR: The purpose of this Review is to examine the fundamental development of the concept of pseudocapacitance and how it came to prominence in electrochemical energy storage as well as to describe new classes of materials whose electrochemicalEnergy storage behavior can be described as pseudOCapacitive.
Abstract: There is an urgent global need for electrochemical energy storage that includes materials that can provide simultaneous high power and high energy density One strategy to achieve this goal is with pseudocapacitive materials that take advantage of reversible surface or near-surface Faradaic reactions to store charge This allows them to surpass the capacity limitations of electrical double-layer capacitors and the mass transfer limitations of batteries The past decade has seen tremendous growth in the understanding of pseudocapacitance as well as materials that exhibit this phenomenon The purpose of this Review is to examine the fundamental development of the concept of pseudocapacitance and how it came to prominence in electrochemical energy storage as well as to describe new classes of materials whose electrochemical energy storage behavior can be described as pseudocapacitive
767 citations
University of California, Davis1, University of California, Berkeley2, California Pacific Medical Center3, Organisation for Economic Co-operation and Development4, North Carolina State University5, International Agency for Research on Cancer6, Brunel University London7, United States Environmental Protection Agency8, University of California, San Francisco9, Maastricht University10, National Institute for Environmental Studies11, National Institutes of Health12, University of Texas at Austin13, California Environmental Protection Agency14
TL;DR: This Expert Consensus Statement reflects on how these ten KCs can be used to identify, organize and utilize mechanistic data when evaluating chemicals as EDCs, and uses diethylstilbestrol, bisphenol A and perchlorate as examples to illustrate this approach.
Abstract: Endocrine-disrupting chemicals (EDCs) are exogenous chemicals that interfere with hormone action, thereby increasing the risk of adverse health outcomes, including cancer, reproductive impairment, cognitive deficits and obesity. A complex literature of mechanistic studies provides evidence on the hazards of EDC exposure, yet there is no widely accepted systematic method to integrate these data to help identify EDC hazards. Inspired by work to improve hazard identification of carcinogens using key characteristics (KCs), we have developed ten KCs of EDCs based on our knowledge of hormone actions and EDC effects. In this Expert Consensus Statement, we describe the logic by which these KCs are identified and the assays that could be used to assess several of these KCs. We reflect on how these ten KCs can be used to identify, organize and utilize mechanistic data when evaluating chemicals as EDCs, and we use diethylstilbestrol, bisphenol A and perchlorate as examples to illustrate this approach.
390 citations
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University of North Carolina at Chapel Hill1, Federal University of Paraíba2, University of Bonn3, Merck & Co.4, University of Gothenburg5, University of New Mexico6, University of Copenhagen7, Moscow State University8, University of Strasbourg9, University of Florida10, Duke University11, North Carolina State University12, University of California, Los Angeles13, University of Toronto14, Novartis15, University of British Columbia16
TL;DR: This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed inQSAR to a wide range of research areas outside of traditional QSar boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics.
Abstract: Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure–activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.
383 citations
Radcliffe Institute for Advanced Study1, University of St Andrews2, University of Konstanz3, Max Planck Society4, Memorial University of Newfoundland5, King Abdullah University of Science and Technology6, Yale University7, Aarhus University8, University of La Rochelle9, North Carolina State University10, North Carolina Museum of Natural Sciences11, Goethe University Frankfurt12, Boston University13, Radboud University Nijmegen14
TL;DR: Reduced human mobility during the pandemic will reveal critical aspects of the authors' impact on animals, providing important guidance on how best to share space on this crowded planet.
Abstract: Reduced human mobility during the pandemic will reveal critical aspects of our impact on animals, providing important guidance on how best to share space on this crowded planet
357 citations
University of Notre Dame1, Royal Institute of Technology2, Commonwealth Scientific and Industrial Research Organisation3, Massachusetts Institute of Technology4, Stanford University5, Georgia Institute of Technology6, Catalan Institute for Water Research7, University of Calabria8, University of Pisa9, Mario Negri Institute for Pharmacological Research10, Federal University of Bahia11, North Carolina State University12, Howard University13, Bangor University14, École Polytechnique Fédérale de Lausanne15, University of Arizona16, Southern Nevada Water Authority17, University of Barcelona18, University of Yamanashi19, University of California, Santa Barbara20, Hokkaido University21, Indian Institute of Technology Gandhinagar22, Toyama Prefectural University23, Istituto Superiore di Sanità24, University of Naples Federico II25, University of Wisconsin–Milwaukee26, University of Washington27, University of Queensland28, University of North Carolina at Chapel Hill29, University of Antwerp30, Yale University31, Tufts University32, Michigan State University33, Spanish National Research Council34, University of Southern California35, Rice University36, Georgia State University37, University of Osnabrück38, University of Michigan39
TL;DR: Author(s): Bivins, Aaron; North, Devin; Ahmad, Arslan; Ahmed, Warish; Alm, Eric; Been, Frederic; Bhattacharya, Prosun; Bijlsma, Lubertus; Boehm, Alexandria B; Brown, Joe; Buttiglieri, Gianluigi; Calabro, Vincenza; Carducci, Annalaura; Castiglioni, Sara; Cetecioglu Guro
Abstract: Author(s): Bivins, Aaron; North, Devin; Ahmad, Arslan; Ahmed, Warish; Alm, Eric; Been, Frederic; Bhattacharya, Prosun; Bijlsma, Lubertus; Boehm, Alexandria B; Brown, Joe; Buttiglieri, Gianluigi; Calabro, Vincenza; Carducci, Annalaura; Castiglioni, Sara; Cetecioglu Gurol, Zeynep; Chakraborty, Sudip; Costa, Federico; Curcio, Stefano; de Los Reyes, Francis L; Delgado Vela, Jeseth; Farkas, Kata; Fernandez-Casi, Xavier; Gerba, Charles; Gerrity, Daniel; Girones, Rosina; Gonzalez, Raul; Haramoto, Eiji; Harris, Angela; Holden, Patricia A; Islam, Md Tahmidul; Jones, Davey L; Kasprzyk-Hordern, Barbara; Kitajima, Masaaki; Kotlarz, Nadine; Kumar, Manish; Kuroda, Keisuke; La Rosa, Giuseppina; Malpei, Francesca; Mautus, Mariana; McLellan, Sandra L; Medema, Gertjan; Meschke, John Scott; Mueller, Jochen; Newton, Ryan J; Nilsson, David; Noble, Rachel T; van Nuijs, Alexander; Peccia, Jordan; Perkins, T Alex; Pickering, Amy J; Rose, Joan; Sanchez, Gloria; Smith, Adam; Stadler, Lauren; Stauber, Christine; Thomas, Kevin; van der Voorn, Tom; Wigginton, Krista; Zhu, Kevin; Bibby, Kyle
325 citations
TL;DR: An overview of wearables market trends, different active and passive methods of body energy harvesting for powering low-consumption electronic devices are introduced, and challenges of device fabrication are discussed.
323 citations
TL;DR: In this article, the use of oxygen carriers or redox catalysts for chemical production has been investigated and shown to offer significant opportunities for process intensification and exergy loss minimization.
Abstract: As a promising approach for carbon dioxide capture, chemical looping combustion has been extensively investigated for more than two decades. However, the chemical looping strategy can be and has been extended well beyond carbon capture. In fact, significant impacts on emission reduction, energy conservation, and value-creation can be anticipated from chemical looping beyond combustion (CLBC). This article aims to demonstrate the versatility and transformational benefits of CLBC. Specifically, we focus on the use of oxygen carriers or redox catalysts for chemical production – a $4 trillion industry that consumes 40.9 quadrillion BTU of energy. Compared to state-of-the-art chemical production technologies, we illustrate that chemical looping offers significant opportunities for process intensification and exergy loss minimization. In many cases, an order of magnitude reduction in energy consumption and CO2 emission can be realized without the needs for carbon dioxide capture. In addition to providing various CLBC examples, this article elaborates on generalized design principles for CLBC, potential benefits and pitfalls, as well as redox catalyst selection, design, optimization, and redox reaction mechanism.
295 citations
TL;DR: In this article, a review of the mechanism of embedding different continuous fibers into different plastics and their microstructural and mechanical properties including predicting models have been critically reviewed and based on the limitations of current technology future research directions have been defined.
272 citations
TL;DR: Latest developments in terms of constituents, fabrication technologies, structural, and bioactive properties of these materials that may represent an effective solution for tissue engineering materials, making them a realistic clinical alternative in the near future are covered.
267 citations
TL;DR: The nuclear physics landscape has been redesigned as a sequence of effective field theories (EFTs) connected to the Standard Model through symmetries and lattice simulations of Quantum Chromodynamics (QCD) as mentioned in this paper.
Abstract: The nuclear physics landscape has been redesigned as a sequence of effective field theories (EFTs) connected to the Standard Model through symmetries and lattice simulations of Quantum Chromodynamics (QCD). EFTs in this sequence are expansions around different low-energy limits of QCD, each with its own characteristics, scales, and ranges of applicability regarding energy and number of nucleons. We review each of the three main nuclear EFTs---Chiral, Pionless, Halo/Cluster---highlighting their similarities, differences, and connections. In doing so, we survey the structural properties and reactions of nuclei that have been derived from the ab initio solution of the few- and many-body problem built upon EFT input.
TL;DR: The 2.5 release of Hyphy includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backwards compatible with previous HyPhy releases.
Abstract: HYpothesis testing using PHYlogenies (HyPhy) is a scriptable, open-source package for fitting a broad range of evolutionary models to multiple sequence alignments, and for conducting subsequent parameter estimation and hypothesis testing, primarily in the maximum likelihood statistical framework. It has become a popular choice for characterizing various aspects of the evolutionary process: natural selection, evolutionary rates, recombination, and coevolution. The 2.5 release (available from www.hyphy.org) includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backward compatible with previous HyPhy releases.
Tsinghua University1, Drexel University2, North Carolina State University3, University of Pennsylvania4, University of Würzburg5, Heriot-Watt University6, University of Strathclyde7, University of Tokyo8, Pohang University of Science and Technology9, University of California, Los Angeles10, Massachusetts Institute of Technology11, Maastricht University12, Pennsylvania State University13
TL;DR: This bioprinting roadmap features salient advances in selected applications of the technique and highlights the status of current developments and challenges, as well as envisioned advances in science and technology, to address the challenges to the young and evolving technique.
Abstract: This bioprinting roadmap features salient advances in selected applications of the technique and highlights the status of current developments and challenges, as well as envisioned advances in science and technology, to address the challenges to the young and evolving technique. The topics covered in this roadmap encompass the broad spectrum of bioprinting; from cell expansion and novel bioink development to cell/stem cell printing, from organoid-based tissue organization to bioprinting of human-scale tissue structures, and from building cell/tissue/organ-on-a-chip to biomanufacturing of multicellular engineered living systems. The emerging application of printing-in-space and an overview of bioprinting technologies are also included in this roadmap. Due to the rapid pace of methodological advancements in bioprinting techniques and wide-ranging applications, the direction in which the field should advance is not immediately clear. This bioprinting roadmap addresses this unmet need by providing a comprehensive summary and recommendations useful to experienced researchers and newcomers to the field.
TL;DR: The physiologic aspects of collaborative bile acid metabolism by the host and gut microbiota are described and the effects of ursodeoxycholic acid (UDCA) administration, a common therapeutic bile acids administration, on the gut microbiota-bile acid-host axis are discussed.
Abstract: Bile acid biotransformation is a collaborative effort by the host and the gut microbiome. Host hepatocytes synthesize primary bile acids from cholesterol. Once these host-derived primary bile acids enter the gastrointestinal tract, the gut microbiota chemically modify them into secondary bile acids. Interest into the gut-bile acid-host axis is expanding in diverse fields including gastroenterology, endocrinology, oncology, and infectious disease. This review aims to 1) describe the physiologic aspects of collaborative bile acid metabolism by the host and gut microbiota; 2) to evaluate how gut microbes influence bile acid pools, and in turn how bile acid pools modulate the gut microbial community structure; 3) to compare species differences in bile acid pools; and lastly, 4) discuss the effects of ursodeoxycholic acid (UDCA) administration, a common therapeutic bile acid, on the gut microbiota-bile acid-host axis.
North Carolina State University1, National Institutes of Health2, East Carolina University3, Residence Inn by Marriott4, University of North Texas Health Science Center5, Natural Resources Defense Council6, European Environment Agency7, Indiana University8, Harvard University9, ETH Zurich10, University of California, Berkeley11
TL;DR: Options for how governments and industry can apply the class-based approach to PFAS are presented, emphasizing the importance of eliminating non-essential uses of PFAS, and further developing safer alternatives and methods to remove existing PFAS from the environment.
Abstract: This commentary presents a scientific basis for managing as one chemical class the thousands of chemicals known as PFAS (per- and polyfluoroalkyl substances). The class includes perfluoroalkyl acids, perfluoroalkylether acids, and their precursors; fluoropolymers and perfluoropolyethers; and other PFAS. The basis for the class approach is presented in relation to their physicochemical, environmental, and toxicological properties. Specifically, the high persistence, accumulation potential, and/or hazards (known and potential) of PFAS studied to date warrant treating all PFAS as a single class. Examples are provided of how some PFAS are being regulated and how some businesses are avoiding all PFAS in their products and purchasing decisions. We conclude with options for how governments and industry can apply the class-based approach, emphasizing the importance of eliminating non-essential uses of PFAS, and further developing safer alternatives and methods to remove existing PFAS from the environment.
TL;DR: A brief overview of the structural features of PBDB-T congeners and the strategies used to design these polymers is given in this article, where a meta-analysis of a library of high-performance polymers, which are compared with other types of conjugated polymers are suggested.
Kansas State University1, University of Montana2, Michigan State University3, Woods Hole Research Center4, University of Tennessee5, National Center for Atmospheric Research6, Tall Timbers Research Station and Land Conservancy7, University of Colorado Boulder8, Washington University in St. Louis9, University of Melbourne10, University of Nevada, Reno11, University of California, Irvine12, Boise State University13, Syracuse University14, University of Florida15, University of British Columbia16, Murdoch University17, University of Washington18, Oregon State University19, Auburn University20, Northern Arizona University21, University of Idaho22, Colgate University23, University of Amsterdam24, University of California, Santa Barbara25, Spanish National Research Council26, Stanford University27, Louisiana State University28, United States Forest Service29, University of California, Merced30, North Carolina State University31, Humboldt State University32, Davidson College33, Colorado State University34, Desert Research Institute35
TL;DR: In this paper, the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth is described, and the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts.
Abstract: 1. Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire-dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. 2. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above-ground ecology, (d) fire effects on below-ground ecology, (e) fire behaviour and (f) fire ecology modelling. 3. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. 4. Synthesis: As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives.
TL;DR: A wireless, non-invasive technology is presented that not only offers measurement equivalency to existing clinical standards for heart rate, respiration rate, temperature and blood oxygenation, but also provides a range of important additional features, as supported by data from pilot clinical studies in both the NICU and PICU.
Abstract: Standard clinical care in neonatal and pediatric intensive-care units (NICUs and PICUs, respectively) involves continuous monitoring of vital signs with hard-wired devices that adhere to the skin and, in certain instances, can involve catheter-based pressure sensors inserted into the arteries. These systems entail risks of causing iatrogenic skin injuries, complicating clinical care and impeding skin-to-skin contact between parent and child. Here we present a wireless, non-invasive technology that not only offers measurement equivalency to existing clinical standards for heart rate, respiration rate, temperature and blood oxygenation, but also provides a range of important additional features, as supported by data from pilot clinical studies in both the NICU and PICU. These new modalities include tracking movements and body orientation, quantifying the physiological benefits of skin-to-skin care, capturing acoustic signatures of cardiac activity, recording vocal biomarkers associated with tonality and temporal characteristics of crying and monitoring a reliable surrogate for systolic blood pressure. These platforms have the potential to substantially enhance the quality of neonatal and pediatric critical care. Soft electronic patches worn on the skin of infants or children in intensive-care units have a wide range of capabilities in aiding critical care, including monitoring of hemodynamic parameters, cardiac activity, movement and crying.
TL;DR: Telemedicine during the coronavirus epidemic has been the doctors’ first line of defense to slow the spread of the coronvirus, keeping social distancing and providing services by phone or videoconferencing for mild to focus personal care and limited supplies to the most urgent cases.
Abstract: The novel coronavirus SARS-CoV-2 is a positive single-stranded RNA virus that can be immediately translated and integrated into the host cell with its own RNA messenger, facilitating replication inside the cell and infectivity. The rapid progression of the disease presents a real challenge for the whole world. As the usual capacity for citizen care is exceeded, health professionals and governments struggle. One of the most important strategies to reduce and mitigate the advance of the epidemic are social distance measures; this is where telemedicine can help, and provide support to the healthcare systems, especially in the areas of public health, prevention and clinical practices, just as it is doing in others sectors. Telemedicine connects the convenience, low cost, and ready accessibility of health-related information and communication using the Internet and associated technologies. Telemedicine during the coronavirus epidemic has been the doctors' first line of defense to slow the spread of the coronavirus, keeping social distancing and providing services by phone or videoconferencing for mild to focus personal care and limited supplies to the most urgent cases.
TL;DR: In this paper, a land surface phenology (LSP) algorithm is proposed to estimate the timing of phenophase transitions and quantify the nature and magnitude of seasonality in remotely sensed land surface conditions.
Sage Bionetworks1, Kaiser Permanente2, University of Washington3, Eötvös Loránd University4, University of Michigan5, Tencent6, National University of Singapore7, University Health System8, Spanish National Research Council9, Polytechnic University of Valencia10, University College London11, University of Illinois at Urbana–Champaign12, IBM13, University of Haifa14, Stanford University15, Karolinska Institutet16, Icahn School of Medicine at Mount Sinai17, Fred Hutchinson Cancer Research Center18, Bill & Melinda Gates Foundation19, Center for Devices and Radiological Health20, Karolinska University Hospital21, Microsoft22, North Carolina State University23, University of California, San Francisco24, Emory University25, New York University26, Dortmund University of Applied Sciences and Arts27, Queensland University of Technology28, Institute for Infocomm Research Singapore29, Duke University30, Korea University31
TL;DR: This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.
Abstract: Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists’ specificity with radiologists’ sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists’ recall assessment was developed and evaluated. Results Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists’ sensitivity, lower than community-practice radiologists’ specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation.
TL;DR: The nature of these molecular networks, including both nutrient availability as a result of diet and growth factor signalling and their role in mediating cellular responses are discussed and their modifiability through dietary and pharmacological interventions are explored.
Abstract: Molecular inputs to chromatin via cellular metabolism are modifiers of the epigenome. These inputs — which include both nutrient availability as a result of diet and growth factor signalling — are implicated in linking the environment to the maintenance of cellular homeostasis and cell identity. Recent studies have demonstrated that these inputs are much broader than had previously been known, encompassing metabolism from a wide variety of sources, including alcohol and microbiotal metabolism. These factors modify DNA and histones and exert specific effects on cell biology, systemic physiology and pathology. In this Review, we discuss the nature of these molecular networks, highlight their role in mediating cellular responses and explore their modifiability through dietary and pharmacological interventions. Various cellular metabolites provide the chemical moieties for DNA and histone modifications, resulting in a complex interplay between metabolism and epigenetics. In this Review, Dai, Ramesh and Locasale discuss the metabolic regulation of diverse types of chromatin modifications and the functional consequences of these modifications at the molecular, cellular and organismal levels, as well as influences from diet and microbiota.
TL;DR: Deep eutectic solvent pretreatment showed that enzymatic digestibility of DES-pretreated bamboo residues was enhanced with the increasing molar ratio of choline chloride/lactic acid, which was due to DES pretreatment's ability to remove lignin and xylan, reduce the degree of polymerization of cellulose, enhance the crystallite size of cellulOSE, and improve cellulose accessibility.
Northwestern University1, Bowling Green State University2, University of Nevada, Reno3, Pacific Northwest National Laboratory4, Princeton University5, University of California, San Diego6, Massachusetts Institute of Technology7, University of Wisconsin-Madison8, University of Michigan9, University of New Mexico10, Michigan State University11, North Carolina State University12, University of Washington13, University of California, Berkeley14
TL;DR: In this paper, the authors discuss how chemical systems and reactions can impact quantum computing, communication and sensing, and propose a broad range of possibilities to realize practical quantum information science applications.
Abstract: The power of chemistry to prepare new molecules and materials has driven the quest for new approaches to solve problems having global societal impact, such as in renewable energy, healthcare and information science In the latter case, the intrinsic quantum nature of the electronic, nuclear and spin degrees of freedom in molecules offers intriguing new possibilities to advance the emerging field of quantum information science In this Perspective, which resulted from discussions by the co-authors at a US Department of Energy workshop held in November 2018, we discuss how chemical systems and reactions can impact quantum computing, communication and sensing Hierarchical molecular design and synthesis, from small molecules to supramolecular assemblies, combined with new spectroscopic probes of quantum coherence and theoretical modelling of complex systems, offer a broad range of possibilities to realize practical quantum information science applications Molecular design and synthesis, from small molecules to supramolecular assemblies, combined with new spectroscopic probes of quantum coherence and theoretical modelling, offer a broad range of possibilities to realize practical quantum information science applications in computing, communications and sensing
TL;DR: It is demonstrated that the exosomes' ability to target the parent cancer is a phenomenon that opens up new ways to devise targeted therapies to deliver anti-tumor drugs.
Abstract: Cancer is the second leading cause of death worldwide and patients are in urgent need of therapies that can effectively target cancer with minimal off-target side effects. Exosomes are extracellular nano-shuttles that facilitate intercellular communication between cells and organs. It has been established that tumor-derived exosomes contain a similar protein and lipid composition to that of the cells that secrete them, indicating that exosomes might be uniquely employed as carriers for anti-cancer therapeutics. Methods: We isolated exosomes from two cancer cell lines, then co-cultured each type of cancer cells with these two kinds of exosomes and quantified exosome. HT1080 or Hela exosomes were systemically injected to Nude mice bearing a subcutaneous HT1080 tumor to investigate their cancer-homing behavior. Moreover, cancer cell-derived exosomes were engineered to carry Doxil (a common chemotherapy drug), known as D-exo, were used to detect their target and therapeutic efficacy as anti-cancer drugs. Exosome proteome array analysis were used to reveal the mechanism underly this phenomenon. Results: Exosomes derived from cancer cells fuse preferentially with their parent cancer cells, in vitro. Systemically injected tumor-derived exosomes home to their original tumor tissues. Moreover, compared to Doxil alone, the drug-loaded exosomes showed enhanced therapeutic retention in tumor tissues and eradicated them more effectively in nude mice. Exosome proteome array analysis revealed distinct integrin expression patterns, which might shed light on the underlying mechanisms that explain the exosomal cancer-homing behavior. Conclusion: Here we demonstrate that the exosomes' ability to target the parent cancer is a phenomenon that opens up new ways to devise targeted therapies to deliver anti-tumor drugs.
TL;DR: It is shown that the secretome and exosomes of lung spheroid cells is effective as inhalation treatment in rodent models of lung injury and fibrosis and superior to the counterparts derived from mesenchymal stem cells.
Abstract: Idiopathic pulmonary fibrosis (IPF) is a fatal and incurable form of interstitial lung disease in which persistent injury results in scar tissue formation. As fibrosis thickens, the lung tissue loses the ability to facilitate gas exchange and provide cells with needed oxygen. Currently, IPF has few treatment options and no effective therapies, aside from lung transplant. Here we present a series of studies utilizing lung spheroid cell-secretome (LSC-Sec) and exosomes (LSC-Exo) by inhalation to treat different models of lung injury and fibrosis. Analysis reveals that LSC-Sec and LSC-Exo treatments could attenuate and resolve bleomycin- and silica-induced fibrosis by reestablishing normal alveolar structure and decreasing both collagen accumulation and myofibroblast proliferation. Additionally, LSC-Sec and LSC-Exo exhibit superior therapeutic benefits than their counterparts derived from mesenchymal stem cells in some measures. We showed that an inhalation treatment of secretome and exosome exhibited therapeutic potential for lung regeneration in two experimental models of pulmonary fibrosis. Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease and adult lung spheroid cells have been shown to promote regeneration in animal models of IPF. Here the authors show that the secretome and exosomes of lung spheroid cells is effective as inhalation treatment in rodent models of lung injury and fibrosis and superior to the counterparts derived from mesenchymal stem cells.
TL;DR: A broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.
Abstract: In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.
Nagoya University1, North Carolina State University2, University of Padua3, Ferdinand-Braun-Institut4, Kyoto University5, Technical University of Berlin6, University of Strathclyde7, Georgia Institute of Technology8, Tyndall National Institute9, Ohio State University10, University of Kassel11, Indian Institute of Technology Roorkee12, University of Ulm13, Asahi Kasei14, University of Bath15, University of Sheffield16, National Taiwan University17, Xerox18
TL;DR: In this article, the state of the art for the most important aspects of UV emitters, their challenges and their outlook for future developments are summarized. But, the development since the first realization of UV electroluminescence in the 1970s shows that an improvement in understanding and technology allows the performance ofUV emitters to be pushed far beyond the current state.
Abstract: Solid state UV emitters have many advantages over conventional UV sources. The (Al,In,Ga)N material system is best suited to produce LEDs and laser diodes from 400 nm down to 210 nm—due to its large and tuneable direct band gap, n- and p-doping capability up to the largest bandgap material AlN and a growth and fabrication technology compatible with the current visible InGaN-based LED production. However AlGaN based UV-emitters still suffer from numerous challenges compared to their visible counterparts that become most obvious by consideration of their light output power, operation voltage and long term stability. Most of these challenges are related to the large bandgap of the materials. However, the development since the first realization of UV electroluminescence in the 1970s shows that an improvement in understanding and technology allows the performance of UV emitters to be pushed far beyond the current state. One example is the very recent realization of edge emitting laser diodes emitting in the UVC at 271.8 nm and in the UVB spectral range at 298 nm. This roadmap summarizes the current state of the art for the most important aspects of UV emitters, their challenges and provides an outlook for future developments.
TL;DR: Worrying observations include increasing acaricide resistance in the varroa population and sinking economic treatment thresholds, suggesting that the mites or their vectored viruses are becoming more virulent.
California Institute of Technology1, Heidelberg University2, University of Greifswald3, Humboldt University of Berlin4, National Institutes of Health5, University of Tübingen6, Instituto Gulbenkian de Ciência7, Aix-Marseille University8, Ansys9, Newcastle University10, University of Nebraska–Lincoln11, University of Virginia12, University of Connecticut13, University of Utah14, PSL Research University15, VU University Amsterdam16, University of Washington17, The Turing Institute18, University of Pittsburgh19, ETH Zurich20, Université Paris-Saclay21, University of Oxford22, North Carolina State University23, University of California, Irvine24, Indian Institute of Technology Madras25, Babraham Institute26, Virginia Tech27, California State University, Northridge28, University of Liverpool29, IBM30, University of California, San Diego31, Virginia Mason Medical Center32, Okinawa Institute of Science and Technology33, Keio University34, Amazon.com35, University of Milan36, University of Toronto37, Masaryk University38, University of Tennessee39, Oregon Health & Science University40, Illumina41, Uppsala University42, Maastricht University43, Alpen-Adria-Universität Klagenfurt44, Medical University of Vienna45, European Bioinformatics Institute46, University of Rostock47, Leibniz Association48, Lorentz Institute49, Shinshu University50, Icahn School of Medicine at Mount Sinai51, Heidelberg Institute for Theoretical Studies52, Greifswald University Hospital53, Max Planck Society54, University of Jena55, École Polytechnique56, University of Southern California57, École Normale Supérieure58, Stellenbosch University59, École Polytechnique Fédérale de Lausanne60, Mizuho Information & Research Institute61, Pacific Northwest National Laboratory62
TL;DR: The latest edition of the Systems Biology Markup Language (SBML) is reviewed, a format designed for this purpose that leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models.
Abstract: Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.