Showing papers by "University of Freiburg published in 2018"
Clotilde Théry1, Kenneth W. Witwer2, Elena Aikawa3, María José Alcaraz4 +414 more•Institutions (209)
TL;DR: The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities, and a checklist is provided with summaries of key points.
Abstract: The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
5,988 citations
Lorenzo Galluzzi1, Lorenzo Galluzzi2, Ilio Vitale3, Stuart A. Aaronson4 +183 more•Institutions (111)
TL;DR: The Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives.
Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.
3,301 citations
TL;DR: Improvements to Galaxy's core framework, user interface, tools, and training materials enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed.
Abstract: Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.
2,601 citations
TL;DR: A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent and significant loci and finds important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia.
Abstract: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
1,898 citations
Columbia University1, University of Amsterdam2, University of Bologna3, University of Mainz4, University of Münster5, University of Coimbra6, New York University Abu Dhabi7, University of Zurich8, Stockholm University9, Rensselaer Polytechnic Institute10, Max Planck Society11, Weizmann Institute of Science12, University of Freiburg13, University of Nantes14, University of California, San Diego15, University of Chicago16, Purdue University17, Rice University18, Pierre-and-Marie-Curie University19, University of California, Los Angeles20
TL;DR: In this article, a search for weakly interacting massive particles (WIMPs) using 278.8 days of data collected with the XENON1T experiment at LNGS is reported.
Abstract: We report on a search for weakly interacting massive particles (WIMPs) using 278.8 days of data collected with the XENON1T experiment at LNGS. XENON1T utilizes a liquid xenon time projection chamber with a fiducial mass of (1.30±0.01) ton, resulting in a 1.0 ton yr exposure. The energy region of interest, [1.4,10.6] keVee ([4.9,40.9] keVnr), exhibits an ultralow electron recoil background rate of [82-3+5(syst)±3(stat)] events/(ton yr keVee). No significant excess over background is found, and a profile likelihood analysis parametrized in spatial and energy dimensions excludes new parameter space for the WIMP-nucleon spin-independent elastic scatter cross section for WIMP masses above 6 GeV/c2, with a minimum of 4.1×10-47 cm2 at 30 GeV/c2 and a 90% confidence level.
1,808 citations
Proceedings Article•
27 Sep 2018TL;DR: Recently, this paper proposed a decoupled weight decay regularization that decouples the optimal weight decay factor from the setting of the learning rate for both standard SGD and Adam and substantially improves Adam's generalization performance.
Abstract: L$_2$ regularization and weight decay regularization are equivalent for standard stochastic gradient descent (when rescaled by the learning rate), but as we demonstrate this is \emph{not} the case for adaptive gradient algorithms, such as Adam. While common implementations of these algorithms employ L$_2$ regularization (often calling it "weight decay" in what may be misleading due to the inequivalence we expose), we propose a simple modification to recover the original formulation of weight decay regularization by \emph{decoupling} the weight decay from the optimization steps taken w.r.t. the loss function. We provide empirical evidence that our proposed modification (i) decouples the optimal choice of weight decay factor from the setting of the learning rate for both standard SGD and Adam and (ii) substantially improves Adam's generalization performance, allowing it to compete with SGD with momentum on image classification datasets (on which it was previously typically outperformed by the latter). Our proposed decoupled weight decay has already been adopted by many researchers, and the community has implemented it in TensorFlow and PyTorch; the complete source code for our experiments is available at this https URL
1,780 citations
TL;DR: This work presents a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and shows that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods.
Abstract: Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
1,620 citations
Posted Content•
TL;DR: An overview of existing work in this field of research is provided and neural architecture search methods are categorized according to three dimensions: search space, search strategy, and performance estimation strategy.
Abstract: Deep Learning has enabled remarkable progress over the last years on a variety of tasks, such as image recognition, speech recognition, and machine translation. One crucial aspect for this progress are novel neural architectures. Currently employed architectures have mostly been developed manually by human experts, which is a time-consuming and error-prone process. Because of this, there is growing interest in automated neural architecture search methods. We provide an overview of existing work in this field of research and categorize them according to three dimensions: search space, search strategy, and performance estimation strategy.
1,362 citations
Posted Content•
15 Feb 2018TL;DR: This work decouples the optimal choice of weight decay factor from the setting of the learning rate for both standard SGD and Adam and substantially improves Adam's generalization performance, allowing it to compete with SGD with momentum on image classification datasets.
Abstract: We note that common implementations of adaptive gradient algorithms, such as Adam, limit the potential benefit of weight decay regularization, because the weights do not decay multiplicatively (as would be expected for standard weight decay) but by an additive constant factor. We propose a simple way to resolve this issue by decoupling weight decay and the optimization steps taken w.r.t. the loss function. We provide empirical evidence that our proposed modification (i) decouples the optimal choice of weight decay factor from the setting of the learning rate for both standard SGD and Adam, and (ii) substantially improves Adam's generalization performance, allowing it to compete with SGD with momentum on image classification datasets (on which it was previously typically outperformed by the latter). We also demonstrate that longer optimization runs require smaller weight decay values for optimal results and introduce a normalized variant of weight decay to reduce this dependence. Finally, we propose a version of Adam with warm restarts (AdamWR) that has strong anytime performance while achieving state-of-the-art results on CIFAR-10 and ImageNet32x32. Our source code will become available after the review process.
1,173 citations
University of Oxford1, University of Michigan2, Wellcome Trust Sanger Institute3, Amgen4, University of Cambridge5, University of Copenhagen6, University of Liverpool7, University of Freiburg8, Boston University9, University of Tartu10, Erasmus University Medical Center11, Leiden University Medical Center12, Pasteur Institute13, Icahn School of Medicine at Mount Sinai14, UCLA Medical Center15, Vanderbilt University Medical Center16, Wake Forest University17, National University of Singapore18, Imperial College London19, London North West Healthcare NHS Trust20, Charité21, Innsbruck Medical University22, Washington University in St. Louis23, Queen Mary University of London24, University of Southern Denmark25, National and Kapodistrian University of Athens26, Robertson Centre for Biostatistics27, University of Exeter28, Uppsala University29, University of Düsseldorf30, Steno Diabetes Center31, Aalborg University32, University of Eastern Finland33, Broad Institute34, Frederiksberg Hospital35, Lund University36, University of Bergen37, Technische Universität München38, University of North Carolina at Chapel Hill39, University of Edinburgh40, Ninewells Hospital41, University of Minnesota42, University of Glasgow43, Ludwig Maximilian University of Munich44, University of Iceland45, Aarhus University46, Stanford University47, Science for Life Laboratory48, University of Helsinki49, National Institutes of Health50, University of Dundee51, Harvard University52
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
1,136 citations
TL;DR: It is established that graft-derived macrophages acquire, over time, microglia characteristics, including ramified morphology, longevity, radio-resistance and clonal expansion, however, even after prolonged CNS residence, transcriptomes and chromatin accessibility landscapes of engrafted, BM-derived Macrophages remain distinct from yolk sac-derived host microglial.
Abstract: Microglia are yolk sac-derived macrophages residing in the parenchyma of brain and spinal cord, where they interact with neurons and other glial. After different conditioning paradigms and bone marrow (BM) or hematopoietic stem cell (HSC) transplantation, graft-derived cells seed the brain and persistently contribute to the parenchymal brain macrophage compartment. Here we establish that graft-derived macrophages acquire, over time, microglia characteristics, including ramified morphology, longevity, radio-resistance and clonal expansion. However, even after prolonged CNS residence, transcriptomes and chromatin accessibility landscapes of engrafted, BM-derived macrophages remain distinct from yolk sac-derived host microglia. Furthermore, engrafted BM-derived cells display discrete responses to peripheral endotoxin challenge, as compared to host microglia. In human HSC transplant recipients, engrafted cells also remain distinct from host microglia, extending our finding to clinical settings. Collectively, our data emphasize the molecular and functional heterogeneity of parenchymal brain macrophages and highlight potential clinical implications for HSC gene therapies aimed to ameliorate lysosomal storage disorders, microgliopathies or general monogenic immuno-deficiencies. Irradiation depletes brain microglia cells and induces replenishment of the pool by bone marrow (BM)-derived macrophage. Here the authors show, using mouse BM chimera, that BM-derived macrophages establish long-term residency in the brain, but remain distinct from resident microglia in their transcriptome and gene accessibility landscape.
Catholic University of the Sacred Heart1, Harvard University2, Columbia University3, Stanford University4, University of Western Ontario5, Washington University in St. Louis6, University of Texas Southwestern Medical Center7, University of Freiburg8, Children's Memorial Hospital9, University of California, Los Angeles10, University of Gothenburg11, Biogen Idec12, Nemours Foundation13
TL;DR: Among children with later‐onset SMA, those who received nusinersen had significant and clinically meaningful improvement in motor function as compared with those in the control group.
Abstract: Background Nusinersen is an antisense oligonucleotide drug that modulates pre–messenger RNA splicing of the survival motor neuron 2 (SMN2) gene. It has been developed for the treatment of spinal muscular atrophy (SMA). Methods We conducted a multicenter, double-blind, sham-controlled, phase 3 trial of nusinersen in 126 children with SMA who had symptom onset after 6 months of age. The children were randomly assigned, in a 2:1 ratio, to undergo intrathecal administration of nusinersen at a dose of 12 mg (nusinersen group) or a sham procedure (control group) on days 1, 29, 85, and 274. The primary end point was the least-squares mean change from baseline in the Hammersmith Functional Motor Scale–Expanded (HFMSE) score at 15 months of treatment; HFMSE scores range from 0 to 66, with higher scores indicating better motor function. Secondary end points included the percentage of children with a clinically meaningful increase from baseline in the HFMSE score (≥3 points), an outcome that indicates impro...
Goethe University Frankfurt1, University of Maryland, College Park2, University of Guelph3, Duke University4, Radboud University Nijmegen5, Swedish University of Agricultural Sciences6, Federal University of Mato Grosso do Sul7, University of Alberta8, Royal Veterinary College9, Wildlife Conservation Society10, Mississippi State University11, Sao Paulo State University12, Michigan Department of Natural Resources13, University of California, Davis14, Aarhus University15, Max Planck Society16, University of Potsdam17, Middle Tennessee State University18, Mammal Research Institute19, Harvard University20, Edmund Mach Foundation21, Smithsonian Conservation Biology Institute22, University of Évora23, University of Montpellier24, Monash University25, Parks Victoria26, Ohio State University27, Fiji National University28, University of Massachusetts Amherst29, United States Geological Survey30, University of Oxford31, Save the Elephants32, German Primate Center33, Technische Universität München34, Institute of Ecosystem Studies35, University of British Columbia36, University of Zurich37, University of Wyoming38, University of Washington39, University of Montana40, University of Freiburg41, Bavarian Forest National Park42, University of Toulouse43, University of Veterinary Medicine Vienna44, University College Cork45, North Carolina Museum of Natural Sciences46, North Carolina State University47, Karatina University48, University of Lethbridge49, Lamont–Doherty Earth Observatory50, University of Valencia51, Stony Brook University52, International Union for Conservation of Nature and Natural Resources53, University of Alicante54, Empresa Brasileira de Pesquisa Agropecuária55, University of Glasgow56, New York University57, University of Oslo58, Hebrew University of Jerusalem59, Norwegian University of Science and Technology60, Field Museum of Natural History61, University of Grenoble62, University of Bayreuth63, University of New South Wales64, Pennsylvania Game Commission65, Princeton University66, University of Konstanz67, University of Haifa68, Polish Academy of Sciences69, Instituto Superior de Agronomia70, University of Porto71, University of Lisbon72, University of California, Santa Cruz73, University of Pretoria74, Colorado State University75
TL;DR: Using a unique GPS-tracking database of 803 individuals across 57 species, it is found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in area with a low human footprint.
Abstract: Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
TL;DR: The present Bioconda, a distribution of bioinformatics software for the lightweight, multi-platform and language-agnostic package manager Conda, improves analysis reproducibility by allowing users to define isolated environments with defined software versions.
Abstract: We present Bioconda (https://bioconda.github.io), a distribution of bioinformatics software for the lightweight, multi-platform and language-agnostic package manager Conda. Currently, Bioconda offers a collection of over 3000 software packages, which is continuously maintained, updated, and extended by a growing global community of more than 200 contributors. Bioconda improves analysis reproducibility by allowing users to define isolated environments with defined software versions, all of which are easily installed and managed without administrative privileges.
TL;DR: The Python package tsfresh (Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests) accelerates this process by combining 63 time series characterization methods, which by default compute a total of 794 time series features, with feature selection on basis automatically configured hypothesis tests.
TL;DR: It is reported that TGFα and VEGF-B produced by microglia regulate the pathogenic activities of astrocytes in the experimental autoimmune encephalomyelitis mouse model of multiple sclerosis, and this pathway may guide new therapies for multiple sclerosis and other neurological disorders.
Abstract: Microglia and astrocytes modulate inflammation and neurodegeneration in the central nervous system (CNS)1–3. Microglia modulate pro-inflammatory and neurotoxic activities in astrocytes, but the mechanisms involved are not completely understood4,5. Here we report that TGFα and VEGF-B produced by microglia regulate the pathogenic activities of astrocytes in the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis. Microglia-derived TGFα acts via the ErbB1 receptor in astrocytes to limit their pathogenic activities and EAE development. Conversely, microglial VEGF-B triggers FLT-1 signalling in astrocytes and worsens EAE. VEGF-B and TGFα also participate in the microglial control of human astrocytes. Furthermore, expression of TGFα and VEGF-B in CD14+ cells correlates with the multiple sclerosis lesion stage. Finally, metabolites of dietary tryptophan produced by the commensal flora control microglial activation and TGFα and VEGF-B production, modulating the transcriptional program of astrocytes and CNS inflammation through a mechanism mediated by the aryl hydrocarbon receptor. In summary, we identified positive and negative regulators that mediate the microglial control of astrocytes. Moreover, these findings define a pathway through which microbial metabolites limit pathogenic activities of microglia and astrocytes, and suppress CNS inflammation. This pathway may guide new therapies for multiple sclerosis and other neurological disorders.
TL;DR: Software to identify high-resolution TAD boundaries and reveal their relationship to underlying DNA motifs is developed and it is demonstrated that boundaries can be accurately predicted using only the motif sequences at open chromatin sites.
Abstract: Despite an abundance of new studies about topologically associating domains (TADs), the role of genetic information in TAD formation is still not fully understood. Here we use our software, HiCExplorer (hicexplorer.readthedocs.io) to annotate >2800 high-resolution (570 bp) TAD boundaries in Drosophila melanogaster. We identify eight DNA motifs enriched at boundaries, including a motif bound by the M1BP protein, and two new boundary motifs. In contrast to mammals, the CTCF motif is only enriched on a small fraction of boundaries flanking inactive chromatin while most active boundaries contain the motifs bound by the M1BP or Beaf-32 proteins. We demonstrate that boundaries can be accurately predicted using only the motif sequences at open chromatin sites. We propose that DNA sequence guides the genome architecture by allocation of boundary proteins in the genome. Finally, we present an interactive online database to access and explore the spatial organization of fly, mouse and human genomes, available at http://chorogenome.ie-freiburg.mpg.de
. Although topologically associating domains (TADs) have been extensively investigated, it is not clear to what extent DNA sequence contributes to their formation. Here the authors develop software to identify high-resolution TAD boundaries and reveal their relationship to underlying DNA motifs.
TL;DR: It is demonstrated that peripherally applied inflammatory stimuli induce acute immune training and tolerance in the brain and lead to differential epigenetic reprogramming of brain-resident macrophages (microglia) that persists for at least six months.
Abstract: Innate immune memory is a vital mechanism of myeloid cell plasticity that occurs in response to environmental stimuli and alters subsequent immune responses. Two types of immunological imprinting can be distinguished—training and tolerance. These are epigenetically mediated and enhance or suppress subsequent inflammation, respectively. Whether immune memory occurs in tissue-resident macrophages in vivo and how it may affect pathology remains largely unknown. Here we demonstrate that peripherally applied inflammatory stimuli induce acute immune training and tolerance in the brain and lead to differential epigenetic reprogramming of brain-resident macrophages (microglia) that persists for at least six months. Strikingly, in a mouse model of Alzheimer’s pathology, immune training exacerbates cerebral β-amyloidosis and immune tolerance alleviates it; similarly, peripheral immune stimulation modifies pathological features after stroke. Our results identify immune memory in the brain as an important modifier of neuropathology.
TL;DR: It is shown that the fastest rates of speciation occur in species-poor regions outside the tropics, and that high-latitude fish lineages form new species at much faster rates than their tropical counterparts.
Abstract: Far more species of organisms are found in the tropics than in temperate and polar regions, but the evolutionary and ecological causes of this pattern remain controversial1,2. Tropical marine fish communities are much more diverse than cold-water fish communities found at higher latitudes3,4, and several explanations for this latitudinal diversity gradient propose that warm reef environments serve as evolutionary ‘hotspots’ for species formation5–8. Here we test the relationship between latitude, species richness and speciation rate across marine fishes. We assembled a time-calibrated phylogeny of all ray-finned fishes (31,526 tips, of which 11,638 had genetic data) and used this framework to describe the spatial dynamics of speciation in the marine realm. We show that the fastest rates of speciation occur in species-poor regions outside the tropics, and that high-latitude fish lineages form new species at much faster rates than their tropical counterparts. High rates of speciation occur in geographical regions that are characterized by low surface temperatures and high endemism. Our results reject a broad class of mechanisms under which the tropics serve as an evolutionary cradle for marine fish diversity and raise new questions about why the coldest oceans on Earth are present-day hotspots of species formation.
TL;DR: Single-cell RNA sequencing unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and monocyte-derived dendritic cells in atherosclerotic arteries and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions.
Abstract: Rationale: It is assumed that atherosclerotic arteries contain several macrophage subsets endowed with specific functions. The precise identity of these subsets is poorly characterized as they ha ve been defined by the expression of a restricted number of markers. Objective: We have applied single-cell RNA-seq as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis. Methods and Results: We performed single-cell RNA sequencing of total aortic CD45 + cells extracted from the non-diseased (chow fed) and atherosclerotic (11 weeks of high fat diet) aorta of Ldlr -/- mice. Unsupervised clustering singled out 13 distinct aortic cell clusters. Among the myeloid cell populations, Resident-like macrophages with a gene expression profile similar to aortic resident macrophages were found in healthy and diseased aortae, whereas monocytes, monocyte-derived dendritic cells (MoDC), and two populations of macrophages were almost exclusively detectable in atherosclerotic aortae, comprising Inflammatory macrophages showing enrichment in I l1b , and previously undescribed TREM2 hi macrophages. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these three macrophage subsets and MoDC, and uncovered putative functions of each cell type. Notably, TREM2 hi macrophages appeared to be endowed with specialized functions in lipid metabolism and catabolism, and presented a gene expression signature reminiscent of osteoclasts, suggesting a role in lesion calcification. TREM2 expression was moreover detected in human lesional macrophages. Importantly, these macrophage populations were present also in advanced atherosclerosis and in Apoe -/- aortae, indicating relevance of our findings in different stages of atherosclerosis and mouse models. Conclusions: These data unprecedentedly uncovered the transcriptional landscape and phenotypic heterogeneity of aortic macrophages and MoDCs in atherosclerotic and identified previously unrecognized macrophage populations and their gene expression signature, suggesting specialized functions. Our findings will open up novel opportunities to explore distinct myeloid cell populations and their functions in atherosclerosis.
TL;DR: The Intestine Chip may be useful as a research tool for applications where normal intestinal function is crucial, including studies of metabolism, nutrition, infection, and drug pharmacokinetics, as well as personalized medicine.
Abstract: Here we describe a method for fabricating a primary human Small Intestine-on-a-Chip (Intestine Chip) containing epithelial cells isolated from healthy regions of intestinal biopsies. The primary epithelial cells are expanded as 3D organoids, dissociated, and cultured on a porous membrane within a microfluidic device with human intestinal microvascular endothelium cultured in a parallel microchannel under flow and cyclic deformation. In the Intestine Chip, the epithelium forms villi-like projections lined by polarized epithelial cells that undergo multi-lineage differentiation similar to that of intestinal organoids, however, these cells expose their apical surfaces to an open lumen and interface with endothelium. Transcriptomic analysis also indicates that the Intestine Chip more closely mimics whole human duodenum in vivo when compared to the duodenal organoids used to create the chips. Because fluids flowing through the lumen of the Intestine Chip can be collected continuously, sequential analysis of fluid samples can be used to quantify nutrient digestion, mucus secretion and establishment of intestinal barrier function over a period of multiple days in vitro. The Intestine Chip therefore may be useful as a research tool for applications where normal intestinal function is crucial, including studies of metabolism, nutrition, infection, and drug pharmacokinetics, as well as personalized medicine.
TL;DR: A review of the history of the antimicrobial photodynamic therapy (aPDT), its fundamental photochemical and photophysical mechanisms as well as photosensitizers and light sources that are currently applied for aPDT in vitro and implications for proper comparison of in vitro studies regarding a PDT are given.
Abstract: Considering increasing number of pathogens resistant towards commonly used antibiotics as well as antiseptics, there is a pressing need for antimicrobial approaches that are capable of inac...
TL;DR: The need for better evaluation metrics is explained, the importance and unique challenges for deep robotic learning in simulation are highlighted, and the spectrum between purely data-driven and model-driven approaches is explored.
Abstract: The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and machine learning communities. In this paper we discuss a number of robotics-specific learning, reasoning, and embodiment challenges for deep learning. We explain the need for better evaluation metrics, highlight the importance and unique challenges for deep robotic learning in simulation, and explore the spectrum between purely data-driven and model-driven approaches. We hope this paper provides a motivating overview of important research directions to overcome the current limitations, and helps to fulfill the promising potentials of deep learning in robotics.
Proceedings Article•
03 Jul 2018TL;DR: The authors combine the benefits of both Bayesian optimization and bandit-based methods, in order to achieve the best of both worlds: strong anytime performance and fast convergence to optimal configurations.
Abstract: Modern deep learning methods are very sensitive to many hyperparameters, and, due to the long training times of state-of-the-art models, vanilla Bayesian hyperparameter optimization is typically computationally infeasible. On the other hand, bandit-based configuration evaluation approaches based on random search lack guidance and do not converge to the best configurations as quickly. Here, we propose to combine the benefits of both Bayesian optimization and bandit-based methods, in order to achieve the best of both worlds: strong anytime performance and fast convergence to optimal configurations. We propose a new practical state-of-the-art hyperparameter optimization method, which consistently outperforms both Bayesian optimization and Hyperband on a wide range of problem types, including high-dimensional toy functions, support vector machines, feed-forward neural networks, Bayesian neural networks, deep reinforcement learning, and convolutional neural networks. Our method is robust and versatile, while at the same time being conceptually simple and easy to implement.
TL;DR: The use of ROBINS-I in GRADE assessments may allow for a better comparison of evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias.
TL;DR: How microfluidic Intestine Chips offer new capabilities not possible with conventional culture systems or organoid cultures, including the ability to analyze contributions of individual cellular, chemical, and physical control parameters one-at-a-time is described.
Abstract: Microfluidic organ-on-a-chip models of human intestine have been developed and used to study intestinal physiology and pathophysiology. In this article, we review this field and describe how microfluidic Intestine Chips offer new capabilities not possible with conventional culture systems or organoid cultures, including the ability to analyze contributions of individual cellular, chemical, and physical control parameters one-at-a-time; to coculture human intestinal cells with commensal microbiome for extended times; and to create human-relevant disease models. We also discuss potential future applications of human Intestine Chips, including how they might be used for drug development and personalized medicine.
Daniel S. Karp1, Rebecca Chaplin-Kramer2, Timothy D. Meehan3, Emily A. Martin4 +153 more•Institutions (81)
TL;DR: Analysis of the largest pest-control database of its kind shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others.
Abstract: The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.
01 Jun 2018
TL;DR: Tangent convolutions as discussed by the authors is a new construction for convolutional networks on 3D data that operates directly on surface geometry and is applicable to unstructured point clouds and other noisy real-world data.
Abstract: We present an approach to semantic scene analysis using deep convolutional networks. Our approach is based on tangent convolutions - a new construction for convolutional networks on 3D data. In contrast to volumetric approaches, our method operates directly on surface geometry. Crucially, the construction is applicable to unstructured point clouds and other noisy real-world data. We show that tangent convolutions can be evaluated efficiently on large-scale point clouds with millions of points. Using tangent convolutions, we design a deep fully-convolutional network for semantic segmentation of 3D point clouds, and apply it to challenging real-world datasets of indoor and outdoor 3D environments. Experimental results show that the presented approach outperforms other recent deep network constructions in detailed analysis of large 3D scenes.
TL;DR: This review highlights the available therapies for cartilage repair and retraces the research on different biomaterials developed for tissue engineering strategies, and a perspective of the limitations of the current research is given in the light of the emerging technologies supporting tissue engineering of articular cartilage.