Cardiac tissues generated from human induced pluripotent stem cells (iPSCs) can serve as platforms for patient-specific studies of physiology and disease
. However, the predictive power of these ...models is presently limited by the immature state of the cells
. Here we show that this fundamental limitation can be overcome if cardiac tissues are formed from early-stage iPSC-derived cardiomyocytes soon after the initiation of spontaneous contractions and are subjected to physical conditioning with increasing intensity over time. After only four weeks of culture, for all iPSC lines studied, such tissues displayed adult-like gene expression profiles, remarkably organized ultrastructure, physiological sarcomere length (2.2 µm) and density of mitochondria (30%), the presence of transverse tubules, oxidative metabolism, a positive force-frequency relationship and functional calcium handling. Electromechanical properties developed more slowly and did not achieve the stage of maturity seen in adult human myocardium. Tissue maturity was necessary for achieving physiological responses to isoproterenol and recapitulating pathological hypertrophy, supporting the utility of this tissue model for studies of cardiac development and disease.
Lignin biosynthesis is evolutionarily conserved among higher plants and features a critical 3-hydroxylation reaction involving phenolic esters. However, increasing evidence questions the involvement ...of a single pathway to lignin formation in vascular plants. Here we describe an enzyme catalyzing the direct 3-hydroxylation of 4-coumarate to caffeate in lignin biosynthesis as a bifunctional peroxidase that oxidizes both ascorbate and 4-coumarate at comparable rates. A combination of biochemical and genetic evidence in the model plants Brachypodium distachyon and Arabidopsis thaliana supports a role for this coumarate 3-hydroxylase (C3H) in the early steps of lignin biosynthesis. The subsequent efficient O-methylation of caffeate to ferulate in grasses is substantiated by in vivo biochemical assays. Our results identify C3H as the only non-membrane bound hydroxylase in the lignin pathway and revise the currently accepted models of lignin biosynthesis, suggesting new gene targets to improve forage and bioenergy crops.
Episodic Training for Domain Generalization Li, Da; Zhang, Jianshu; Yang, Yongxin ...
2019 IEEE/CVF International Conference on Computer Vision (ICCV),
2019-Oct.
Conference Proceeding
Odprti dostop
Domain generalization (DG) is the challenging and topical problem of learning models that generalize to novel testing domains with different statistics than a set of known training domains. The ...simple approach of aggregating data from all source domains and training a single deep neural network end-to-end on all the data provides a surprisingly strong baseline that surpasses many prior published methods. In this paper we build on this strong baseline by designing an episodic training procedure that trains a single deep network in a way that exposes it to the domain shift that characterises a novel domain at runtime. Specifically, we decompose a deep network into feature extractor and classifier components, and then train each component by simulating it interacting with a partner who is badly tuned for the current domain. This makes both components more robust, ultimately leading to our networks producing state-of-the-art performance on three DG benchmarks. Furthermore, we consider the pervasive workflow of using an ImageNet trained CNN as a fixed feature extractor for downstream recognition tasks. Using the Visual Decathlon benchmark, we demonstrate that our episodic-DG training improves the performance of such a general purpose feature extractor by explicitly training a feature for robustness to novel problems. This shows that DG training can benefit standard practice in computer vision.
The problem of fine-grained sketch-based image retrieval (FG-SBIR) is defined and investigated in this paper. In FG-SBIR, free-hand human sketch images are used as queries to retrieve photo images ...containing the same object instances. It is thus a cross-domain (sketch to photo) instance-level retrieval task. It is an extremely challenging problem because (i) visual comparisons and matching need to be executed under large domain gap, i.e., from black and white line drawing sketches to colour photos; (ii) it requires to capture the fine-grained (dis)similarities of sketches and photo images while free-hand sketches drawn by different people present different levels of deformation and expressive interpretation; and (iii) annotated cross-domain fine-grained SBIR datasets are scarce, challenging many state-of-the-art machine learning techniques, particularly those based on deep learning. In this paper, for the first time, we address all these challenges, providing a step towards the capabilities that would underpin a commercial sketch-based object instance retrieval application. Specifically, a new large-scale FG-SBIR database is introduced which is carefully designed to reflect the real-world application scenarios. A deep cross-domain matching model is then formulated to solve the intrinsic drawing style variability, large domain gap issues, and capture instance-level discriminative features. It distinguishes itself by a carefully designed attention module. Extensive experiments on the new dataset demonstrate the effectiveness of the proposed model and validate the need for a rigorous definition of the FG-SBIR problem and collecting suitable datasets.
Native Americans from the Amazon, Andes, and coastal geographic regions of South America have a rich cultural heritage but are genetically understudied, therefore leading to gaps in our knowledge of ...their genomic architecture and demographic history. In this study, we sequence 150 genomes to high coverage combined with an additional 130 genotype array samples from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date. Demographic modeling reveals that the peopling of Peru began ∼12,000 y ago, consistent with the hypothesis of the rapid peopling of the Americas and Peruvian archeological data. We find that the Native American populations possess distinct ancestral divisions, whereas the mestizo groups were admixtures of multiple Native American communities that occurred before and during the Inca Empire and Spanish rule. In addition, the mestizo communities also show Spanish introgression largely following Peruvian Independence, nearly 300 y after Spain conquered Peru. Further, we estimate migration events between Peruvian populations from all three geographic regions with the majority of between-region migration moving from the high Andes to the low-altitude Amazon and coast. As such, we present a detailed model of the evolutionary dynamics which impacted the genomes of modern-day Peruvians and a Native American ancestry dataset that will serve as a beneficial resource to addressing the underrepresentation of Native American ancestry in sequencing studies.
The problem of domain generalization is to learn from multiple training domains, and extract a domain-agnostic model that can then be applied to an unseen domain. Domain generalization (DG) has a ...clear motivation in contexts where there are target domains with distinct characteristics, yet sparse data for training. For example recognition in sketch images, which are distinctly more abstract and rarer than photos. Nevertheless, DG methods have primarily been evaluated on photo-only benchmarks focusing on alleviating the dataset bias where both problems of domain distinctiveness and data sparsity can be minimal. We argue that these benchmarks are overly straightforward, and show that simple deep learning baselines perform surprisingly well on them. In this paper, we make two main contributions: Firstly, we build upon the favorable domain shift-robust properties of deep learning methods, and develop a low-rank parameterized CNN model for end-to-end DG learning. Secondly, we develop a DG benchmark dataset covering photo, sketch, cartoon and painting domains. This is both more practically relevant, and harder (bigger domain shift) than existing benchmarks. The results show that our method outperforms existing DG alternatives, and our dataset provides a more significant DG challenge to drive future research.
Epigenome editing with the CRISPR (clustered, regularly interspaced, short palindromic repeats)-Cas9 platform is a promising technology for modulating gene expression to direct cell phenotype and to ...dissect the causal epigenetic mechanisms of gene regulation. Fusions of nuclease-inactive dCas9 to the Krüppel-associated box (KRAB) repressor (dCas9-KRAB) can silence target gene expression, but the genome-wide specificity and the extent of heterochromatin formation catalyzed by dCas9-KRAB are not known. We targeted dCas9-KRAB to the HS2 enhancer, a distal regulatory element that orchestrates the expression of multiple globin genes, and observed highly specific induction of H3K9 trimethylation (H3K9me3) at the enhancer and decreased chromatin accessibility of both the enhancer and its promoter targets. Targeted epigenetic modification of HS2 silenced the expression of multiple globin genes, with minimal off-target changes in global gene expression. These results demonstrate that repression mediated by dCas9-KRAB is sufficiently specific to disrupt the activity of individual enhancers via local modification of the epigenome.
The generation and primary migration of hydrocarbons in organic-rich shale leaves void space in organic matter, which is the porosity associated with organic matter commonly observed under scanning ...electron microscope (SEM). In this study, Middle Devonian black shale core samples were collected from three wells penetrating the organic-rich Marcellus Shale and the organic-lean Mahantango Formation in Pennsylvania and West Virginia. Pyrolysis, ion milled SEM and low-pressure nitrogen adsorption analysis were conducted to investigate the organic richness and the properties of the pore system. Vitrinite reflectance (Ro) values in the range of 1.36%–2.89% represent a maturity spectrum covering the wet-gas to post-mature zones. In general, the pore system is composed of organic matter-hosted pores and mineral-hosted pores. However, the dominant pore types and pore sizes vary stratigraphically across lithology and abundance of organic matter. All the organic matter observed in this study shows an amorphous occurrence. Pore space between mineral grains (both silt-size and clay-size) can be filled by organic matter, which contains secondary porosity generated by thermal cracking of kerogen. Mineral-hosted pores are concentrated in organic-lean samples in which secondary organic matter could not fill most of the primary pore space. The destruction of primary mineral-hosted pores and the generation of secondary organic matter-hosted pores were observed. TOC values show positive correlations with the porosity, specific surface area, and the abundance of micropores. Increasing thermal maturity correlates with a significant decrease of pore volume and surface area, primarily through diminishing or vanishing of micropores. The richness and thermal maturity of organic matter in organic-rich Devonian shale can be effective parameters for evaluation of reservoir quality and upscaling the appraisal.
•The pore structure of the Marcellus Shale and Mahantango Formation were characterized.•The evolution of the pore system is driven by compaction, cementation, and organic matter maturation.•A stratigraphic distribution of pore networks is identified and classified into four pore facies.•The mechanism of generation and preservation of organic matter hosted porosity is discussed.•The storage capacity also shows a stratigraphic distribution with respect to the pore system.
Dual‐carbon batteries (DCBs) with both electrodes composed of carbon materials are currently at the forefront of industrial consideration. This is due to their low cost, safety, sustainability, fast ...charging, and simpler electrochemistry than lithium and other post‐lithium metal‐ion batteries. This article provides an overview of the past lessons on rechargeable DCBs and their future promises. In brief, it introduces the reader to DCBs as one of the most promising energy storage solutions for balancing sustainability, cost and performance, their history, electrochemistry and associated charge storage mechanisms. Then, the past lessons with respect to their ion intercalation are provided. These include DCB mechanisms during different anion/cation intercalation in layered carbons and their intercalation compounds and electrode structures versus electrochemical performance. This is followed by a description of the current issues affecting DCBs like capacity fading and self‐discharging, electrolyte instability, low energy densities and electrode exfoliation, together with their remedies. Finally, an insightful perspective proposing key areas requiring significant research efforts toward the success of DCBs is provided responsible for accelerating the commercialization and adoption of DCBs toward a sustainable and circular economy. This article is a simplified guide to understanding the current state and future research needed to develop sustainable DCBs.
Currently, sustainability is an important factor in batteries just like cost and performance. The goal of balancing the three factors during the development of next‐generation batteries is critical. Dual carbon batteries (DCBs) have great potential to fit into this balance. The article provides an account of the rapid progress, current understanding, and future strategies for realizing DCB battery technology.
Deep Learning for Free-Hand Sketch: A Survey Xu, Peng; Hospedales, Timothy M.; Yin, Qiyue ...
IEEE transactions on pattern analysis and machine intelligence,
2023-Jan.-1, 2023-Jan, 2023-1-1, 20230101, Letnik:
45, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Free-hand sketches are highly illustrative, and have been widely used by humans to depict objects or stories from ancient times to the present. The recent prevalence of touchscreen devices has made ...sketch creation a much easier task than ever and consequently made sketch-oriented applications increasingly popular. The progress of deep learning has immensely benefited free-hand sketch research and applications. This paper presents a comprehensive survey of the deep learning techniques oriented at free-hand sketch data, and the applications that they enable. The main contents of this survey include: (i) A discussion of the intrinsic traits and unique challenges of free-hand sketch, to highlight the essential differences between sketch data and other data modalities, e.g., natural photos. (ii) A review of the developments of free-hand sketch research in the deep learning era, by surveying existing datasets, research topics, and the state-of-the-art methods through a detailed taxonomy and experimental evaluation. (iii) Promotion of future work via a discussion of bottlenecks, open problems, and potential research directions for the community.
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