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  • 1
    In: Nature, Springer Science and Business Media LLC, Vol. 606, No. 7912 ( 2022-06-02), p. 64-69
    Abstract: Though immensely successful, the standard model of particle physics does not offer any explanation as to why our Universe contains so much more matter than antimatter. A key to a dynamically generated matter–antimatter asymmetry is the existence of processes that violate the combined charge conjugation and parity (CP) symmetry 1 . As such, precision tests of CP symmetry may be used to search for physics beyond the standard model. However, hadrons decay through an interplay of strong and weak processes, quantified in terms of relative phases between the amplitudes. Although previous experiments constructed CP observables that depend on both strong and weak phases, we present an approach where sequential two-body decays of entangled multi-strange baryon–antibaryon pairs provide a separation between these phases. Our method, exploiting spin entanglement between the double-strange Ξ − baryon and its antiparticle 2 $${\bar{{\Xi }}}^{+}$$ Ξ ¯ + , has enabled a direct determination of the weak-phase difference, ( ξ P  −  ξ S ) = (1.2 ± 3.4 ± 0.8) × 10 −2  rad. Furthermore, three independent CP observables can be constructed from our measured parameters. The precision in the estimated parameters for a given data sample size is several orders of magnitude greater than achieved with previous methods 3 . Finally, we provide an independent measurement of the recently debated Λ decay parameter α Λ (refs.  4,5 ). The $${\Lambda }\bar{{\Lambda }}$$ Λ Λ ¯ asymmetry is in agreement with and compatible in precision to the most precise previous measurement 4 .
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 2
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 51, No. D1 ( 2023-01-06), p. D18-D28
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global academic and industrial communities. With the explosive accumulation of multi-omics data generated at an unprecedented rate, CNCB-NGDC constantly expands and updates core database resources by big data archive, integrative analysis and value-added curation. In the past year, efforts have been devoted to integrating multiple omics data, synthesizing the growing knowledge, developing new resources and upgrading a set of major resources. Particularly, several database resources are newly developed for infectious diseases and microbiology (MPoxVR, KGCoV, ProPan), cancer-trait association (ASCancer Atlas, TWAS Atlas, Brain Catalog, CCAS) as well as tropical plants (TCOD). Importantly, given the global health threat caused by monkeypox virus and SARS-CoV-2, CNCB-NGDC has newly constructed the monkeypox virus resource, along with frequent updates of SARS-CoV-2 genome sequences, variants as well as haplotypes. All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 3
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2019
    In:  Proceedings of the National Academy of Sciences Vol. 116, No. 18 ( 2019-04-30), p. 9078-9083
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 116, No. 18 ( 2019-04-30), p. 9078-9083
    Abstract: Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2019
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  • 4
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 50, No. D1 ( 2022-01-07), p. D27-D38
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
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  • 5
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 15 ( 2022-04-12)
    Abstract: Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub ( https://covid19forecasthub.org/ ) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
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  • 6
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 375, No. 6584 ( 2022-03-04)
    Abstract: Drosophila melanogaster has had a fruitful history in biological research because it has contributed to many key discoveries in genetics, development, and neurobiology. The fruit fly genome contains ~14,000 protein-coding genes, ~63% of which have human orthologs. Single-cell RNA-sequencing has recently been applied to multiple Drosophila tissues and developmental stages. However, these data have been generated by different laboratories on different genetic backgrounds with different dissociation protocols and sequencing platforms, which has hindered the systematic comparison of gene expression across cells and tissues. RATIONALE We aimed to establish a cell atlas for the entire adult Drosophila with the same genetic background, dissociation protocol, and sequencing platform to (i) obtain a comprehensive categorization of cell types, (ii) integrate single-cell transcriptome data with existing knowledge about gene expression and cell types, (iii) systematically compare gene expression across the entire organism and between males and females, and (iv) identify cell type–specific markers across the entire organism. We chose single-nucleus RNA-sequencing (snRNA-seq) to circumvent the difficulties of dissociating cells that are embedded in the cuticle (e.g., sensory neurons) or that are multinucleated (e.g., muscle cells). We took two complementary strategies: sequencing nuclei from dissected tissues to know the identity of the tissue source and sequencing nuclei from the entire head and body to ensure that all cells are sampled. Experts from 40 laboratories participated in crowd annotation to assign transcriptomic cell types with the best knowledge available. RESULTS We sequenced 570,000 cells using droplet-based 10x Genomics from 15 dissected tissues as well as whole heads and bodies, separately in females and males. We also sequenced 10,000 cells from dissected tissues using the plate-based Smart-seq2 platform, providing deeper coverage per cell. We developed reproducible analysis pipelines using NextFlow and implemented a distributed cell-type annotation system with controlled vocabularies in SCope. Crowd-based annotations of transcriptomes from dissected tissues identified 17 main cell categories and 251 detailed cell types linked to FlyBase ontologies. Many of these cell types are characterized for the first time, either because they emerged only after increasing cell coverage or because they reside in tissues that had not been previously subjected to scRNA-seq. The excellent correspondence of transcriptomic clusters from whole body and dissected tissues allowed us to transfer annotations and identify a few cuticular cell types not detected in individual tissues. Cross-tissue analysis revealed location-specific subdivisions of muscle cells and heterogeneity within blood cells. We then determined cell type–specific marker genes and transcription factors with different specificity levels, enabling the construction of gene regulatory networks. Finally, we explored sexual dimorphism, finding a link between sex-biased expression and the presence of doublesex , and investigated tissue dynamics through trajectory analyses. CONCLUSION Our Fly Cell Atlas (FCA) constitutes a valuable resource for the Drosophila community as a reference for studies of gene function at single-cell resolution. All the FCA data are freely available for further analysis through multiple portals and can be downloaded for custom analyses using other single-cell tools. The ability to annotate cell types by sequencing the entire head and body will facilitate the use of Drosophila in the study of biological processes and in modeling human diseases at a whole-organism level with cell-type resolution. All data with annotations can be accessed from www.flycellatlas.org , which provides links to SCope, ASAP, and cellxgene portals. Tabula Drosophilae . In this single-cell atlas of the adult fruit fly, 580,000 cells were sequenced and 〉 250 cell types were annotated. They are from 15 individually dissected sexed tissues as well as the entire head and body. All data are freely available for visualization and download, with featured analyses shown at the bottom right.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2022
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  • 7
    In: Nature, Springer Science and Business Media LLC, Vol. 598, No. 7879 ( 2021-10-07), p. 174-181
    Abstract: Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types 1,2 , yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 8
    In: Nature, Springer Science and Business Media LLC, Vol. 598, No. 7879 ( 2021-10-07), p. 86-102
    Abstract: Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization 1–5 . First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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  • 9
    In: Nature, Springer Science and Business Media LLC, Vol. 614, No. 7947 ( 2023-02-09), p. 244-248
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 10
    In: DNA and Cell Biology, Mary Ann Liebert Inc, Vol. 39, No. 7 ( 2020-07-01), p. 1228-1242
    Type of Medium: Online Resource
    ISSN: 1044-5498 , 1557-7430
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    Language: English
    Publisher: Mary Ann Liebert Inc
    Publication Date: 2020
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