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scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

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Cell systems 2023年第4期14卷 302-311.e4页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

关键词： cell-cell interaction cellular communication gene regression network machine learning manifold alignment neural networks scRNA-seq single-cell RNA sequencing

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Erratum to: An approach to the research on ion and water properties in the interphase between the plasma membrane and bulk extracellular solution

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The journal of physiological sciences : JPS 2018年第1期68卷 101页

作者： Hiroshi Hibino Madoka Takai Hidenori Noguchi Seishiro Sawamura Yasufumi Takahashi Hideki Sakai Hitoshi Shiku Department of Molecular Physiology Niigata University School of Medicine 1-757 Asahimachi-dori Chuo-ku Niigata Niigata 951-8510 Japan. hibinoh@med.niigata-u.ac.jp. Center for Transdisciplinary Research Niigata University Niigata Niigata 950-2181 Japan. hibinoh@med.niigata-u.ac.jp. AMED-CREST AMED Niigata Japan. hibinoh@med.niigata-u.ac.jp. Department of Bioengineering School of Engineering The University of Tokyo Tokyo Japan. International Center for Materials Nanoarchitectonics and Global Research Center for Environment and Energy Based on Nanomaterials Science National Institute for Materials Science Tsukuba Ibaraki Japan. Department of Molecular Physiology Niigata University School of Medicine 1-757 Asahimachi-dori Chuo-ku Niigata Niigata 951-8510 Japan. Division of Electrical Engineering and Computer Science Kanazawa University Kakuma-machi Kanazawa 920-1192 Japan. Precursory Research for Embryonic Science and Technology (PRESTO) Japan Science and Technology Agency (JST) Saitama 332-0012 Japan. Department of Pharmaceutical Physiology Graduate School of Medicine and Pharmaceutical Sciences University of Toyama Toyama Japan. Graduate School of Engineering Tohoku University Sendai 980-8579 Japan.

The article An approach to the research on ion and water properties in the interphase between the plasma membrane and bulk extracellular solution, written by Hiroshi Hibino, Madoka Takai, Hidenori Noguchi, Seishiro Sawamura, Yasufumi Takahashi, Hideki Sakai and Hitoshi Shiku, was originally published Online First without open access.

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THz generation by exchange-coupled spintronic emitters

npj Spintronics

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npj Spintronics 2024年第1期2卷 1-8页

作者： Roman Adam Derang Cao Daniel E. Bürgler Sarah Heidtfeld Fangzhou Wang Christian Greb Markus Büscher Claus M. Schneider Jing Cheng Debamitra Chakraborty Ivan Komissarov Roman Sobolewski Martin Mikulics Hilde Hardtdegen Peter Grünberg Institute Research Centre Jülich Jülich Germany College of Physics Qingdao University Qingdao China Faculty of Physics University Duisburg-Essen Duisburg Germany Institut für Laser- und Plasmaphysik Heinrich-Heine Universität Düsseldorf Düsseldorf Germany Materials Science Graduate Program University of Rochester Rochester NY USA Laboratory for Laser Energetics University of Rochester Rochester NY USA Department of Electrical and Computer Engineering University of Rochester Rochester NY USA Ernst Ruska Centre Research Centre Jülich Jülich Germany

The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintronic THz emitters separated by a thin (tCr≤ 3nm) wedge-shaped Cr spacer. In such an arrangement, magnetization alignment of the two Fe films can be controlled by the interplay between Cr-mediated interlayer exchange coupling (IEC) and an external magnetic field. This in turn results in a strong variation of the THz amplitudeA, withA↑↓reaching up to 14 timesA↑↑(arrows indicate the relative alignment of the magnetization of the two magnetic layers). This observed functionality is ascribed to the interference of THz transients generated by two closely spaced THz emitters. Moreover, the magnetic field dependenceA(H) shows a strong asymmetry that points to an additional performance modulation of the THz emitter via IEC and multilayer design.

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Input optics systems of the KAGRA detector during O3GK (vol 2023, 023F01, 2023)

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PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS 2023年第5期2023卷

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M. A. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chiang, C-I Chu, H. Chu, Y-K Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fujikawa, Y. Fukunaga, M. Fukushima, M. Furuhata, T. Gao, D. Ge, G-G Ha, S. Hagiwara, A. Haino, S. Han, W-B Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B-H Huang, G-Z Huang, H-Y Huang, P. Huang, Y-C Huang, Y-J Hui, D. C. Y. Ide, S. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Ito, K. Itoh, Y. Izumi, K. Jeon, C. Jin, H-B Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kang, G. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J. Kim, J. C. Kim, Ws Kim, Y-M Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A. K. H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H-S Kuromiya, Y. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H. K. Lee, H. W. Lee, R. Leonardi, M. Li, K. L. Lin, L. C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H. L. Liu, G. C. Luo, L-W Majorana, E. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Nakayama, Y. Narikawa, T. Naticchioni, L. Negishi, R. Quynh, L. Nguyen Ni, W-T Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J. J. Oh, S. H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohta, H. Okutani, Y. Okutomi, K. Oohara, K. Ooi, C. Oshino, S. Otabe, S. Pan, K-C Pang, H. Parisi, A. Park, J. Arellano, F. E. Pena Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shao, L. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E. J. Sotani, H. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Hirosaki Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Republic of Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Road Danshui Dist. New Taipei City 25137 Taiwan Department of Physics

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.

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Evidence for Gravitational Lensing of the Cosmic Microwave Background Polarization from Cross-Correlation with the Cosmic Infrared Background

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Physical Review Letters 2014年第13期112卷 131302-131302页

作者： P. A. R. Ade Y. Akiba A. E. Anthony K. Arnold M. Atlas D. Barron D. Boettger J. Borrill C. Borys S. Chapman Y. Chinone M. Dobbs T. Elleflot J. Errard G. Fabbian C. Feng D. Flanigan A. Gilbert W. Grainger N. W. Halverson M. Hasegawa K. Hattori M. Hazumi W. L. Holzapfel Y. Hori J. Howard P. Hyland Y. Inoue G. C. Jaehnig A. Jaffe B. Keating Z. Kermish R. Keskitalo T. Kisner M. Le Jeune A. T. Lee E. M. Leitch E. Linder M. Lungu F. Matsuda T. Matsumura X. Meng N. J. Miller H. Morii S. Moyerman M. J. Myers M. Navaroli H. Nishino H. Paar J. Peloton D. Poletti E. Quealy G. Rebeiz C. L. Reichardt P. L. Richards C. Ross K. Rotermund I. Schanning D. E. Schenck B. D. Sherwin A. Shimizu C. Shimmin M. Shimon P. Siritanasak G. Smecher H. Spieler N. Stebor B. Steinbach R. Stompor A. Suzuki S. Takakura A. Tikhomirov T. Tomaru B. Wilson A. Yadav O. Zahn School of Physics and Astronomy Cardiff University Cardiff CF10 3XQ United Kingdom The Graduate University for Advanced Studies Hayama Miura District Kanagawa 240-0115 Japan Center for Astrophysics and Space Astronomy University of Colorado Boulder CO 80309 USA Department of Astrophysical and Planetary Sciences University of Colorado Boulder CO 80309 USA Department of Physics University of California San Diego CA 92093-0424 USA Computational Cosmology Center Lawrence Berkeley National Laboratory Berkeley CA 92093-0424 USA Space Sciences Laboratory University of California Berkeley CA 94720 USA California Institute of Technology Pasadena California USA Department of Physics and Atmospheric Science Dalhousie University Halifax NS B3H 4R2 Canada High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki 305-0801 Japan Department of Physics University of California Berkeley CA 94720 USA Physics Department McGill University Montreal QC H3A 0G4 Canada AstroParticule et Cosmologie Univ Paris Diderot CNRS/IN2P3 CEA/Irfu Obs de Paris Sorbonne Paris Cité France International School for Advanced Studies (SISSA) Trieste 34014 Italy Department of Physics Columbia University New York NY 10027 USA Rutherford Appleton Laboratory STFC Swindon SN2 1SZ United Kingdom Department of Physics University of Colorado Boulder CO 80309 USA Kavli Institute for the Physics and Mathematics of the Universe (WPI) Todai Institutes for Advanced Study The University of Tokyo Kashiwa Chiba 277-8583 Japan Department of Physics University of Oxford Oxford OX1 2JD United Kingdom Physics Department Austin College Sherman TX 75090 USA Department of Physics Imperial College London London SW7 2AZ United Kingdom Physics Department Princeton University Princeton NJ 08544 USA Physics Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA Department of Astronomy and Astrophysics University of Chicago Chicago IL 60637 USA Kavli Institute for Cosm

We reconstruct the gravitational lensing convergence signal from cosmic microwave background (CMB) polarization data taken by the Polarbear experiment and cross-correlate it with cosmic infrared background maps from the Herschel satellite. From the cross spectra, we obtain evidence for gravitational lensing of the CMB polarization at a statistical significance of 4.0σ and indication of the presence of a lensing B-mode signal at a significance of 2.3σ. We demonstrate that our results are not biased by instrumental and astrophysical systematic errors by performing null tests, checks with simulated and real data, and analytical calculations. This measurement of polarization lensing, made via the robust cross-correlation channel, not only reinforces POLARBEAR auto-correlation measurements, but also represents one of the early steps towards establishing CMB polarization lensing as a powerful new probe of cosmology and astrophysics.

关键词： GRAVITATIONAL lenses COSMIC background radiation POLARIZATION (Nuclear physics) COSMOLOGY ASTROPHYSICS AUTOCORRELATION (Statistics)

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Measurement of the Cosmic Microwave Background Polarization Lensing Power Spectrum with the POLARBEAR Experiment

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Physical Review Letters 2014年第2期113卷 021301-021301页

作者： P. A. R. Ade Y. Akiba A. E. Anthony K. Arnold M. Atlas D. Barron D. Boettger J. Borrill S. Chapman Y. Chinone M. Dobbs T. Elleflot J. Errard G. Fabbian C. Feng D. Flanigan A. Gilbert W. Grainger N. W. Halverson M. Hasegawa K. Hattori M. Hazumi W. L. Holzapfel Y. Hori J. Howard P. Hyland Y. Inoue G. C. Jaehnig A. Jaffe B. Keating Z. Kermish R. Keskitalo T. Kisner M. Le Jeune A. T. Lee E. Linder E. M. Leitch M. Lungu F. Matsuda T. Matsumura X. Meng N. J. Miller H. Morii S. Moyerman M. J. Myers M. Navaroli H. Nishino H. Paar J. Peloton E. Quealy G. Rebeiz C. L. Reichardt P. L. Richards C. Ross I. Schanning D. E. Schenck B. Sherwin A. Shimizu C. Shimmin M. Shimon P. Siritanasak G. Smecher H. Spieler N. Stebor B. Steinbach R. Stompor A. Suzuki S. Takakura T. Tomaru B. Wilson A. Yadav O. Zahn School of Physics and Astronomy Cardiff University Cardiff CF10 3XQ United Kingdom The Graduate University for Advanced Studies Hayama Miura District Kanagawa 240-0115 Japan Center for Astrophysics and Space Astronomy University of Colorado Boulder Colorado 80309 USA Department of Physics University of California San Diego La Jolla California 92093-0424 USA Computational Cosmology Center Lawrence Berkeley National Laboratory Berkeley California 92093-0424 USA Space Sciences Laboratory University of California Berkeley Berkeley California 94720 USA Department of Physics and Atmospheric Science Dalhousie University Halifax Nova Scotia B3H 4R2 Canada High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki 305-0801 Japan Department of Physics University of California Berkeley Berkeley California 94720 USA Physics Department McGill University Montreal Quebec H3A 0G4 Canada AstroParticule et Cosmologie Univ Paris Diderot CNRS/IN2P3 CEA/Irfu Obs de Paris Sorbonne Paris Cité France International School for Advanced Studies (SISSA) Trieste 34014 Italy Columbia University New York New York 10027 USA Rutherford Appleton Laboratory STFC Swindon SN2 1SZ United Kingdom Department of Astrophysical and Planetary Sciences University of Colorado Boulder Colorado 80309 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Kavli Institute for the Physics and Mathematics of the Universe (WPI) Todai Institutes for Advanced Study The University of Tokyo Kashiwa Chiba 277-8583 Japan Department of Physics University of Oxford Oxford OX1 2JD United Kingdom Physics Department Austin College Sherman Texas 75090 USA Department of Physics Imperial College London London SW7 2AZ United Kingdom Physics Department Princeton University Princeton New Jersey 08544 USA Physics Division Lawrence Berkeley National Laboratory Berkeley California 92093-0424 USA Department of Astronomy and Astrophysics University of Chicago 5640 South

Gravitational lensing due to the large-scale distribution of matter in the cosmos distorts the primordial cosmic microwave background (CMB) and thereby induces new, small-scale B-mode polarization. This signal carries detailed information about the distribution of all the gravitating matter between the observer and CMB last scattering surface. We report the first direct evidence for polarization lensing based on purely CMB information, from using the four-point correlations of even- and odd-parity E- and B-mode polarization mapped over ∼30 square degrees of the sky measured by the POLARBEAR experiment. These data were analyzed using a blind analysis framework and checked for spurious systematic contamination using null tests and simulations. Evidence for the signal of polarization lensing and lensing B modes is found at 4.2σ (stat+sys) significance. The amplitude of matter fluctuations is measured with a precision of 27%, and is found to be consistent with the Lambda cold dark matter cosmological model. This measurement demonstrates a new technique, capable of mapping all gravitating matter in the Universe, sensitive to the sum of neutrino masses, and essential for cleaning the lensing B-mode signal in searches for primordial gravitational waves.

关键词： COSMIC background radiation POLARIZATION (Nuclear physics) GRAVITATIONAL lenses GRAVITATIONAL waves DARK matter (Astronomy) NEUTRINO mass

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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Genomic Surveillance of SARS-CoV-2 in Taiwan: A Perspective on Evolutionary Data Interpretation and Sequencing Issues

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Biomedical journal 2024年 100820页

作者： Yu-Nong Gong Nai-Yu Kuo Ting-Syuan Yeh Shin-Ru Shih Guang-Wu Chen Research Center for Emerging Viral Infections College of Medicine Chang Gung University Taoyuan Taiwan International Master Degree Program for Molecular Medicine in Emerging Viral Infections College of Medicine Chang Gung University Taoyuan Taiwan Department of Laboratory Medicine Linkou Chang Gung Memorial Hospital Taoyuan Taiwan. Medical Education Department Linkou Chang Gung Memorial Hospital Taoyuan Taiwan. National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Taiwan. Department of Laboratory Medicine Linkou Chang Gung Memorial Hospital Taoyuan Taiwan Department of Medical Biotechnology and Laboratory Science College of Medicine Chang Gung University Taoyuan Taiwan Research Center for Chinese Herbal Medicine Research Center for Food and Cosmetic Safety and Graduate Institute of Health Industry Technology College of Human Ecology Chang Gung University of Science and Technology Taoyuan Taiwan. Department of Computer Science and Information Engineering College of Engineering Chang Gung University Taoyuan Taiwan. Electronic address: gwchen@mail.cgu.edu.tw.

This review presents a comprehensive perspective on the genomic surveillance of SARS-CoV-2 in Taiwan, with a focus on next-generation sequencing and phylogenetic interpretation. This article aimed to explore how Taiwan has utilized genomic sequencing technologies and surveillance to monitor and mitigate the spread of COVID-19. We examined databases and sources of genomic sequences and highlighted the role of data science methodologies in the explanation and analyses of evolutionary data. This review addressed the challenges and limitations inherent in genomic surveillance, such as concerns regarding data quality and the necessity for interdisciplinary expertise for accurate data interpretation. Special attention was given to the unique challenges faced by Taiwan, including its high population density and major transit destination for international travelers. We underscored the far-reaching implications of genomic surveillance data for public health policy, particularly in influencing decisions regarding travel restrictions, vaccine administration, and public health decision-making. Studies were examined to demonstrate the effectiveness of using genomic data to implement public health measures. Future research should prioritize the integration of methodologies and technologies in evolutionary data science, particularly focusing on phylodynamic analytics. This integration is crucial to enhance the precision and applicability of genomic data. Overall, we have provided an overview of the significance of genomic surveillance in tracking SARS-CoV-2 variants globally and the pivotal role of data science methodologies in interpreting these data for effective public health interventions.

关键词： SARS-CoV-2 data science genomic surveillance next-generation sequencing phylodynamics

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Learning from learning machines: A new generation of AI technology to meet the needs of science

arXiv

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arXiv 2021年

作者： Pion-Tonachini, Luca Bouchard, Kristofer Martin, Hector Garcia Peisert, Sean Holtz, W. Bradley Aswani, Anil Dwivedi, Dipankar Wainwright, Haruko Pilania, Ghanshyam Nachman, Benjamin Marrone, Babetta L. Falco, Nicola Prabhat Arnold, Daniel Wolf-Yadlin, Alejandro Powers, Sarah Climer, Sharlee Jackson, Quinn Carlson, Ty Sohn, Michael Zwart, Petrus Kumar, Neeraj Justice, Amy Tomlin, Claire Jacobson, Daniel Micklem, Gos Gkoutos, Georgios V. Bickel, Peter J. Cazier, Jean-Baptiste Müller, Juliane Webb-Robertson, Bobbie-Jo Stevens, Rick Anderson, Mark Kreutz-Delgado, Ken Mahoney, Michael W. Brown, James B. Pattern Computer Inc. Friday HarborWA98250 United States Biosciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Helen Wils Neuroscience Institute Redwood Center for Theoretical Neuroscience Uc Berkeley BerkeleyCA94720 United States Doe Agile BioFoundry Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Joint BioEnergy Institute Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Bcam Basque Center for Applied Mathematics Bilbao48009 Spain Computer Science University of California Davis DavisCA95616 United States Cenic La MiradaCA90638 United States Health Informatics University of California Davis School of Medicine SacramentoCA95817 United States Berkeley Institute for Data Science University of California Berkeley BerkeleyCA94720 United States Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA94720 United States Environmental & Earth Sciences Area Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Nuclear Engineering University of California Berkeley BerkeleyCA94720 United States Materials Science and Technology Division Los Alamos National Laboratory Los AlamosNM87545 United States Physics Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Bioscience Division Los Alamos National Laboratory Los AlamosNM87545 United States Earth and Environmental Sciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Energy Technologies Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computing and Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Industrial & Systems Engineering The University of Tennessee KnoxvilleTN37996 United States Department of Computer Science University of Missouri-Saint Louis St. LouisMO63121 United

We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery. The distinct goals of AI for industry versus the goals of AI for science create tension between identifying patterns in data versus discovering patterns in the world from data. If we address the fundamental challenges associated with "bridging the gap" between domain-driven scientific models and data-driven AI learning machines, then we expect that these AI models can transform hypothesis generation, scientific discovery, and the scientific process itself. © 2021, CC BY.

关键词： Learning systems

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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