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91st Annual Water Environment Federation Technical Exhibition and Conference, WEFTEC 2018

作者： Rehman, U. Audenaert, W. Bellandi, G. Flameling, T. Weijers, S. Nopens, I. BIOMATH Department of Mathematical Modeling Statistics and Bioinformatics Faculty of Bioscience Engineering Ghent University Coupure Links 653 Gent9000 Belgium AM-TEAM Advanced modelling for process optimisation Hulstbaan 63 Sint-Niklaas9112 Belgium Waterboard De Dommel PO Box 10.001 DA Boxtel5280 Netherlands Department of Civil and Environmental Engineering University of Florence via di S. Marta 3 Florence50139 Italy

ISBN: (纸本)9781510877474

Besides trial-and-error approaches, conventional flowsheet modelling (such as tanks-in-series (TIS)) is widely used to optimize the performance of Water Resource Recovery Facilities (WRRFs). However, this modelling approach lacks the ability to consider design parameters such as propellers and aerator configurations. Trial-and-error based optimisation of such parameters is in many cases highly risky or even impossible. By appropriate use of computational fluid dynamics (CFD), one can accurately and efficiently evaluate different design changes prior to actual implementation, while severely extending system understanding. The current study shows the practical application of CFD for full-scale bioreactor optimization in terms of performance (lower effluent nitrate) and cost. The CFD model was unprecedentedly validated using a construction crane for dissolved oxygen profiling. Also flow velocities were measured. Different new propeller settings and aerator configurations were tested. Unwanted oxygen near the inlet of the anoxic zone could be reduced up to 20%. One of the promising scenarios was implemented in practice and the impact on effluent quality is currently being evaluated. The operational change will have a potential operational cost saving of minimum 500,000 EUR/y. Copyright © 2018 Water Environment Federation

关键词： Bioreactors

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Automating Care by Self-maintainability for Full Laboratory Automation

arXiv

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arXiv 2025年

作者： Ochiai, Koji Tahara-Arai, Yuya Kato, Akari Kaizu, Kazunari Kariyazaki, Hirokazu Umeno, Makoto Takahashi, Koichi Kanda, Genki N. Ozaki, Haruka Laboratory for Biologically Inspired Computing RIKEN Center for Biosystems Dynamics Research 6-7-1 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Bioinformatics Laboratory Institute of Medicine University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Ph.D. Program in Humanics School of Integrative and Global Majors University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Laboratory Automation Suppliers’ Association 2-1-8 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Cell Modeling and Simulation Group Exploratory Research Center on Life and Living Systems National Institutes of Natural Sciences 5-1 Higashiyama Myodaiji Aichi Okazaki444-8787 Japan Robotics Division YASKAWA Electric Corporation 2-1 Kurosaki Shiroishi Yahatanishi-ku Kitakyushu Fukuoka806-0004 Japan BAIKEIDO LLC 3-8-1 Asano Kokurakita-ku Kitakyushu Fukuoka802-0001 Japan Graduate School of Media and Governance Keio University 5322 Endo Fujisawa-shi Kanagawa252-0882 Japan Medical Research Laboratory Institute of Integrated Research Institute of Science Tokyo 1-5-45 Yushima Bunkyo-ku Tokyo113-8519 Japan Center for Artificial Intelligence Research University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan

The automation of experiments in life sciences and chemistry has significantly advanced with the development of various instruments and AI technologies. However, achieving full laboratory automation, where experiments conceived by scientists are seamlessly executed in automated laboratories, remains a challenge. We identify the lack of automation in planning and operational tasks—critical human-managed processes collectively termed "care"—as a major barrier. Automating care is the key enabler for full laboratory automation. To address this, we propose the concept of self-maintainability (SeM): the ability of a laboratory system to autonomously adapt to internal and external disturbances, maintaining operational readiness akin to living cells. A SeM-enabled laboratory features autonomous recognition of its state, dynamic resource and information management, and adaptive responses to unexpected conditions. This shifts the planning and execution of experimental workflows, including scheduling and reagent allocation, from humans to the system. We present a conceptual framework for implementing SeM-enabled laboratories, comprising three modules—Requirement manager, Labware manager, and Device manager—and a Central manager. SeM not only enables scientists to execute envisioned experiments seamlessly but also provides developers with a design concept that drives the technological innovations needed for full automation. Copyright © 2025, The Authors. All rights reserved.

关键词： Information management

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A Kinetic Description of Cytosolic K + Binding to the Human Sertotonin Transporter Under Turnover Conditions

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Biophysical Journal 2020年第3期118卷 443a-443a页

作者： Zhiyu Zhao Emad Tajkhorshid Department of Biochemistry Center for Biophysics and Quantitative Biology University of Illinois Urbana IL USA NIH Center for Macromolecular Modeling and Bioinformatics Beckman Institute University of Illinois Urbana IL USA

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MRPC: An R package for accurate inference of causal graphs

arXiv

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arXiv 2018年

作者： Badsha, M. Bahadur Martin, Evan A. Fu, Audrey Qiuyan Department of Statistical Science Institute of Bioinformatics and Evolutionary Studies Center for Modeling Complex Interactions University of Idaho

We present MRPC, an R package that learns causal graphs with improved accuracy over existing packages, such as pcalg and bnlearn. Our algorithm builds on the powerful PC algorithm, the canonical algorithm in computer science for learning directed acyclic graphs. The improvement in accuracy results from online control of the false discovery rate (FDR) that reduces false positive edges, a more accurate approach to identifying v-structures (i.e., T1 → T2 ← T3), and robust estimation of the correlation matrix among nodes. For genomic data that contain genotypes and gene expression for each sample, MRPC incorporates the principle of Mendelian randomization to orient the edges. Our package can be applied to continuous and discrete data. Copyright © 2018, The Authors. All rights reserved.

关键词： Directed graphs

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Channelrhodopsin-mediated optogenetics highlights a central role of depolarization-dependent plant proton pumps (vol 117, pg 20920, 2020)

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2020年第38期117卷 24004-24004页

作者： Reyer, Antonella Haessler, Melanie Scherzer, Soenke Huang, Shouguang Pedersen, Jesper Torbol Al-Rasheid, Khaled A. S. Bamberg, Ernst Palmgren, Michael Dreyer, Ingo Nagel, Georg Hedrich, Rainer Becker, Dirk Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Department of Plant and Environmental Sciences University of Copenhagen DK-1871 Frederiksberg C Denmark Zoology Department College of Science King Saud University 11451 Riyadh Saudi Arabia Department of Biophysical Chemistry Max Planck Institute of Biophysics D-60438 Frankfurt am Main Germany Department of Plant and Environmental Sciences University of Copenhagen DK-1871 Frederiksberg C Denmark Center of Bioinformatics Simulation and Modeling Faculty of Engineering Universidad de Talca 3460000 Talca Chile Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany Institute for Molecular Plant Physiology and Biophysics University of Würzburg D-97082 Würzburg Germany

In plants, environmental stressors trigger plasma membrane depolarizations. Being electrically interconnected via plasmodesmata, proper functional dissection of electrical signaling by electrophysiology is basically impossible. The green alga Chlamydomonas reinhardtii evolved blue light-excited channelrhodopsins (ChR1, 2) to navigate. When expressed in excitable nerve and muscle cells, ChRs can be used to control the membrane potential via illumination. In Arabidopsis plants, we used the algal ChR2-light switches as tools to stimulate plasmodesmata-interconnected photosynthetic cell networks by blue light and monitor the subsequent plasma membrane electrical responses. Blue-dependent stimulations of ChR2 expressing mesophyll cells, resting around −160 to −180 mV, reproducibly depolarized the membrane potential by 95 mV on average. Following excitation, mesophyll cells recovered their prestimulus potential not without transiently passing a hyperpolarization state. By combining optogenetics with voltage-sensing microelectrodes, we demonstrate that plant plasma membrane AHA-type H+-ATPase governs the gross repolarization process. AHA2 protein biochemistry and functional expression analysis in Xenopus oocytes indicates that the capacity of this H+ pump to recharge the membrane potential is rooted in its voltage- and pH-dependent functional anatomy. Thus, ChR2 optogenetics appears well suited to noninvasively expose plant cells to signal specific depolarization signatures. From the responses we learn about the molecular processes, plants employ to channel stress-associated membrane excitations into physiological responses.

关键词： Arabidopsis optogenetics electrical signaling PM H+-ATPase

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Front Cover: Origin of the Isomer Stability of Polymethylated DOTA Chelates Complexed with Ln3+Ions (Eur. J. Inorg. Chem. 15/2021)

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European Journal of Inorganic Chemistry 2021年第15期2021卷

作者： Dr. Yong-Sok Lee Dr. Zhongyu Mou Dr. Ana Christina L. Opina Dr. Olga Vasalatiy Center for Molecular Modeling Office of Intramural Research Center for Information Technology National Institutes of Health Bethesda MD 20892 USA Present address: Bioinformatics and Computational Bioscience Branch National Institute of Allergy and Infectious Diseases National Institutes of Health Bethesda MD 20892 USA Present address: Intramural Research Program National Library of Medicine National Institutes of Health Bethesda MD 20892 USA Chemistry and Synthesis Center National Heart Lung and Blood Institute National Institutes of Health Rockville MD 20850 USA

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A retinoic acid:YAP1 signaling axis controls atrial lineage commitment

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Cell Reports 2025年第5期44卷 115687页

作者： Abraham, Elizabeth Kostina, Aleksandra Volmert, Brett Roule, Thomas Huang, Ling Yu, Jingting Williams, April E. Megill, Emily Douglas, Aidan Pericak, Olivia M. Morris, Alex Stronati, Eleonora Larrinaga-Zamanillo, Arantza Fueyo, Raquel Zubillaga, Mikel Andrake, Mark D. Akizu, Naiara Aguirre, Aitor Estaras, Conchi Department of Cardiovascular Sciences Aging + Cardiovascular Discovery Center Lewis Katz School of Medicine Temple University Philadelphia 19140 PA United States Institute for Quantitative Health Science and Engineering Division of Developmental and Stem Cell Biology Michigan State University East Lansing 48824 MI United States Department of Biomedical Engineering College of Engineering Michigan State University East Lansing 48824 MI United States Raymond G. Perelman Center for Cellular and Molecular Therapeutics The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Integrative Genomics and Bioinformatics Core Salk Institute for Biological Studies La Jolla 92037 CA United States Department of Child and Adolescence Psychiatry The Children's Hospital of Philadelphia Philadelphia 19104 PA United States Department of Chemical and Systems Biology Stanford University School of Medicine Stanford 94305 CA United States Cancer Epigenetics Institute Fox Chase Cancer Center Philadelphia 19111 PA United States Molecular Modeling Facility Program in Cancer Signaling and Microenvironment Fox Chase Cancer Center Philadelphia 19111 PA United States

In cardiac progenitor cells (CPCs), retinoic acid (RA) signaling induces atrial lineage gene expression and acquisition of an atrial cell fate. To achieve this, RA coordinates a complex regulatory network of downstream effectors that is not fully identified. To address this gap, we applied a functional genomics approach (i.e., scRNA-seq and snATAC-seq) to untreated and RA-treated human embryonic stem cell (hESC)-derived CPCs. Unbiased analysis revealed that the Hippo effectors YAP1 and TEAD4 are integrated with the atrial transcription factor enhancer network and that YAP1 activates RA enhancers in CPCs. Furthermore, Yap1 deletion in mouse embryos compromises the expression of RA-induced genes, such as Nr2f2, in the CPCs of the second heart field. Accordingly, in hESC-derived patterned heart organoids, YAP1 regulates the formation of an atrial chamber but is dispensable for the formation of a ventricle. Overall, our findings revealed that YAP1 cooperates with RA signaling to induce atrial lineages during cardiogenesis. © 2025 The Author(s)

关键词： atrial differentiation cardiac enhancers cardiac progenitors chamber development CP: Developmental biology heart organoids NR2F2 retinoic acid signaling SHF TEAD4 YAP1

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Generalized net model of surface emg data processing for control of active elbow orthosis device

Generalized net model of surface emg data processing for con...

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Advances in Neural Networks and Applications 2018, ANNA 2018

作者： Ribagin, Simeon Pencheva, Tania Shannon, Anthony Department of Bioinformatics and Mathematical Modelling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Sofia Bulgaria Department of Health and Social Care Medical College University "Prof. D-r Asen Zlatarov" Burgas Bulgaria Department of QSAR and Molecular Modeling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Sofia Bulgaria Warrane College University of New South Wales KensingtonNSW2033 Australia

ISBN: (纸本)9783800747566

Surface Electromyography (sEMG) signals have been increasingly used in many applications, including biomedical, neuroprosthetic limbs, orthotic or rehabilitation devices, human machine interactions etc. In order to use such signals for the control purposes, a certain processing algorithm has to be performed. This paper presents a novel approach for sEMG data processing with the usage of generalized nets theory. We propose an abstract model representing the sEMG data processing, which can be used in the control frameworks of active elbow orthosis devices. © 2018 VDE VERLAG GMBH Berlin Offenbach

关键词： Data handling

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Generalized Net Model of Surface EMG Data Processing for Control of Active Elbow Orthosis Device

Generalized Net Model of Surface EMG Data Processing for Con...

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ANNA '18;Advances in Neural Networks and Applications 2018

作者： Simeon Ribagin Tania Pencheva Anthony Shannon Department of Bioinformatics and Mathematical Modelling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Department of QSAR and Molecular Modeling Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Warrane College The University of New South Wales

ISBN: (纸本)9783800747566

关键词： Standing Orders SEMA5B gene Surface Electromyography Automatic data processing data processing Orthotic Devices network model Elbow signals

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Precision Medicine in Morocco: State of art and challenges for implementation

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Journal of cancer policy 2025年 45卷 100598页

作者： Meriem Khyatti Fouzia Radouani Ichrak Benamri Amina Gihbid Hicham Charoute Adil El Hamouchi Imane Chaoui Abdellatif Benider Nadia Benchakroun Hicham El Attar Khaoula Errafii Tariq Daouda Mohammed El Mzibri Abdelhamid Barakat Laboratory of Viral Oncology and cellular therapy Institut Pasteur du Maroc Casablanca. Electronic address: meriem.khyatti@pasteur.ma. Chlamydiae and Mycoplasmas Laboratory Institut Pasteur du Maroc Casablanca Morocco. Laboratory of Information Technology and Modeling Faculty of Sciences Ben M'sik Hassan II University Casablanca Morocco. Higher Institute of Nursing Professions and Health Techniques Ministry of Health and Social Protection Casablanca-Settat Morocco. Research Unit of Epidemiology Biostatistics and Bioinformatics Institut Pasteur du Maroc Casablanca Morocco. Laboratory of Genomics and Human Genetics Institut Pasteur du Maroc Casablanca Morocco. Biology and Medical Research Unit National Center of Energy Sciences and Nuclear Techniques Rabat Morocco. Moroccan Association of Cancer Registries Casablanca Morocco. Mohamed VI Center for Cancer Treatment Ibn Rochd University Hospital Casablanca Morocco. Faculty of Medical Sciences Mohammed VI Polytechnic University Benguerir Morocco. African Genome Centre Mohammed VI Polytechnic University Benguerir Morocco. Artificial Intelligence and Biomedical Informatics Laboratory Faculty of Medical Sciences Mohammed VI Polytechnic University Benguerir Morocco.

Precision Medicine (PM) is an innovative approach that takes into account individuals' genetic differences, environments, and lifestyles to provide personalised patient care. Policy development for PM implementation requires assessing a wide range of issues extending from knowledge and skills in terms of OMICs, specimen collection and management, as well as data analyses and sharing to whether and how to utilise advanced technologies for diagnosis, clinical practice and diverse public health initiatives. For this purpose, within the "Personalized Medicine in North Africa" (PerMediNA) project, we conducted a survey among Moroccan scientists, physicians, and stakeholders with an interest in genomics and PM. The survey aimed to evaluate their knowledge and understanding of the field, the institutional environment and infrastructure availability, the state and awareness of the field in their contexts, information dissemination to potential users, training programs, and capacity building for specialised personnel, as well as engaging political stakeholders and policymakers. As a summary, based on various stakeholders' feedback, in addition to our effort in exploring the challenges faced when putting in place genomic medicine programs, we were enabled to formulate feasible recommendations that may be applicable to start the process of implementing and strengthening PM in the Moroccan context.

关键词： Mapping Morocco Oncology Precision Medicine Readiness level

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