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Enriched Peripheral Blood-Derived Mononuclear Cells for Treating Knee Osteoarthritis

Cell transplantation 2023年 32卷

作者： Chang-Han Chuang Chi-Chung Kuo Yueh-Feng Chiang Pei-Yuan Lee Fu-Hui Wang Chia-Ying Hsieh Ching-I Shen Yu-Hsuan Chung Kuan-Der Lee Shih-Fang Wu Hong-Lin Su Chih-Lung Lin Department of Orthopedics Show Chwan Memorial Hospital Changhua Taiwan. PhD Program in Translational Medicine National Chung Hsing University Taichung Taiwan. Rong Hsing Research Center for Translational Medicine National Chung Hsing University Taichung Taiwan. Department of Neurology Taichung Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Taichung Taiwan. School of Post-Baccalaureate Chinese Medicine Tzu Chi University Hualien Taiwan. Department of Orthopedics Taichung Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Taichung. DuoGenic StemCells Corporation Taichung Taiwan. Department of Medical Research and Cell Therapy and Regenerative Medicine Center Taichung Veterans General Hospital Taichung Taiwan. Department of Medicine and Center for Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei City Taiwan. The Joint Program of Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan. National Health Research Institutes Taichung Taiwan. Department of Life Sciences National Chung Hsing University Taichung Taiwan. Department of Neurosurgery Asia University Hospital Taichung Taiwan. Department of Occupational Therapy Asia University Taichung Taiwan.

Osteoarthritis (OA) is a common chronic skeletal disease in the elderly. There is no effective therapy to reverse disease severity and knee OA (KOA) progression, particularly at the late stage. This study aims to examine the effect of peripheral blood-derived mononuclear cells (PBMNCs) on pain and motor function rescue in patients with Kellgren-Lawrence (KL) grade II to IV KOA. Participants received one intra-articular (IA) injection of autologous PBMNCs. The mononuclear cells were isolated from peripheral blood, enriched by a specialized medium (MoFi medium), and separated by Ficoll-Paque solution. The isolated and enriched PBMNCs could differentiate into M1 and M2 macrophages . The anti-inflammatory effect of the PBMNCs was similar to that of bone marrow mesenchymal stem cells, evaluated by complete Freund's adjuvant-induced arthritis in rodents. A single-arm and open-label pilot study showed that patients' knee pain and motor dysfunction were significantly attenuated after the cell transplantation, assessed by visual analogue scale (VAS) and Knee injury and Osteoarthritis Outcome Score (KOOS) at 6 and 12 months post-treatment. Notably, the therapeutic effect of the PBMNCs treatment can be stably maintained for 24 months, as revealed by the KOOS scores. These preclinical and pilot clinical data suggest that IA injection of MoFi-PBMNCs might serve as a novel medical technology to control the pain and the progress of KOA.

关键词： macrophages monocytes osteoarthritis peripheral blood mononuclear cells

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Correction: Visible-light photooxidation in water by 1O2-generating supramolecular hydrogels

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Chemical science 2020年第22期11卷 5836页

作者： Sankarsan Biswas Mohit Kumar Andrew M Levine Ian Jimenez Rein V Ulijn Adam B Braunschweig Advanced Science Research Center Graduate Center City University of New York 85 St. Nicholas Terrace New York NY 10031 USA abraunschweig@gc.cuny.edu. Department of Chemistry Hunter College 695 Park Avenue New York NY 10065 USA. PhD Program in Chemistry Graduate Center City University of New York New York NY 10016 USA. The High School for Math Science and Engineering The City College of New York 240 Convent Avenue New York NY 10031 USA. PhD Program in Biochemistry Graduate Center City University of New York New York NY 10016 USA.

[This corrects the article DOI: 10.1039/C9SC06481H.].

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P.639 The individual's personal experience of the living environment affects serotoninergic antidepressant treatment outcome

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European Neuropsychopharmacology 2020年 40卷 S360-S361页

作者： Albanese, N. Ciano Poggini, S. Reccagni, A. D'Andrea, I. Branchi, I. Istituto Superiore di Sanità Center for Behavioral Sciences and Mental Health Rome Italy Sapienza University of Rome PhD program in Behavioral Neuroscience Rome Italy Sorbonne Université- Sciences and Engineering Faculty- Institut du Fer à Moulin Institut national de la santé et de la recherche médicale INSERM UMR-S 1270 Paris France

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Environmental assessment of a large-scale production of TiO2 nanoparticles via green chemistry

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Chemical engineering Transactions 2018年 70卷 1063-1068页

作者： Meramo, Samir I. Bonfante, Heidy De Avila-Montiel, Gesira Herrera-Barros, Adriana Gonzalez-Delgado, Angel Chemical Engineering Department Faculty of Engineering University of Cartagena Av. del Consulado Calle 30 No. 48-152 Cartagena Colombia Chemical Engineering Department University of Cartagena Av. del Consulado Calle 30 No. 48-152 Cartagena Colombia Engineering PhD. Program University of Cartagena Av. del Consulado Calle 30 No. 48-152 Cartagena Colombia

Green chemistry concept is currently implemented in order to stimulate the development of sustainability processes and pollution prevention. However, not for all cases the use of this type of process generates an operation with good environmental performance, also in the development and evaluation of new topologies, such as the one presented in this paper, environmental assessment becomes in an important tool in order to optimize the process. In this work for developed a synthesis of titanium dioxide (TiO2) nanoparticles from titanium isopropoxide (TTIP) via green chemistry. Environmental assessment was performed using software WAR GUI, which use Waste Reduction Algorithm in order to quantify potential environmental impacts generation and output environmental impacts for this process for 4 different cases. Results show that the process doesn't generate high potential environmental impacts (PEI) with a rate of 1.43X102 PEI/h for the case that include energy and product contributions, which represents a very low value compared to the total output rate for this case (1.21X104 PEI/h). For toxicological categories, it was obtained that for human toxicity by ingestion (HTPI) and terrestrial toxicity potential (TTP) categories exist some environmental impacts due to presence of TTIP in a high concentration, additionally these effects are increased by propanol, as a subproduct of the hydrolysis, and ethanol as solvent for the purification stage. For the aquatic matrix the potential impacts obtained was relatively low. On the other hand, it was determined for atmospheric effects that the presence of the alcohols in the process rises the potential impact related to the photochemical oxidation potential category. Copyright © 2018, AIDIC Servizi S.r.l.

关键词： Environmental impact

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Unravelling the linkages between conflict and antimicrobial resistance

npj antimicrobials and resistance

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npj antimicrobials and resistance 2025年第1期3卷 29页

作者： Aula Abbara Clare Shortall Richard Sullivan Wim Zwijnenburg Krystel Moussally Reem Aboshamr Carine Naim Angela Uyen Muhammad H Zaman Nabil Karah Ahmad Kejah Marwan Osman Antoine Abou Fayad Omar Dewachi Department of Infection Imperial College London UK. a.abbara15@ic.ac.uk. Médecins Sans Frontières Operational Centre Amsterdam Manson Unit London UK. a.abbara15@ic.ac.uk. Médecins Sans Frontières Operational Centre Amsterdam Manson Unit London UK. Centre for Conflict and Health Research King's College London London UK. PAX Utrecht Netherlands. Médecins Sans Frontières Operational Centre Brussels Middle-East Medical Unit Beirut Lebanon. Joint PhD Program on Water Technology Islamic University of Gaza Gaza Palestine. Médecins Sans Frontières Operational Centre Brussels Analysis Department Brussels Belgium. Department of Biomedical Engineering and Center on Forced Displacement Boston University Boston MA USA. Department of Molecular Biology Umeå University Umeå Sweden. Department of Microbiology Free Aleppo University Aleppo Syria. Department of Neurosurgery Yale University School of Medicine New Haven CT USA. Department of Experimental Pathology Immunology & Microbiology American University of Beirut Beirut Lebanon. Anthropology Department Rutgers The State University of New Jersey New Brunswick NJ USA.

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Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics (vol 9, 12588, 2019)

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SCIENTIFIC REPORTS 2019年第1期9卷 12588-12588页

作者： Bermant, Peter C. Bronstein, Michael M. Wood, Robert J. Gero, Shane Gruber, David F. Radcliffe Institute for Advanced Study Harvard University Cambridge MA USA Department of Computing Imperial College London UK Twitter 20 Air Street London W1B 5DL United Kingdom Wyss Institute for Biologically Inspired Engineering Harvard University Cambridge MA USA Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA Department of Zoophysiology Institute for Bioscience Aarhus University C.F. Møllers Allé 3 8000 Aarhus Denmark Department of Natural Sciences Baruch College and The Graduate Center PhD Program in Biology City University of New York New York NY USA

We implemented Machine Learning (ML) techniques to advance the study of sperm whale (Physeter macrocephalus) bioacoustics. This entailed employing Convolutional Neural Networks (CNNs) to construct an echolocation click detector designed to classify spectrograms generated from sperm whale acoustic data according to the presence or absence of a click. The click detector achieved 99.5% accuracy in classifying 650 spectrograms. The successful application of CNNs to clicks reveals the potential of future studies to train CNN-based architectures to extract finer-scale details from cetacean spectrograms. Long short-term memory and gated recurrent unit recurrent neural networks were trained to perform classification tasks, including (1) 'coda type classification' where we obtained 97.5% accuracy in categorizing 23 coda types from a Dominica dataset containing 8,719 codas and 93.6% accuracy in categorizing 43 coda types from an Eastern Tropical Pacific (ETP) dataset with 16,995 codas; (2) 'vocal clan classification' where we obtained 95.3% accuracy for two clan classes from Dominica and 93.1% for four ETP clan types; and (3) 'individual whale identification' where we obtained 99.4% accuracy using two Dominica sperm whales. These results demonstrate the feasibility of applying ML to sperm whale bioacoustics and establish the validity of constructing neural networks to learn meaningful representations of whale vocalizations. [ABSTRACT FROM AUTHOR]

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Machine learning for early prediction of circulatory failure in the intensive care unit

arXiv

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arXiv 2019年

作者： Hyland, Stephanie L. Faltys, Martin Hüser, Matthias Lyu, Xinrui Gumbsch, Thomas Esteban, Cristóbal Bock, Christian Horn, Max Moor, Michael Rieck, Bastian Zimmermann, Marc Bodenham, Dean Borgwardt, Karsten Rätsch, Gunnar Merz, Tobias M. Department of Computer Science ETH Zürich Zürich Switzerland Computational Biology Program Memorial Sloan Kettering Cancer Center New York United States Tri-Institutional PhD Program in Computational Biology and Medicine Weill Cornell Medicine New York United States Medical Informatics Group Zürich University Hospital Zürich Switzerland Department of Intensive Care Medicine University Hospital University of Bern Bern Switzerland Department of Biosystems and Engineering ETH Zürich Basel Switzerland Department of Biology ETH Zürich Zürich Switzerland Swiss Institute for Bioinformatics Lausanne Switzerland Cardiovascular Intensive Care Unit Auckland City Hospital Auckland New Zealand

Intensive care clinicians are presented with large quantities of patient information and measurements from a multitude of monitoring systems. The limited ability of humans to process such complex information hinders physicians to readily recognize and act on early signs of patient deterioration. We used machine learning to develop an early warning system for circulatory failure based on a high-resolution ICU database with 240 patient-years of data. This automatic system predicts 90.0% of circulatory failure events (prevalence 3.1%), with 81.8% identified more than two hours in advance, resulting in an area under the receiver operating characteristic curve of 94.0% and area under the precision recall curve of 63.0%. The model was externally validated in a large independent patient cohort. Copyright © 2019, The Authors. All rights reserved.

关键词： Intensive care units

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Gaussian and exponential lateral connectivity on distributed spiking neural network simulation

arXiv

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arXiv 2018年

作者： Pastorelli, Elena Paolucci, Pier Stanislao Simula, Francesco Biagioni, Andrea Capuani, Fabrizio Cretaro, Paolo De Bonis, Giulia Lo Cicero, Francesca Lonardo, Alessandro Martinelli, Michele Pontisso, Luca Vicini, Piero Ammendola, Roberto INFN Sezione di Roma PhD Program in Behavioural Neuroscience Sapienza University of Rome Rome Italy INFN Sezione di Roma Rome Italy INFN Sezione di Tor Vergata Electronic Engineering Dept. University of Roma Tor Vergata Rome Italy

We measured the impact of long-range exponentially decaying intra-areal lateral connectivity on the scaling and memory occupation of a distributed spiking neural network simulator compared to that of short-range Gaussian decays. While previous studies adopted short-range connectivity, recent experimental neurosciences studies are pointing out the role of longer-range intra-areal connectivity with implications on neural simulation platforms. Two-dimensional grids of cortical columns composed by up to 11 M point-like spiking neurons with spike frequency adaption were connected by up to 30 G synapses using short- and long-range connectivity models. The MPI processes composing the distributed simulator were run on up to 1024 hardware cores, hosted on a 64 nodes server platform. The hardware platform was a cluster of IBM NX360 M5 16-core compute nodes, each one containing two Intel Xeon Haswell 8-core E5-2630 v3 processors, with a clock of 2.40 G Hz, interconnected through an InfiniBand network, equipped with 4× QDR switches. Copyright © 2018, The Authors. All rights reserved.

关键词： Neural networks

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Real-time cortical simulations: Energy and interconnect scaling on distributed systems

arXiv

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arXiv 2018年

作者： Simula, Francesco Pastorelli, Elena Paolucci, Pier Stanislao Martinelli, Michele Lonardo, Alessandro Biagioni, Andrea Capone, Cristiano Capuani, Fabrizio Cretaro, Paolo de Bonis, Giulia Cicero, Francesca Lo Pontisso, Luca Vicini, Piero Ammendola, Roberto INFN Sezione di Roma Rome Italy INFN Sezione di Roma and PhD Program in Behavioural Neuroscience "Sapienza" University of Rome Rome Italy INFN Sezione di Tor Vergata and Electronic Engineering Dept. University of Roma "Tor Vergata" Rome Italy

We profile the impact of computation and inter-processor communication on the energy consumption and on the scaling of cortical simulations approaching the real-time regime on distributed computing platforms. Also, the speed and energy consumption of processor architectures typical of standard HPC and embedded platforms are compared. We demonstrate the importance of the design of low-latency interconnect for speed and energy consumption. The cost of cortical simulations is quantified using the Joule per synaptic event metric on both architectures. Reaching efficient real-time on large scale cortical simulations is of increasing relevance for both future bio-inspired artificial intelligence applications and for understanding the cognitive functions of the brain, a scientific quest that will require to embed large scale simulations into highly complex virtual or real worlds. This work stands at the crossroads between the WaveScalES experiment in the Human Brain Project (HBP), which includes the objective of large scale thalamo-cortical simulations of brain states and their transitions, and the ExaNeSt and EuroExa projects, that investigate the design of an ARM-based, low-power High Performance Computing (HPC) architecture with a dedicated interconnect scalable to million of cores;simulation of deep sleep Slow Wave Activity (SWA) and Asynchronous aWake (AW) regimes expressed by thalamo-cortical models are among their benchmarks. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy utilization

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Computer aided environmental analysis of a large-scale production of chitosan micro-beads modified with thiourea and magnetite

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IOP Conference Series: Materials Science and engineering 2019年第1期519卷

作者： F Bertel G Cogollo S Meramo-Hurtado A González-Delgado Nanomaterials and Computer Aided Process Engineering Research Group (NIPAC) Chemical Engineering Department Faculty of Engineering University of Cartagena Av. Del Consulado Calle 30 No. 48-152 Cartagena Colombia. Engineering PhD. Program University of Cartagena Av. Del Consulado Calle 30 No. 48-152 Cartagena Colombia.

In this work, environmental assessment of a large-scale production of chitosan micro-beads modified with thiourea and magnetite was performed using Waste Reduction Algorithm (WAR). This methodology evaluates eight impact categories, four toxicological and four atmospherics. Initially, the simulation of production process of micro-beads was realized. Then, WAR GUI software, which is based on WAR algorithm, was employed to quantify potential environmental impacts (PEI) generation and output rate for this process under 4 different cases. The synthesis of micro-beads was analysed using computer-aided process engineering, this is related to the fact that there is no bibliography reported for the industrial scale-up, simulation and environmental evaluation of this type of process Results shows that photochemical oxidation potential is the evaluated category which emits the biggest output rate of PEI, contributing in all cases with more than 49% of the total rate. In general terms, the process has a negative generated PEI which means that the process has a convenient environmental performance. This leads to the conclusion that the process is environmentally beneficial because it consumes environmental impacts.

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