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This study aimed to assess changes in fasting blood sugar (FBS) levels, time to diabetic retinopathy (DR) and its predictors among type 2 diabetes patients in Ethiopia. An institution-based retrospective follow-up study was conducted at the University of Gondar Comprehensive Specialized Hospital. The linear mixed effect model and Cox proportional hazard models were fitted separately, and later, the two models were fitted jointly using R software. Variables with a p value 1 antidiabetic oral agent (AHR = 4.90; 95% CI 1.07–20.0) and more than 10 years duration (AHR = 0.17, 95% CI 0.06–0.46) were predictors of time to DR. This study revealed that the current value of FBS and the rate of FBS change were significantly associated with the time to DR.

Made available in DSpace on 2022-04-29T08:35:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-12-01 Division of Intramural Research, National Institute of Allergy and Infectious Diseases Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases National Institute of Allergy and Infectious Diseases National Center for Advancing Translational Sciences National Heart, Lung, and Blood Institute National Institute of Environmental Health Sciences U.S. National Library of Medicine National Institute of Neurological Disorders and Stroke Division of Cancer Prevention, National Cancer Institute Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Department of Biomedical Informatics Harvard Medical School Department of Neurology University of Pittsburgh, Biomedical Science Tower 3, Suite 7014, 3501 5th Avenue Department of Pediatrics Wake Forest School of Medicine Department of Critical Care National University Health Systems Department of Preventive Medicine Northwestern University Department of Biomedical Informatics University of Pittsburgh Department of Surgery National University Health Systems Department of Internal Medicine University of Kansas Medical Center Data Analytics Center University of Pennsylvania Health System Department of Computational Medicine and Bioinformatics University of Michigan Department of Biomedical Informatics University of Kentucky Department of Legal Economic and Social Sciences University Magna Graecia of Catanzaro Health Catalyst INC. Department of Surgery ASST Pavia Lombardia Region Health System Clinical Research Unit of Botucatu Medical School São Paulo State University Pediatric Emergency Department Hôpital Necker-Enfants Malades Assistance Publique-Hôpitaux de Paris National Center for Infectious Diseases Tan Tock Seng Hospital Departments of Biomedical Informatics Pediatrics Cincinnati Children’s Hospital Medical Center University of Cincinnati Department of Pediatrics Medical University of South Carolina Department of Surgery St. Luke’s University Health Network Department of Medicine David Geffen School of Medicine at UCLA UOC Ricerca Innovazione e Brand Reputation ASST Papa Giovanni XXIII Department of Electrical Computer and Biomedical Engineering University of Pavia IT Department Innovation & Data APHP Greater Paris University Hospital I.T. Department ASST Pavia Health Informatics Hospital Universitario, 12 de Octubre Strategy and Transformation Department APHP Greater Paris University Hospital Faculty of Medicine and Medical Center University of Freiburg Digital Research Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children Scientific Direction IRCCS Ca’ Granda Ospedale Maggiore Policlinico di Milano North Carolina Translational and Clinical Sciences (NC TraCS) Institute University of North Carolina BIOMERIS (BIOMedical Research Informatics Solutions) Department of Biomedical Informatics HEGP APHP Greater Paris University Hospital Department of Medical and Surgical Sciences Data Analytics Research Center University Magna Graecia of Catanzaro Department of Anesthesia St. Luke’s University Health Network Université Paris-Saclay Inria CEA INRIA Sophia-Antipolis–ZENITH Team LIRMM Computational Health Informatics Program Boston Children’s Hospital Department of Internal Medicine University of Kentucky Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Department of Internal Medicine and Therapeutics University of Pavia Informatics Institute University of Alabama at Birmingham IAM Unit Bordeaux University Hospital/ERIAS-Inserm U1219 BPH Biomedical Informatics Center Medical University of South Carolina Clinical Research Informatics Boston Children’s Hospital Department of Biomedical and Health Informatics Children’s Hospital of Philadelphia SED/SIERRA Inria Centre de Paris Health Information Technology & Services University of Michigan Internal Medicine Department Botucatu Medical School São Paulo State University Heinrich-Lanz-Center for Digital Health University Medicine Mannheim Heidelberg University Department of Anesthesiology Critical Care and Pain Medicine Boston Children’s Hospital Department of Learning Health Sciences University of Michigan Medical School MSHI Medical University of South Carolina Department of Medicine Massachusetts General Hospital Division of Human Genetics Department of Pediatrics The Children’s Hospital of Philadelphia Center for Medical Information and Communication Technology University Hospital Renaissance Computing Institute/Department of Computer Science University of North Carolina Clinical Research Unit Saint Antoine Hospital APHP Greater Paris University Hospital Clevy.io Department of Biostatistics Harvard T.H. Chan School of Public Health VA Informatics and Computing Infrastructure VA Salt Lake City Health Care System MICHR Informatics University of Michigan Laboratory of Informatics and Systems Engineering for Clinical Research Istituti Clinici Scientifici Maugeri SpA SB IRCCS Harvard Catalyst Harvard Medical School Clinical Research Unit Paris Saclay APHP Greater Paris University Hospital Department of Anesthesiology and Critical Care Children’s Hospital of Philadelphia VA Informatics and Computing Infrastructure Tennessee Valley Healthcare System Veterans Affairs Medical Center École Normale Supérieure PSL Université Paris BIG-ARC The University of Texas Health Science Center at Houston School of Biomedical Informatics Pediatric Infectious Disease Department Hospital Universitario, 12 de Octubre Department of Infectious Diseases Great Ormond Street Hospital for Children Department of Neurology Massachusetts General Hospital Internal Medicine Department of Botucatu Medical School São Paulo State University Department of Pediatrics Boston Children’s Hospital Center for Biomedical Informatics Wake Forest School of Medicine Department of Medical Informatics University of Erlangen-Nürnberg Department of Veterans Affairs Office of Research and Development Biomedical Data Science Lab ITACA Institute Universitat Politècnica de València Nurse Department of FMB-Medicine School of Botucatu Management Engineering ASST Pavia Lombardia Region Health System Department of Anesthesiology University Hospital Erlangen FAU Erlangen-Nürnberg Critical Care Medicine Department of Medicine St. Luke’s University Health Network Department of Medicine National University Hospital Department of Information Management Chang Gung University Clinical & Translational Science Institute Medical College of Wisconsin Montréal Neurological Institute McGill University SequeL Inria Lille Respiratory Department ICS S Maugeri IRCCS Department of Health Management and Informatics University of Missouri Department of Oncology ASST Papa Giovanni XXIII Clinical Research Unit of Botucatu Medical School São Paulo State University Internal Medicine Department Botucatu Medical School São Paulo State University Internal Medicine Department of Botucatu Medical School São Paulo State University Division of Intramural Research, National Institute of Allergy and Infectious Diseases: AI11679 Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases: AI11679 National Institute of Allergy and Infectious Diseases: AI11679 National Center for Advancing Translational Sciences: CTSA Award #UL1TR001878 National Center for Advancing Translational Sciences: CTSA Award #UL1TR002366 National Heart, Lung, and Blood Institute: K23HL148394 National Institute of Environmental Health Sciences: P30ES017885 U.S. National Library of Medicine: R01LM012095 National Institute of Neurological Disorders and Stroke: R01NS098023 Division of Cancer Prevention, National Cancer Institute: U24CA210967 National Center for Advancing Translational Sciences: UL1TR001420 National Center for Advancing Translational Sciences: UL1TR001857

Correction to: Scientific Reports https://doi.org/10.1038/s41598-019-46283-9, published online 09 July 2019 The original version of this Article contained an error. The information in the “Dipstick development and assay” section was incomplete. Therefore, the original text, “The assay comprises of incubation of the dipstick with diluted serum samples (1:2000) for 30 min which is followed by washing with TBST (twice). Subsequently, it is incubated with HRP conjugated anti-human IgG (1: 2000) for 30 min. Finally, after two washes in TBST and one in TBS, the strips are dipped in a freshly prepared substrate composed of 0.05% 3, 3′-diaminobenzidine tetrahydrochloride (DAB, Sigma, USA) containing 0.05% of H2O2 in 100 mM TBS. The reaction is stopped by dipping in distilled water. The appearance of dark brown coloured bands at both the test and control line indicates VL positivity and a single band at the control line is indicative of VL negativity.” now reads: “The general assay consists of incubation of the dipsticks with diluted serum (1:2000) samples for 30 min, followed by washing with TBST (twice). Subsequently, it is incubated with HRP conjugated anti-human IgG (1:2000) for 30 min. Finally, after two washes in TBST and one in TBS, the strips are dipped in a freshly prepared substrate composed of 0.05% 3, 3′-diaminobenzidine tetrahydrochloride (DAB, Sigma, USA), containing 0.05% of H2O2 in 100 mM TBS. The reaction is stopped by dipping in distilled water, and the strips dried at RT. In Spain, there were several modifications to the assay; the dipsticks are incubated in diluted serum (1:100), and HRP conjugated anti-human IgG, for 60 min, followed by a 10 min incubation in substrate composed of 0.07% of DAB and 0.2% of H2O2 in 60 mM TBS, before being dried at RT. The appearance of dark brown coloured bands at both the test and control line indicates VL positivity and a single band at the control line is indicative of VL negativity. Whenever this signal was hard to assess, we classified it as not clear, and therefore grouped it together with those displaying no bands. Dipsticks that did not present with a reactive band, or a control band, were excluded from further consideration.” These changes do not affect the overall conclusions of the Article. This has now been corrected in the PDF and HTML versions of the Article.

Neuregulin protein 1 (NRG1) is a large (> 60–amino-acid) natural peptide ligand for the ErbB protein family members HER3 and HER4. We developed an agonistic antibody modality, termed antibody ligand mimetics (ALM), by incorporating complex ligand agonists such as NRG1 into an antibody scaffold. We optimized the linker and ligand length to achieve native ligand activity in HEK293 cells and cardiomyocytes derived from induced pluripotent stem cells (iPSCs) and used a monomeric Fc-ligand fusion platform to steer the ligand specificity toward HER4-dominant agonism. With the help of selectivity engineering, these enhanced ALM molecules can provide an antibody scaffold with increased receptor specificity and the potential to greatly improve the pharmacokinetics, stability, and downstream developability profiles from the natural ligand approach. This ligand mimetic design and optimization approach can be expanded to apply to other cardiovascular disease targets and emerging therapeutic areas, providing differentiated drug molecules with increased specificity and extended half-life.

More than 20 unique diseases such as diabetes, Alzheimer’s disease, Parkinson’s disease are caused by the abnormal aggregations of pathogenic proteins such as amylin, β-amyloid (Aβ), and α-synuclein. All pathogenic proteins differ from each other in biological function, primary sequences, and morphologies; however, the proteins are toxic when aggregated. Here, we investigated the cellular toxicity of pathogenic or non-pathogenic protein aggregates. In this study, six proteins were selected and they were incubated at acid pH and high temperature. The aggregation kinetic and cellular toxicity of protein species with time were characterized. Three non-pathogenic proteins, bovine serum albumin (BSA), catalase, and pepsin at pH 2 and 65 °C were stable in protein structure and non-toxic at a lower concentration of 1 mg/mL. They formed aggregates at a higher concentration of 20 mg/mL with time and they induced the toxicity in short incubation time points, 10 min and 20 min only and they became non-toxic after 30 min. Other three pathogenic proteins, lysozyme, superoxide dismutase (SOD), and insulin, also produced the aggregates with time and they caused cytotoxicity at both 1 mg/mL and 20 mg/mL after 10 min. TEM images and DSC analysis demonstrated that fibrils or aggregates at 1 mg/mL induced cellular toxicity due to low thermal stability. In DSC data, fibrils or aggregates of pathogenic proteins had low thermal transition compared to fresh samples. The results provide useful information to understand the aggregation and cellular toxicity of pathogenic and non-pathogenic proteins.

The Josephson effect, tunnelling of a supercurrent through a thin insulator layer between two superconducting islands, is a phenomena characterized by a spatially distributed phase of the superconducting condensate. In recent years, there has been a growing focus on Josephson junction devices particularly for the applications of quantum metrology and superconducting qubits. In this study, we report the development of Josephson junction circuit formed by serially connecting many Superconducting Quantum Interference Devices, SQUIDs. We present experimental measurements as well as numerical simulations of a phase-slip center, a SQUID with weaker junctions, embedded in a Josephson junction chain. The DC transport properties of the chain are the result of phase slips which we simulate using a classical model that includes linear external damping, terminating impedance, as well as internal nonlinear quasiparticle damping. We find good agreement between the simulated and the experimental current voltage characteristics. The simulations allow us to examine the spatial and temporal distribution of phase-slip events occurring across the chains and also the existence of travelling voltage pulses which reflect at the chain edges.

We numerically demonstrate acoustophoretic separation of spherical solid particles in air by means of an acoustic Fresnel lens. Beside gravitational and drag forces, freely-falling millimeter-size particles experience large acoustic radiation forces around the focus of the lens, where interplay of forces lead to differentiation of particle trajectories with respect to either size or material properties. Due to the strong acoustic field at the focus, radiation force can divert particles with source intensities significantly smaller than those required for acoustic levitation in a standing field. When the lens is designed to have a focal length of 100 mm at 25 kHz, finite-element method simulations reveal a sharp focus with a full-width at half-maximum of 0.5 wavelenghts and a field enhancement of 18 dB. Through numerical calculation of forces and simulation of particle trajectories, we demonstrate size-based separation of acrylic particles at a source sound pressure level of 153 dB such that particles with diameters larger than 0.5 mm are admitted into the central hole, whereas smaller particles are rejected. Besides, efficient separation of particles with similar acoustic properties such as polyethylene, polystyrene and acrylic particles of the same size is also demonstrated.

Acoustophoresis revolutionized the field of container-less manipulation of liquids and solids by enabling mixing procedures which avoid contamination and loss of reagents due to the contact with the support. While its applications to chemistry and engineering are straightforward, additional developments are needed to obtain reliable biological protocols in a contactless environment. Here, we provide a first, fundamental step towards biological reactions in air by demonstrating the acoustophoretic DNA transfection of mammalian cells. We developed an original acoustophoretic design capable of levitating, moving and mixing biological suspensions of living mammalians cells and of DNA plasmids. The precise and sequential delivery of the mixed solutions into tissue culture plates is actuated by a novel mechanism based on the controlled actuation of the acoustophoretic force. The viability of the contactless procedure is tested using a cellular model sensitive to small perturbation of neuronal differentiation pathways. Additionally, the efficiency of the transfection procedure is compared to standard, container-based methods for both single and double DNA transfection and for different cell types including adherent growing HeLa cancer cells, and low adhesion neuron-like PC12 cells. In all, this work provides a proof of principle which paves the way to the development of high-throughput acoustophoretic biological reactors., Scientific Reports, 6, ISSN:2045-2322