Performance enhancement of a GIS-based facility location problem using desktop grid infrastructure

This paper presents the integration of desktop grid infrastructure with GIS technologies, by proposing a parallel resolution method in a generic distributed environment. A case study focused on a discrete facility location problem, in the biomass area, exemplifies the high amount of computing resources (CPU, memory, HDD) required to solve the spatial problem. A comprehensive analysis is undertaken in order to analyse the behaviour of the grid-enabled GIS system. This analysis, consisting of a set of the experiments on the case study, concludes that the desktop grid infrastructure is able to use a commercial GIS system to solve the spatial problem achieving high speedup and computational resource utilization. Particularly, the results of the experiments showed an increase in speedup of fourteen times using sixteen computers and a computational efficiency greater than 87 % compared with the sequential procedure.This work has been developed under the support of the program Formacion de Personal Investigador, grants number BFPI/2009/103 and BES-2007-17019, from the Conselleria d'Educacio of the Generalitat Valenciana and the Spanish Ministry of Science and Technology.García García, A.; Perpiñá Castillo, C.; Alfonso Laguna, CD.; Hernández García, V. (2013). Performance enhancement of a GIS-based facility location problem using desktop grid infrastructure. Earth Science Informatics. 6(4):199-207. https://doi.org/10.1007/s12145-013-0119-1S19920764Anderson D (2004) Boinc: a system for public-resource computing and storage. Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, Washington DC, pp 4–10Available scripts webpage: http://personales.upv.es/angarg12/Campos I et al (2012) Modelling of a watershed: a distributed parallel application in a grid framework. Comput Informat 27(2):285–296Church RL (2002) Geographical information systems and location science. Comput Oper Res 29:541–562Clarke KC (1986) Advances in geographic information systems, computers. Environ Urban Syst 10:175–184Dowers S, Gittings BM, Mineter MJ (2000) Towards a framework for high-performance geocomputation: handling vector-topology within a distributed service environment. Comput Environ Urban Syst 24:471–486Geograma SL (2009). Teleatlas. http://www.geograma.com . Accessed September 2009GRASS Development Team (2012) GRASS GIS. http://grass.osgeo.org/Hoekstra AG, Sloot PMA (2005) Introducing grid speedup: a scalability metric for parallel applications on the grid, EGC 2005, LNCS 3470, pp. 245–254Hu Y et al. (2004) Feasibility study of geo-spatial analysis using grid computing. Computational Science-ICCS. Springer Berlin Heidelberg, 956–963Huang Z et al (2009) Geobarn: a practical grid geospatial database system. Adv Electr Comput Eng 9:7–11Huang F et al (2011) Explorations of the implementation of a parallel IDW interpolation algorithm in a Linux cluster-based parallel GIS. Comput Geosci 37:426–434Laure E et al (2006) Programming the grid with gLite. CMST 12(1):33–45Li WJ et al (2005) The Design and Implementation of GIS Grid Services. In: Zhuge H, Fox G (eds) Grid and Cooperative Computing. Vol. 3795 of Lecture Notes in Computer Science 10. Springer, Berlin, pp 220–225National Geographic Institute (2010) BCN25: numerical cartographic database. http://www.ign.es/ign/main/index.do . Accessed April 2010Open Geospatial Consortium, Inc (2012) Open GIS Specification Model, http://www.opengeospatial.org/Openshaw S, Turton I (1996) A parallel Kohonen algorithm for the classification of large spatial datasets. Comput Geosci 22:1019–1026Perpiñá C, Alfonso D, Pérez-Navarro A (2007) BIODER project: biomass distributed energy resources assessment and logistic strategies for sitting biomass plants in the Valencia province (Spain), 17th European Biomass Conference and Exhibition Proceedings, Hamburg, Germany, pp. 387–393Perpiñá C et al (2008) Methodology based on Geographic Information Systems for biomass logistics and transport optimization. Renew Energ 34:555–565Shen Z et al (2007) Distributed computing model for processing remotely sensed images based on grid computing. Inf Sci 177:504–518Spanish Ministry of Agriculture, fisheries and food (2009). http://www.magrama.gob.es/es/ . Accessed March 2009Spanish Ministry of Environment (2008). http://www.magrama.gob.es/es/ . Accessed May 2008University of California. List of BOINC projects. http://boinc.berkeley.edu/projects.phpXiao N, Fu W (2003) SDPG: Spatial data processing grid. J Comput Sci Technol 18:523–53

Potential therapeutic implications of new insights into respiratory syncytial virus disease

Viral bronchiolitis is the most common cause of hospitalization in infants under 6 months of age, and 70% of all cases of bronchiolitis are caused by respiratory syncytial virus (RSV). Early RSV infection is associated with respiratory problems such as asthma and wheezing later in life. RSV infection is usually spread by contaminated secretions and infects the upper then lower respiratory tracts. Infected cells release proinflammatory cytokines and chemokines, including IL-1, tumor necrosis factor-α, IL-6, and IL-8. These activate other cells and recruit inflammatory cells, including macrophages, neutrophils, eosinophils, and T lymphocytes, into the airway wall and surrounding tissues. The pattern of cytokine production by T lymphocytes can be biased toward 'T-helper-1' or 'T-helper-2' cytokines, depending on the local immunologic environment, infection history, and host genetics. T-helper-1 responses are generally efficient in antiviral defense, but young infants have an inherent bias toward T-helper-2 responses. The ideal intervention for RSV infection would be preventive, but the options are currently limited. Vaccines based on protein subunits, live attenuated strains of RSV, DNA vaccines, and synthetic peptides are being developed; passive antibody therapy is at present impractical in otherwise healthy children. Effective vaccines for use in neonates continue to be elusive but simply delaying infection beyond the first 6 months of life might reduce the delayed morbidity associated with infantile disease

Can vaccinia virus be replaced by MVA virus for testing virucidal activity of chemical disinfectants?

Background: Vaccinia virus strain Lister Elstree (VACV) is a test virus in the DVV/RKI guidelines as representative of the stable enveloped viruses. Since the potential risk of laboratory-acquired infections with VACV persists and since the adverse effects of vaccination with VACV are described, the replacement of VACV by the modified vaccinia Ankara strain (MVA) was studied by testing the activity of different chemical biocides in three German laboratories. Methods: The inactivating properties of different chemical biocides (peracetic acid, aldehydes and alcohols) were tested in a quantitative suspension test according to the DVV/RKI guideline. All tests were performed with a protein load of 10% fetal calf serum with both viruses in parallel using different concentrations and contact times. Residual virus was determined by endpoint dilution method. Results: The chemical biocides exhibited similar virucidal activity against VACV and MVA. In three cases intra-laboratory differences were determined between VACV and MVA - 40% (v/v) ethanol and 30% (v/v) isopropanol are more active against MVA, whereas MVA seems more stable than VACV when testing with 0.05% glutardialdehyde. Test accuracy across the three participating laboratories was high. Remarkably inter-laboratory differences in the reduction factor were only observed in two cases. Conclusions: Our data provide valuable information for the replacement of VACV by MVA for testing chemical biocides and disinfectants. Because MVA does not replicate in humans this would eliminate the potential risk of inadvertent inoculation with vaccinia virus and disease in non-vaccinated laboratory workers

Induction of tumour-specific CD8+ cytotoxic T lymphocytes by tumour lysate-pulsed autologous dendritic cells in patients with uterine serous papillary cancer

Uterine serous papillary carcinoma is a highly aggressive variant of endometrial cancer histologically similar to high grade ovarian cancer. Unlike ovarian cancer, however, it is a chemoresistant disease from onset, with responses to combined cisplatinum-based chemotherapy in the order of 20% and an extremely poor prognosis. In this study, we demonstrate that tumour lysate-pulsed autologous dendritic cells can elicit a specific CD8+ cytotoxic T lymphocyte response against autologous tumour target cells in three patients with uterine serous papillary cancer. CTL from patients 1 and 2 expressed strong cytolytic activity against autologous tumour cells, did not lyse autologous lymphoblasts or autologous EBV-transformed cell lines, and were variably cytotoxic against the NK-sensitive cell line K-562. Patient 3 CD8+ T cells expressed a modest but reproducible cytotoxicity against autologous tumour cells only at the time of the first priming. Further priming attempts with PBL collected from patient 3 after tumour progression in the lumboaortic lymph nodes were unsuccesful. Cytotoxicity against autologous tumour cells could be significantly inhibited by anti-HLA class I (W6/32) and anti-LFA-1 MAbs. Highly cytotoxic CD8+ T cells from patients 1 and 2 showed a heterogeneous CD56 expression while CD56 was not expressed by non-cytotoxic CD8+ T cells from patient 3. Using two colour flow cytometric analysis of intracellular cytokine expression at the single cell level, a striking dominance of IFN-γ expressors was detectable in CTL populations of patients 1 and 2 while in patient 3 a dominant population of CD8+ T cells expressing IL-4 and IL-10 was consistently detected. Taken together, these data demonstrate that tumour lysate-pulsed DC can be an effective tool in inducing uterine serous papillary cancer-specific CD8+ CTL able to kill autologous tumour cells in vitro. However, high levels of tumour specific tolerance in some patients may impose a significant barrier to therapeutic vaccination. These results may have important implications for the treatment in the adjuvant setting of uterine serous papillary cancer patients with active or adoptive immunotherapy

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London

Risk of adverse outcomes in patients with underlying respiratory conditions admitted to hospital with COVID-19:a national, multicentre prospective cohort study using the ISARIC WHO Clinical Characterisation Protocol UK

Background Studies of patients admitted to hospital with COVID-19 have found varying mortality outcomes associated with underlying respiratory conditions and inhaled corticosteroid use. Using data from a national, multicentre, prospective cohort, we aimed to characterise people with COVID-19 admitted to hospital with underlying respiratory disease, assess the level of care received, measure in-hospital mortality, and examine the effect of inhaled corticosteroid use. Methods We analysed data from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study. All patients admitted to hospital with COVID-19 across England, Scotland, and Wales between Jan 17 and Aug 3, 2020, were eligible for inclusion in this analysis. Patients with asthma, chronic pulmonary disease, or both, were identified and stratified by age (<16 years, 16–49 years, and ≥50 years). In-hospital mortality was measured by use of multilevel Cox proportional hazards, adjusting for demographics, comorbidities, and medications (inhaled corticosteroids, short-acting β-agonists [SABAs], and long-acting β-agonists [LABAs]). Patients with asthma who were taking an inhaled corticosteroid plus LABA plus another maintenance asthma medication were considered to have severe asthma. Findings 75 463 patients from 258 participating health-care facilities were included in this analysis: 860 patients younger than 16 years (74 [8·6%] with asthma), 8950 patients aged 16–49 years (1867 [20·9%] with asthma), and 65 653 patients aged 50 years and older (5918 [9·0%] with asthma, 10 266 [15·6%] with chronic pulmonary disease, and 2071 [3·2%] with both asthma and chronic pulmonary disease). Patients with asthma were significantly more likely than those without asthma to receive critical care (patients aged 16–49 years: adjusted odds ratio [OR] 1·20 [95% CI 1·05–1·37]; p=0·0080; patients aged ≥50 years: adjusted OR 1·17 [1·08–1·27]; p<0·0001), and patients aged 50 years and older with chronic pulmonary disease (with or without asthma) were significantly less likely than those without a respiratory condition to receive critical care (adjusted OR 0·66 [0·60–0·72] for those without asthma and 0·74 [0·62–0·87] for those with asthma; p<0·0001 for both). In patients aged 16–49 years, only those with severe asthma had a significant increase in mortality compared to those with no asthma (adjusted hazard ratio [HR] 1·17 [95% CI 0·73–1·86] for those on no asthma therapy, 0·99 [0·61–1·58] for those on SABAs only, 0·94 [0·62–1·43] for those on inhaled corticosteroids only, 1·02 [0·67–1·54] for those on inhaled corticosteroids plus LABAs, and 1·96 [1·25–3·08] for those with severe asthma). Among patients aged 50 years and older, those with chronic pulmonary disease had a significantly increased mortality risk, regardless of inhaled corticosteroid use, compared to patients without an underlying respiratory condition (adjusted HR 1·16 [95% CI 1·12–1·22] for those not on inhaled corticosteroids, and 1·10 [1·04–1·16] for those on inhaled corticosteroids; p<0·0001). Patients aged 50 years and older with severe asthma also had an increased mortality risk compared to those not on asthma therapy (adjusted HR 1·24 [95% CI 1·04–1·49]). In patients aged 50 years and older, inhaled corticosteroid use within 2 weeks of hospital admission was associated with decreased mortality in those with asthma, compared to those without an underlying respiratory condition (adjusted HR 0·86 [95% CI 0·80−0·92]). Interpretation Underlying respiratory conditions are common in patients admitted to hospital with COVID-19. Regardless of the severity of symptoms at admission and comorbidities, patients with asthma were more likely, and those with chronic pulmonary disease less likely, to receive critical care than patients without an underlying respiratory condition. In patients aged 16 years and older, severe asthma was associated with increased mortality compared to non-severe asthma. In patients aged 50 years and older, inhaled corticosteroid use in those with asthma was associated with lower mortality than in patients without an underlying respiratory condition; patients with chronic pulmonary disease had significantly increased mortality compared to those with no underlying respiratory condition, regardless of inhaled corticosteroid use. Our results suggest that the use of inhaled corticosteroids, within 2 weeks of admission, improves survival for patients aged 50 years and older with asthma, but not for those with chronic pulmonary disease

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC