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News Article | August 4, 2017

Rigshospitalet is seen after a major IT breakdown on Friday morning affecting major IT systems at hospitals in the region, in Copenhagen, Denmark, August 4, 2017. Scanpix Denmark/Mads Claus Rasmussen via REUTERS COPENHAGEN (Reuters) - All computer systems are up and running again in Copenhagen's hospitals after an error caused a major network breakdown on Friday, a local authority said. "The network crash today was due to an error that occurred during a standard procedure on a central network component," the Capital Region of Denmark, which is responsible for hospitals in the Copenhagen area, said on Twitter.

Logistical study to deal with the practical issues of how the product fits into the current Danish national CRC screening programNAMUR, Belgium, Mar. 2, 2017 /PRNewswire/ -- Volition (NYSE MKT: VNRX) announced today that it has begun a two-phase logistical study of the Company's novel Nu.QTM Colorectal Cancer Screening Triage blood test. The study is in collaboration with Hvidovre Hospital and The Danish Research Group on Early Detection of Colorectal Cancer; both phases are expected to be completed within 6 months. The first phase of the study starts today in the Capital Region of Denmark and involves three centres and up to 250 subjects. The aim of the study is to evaluate the logistics in collecting and processing blood samples at a local screening centre and subsequently shipping the samples to a central laboratory in Denmark to run the Nu.QTM analysis. This phase is expected to be completed within 2 months. The second phase of the study is due to start after Ethical Approval and will involve five centres and up to 500 subjects. Specifically, this phase will assess the time taken between blood collection, analysis and results. When added to the existing clinical data previously announced, this logistics study aims to complete the information needed to add our test to the national screening program. Morten Rasmussen MD. Ph.D., head of the colorectal screening program in the Capital Region of Denmark, commented "We have been impressed with the preliminary clinical data of the Nu.QTM Colorectal Cancer Screening Triage Test and the potential to reduce unnecessary colonoscopies. Many healthcare systems in Europe, including Denmark, are struggling to meet the increased colonoscopy demand that has come from the implementation of fecal-based colorectal cancer screening programs. Before introducing any such test into the Danish National Screening program, we need to determine the very practical logistics of putting into practice Volition's Nu.QTM Triage Test to ensure a smooth, patient-friendly, and efficient implementation of our screening programme." Volition's CEO Cameron Reynolds added: "This is extremely important news for Volition in the implementation of our commercialisation strategy for our first product. Denmark has one of the most advanced healthcare systems in the world and is viewed by many as strong innovators. We have had a long, mutually beneficial relationship with our collaborators in Denmark and are very pleased that this logistics study will be undertaken to answer key issues to make sure any potential roll out nationally would be smooth. We also envisage this study will assist other countries in assessing the implementation of the Nu.QTM Triage Test within their National Screening Programs." There is currently a significant strain on colonoscopy capacity which can lead to longer waiting times in European healthcare systems due to the expansion of colorectal cancer screening programs. Therefore, there is a pressing need to prioritise the colonoscopy referrals for those at high risk. Volition aims to meet this need with its new Nu.QTM Colorectal Cancer Screening Triage Test. Having received a CE mark for the Nu.QTM Colorectal Cancer Screening Triage Test in December 2016, Volition plans to launch the test for the European Union screening population. Volition is a multi-national life sciences company developing simple, easy to use blood-based cancer tests to accurately diagnose a range of cancers. The tests are based on the science of Nucleosomics®, which is the practice of identifying and measuring nucleosomes in the bloodstream or other bodily fluid -- an indication that disease is present. As cancer screening programs become more and more widespread, our products can help to diagnose a range of cancers quickly, simply, accurately and cost effectively. Early diagnosis has the potential to not only prolong the life of patients, but also to improve their quality of life. Volition's research and development activities are currently centered in Belgium, with additional offices in London, New York and Singapore, as the company focuses on bringing its diagnostic products to market first in Europe, then in the U.S. and ultimately, worldwide. For more information about Volition, join us on our upcoming Earnings Call, visit Volition's website ( or connect with us via: The contents found at Volition's website address, Twitter, LinkedIn, Facebook, and YouTube are not incorporated by reference into this document and should not be considered part of this document. The addresses for Volition's website, Twitter, LinkedIn, Facebook, and YouTube are included in this document as inactive textual references only. Statements in this press release may be "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, that concern matters that involve risks and uncertainties that could cause actual results to differ materially from those anticipated or projected in the forward-looking statements. Words such as "expects," "anticipates," "intends," "plans," "aims," "targets," "believes," "seeks," "estimates," "optimizing," "potential," "goal," "suggests," "could," "would," "should," "may," "will" and similar expressions identify forward-looking statements. These forward-looking statements relate to the effectiveness of the Company's bodily-fluid-based diagnostic tests as well as the Company's ability to develop and successfully commercialize such test platforms for early detection of cancer. The Company's actual results may differ materially from those indicated in these forward-looking statements due to numerous risks and uncertainties. For instance, if we fail to develop and commercialize diagnostic products, we may be unable to execute our plan of operations. Other risks and uncertainties include the Company's failure to obtain necessary regulatory clearances or approvals to distribute and market future products in the clinical IVD market; a failure by the marketplace to accept the products in the Company's development pipeline or any other diagnostic products the Company might develop; the Company will face fierce competition and the Company's intended products may become obsolete due to the highly competitive nature of the diagnostics market and its rapid technological change; and other risks identified in the Company's most recent Annual Report on Form 10-K and Quarterly Reports on Form 10-Q, as well as other documents that the Company files with the Securities and Exchange Commission. These statements are based on current expectations, estimates and projections about the Company's business based, in part, on assumptions made by management. These statements are not guarantees of future performance and involve risks, uncertainties and assumptions that are difficult to predict. Forward-looking statements are made as of the date of this release, and, except as required by law, the Company does not undertake an obligation to update its forward-looking statements to reflect future events or circumstances. Nucleosomics®, NuQ®, Nu.QTM and HyperGenomics® and and their respective logos are trademarks and/or service marks of VolitionRx Limited and its subsidiaries. All other trademarks, service marks and trade names referred to in this press release are the property of their respective owners. To view the original version on PR Newswire, visit:

News Article | May 9, 2017

WASHINGTON--A new large-scale genetic study found that low body mass index (BMI) is likely not a causal risk factor for Alzheimer's disease, as earlier research had suggested, according to a study published in the Endocrine Society's Journal of Clinical Endocrinology & Metabolism. "Although prior studies found an association between Alzheimer's disease and low BMI, the new findings suggest this is not a causal relationship," said the study's senior author, Ruth Frikke-Schmidt, M.D., D.M.Sc., Ph.D., Chief Physician at Rigshospitalet in Copenhagen, Denmark, and Associate Research Professor at the University of Copenhagen. "The association can likely be explained by the fact that individuals with Alzheimer's disease are more likely to have low BMIs due to loss of appetite and weight loss in the early stages of the disease." More than 5 million Americans have Alzheimer's disease, according to the Alzheimer's Association's 2017 Alzheimer's Disease Facts and Figures Report. The disease affects the brain and is a common form of dementia. It is the sixth leading cause of death in the United States. To examine the association between Alzheimer's disease and low BMI, the researchers analyzed blood and DNA samples from 95,578 participants in the Copenhagen General Population Study (CGPS). Of the participants, 645 individuals developed Alzheimer's disease. The researchers analyzed the study participants' DNA for the presence of five genetic variants that have strong associations with BMI. Based on how many variants were found, participants were divided into four groups to reflect the likelihood of low BMI. The researchers also analyzed data from up to 249,796 individuals participating in the Genetic Investigation of ANthropometric Traits (GIANT) consortium for the genetic variants closely linked to low BMI. The analysis found the presence of the genetic variants tied to low BMI was not associated with increased risk of Alzheimer's disease. For comparison, the researchers examined if individuals with genetic variants connected to high BMI were more likely to have type 2 diabetes and did find the expected causal relationship. "We found individuals with lifelong low BMI due to genetic variation were not at increased risk of Alzheimer's disease," Frikke-Schmidt said. "Since genetic variants are not affected by other risk factors or diseases, this is a clean measure that can help to determine causality. The findings highlight that testing causality of a risk factor is pivotal before considering changing public health recommendations based on observational data alone." Other authors of the study include: Liv Tybjærg Nordestgaard and Anne Tybjærg-Hansen, of Rigshospitalet; and Børge G. Nordestgaard, of Herlev and Gentofte Hospital. All three also are affiliated with the University of Copenhagen. The research was supported by the Danish Medical Research Council, the Lundbeck Foundation, the Alzheimer Research Foundation, and the Research Fund at the Capital Region of Denmark. The study, "Body Mass Index and Risk of Alzheimer Disease: a Mendelian Randomization Study of 399,536 Individuals," will be published online at https:/ , ahead of print. Endocrinologists are at the core of solving the most pressing health problems of our time, from diabetes and obesity to infertility, bone health, and hormone-related cancers. The Endocrine Society is the world's oldest and largest organization of scientists devoted to hormone research and physicians who care for people with hormone-related conditions. The Society has more than 18,000 members, including scientists, physicians, educators, nurses and students in 122 countries. To learn more about the Society and the field of endocrinology, visit our site at http://www. . Follow us on Twitter at @TheEndoSociety and @EndoMedia.

Damgaard I.,Technical University of Denmark | Bjerg P.L.,Technical University of Denmark | Jacobsen C.S.,Geological Survey of Denmark | Tsitonaki A.,Orbicon | And 2 more authors.
Groundwater Monitoring and Remediation | Year: 2013

At a low permeability clay till site contaminated with chlorinated ethenes (Gl. Kongevej, Denmark), enhanced reductive dechlorination (ERD) was applied by direct push injection of molasses and dechlorinating bacteria. The performance was investigated by long-term groundwater monitoring, and after 4 years of remediation, the development of degradation in the clay till matrix was investigated by high-resolution subsampling of intact cores. The formation of degradation products, the presence of specific degraders Dehalococcoides spp. with the vinyl chloride (VC) reductase gene vcrA, and the isotope fractionation of trichloroethene, cis-dichloroethene (cis-DCE), and VC showed that degradation of chlorinated ethenes occurred in the clay till matrix as well as in sand lenses, sand stringers, and fractures. Bioactive sections of up to 1.8 m had developed in the clay till matrix, but sections, where degradation was restricted to narrow zones around sand lenses and stringers, were also observed. After 4 years of remediation, an average mass reduction of 24% was estimated. Comparison of the results with model simulation scenarios indicate that a mass reduction of 85% can be obtained within approximately 50 years without further increase in the narrow reaction zones if no donor limitations occur at the site. Long-term monitoring of the concentration of chlorinated ethenes in the underlying chalk aquifer revealed that the aquifer was affected by the more mobile degradation products cis-DCE and VC generated during the remediation by ERD. © 2012, National Ground Water Association.

PubMed | Geosyntec Consultants, Cowi A/S, NIRAS, FLUTe Technology and 2 more.
Type: | Journal: Journal of contaminant hydrology | Year: 2016

Characterization of dense non-aqueous phase liquid (DNAPL) source zones in limestone aquifers/bedrock is essential to develop accurate site-specific conceptual models and perform risk assessment. Here innovative field methods were combined to improve determination of source zone architecture, hydrogeology and contaminant distribution. The FACT is a new technology and it was applied and tested at a contaminated site with a limestone aquifer, together with a number of existing methods including wire-line coring with core subsampling, FLUTe transmissivity profiling and multilevel water sampling. Laboratory sorption studies were combined with a model of contaminant uptake on the FACT for data interpretation. Limestone aquifers were found particularly difficult to sample with existing methods because of core loss, particularly from soft zones in contact with chert beds. Water FLUTe multilevel groundwater sampling (under two flow conditions) and FACT sampling and analysis combined with FLUTe transmissivity profiling and modeling were used to provide a line of evidence for the presence of DNAPL, dissolved and sorbed phase contamination in the limestone fractures and matrix. The combined methods were able to provide detailed vertical profiles of DNAPL and contaminant distributions, water flows and fracture zones in the aquifer and are therefore a powerful tool for site investigation. For the limestone aquifer the results indicate horizontal spreading in the upper crushed zone, vertical migration through fractures in the bryozoan limestone down to about 16-18m depth with some horizontal migrations along horizontal fractures within the limestone. Documentation of the DNAPL source in the limestone aquifer was significantly improved by the use of FACT and Water FLUTe data.

No statistical methods were used to predetermine sample size. Patient recruitment, enrolment and processing. Patients with T2D were either recruited from the Inter99 study population24 or from the out-patient clinic at Steno Diabetes Center, Gentofte, Denmark. Patients with known T2D were included if the patient had clinically defined T2D on the day of examination according to the WHO definition25. Inclusion criteria were fasting serum C-peptide above 200 pmol l−1 and negative testing for serum glutamic acid decarboxylase (GAD) 65 antibodies (to exclude T1D, latent autoimmune diabetes in adults), no secondary forms of diabetes like chronic pancreatitis diabetes or syndromic diabetes, no antibiotic treatment 2 months before inclusion, and no known gastro-intestinal diseases, no previous bariatric surgery or medication known to affect the immune system. All patients with T1D were recruited from the out-patient clinic at Steno Diabetes Center, Gentofte, Denmark (n = 31). Inclusion criteria were dependence on insulin treatment from time of diagnosis, fasting serum C-peptide below 200 pmol l−1, glycated haemoglobin (HbA1c) above 8.0% (64 mmol l−1) to ensure current hyperglycaemia, T1D duration and dependence on insulin treatment > 5 years, no antibiotic treatment at least 2 months before inclusion, and no known gastrointestinal diseases. All study participants were of North European ethnicity. The study participants were examined on 2 days that were approximately 14 days apart. On the first day, study participants were examined after an over-night fast. Height was measured without shoes to the nearest 0.5 cm, and weight was measured without shoes and wearing light clothes to the nearest 0.1 kg. Hip and waist circumference was measured using a non-expandable measuring tape to the nearest 0.5 cm. Waist circumference was measured midway between the lower rib margin and the iliac crest. Hip circumference was measured as the largest circumference between the waist and the thighs. Blood pressure was assessed while the participant was lying in an up-right position after at least 5 min of rest using a cuff of appropriate size (A&D, UA-787 plus digital or A&D, UA-779). Blood pressure was measured at least twice and the average of the measurements was calculated. On the second day of examination, all participants provided a stool sample which was immediately frozen after home collection and stored at −80 °C. Information on medication status was obtained by questionnaire and interview on the first day of examination. Of the 75 T2D patients, 10 patients (13%) received no hyperglycaemic medications and 58 patients (77%) received the biguanide metformin; of these 75 TD2 patients, 28 patients (37%) received metformin as the only anti-hyperglycaemic medication, 10 patients (13%) received sulfonylurea alone or in combination with metformin, 14 patients (19%) received a combination of oral antidiabetic drugs and insulin treatment and 4 patients (5%) were on insulin treatment only. Eleven patients (15%) received dipeptidyl peptidase-4 (DPP4) inhibitors or glucagon-like peptide-1 (GLP1), all of them in combination with metformin. Patients were reported as receiving anti-hypertensive treatment if at least one of the following drugs was reported: spironolactone, thiazides, loop diuretics, beta blockers, calcium channel blockers, moxonidine or drugs affecting the renin–angiotensin system (n = 55 for T2D (73%) and n = 23 (74%) for T1D). Patients receiving statins, fibrates and/or ezetimibe were reported as receiving lipid-lowering medication (n = 56 for T2D (75%; all on statin treatment), and n = 24 for T1D (77%; 74% on statin treatment)). All T1D patients were on insulin treatment as their only blood glucose lowering treatment. All biochemical analyses were performed on blood samples drawn in the morning after an over-night fast of at least 10 h. Plasma glucose was analysed by a glucose oxidase method (Granutest, Merck) with a detection limit of 0.11 mmol l−1 and intra- and interassay coefficients of variation (CV) of <0.8% and <1.4%, respectively. HbA1c was measured on G7 HPLC Analyzer (Tosoh) by ion-exchange high-performance liquid chromatography. Serum C-peptide was measured using a time-resolved fluoroimmunoassay with the AutoDELFIA C-peptide kit (PerkinElmer, Wallac), with a detection limit of 5 pmol l−1 and intra- and interassay CV of <4.7% and <6.4%, respectively. Serum insulin (excluding des and intact proinsulin) was measured using the AutoDELFIA insulin kit (PerkinElmer, Wallac) with a detection limit of 3 pmol l−1 and with intra- and interassay CV of <3.2% and <4.5%, respectively. Plasma cholesterol, plasma high-density lipoprotein cholesterol and plasma triglycerides were all measured on Vitros 5600 using reflect-spectrophotometrics. Plasma low-density lipoprotein cholesterol was calculated using Friedewald’s equation. Blood leukocytes and white blood cell differential count were measured on Sysmex XS 1000i using flow cytometrics. Plasma metformin was determined by high performance liquid chromatography followed by tandem mass spectrometry. Briefly, the proteins were precipitated with acetonitrile containing the deuterated internal standard, metformin-d6, hydrochloride and the supernatant diluted by acetonitrile. The analysis was performed on a Waters Acquity UPLC I-class system connected to a Xevo TQ-S tandem mass spectrometer in electrospray positive ionization mode. Separation was achieved on a Waters XBridgeT BEH Amide 2.5-μm column and gradient elution with 100 mM ammonium formate (pH 3.2), and with acetonitrile. The multiple reaction monitoring transitions used for metformin and metformin-d6 were 130.2 > 71.0 and 136.2 > 60.0. Calibrators were prepared by spiking drug-free serum with metformin to a concentration of 2,000 ng ml−1. B12 was measured using Vitros Immunodiagnostic Products. GAD65 was measured on serum samples by a sandwich ELISA (RSR ltd.). Inter- and intra-assay CV were < 16.6% and < 6.7% respectively, and with a detection limit of 0.57 Uml−1. Stool samples were obtained at the homes of each participant and samples were immediately frozen by storing them in their home freezer. Frozen samples were delivered to Steno Diabetes Center using insulating polystyrene foam containers, and then they were stored at −80 °C until analysis. The time span from sampling to delivery at the Steno Diabetes Center was intended to be as short as possible and no more than 48 h. A frozen aliquot (200 mg) of each faecal sample was suspended in 250 μl of guanidine thiocyanate, 0.1 M Tris, pH 7.5, and 40 μl of 10% N-lauroylsarcosine. Microbial DNA extraction was then performed as previously described12. The DNA concentration and its molecular size were estimated using nanodrop (Thermo Scientific) and agarose gel electrophoresis. Already available Danish metagenomic samples were those reported in ref. 26 and references therein (excluding 14 samples removed due to average read length below 40 nucleotides, and with 5 Chinese and 21 Swedish samples with less than the rarefaction threshold of 7 million reads in total excluded from functional profile or diversity analyses), with newly sequenced samples deposited in the European Bioinformatics Institute Sequence Read Archive under accession ERP004605. All information on Swedish samples was retrieved from previously published data4. In addition to published data on Chinese individuals3, we retrieved information on metformin treatment in a subset of 71 Chinese T2D patients. One-hundred and twelve samples from ref. 3 lacked metformin treatment metadata and were therefore discarded, except for measuring differences between the country data sets disregarding treatment or diabetic status. Characteristics of all study participants included in the present protocol are given in Supplementary Table 1. Additional Danish T2D patients were recruited at the Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen throughout 2014 as a part of the ongoing MicrobDiab study ( T2D patients were included in the study if the time of T2D diagnosis was less than 5 years ago, they were between 35 and 75 years of age, Caucasian and they had not received antibiotics within the past 4 months of inclusion. In total, 30 T2D patients (21 male and 9 female) were identified. Faecal samples were collected at the home of the patients, followed by immediate freezing of samples in home freezers, and transport of samples to the hospital stored on dry ice. The samples were stored at −80 °C until DNA extraction. Information of medication was obtained from questionnaires. In total, 21 (70%) of the T2D patients received metformin. All individuals in both the Danish MetaHIT study and the Danish validation study gave written informed consent before participation in the studies. Both studies were approved by the Ethical Committees of the Capital Region of Denmark (MetaHIT study: HC-2008-017; validation study: H-3-2013-102). Both studies were conducted in accordance with the principles of the Declaration of Helsinki. Illumina shotgun sequencing was applied to DNA extracted from 620 faecal samples originating from the MetaHIT project (Supplementary Table 1). Raw sequencing data were processed using the MOCAT (version 1.1) software package27. Reads were trimmed (option read_trim_filter) using a quality and length cut-off of 20 and 30 bp, respectively. Trimmed reads were subsequently screened against a custom database of Illumina adapters (option screen_fastafile) and the human genome version 19 using a 90% identity cut-off (option screen). The resulting high-quality reads were assembled (option assembly) and assemblies revised (option assembly revision). Genes were predicted on scaftigs with a minimum length of 500 bp (option gene_prediction). Predicted protein-coding genes with a minimum length of 100 bp were clustered at 95% sequence identity using Cd-hit (version 4.6.1)28 with parameters set to: -c 0.95, -G 0 -aS 0.9, -g 1, -r 1. The representative genes of the resulting clusters were ‘padded’ (that is, extended up to 100 bp at each end of the sequence using the sequence information available from the assembled scaftigs), resulting in the final reference gene catalogue used in this study. The reference gene catalogue was functionally annotated using SmashCommunity29 (version 1.6) after aligning the amino acid sequence of each gene to the KEGG30 (version 62) and eggNOG31 (version 3) databases. Raw insert (sequenced fragments of DNA represented by single or paired-end reads) count profiles were generated using MOCAT27 by mapping high-quality reads from each metagenome to the reference gene catalogue (option screen) using an alignment length and identity cut-off of 45% and 95%, respectively. For each gene, the number of inserts that matched the protein-coding region was counted. Counts of inserts that mapped with the same alignment score to multiple genes were distributed equally among them. Taxonomic abundances were computed at the level of metagenomic operational taxonomic units (mOTUs)32, normalized to the length of the concatenated marker genes for each mOTU to yield the abundances used for the study, and subsequently binned at broader taxonomic levels (genus, family, class, etc.). For all metagenome-derived measures except the mOTU taxonomic assignments, read counts were ‘rarefied’ in order to avoid any artefacts of sample size on low-abundance genes. Rarefied matrices were obtained as follows. Data matrices were rarefied to 7 million reads per sample. This threshold was chosen to include most samples, but 5 Chinese and 21 Swedish samples were excluded due to having less than 7 million reads per sample. Rarefactions were performed using a C++ program developed for the Tara project33. In total we performed 30 repetitions, and in each of these we measured the richness, evenness, chao1 and Shannon diversity metrics within a rarefaction. The median value of these was taken as the respective diversity measurement for each sample. The first of 30 rarefactions of each sample were used to create a rarefied gene abundance matrix and KEGG orthologue abundance profiles were calculated by summing the rarefied abundance of genes annotated to the respective KEGG orthologue gene. Clustering of the catalogue genes by co-abundance, as described in ref. 34, defined 10,754 co-abundance gene groups (CAGs) with very high correlations (Pearson correlation coefficient > 0.9). The 925 largest of these, with more than 700 genes, were termed metagenomic species (MGS). The abundance profiles of the CAGs and MGSs were determined as the medium gene abundance (downsized to 7 million reads per sample) throughout the samples. Furthermore, the CAGs and MGS were taxonomically annotated by sequence similarity to known reference genomes. To avoid drawing false conclusions about gut microbial functions from high abundance of single genes remotely homologous to members of a functional pathway, we used an approach that required presence of multiple pathway members. Functional pathway abundance was calculated from gene catalogue KEGG orthologue annotation and MGS abundances per sample. Thus KEGG orthologues present in each MGS were used to determine for that CAG/MGS which functional modules were represented within its genetic repertoire. This required that >90% of KEGG orthologues necessary for the completion of a reaction pathway should be present, when also taking alternative enzymatic pathways into account. The module abundance within a sample was calculated from CAG abundance in each respective sample, summing over all CAGs which had the module present. Rarefied median coverages of CAG/MGS were used, so no further normalization of the module abundance matrix was required. Abundance of genetic potential falling under the same higher-order functional levels was calculated by summing up all abundances of the lower-level functional modules within each sample. Existing functional annotation databases cover gut metabolic pathways relatively poorly. To account for this, a number of additional bacterial gene functional modules were curated and annotated, extending the KEGG system; these are referred to in result tables as GMMs (gut microbial modules) and were previously described in ref. 12. 16S amplicons from frozen samples were sequenced 300 bp and 200 bp paired-end reads using an Illumina miSeq machine. We used the LotuS35 pipeline in short amplicon mode with default quality filtering, clustering and denoising operational taxonomic units (OTUs) with UPARSE36, removing chimaeric OTUs against the RDP reference database ( with uchime37, merging reads with FLASH38 and assigning a taxonomy against the SILVA 119 rRNA database39, and further refined by BLAST searches against the NCBI rRNA database40 to identify Intestinibacter OTUs, using the following LotuS command line options: ‘-p miSeq -refDB SLV -doBlast blast -amplicon_type SSU -tax_group bacteria -derepMin 2 -CL 2 -thr 14’. Microbial taxa where mean abundance over all samples was less than 30 reads, or that were present in less than 3 samples, were excluded from univariate and classifier analyses. All abundances were normalized by total sample sum. For module tables, no feature filters were used except requiring the module to be present in at least 20 samples. Filtered data tables were made available online ( Univariate testing for differential abundances of each taxonomic unit between two or more groups was tested using Mann–Whitney-U or Kruskal–Wallis tests, respectively, corrected for multiple testing using the Benjamini–Hochberg false discovery rate control procedure (Q values)41. Post-hoc statistical testing for significant differences between all combinations of two groups was conducted only for taxa with abundances significantly different at P < 0.2. Wilcoxon rank-sum tests were calculated for all possible group combinations and corrected for multiple testing again using the Benjamini–Hochberg false discovery rate, as implemented in R. When controlling for potential confounders such as source study, we used blocked ‘independence_test’ function calls with options ‘ytrafo = rank, teststat=scalar’ for blocked WRST and ‘ytrafo = rank, teststat=quad’ for blocked Kruskal–Wallis test, as implemented in the COIN software package42 for R. Similarly, we applied these independence tests in the framework of post-hoc testing as described above. Analysis of correlations between taxonomic or functional features, community diversity indices and sample metadata variables were conducted using Spearman correlation tests as implemented in R, and corrected for multiple tests using the Benjamini–Hochberg false discovery rate control procedure. To control for confounders such as source study in univariate correlation analyses, blocked Spearman tests as implemented in COIN (settings ‘independence_test’, options ytrafo = rank, xtrafo = rank, distribution = asymptotic) were used. In some analyses, taxa were corrected for the influence of a continuous confounder variable such as microbial community richness; in these cases, the residual of a linear model between normalized log-transformed taxa abundances and overall sample gene richness was used to correct for the confounding variable. Power analysis was conducted by randomly subsampling to a given sample number, repeated 5 times to achieve robust results. All ordinations (NMDS, dbRDA) and subsequent statistical analyses were calculated using the R package vegan43 using Canberra distances on normalized taxa abundance matrices, then visualized using the ggplot2 R package44. Community differences were calculated using a permutation test on the respective NMDS reduced feature space, as implemented in vegan. Furthermore, we calculated intergroup differences for the microbiota using PERMANOVA45 as implemented in vegan. This test compares the intragroup distances to the intergroup distances in a permutation scheme and from this calculates a P value. For all PERMANOVA tests, we used 2 × 105 randomizations and a normalized genus-level mOTU abundance matrix, using Canberra intersample distances. PERMANOVA post-hoc P values were corrected for multiple testing using the Benjamini–Hochberg false discovery rate control procedure. Analysis of variance broken down by cohort, treatment and disease status was conducted by fitting these distances to a linear model of sample metadata distances, as further described in Supplementary Discussion 3.2. To create classifiers for separating samples from different subsets, an L1 restricted LASSO using the R glmnet package46 was carried out to test for an optimal value of lambda (number of features to be used in the final predictor) in a fivefold cross-validated and internally fourfold cross-validated LASSO run on all data. After this, the previously determined value of lambda was manually controlled for number of features used against the root mean square error of the classifier. In a fivefold cross-validation, an independent LASSO classifier was trained on 4/5 of the data using the previously determined value of lambda, and response values were predicted on 1/5 of the data. LASSO models with a Poisson response type were used in all cases. Binary classifications between T2D and ND control samples were performed with an R reimplementation of the robust recursive feature elimination support vector machine (rRFE-SVM)47 procedure. The SVM was performed in an outer cross-validation scheme on 4/5 of the data. Of these, 90% were randomly selected 200 times in each cross-validation for the RFE, to create a feature ranking from an average over these runs. Classifier performance was validated on the remaining 1/5 of samples using the pre-established feature ranking. In case of several cohorts, the area under the receiver operating characteristic curve (ROC-AUC) scores were measured for each cohort separately. The MGS technology has previously been described34 and is available online ( The mOTU resource has been made publically available ( and was analysed using MOCAT27 which is also publically available ( The 16S pipeline LotuS35 is freely available online ( The novel gene catalogue has been deposited online (, as have the raw amplicon sequences ( Statistical analysis and data visualization was conducted using freely available R libraries: vegan, COIN and ggplot2 and is described in more details elsewhere48, 49. Data matrices and R source code for replicating the central tests conducted on the data have been deposited online ( A subset of the Danish study participants answered a validated food frequency questionnaire in order to obtain information on the habitual dietary habits. A complete data set was obtained for 66% of the nondiabetic individuals and 88% of T2D patients. When evaluating the dietary data, the consumed quantity was determined by multiplying portion size by the corresponding consumption frequency reported. Standard portion sizes for women and men, separately, were used in this calculation50, 51. All food items in the questionnaire were linked to food items in the Danish Food Composition Databank52. Estimation of daily intake of macro- and micronutrients for each participant was based on calculations in the software program FoodCalc version 1.353.

Rytter L.,Glostrup University Hospital | Jakobsen H.N.,Capital Region of Denmark | Ronholt F.,Herlev University Hospital | Hammer A.V.,Metropolitan University College | And 3 more authors.
Scandinavian Journal of Primary Health Care | Year: 2010

Objectives. Many hospital admissions are due to inappropriate medical treatment, and discharge of fragile elderly patients involves a high risk of readmission. The present study aimed to assess whether a follow-up programme undertaken by GPs and district nurses could improve the quality of the medical treatment and reduce the risk of readmission of elderly newly discharged patients. Design and setting. The patients were randomized to either an intervention group receiving a structured home visit by the GP and the district nurse one week after discharge followed by two contacts after three and eight weeks, or to a control group receiving the usual care. Patients. A total of 331 patients aged 78 years discharged from Glostrup Hospital, Denmark, were included. Main outcome measures. Readmission rate within 26 weeks after discharge among all randomized patients. Control of medication, evaluated 12 weeks after discharge on 293 (89%) of the patients by an interview at home and by a questionnaire to the GP. Results. Control-group patients were more likely to be readmitted than intervention-group patients (52% v 40%; p=0.03). In the intervention group, the proportions of patients who used prescribed medication of which the GP was unaware (48% vs. 34%; p=0.02) and who did not take the medication prescribed by the GP (39% vs. 28%; p=0.05) were smaller than in the control group. Conclusion. The intervention shows a possible framework securing the follow-up on elderly patients after discharge by reducing the readmission risk and improving medication control. © 2010 Informa Healthcare.

News Article | November 18, 2015

All animal procedures were conducted under a protocol (#08–1990) approved by the Genentech Institutional Animal Care and Use Committee in an Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC)-accredited facility in accordance with the Guide for the Care and Use of Laboratory Animals and applicable laws and regulations. For cloning of antibodies from human B cells, informed written consent was obtained from all donors and was provided in accordance with the Declaration of Helsinki. Approval was obtained from the health research ethics committee of Denmark through the regional committee for the Capital Region of Denmark. All in vivo experiments were done with MRSA-USA300 NRS384 obtained from NARSA ( unless noted otherwise. The generation of protein-A-deficient strain Δmcr USA300 NRS384, as well as protein-A-deficient USA300 lacking tarM or tarS has been described previously38, 39. The protein-A-deficient strains were used only in some in vitro experiments to determine antibody specificity. The MIC for extracellular bacteria was determined by preparing serial twofold dilutions of the antibiotic in tryptic soy broth. Dilutions of the antibiotic were made in quadruplicate in 96-well culture dishes. MRSA (NRS384 strain of USA300) was taken from an exponentially growing culture and diluted to 1 × 104 c.f.u. ml−1. The bacteria were cultured in the presence of antibiotic for 18–24 h with shaking at 37 °C and bacterial growth was determined by reading the optical density (OD) at 630 nm. The MIC was determined to be the dose of antibiotic that inhibited bacterial growth by >90%. Intracellular MIC was determined on bacteria that were sequestered inside mouse peritoneal macrophages (see later for generation of murine peritoneal macrophages). Macrophages were plated at a density of 4 × 105 cells ml−1 and infected with MRSA at a ratio of 10–20 bacteria per macrophage. Macrophage cultures were maintained in growth media supplemented with 50 μg ml−1 of gentamycin to inhibit the growth of extracellular bacteria and test antibiotics were added to the growth media 1 day after infection. The survival of intracellular bacteria was assessed 24 h after addition of the antibiotics. Macrophages were lysed with Hanks buffered saline solution supplemented with 0.1% bovine serum albumin (BSA) and 0.1% Triton-X, and serial dilutions of the lysate were made in PBS solution containing 0.05% Tween-20. The number of surviving intracellular bacteria was determined by plating on tryptic soy agar plates with 5% defibrinated sheep blood. USA300 stocks were prepared for infection from actively growing cultures in tryptic soy broth. Bacteria were washed three times in PBS and aliquots were frozen at −80 °C in PBS 25% glycerol. Intracellular bacteria infections. Seven-week-old female A/J mice (Stock 000646) were obtained from Jackson Labs and infected by peritoneal injection with 5 × 107 c.f.u. of USA300. Mice were killed 1 day after infection and the peritoneum was flushed with 5 ml of cold PBS. Peritoneal washes were centrifuged for 5 min at 1,000 r.p.m. at 4 °C in a table-top centrifuge. The cell pellet containing peritoneal cells was collected and cells were treated with 50 μg ml−1 of lysostaphin (Cell Sciences, CRL 309C) for 20 min at 37 °C to kill contaminating extracellular bacteria. Peritoneal cells were washed three times in ice-cold PBS to remove the lysostaphin. Peritoneal cells from donor mice were pooled, and recipient mice were injected with cells derived from five donors per each recipient by intravenous injection into the tail vein. To determine the number of live intracellular colony-forming units, a sample of the peritoneal cells were lysed in HB (Hanks balanced salt solution supplemented with 10 mM HEPES and 0.1% BSA) with 0.1% Triton-X, and serial dilutions of the lysate were made in PBS with 0.05% Tween-20. Free bacteria infections. A/J mice were infected with various doses of free bacteria using a fresh aliquot of the glycerol stocks used for the peritoneal injections. Actual infection doses were confirmed by c.f.u. plating. For the data shown in Fig. 1a the actual infection dose for intracellular bacteria was 1.8 × 106 c.f.u. per mouse, and the actual infection dose for free bacteria was 2.9 × 106 c.f.u. per mouse. Selected mice were treated with a single dose of 110 mg kg−1 of vancomycin by intravenous injection immediately after infection. Generation of MRSA-infected peritoneal cells. Six-to-eight-week-old female A/J mice (see earlier) were infected with 1 × 108 c.f.u. of the NRS384 strain of USA300 by peritoneal injection. The peritoneal wash was harvested 1 day after infection, and the infected peritoneal cells were treated with 50 μg ml−1 of lysostaphin diluted in HEPES buffer supplemented with 0.1% BSA (HB buffer) for 20 min at 37 °C. Peritoneal cells were then washed twice in ice-cold HB buffer. The peritoneal cells were diluted to 1 × 106 cells ml−1 in RPMI 1640 tissue culture media supplemented with 10 mM HEPES and 10% fetal calf serum, and 5 μg ml−1 vancomycin. Free MRSA from the primary infection was stored overnight at 4 °C in PBS solution as a control for extracellular bacteria that were not subject to neutrophil killing. Infection of osteoblasts, HBMEC and A549 cells. MG63 cell line (CRL-1427) and A549 cells (CCL185) were obtained from ATCC and maintained in RPMI 1640 tissue culture media supplemented with 10 mM HEPES and 10% fetal calf serum (RPMI-10). HBMEC cells (catalogue #1000) and ECM media (catalogue #1001) were obtained from ScienceCell Research Labs. The cells were used without further authentication or testing for mycoplasma contamination. Cells were plated in 24-well tissue culture plates and cultured to obtain a confluent layer. On the day of the experiment, the cells were washed once in RPMI (without supplements). MRSA or infected peritoneal cells were diluted in complete RPMI-10 and vancomycin was added at 5 μg ml−1 immediately before infection. Peritoneal cells were added to the osteoblasts at 1 × 106 peritoneal cells per ml. A sample of the cells was lysed with 0.1% Triton-X to determine the actual concentration of live intracellular bacteria at the time of infection. The actual titre for all infections was determined by plating serial dilutions of the bacteria on tryptic soy agar with 5% defibrinated sheep blood. The human IgG antibodies against anti-β-GlcNAc WTA monoclonal antibody (mAb) and anti-α-GlcNAc WTA mAb were cloned from peripheral B cells from patients after S. aureus infection using a monoclonal antibody discovery technology that conserves the cognate pairing of antibody heavy and light chains40. Antibodies were expressed by transfection of mammalian cells41. Supernatants containing full-length IgG1 antibodies were harvested after 7 days and used to screen for antigen binding by enzyme-linked immunosorbent assay (ELISA). These antibodies were positive for binding to cell wall preparations from USA300. Antibodies were subsequently produced in 200-ml transient transfections and purified with protein A chromatography (MabSelect SuRe, GE Life Sciences) for further testing. Synthesis of the rifalogue linker drug was performed as follows. Protease cleavable linker MC-VC-PAB-OH23 (1.009 g, 1.762 mmol, 1.000, 1,009 mg) was taken up in N,N-dimethylformamide (6 ml, 77 mmol, 44, 5,700 mg). To this was added a solution of thionyl chloride (1.1 equiv., 1.938 mmol, 1.100, 231 mg) in dichloromethane (DCM) (1 ml, 15.44 mmol, 8.765, 1,325 mg) in portions dropwise (half was added over 1 h, stirred for 1 h at room temperature, then the other half was added over another hour). The solution remained a yellow colour. Another 0.6 equiv. of thionyl chloride was added as a solution in 0.5 ml DCM dropwise, carefully. The reaction remained yellow and was stirred sealed overnight at room temperature. The reaction was monitored by liquid chromatography mass spectrometry (LC/MS), indicating 88% conversion to benzyl chloride. Another 0.22 equiv. of thionyl chloride was added dropwise as a solution in 0.3 ml DCM. When the reaction approached 92% benzyl chloride, the reaction was bubbled with N . The concentration was increased from 0.3 M to 0.6 M. MC-VC-PAB-Cl (0.9 mmol) was cooled to 0 °C and rifalogue (dimethyl piperazinebenzoxazinorifamycin42 (0.75 g, 0.81 mmol, 0.46, 750 mg)) was added. The mixture was diluted with another 1.5 ml of DMF to reach 0.3 M. Stirred open to air for 30 min. N,N-diisopropylethylamine (3.5 mmol, 3.5 mmol, 2.0, 460 mg) was added and the reaction stirred overnight open to air. Over the course of 4 days, four additions of 0.2 equiv. N,N-diisopropylethylamine base were added while the reaction stirred open to air, until the reaction appeared to stop progressing. The reaction was diluted with DMF and purified on high-performance liquid chromatography (HPLC; 20–60% ACN/FA·H O) in several batches to give MC-VC-PAB-rifalogue (0.38 g, 32% yield) m/z = 1,482.8. The non-cleavable rifalogue linker drug was synthesized using the exact same method, but replacing MC-VC-PAB-OH with MC-V-D-Cit-PAB-OH. Construction and production of the THIOMAB variant of anti-WTA antibody was done as reported previously43. Briefly, a cysteine residue was engineered at the Val 205 position of the anti-WTA light chain to produce its THIOMAB variant. The thio anti-WTA was conjugated to MC-vc-PAB-rifalogue. The antibody was reduced in the presence of 50-fold molar excess dithiothreitol (DTT) overnight. The reducing agent and the cysteine and glutathione blocks were purified away using HiTrap SP-HP column (GE Healthcare). The antibody was re-oxidized in the presence of 15-fold molar excess dehydroascorbic acid (MP Biomedical) for 2.5 h. The formation of interchain disulfide bonds was monitored by LC/MS. A threefold molar excess of the linker drug (MC-VC-PAB-rifalogue) over protein was incubated with the THIOMAB for 1 h. The AAC was purified by filtration through a 0.2 μm SFCA filter (Millipore). Excess-free linker drug was removed by filtration. The conjugate was buffer exchanged into 20 mM histidine acetate pH 5.5/240 mM sucrose by dialysis. The number of conjugated MC-VC-PAB-rifalogue molecules per mAb was quantified by LC/MS analysis. Purity was also assessed by size-exclusion chromatography. LC/MS analysis was performed on a 6530 Accurate-Mass Quadrupole Time-of-Flight (Q-TOF) LC/MS (Agilent Technologies). Samples were chromatographed on a PRLP-S column, 1,000 Å, 8 μm (50 mm × 2.1 mm, Agilent Technologies) heated to 80 °C. A linear gradient from 30–60% B in 4.3 min (solvent A, 0.05% TFA in water; solvent B, 0.04% TFA in acetonitrile) was used and the eluent was directly ionized using the electrospray source. Data were collected and deconvoluted using the Agilent Mass Hunter qualitative analysis software. Before LC/MS analysis, AAC was treated with lysyl endopeptidase (Wako) for 30 min at 1:100 w/w enzyme to antibody ratio, pH 8.0, and 37 °C to produce the Fab and the Fc portion for ease of analysis. The drug-to-antibody ratio (DAR) was calculated using the abundance of Fab and Fab+1 calculated by the MassHunter software. Analysis of bacteria isolated from infected mice. Balb/c mice were infected with 1 × 107 c.f.u. of MRSA (USA300) by intravenous injection and kidneys were harvested on day 3 after infection. Kidneys were homogenized using a GentleMACS dissociator in 5 ml volume per two kidneys using M-Tubes and the program RNA01.01 (Miltenyi Biotec). Homogenization buffer was: PBS plus 0.1% Triton-X-100, 10 μg ml−1 DNAase (bovine pancreas grade II, Roche) and protease inhibitors (complete protease inhibitor cocktail, Roche 11-836-153001). After homogenization, the samples were incubated at room temperature for 10 min and then diluted with ice-cold PBS and filtered through a 40 μm cell strainer. Tissue homogenates were washed twice in ice-cold PBS and then suspended in a volume of 0.5 ml per two kidneys in HB buffer (Hanks balanced salt solution supplemented with 10 mM HEPES and 0.1% BSA). The cell suspension was filtered again and 25 μl of the bacterial suspension was taken for each staining reaction (Fig. 2c). Antibody staining for flow cytometry. Bacteria (1 × 107 of in vitro grown bacteria (Fig. 2d), or 25 μl of tissue homogenate described earlier (Fig. 2c) were suspended in HB buffer and blocked by incubation with 400 μg ml−1 of mouse IgG (Sigma, I5381) for 1 h. Fluorescently labelled antibodies were added directly to the blocking reaction and incubated at room temperature for an additional 10–20 min. Bacteria were washed three times in HB buffer and then fixed in PBS 2% paraformaldehyde before FACS analysis. Test antibodies (anti-β-WTA, anti-α-WTA or isotype control-anti CMV-gD) were conjugated with Alexa-488 using amine reactive reagents (Invitrogen, succinimidyl-ester of Alexa Fluor 488, NHS-A488). Antibodies in 50 mM sodium phosphate were reacted with a 5–10-fold molar excess of NHS-A488 in the dark for 2–3 h at room temperature. The labelling mixture was applied to a GE Sepharose S200 column equilibrated in PBS to remove excess reactants from the conjugated antibody. The number of A488 molecules per antibody was determined using the ultraviolet method as described by the manufacturer. For analysis of bacteria in tissue homogenates a non-competing anti-S. aureus antibody (rF1 (ref. 38)) was conjugated to Alexa-647 to distinguish S. aureus from similar sized particles. Test antibodies were examined at a range of doses from 80 ng ml−1 to 50 μg ml−1. Flow cytometry was performed using a Beckton Dickson FACS ARIA (BD Biosciences) and analysis was performed using FlowJo analysis software (Flow Jo LLC). The anti-β-WTA antibody Fab fragment was expressed in Escherichia coli and purified on Protein G Sepharose followed by SP sepharose cation exchange and size-exclusion chromatography. Antibody was concentrated to 30 mg ml−1 in MES buffer (20 mM MES pH 5.5, 150 mM NaCl) and mixed with a 2:1 mol/mol ratio of the WTA analogue (diluted in water) for crystallization trials. Sparse matrix crystallization screening provided initial hits in PEG-8000 based conditions, which were further optimized to provide diffraction quality crystals. Ultimately, data were collected on a crystal grown by the vapour diffusion method in a sitting drop containing 0.5 μl protein and 0.5 μl 0.08 M sodium cacodylate pH 6.5, 0.16 M calcium acetate, 14.4% PEG-8000, and 20% glycerol. Crystals were cryo-protected in mother liquor, flash frozen in liquid nitrogen, and stored for data collection at 100 K. Data were collected to 1.7 Å at beamline 22ID at the Advanced Photon Source (APS) under cryo-cooled conditions (100 K) at a wavelength of 1.0 Å. Data were reduced using HKL2000 and SCALEPACK in the space group P2 2 2 , with unit cell parameters of a = 63.7 Å, b = 111.4Å, c = 158.4 Å (see Extended Data Table 1 for processing statistics). The structure was solved by sequential molecular replacement searches using Fab constant and variable regions (Protein Data Bank accession 4177) as individual search models. Iterative rounds of manual model adjustment with COOT followed by simulated annealing, coordinate, and b-factor refinement with Phenix and BUSTER (Global Phasing) gave a final model with R/R values of 20.6% and 23.7% respectively. Ramachandran statistics calculated by MolProbity indicate that 97.2% of the model residues lie in favoured regions, with 0.5% outliers. Synthesis of dibenzyl phosphorochloridate. A mixture of NCS (3.5 g, 26.6 mmol) was suspended in toluene (80 ml). Then dibenzyl phosphonate (2.0 g, 7.6 mmol) was added. The mixture was stirred at room temperature overnight. The white solid was filtered off and the organic phase was evaporated to give dibenzyl phosphorochloridate (1; 2.1 g, 96%) as light yellow oil. 1H NMR (300 MHz, CDCl , 25 °C) δ 7.36 (s, 10H), 5.20 (m, 4H). Synthesis of 4-O-(2-acetamido-3,4,6-tri-O-acetyl-2-deoxy-β-d-glucopyranosyl)-1-O-acetyl-d-ribitol-5-dibenzylphosphate. A mixture of 2 (described in ref. 44) (500 mg, 0.95 mmol) dissolved in pyridine (12 ml) was cooled to −30 °C and 1 (described ref. 44) (595 mg, 2.0 mmol) was added, stirring for 2 h at −30 °C and warmed to room temperature for 4 h. The mixture was added to H O, and concentrated in vacuo. The residue was purified by column chromatography (silica gel: 200 to ~300 mesh; dichloromethane: methanol in a 30:1 as eluent) to give 4-O-(2-acetamido-3,4,6-tri-O-acetyl-2-deoxy-β-d-glucopyranosyl)-1-O-acetyl-d-ribitol-5-dibenzylphosphate (3; 190 mg, 24%) as light yellow solid. 1H NMR (300 MHz, Acetone-d , 25 °C) δ 7.29–7.23 (m, 10H), 7.08 (d, 1H), 5.08 (t, 1H), 4.99–4.78 (m, 6H), 4.31–3.97 (m, 8H), 3.82–3.63 (m, 3H), 1.88 (s, 3H), 1.86 (s, 6H), 1.79 (s, 3H), 1.69 (s, 3H). LC/MS (m/z) ES+ 784 [M+H]+. Synthesis of 4-O-(2-acetamido-3,4,6-tri-O-acetyl-2-deoxy-β-d-glucopyranosyl)-1-O-acetyl-d-ribitol-5-phosphate. A mixture of 3 (150 mg, 0.19 mmol) dissolved in MeOH (6 ml) was hydrogenated over 10% Pd/C (20 mg) for 2 h at room temperature. Then the mixture was filtered, and the filtrate was evaporated to give 4-O-(2-acetamido-3,4,6-tri-O-acetyl-2-deoxy-β-d-glucopyranosyl)-1-O-acetyl-d-ribitol-5-phosphate (4; 100 mg) as light yellow oil. LC/MS (m/z) ES+ 604 [M+H]+. Synthesis of 4-O-(2-acetamido-2-deoxy-β-d-glucopyranosyl)-d-ribitol-5-phosphate (5). A mixture of 4 (80 mg, 0.16 mmol) dissolved in MeOH (10 ml) was cooled to 5 °C and K CO (30 mg, 0.21 mmol) was added and stirred at 5 °C for 3 h. The reaction was then quenched with 1 N HCl, and concentrated in vacuo. The crude product was purified by gel filtration (LH-20, MeOH) to give 4-O-(2-acetamido-2-deoxy-β-d-glucopyranosyl)-d-ribitol-5-phosphate (5; 13.3 mg, 23%) as a white solid 1H NMR (300 MHz, MeOH-d , 25 °C) δ 4.62 (d, 1H), 4.30–4.02 (m, 3H), 3.92–3.32 (m, 9H), 2.03 (s, 3H). LC/MS (m/z) ES+ 436 [M+H]+. S. aureus (USA300) was taken from an overnight stationary phase culture, washed once in PBS and suspended at 1 × 107 c.f.u. ml−1 in PBS with no antibiotic or with 1 × 10−6 M antibiotic in a 10 ml volume in 50 ml polypropylene centrifuge tubes. The bacteria were incubated at 37 °C overnight with shaking. At each time point, three 1 ml samples were removed from each culture and centrifuged to collect the bacteria. Bacteria were washed once with PBS to remove the antibiotic and the total number of surviving bacteria was determined by plating serial dilutions of the bacteria on agar plates. S. aureus (USA300) was taken from an overnight stationary phase culture, washed once in tryptic soy broth (TSB) and then adjusted to a final concentration of 1 × 107 c.f.u. ml−1 in a total volume of 10 ml of either TSB or TSB with ciprofloxicin (0.05 mM). Cultures were incubated with shaking at 37 °C for 6 h and then the second antibiotic, either rifampicin (1 μg ml−1) or the rifalogue (1 μg ml−1) was added. At the indicated times, samples were removed from each culture, washed once with PBS to remove the antibiotic and re-suspended in PBS. The total number of surviving bacteria was determined by plating serial dilutions of the bacteria on agar plates. At the final time point the remainder of each culture was collected and plated. To quantify the amount of active antibiotic released from AACs after treatment with cathepsin B, AACs were diluted to 200 μg ml−1 in cathepsin buffer (20 mM sodium acetate, 1 mM EDTA, 5 mM l-cysteine, pH 5). Cathepsin-B (from bovine spleen, Sigma C7800) was added at 10 μg ml−1 and the samples were incubated for 1 h at 37 °C. As a control, AACs were incubated in buffer alone. The reaction was stopped by addition of 9 volumes of bacterial growth media, TSB pH 7.4. To estimate the total release of active antibiotic, serial dilutions of the reaction mixture were made in quadruplicate in TSB in 96-well plates and MRSA (USA300) was added to each well at a final density of 2 × 103 c.f.u. ml−1. The cultures were incubated overnight at 37 °C with shaking and bacterial growth was measured by reading absorbance at 630 nM using a plate reader. We synthesized and conjugated a maleimide FRET peptide to the anti-β-WTA THIOMAB antibody. We used a FRET pair of tetramethylrhodamine (TAMRA) and fluorescein. The maleimide FRET peptide was synthesized by standard Fmoc solid-phase chemistry using a PS3 peptide synthesizer (Protein Technologies; B.-C.L., M.D. and R.V., manuscript in preparation)27. Briefly, 0.1 mmol of Rink amide resin was used to generate C-terminal carboxamide. We used a Fmoc-Lys(Mtt)-OH at the N- and C-terminal residues in order to remove the Mtt group on the resin and carry out additional side-chain chemistry to attach TAMRA and fluorescein. The sequence of Val-Cit-Leu was added between the FRET pair as a cathepsin-cleavable spacer. The crude maleimide FRET peptide or maleimidocarproyl-K(TAMRA)-G-V-Cit-L-K(fluorescein) cleaved off from the resin was subjected to further purification by reverse-phase HPLC with a Jupiter 5u C4 column (5 μm, 10 mm × 250 mm; Phenomenex). Our FRET probe allows monitoring not only of the intracelluar trafficking of the antibody conjugate, but also the processing of the linker in the phagolysosome. The intact antibody conjugate fluoresces only in red due to the fluorescence resonance energy transfer from the donor. However, upon the substrate cleavage of the FRET peptide in the phagolysosome, the green fluorescence from the donor is expected to appear. Murine peritoneal macrophages were plated on chamber slides (Ibidi, catalogue 80826) in complete media as described for the macrophage intracellular killing assay. USA300 was labelled with Cell Tracker Violet (Invitrogen C10094) at 100 μg ml−1 in PBS 0.1% BSA by incubation for 30 min at 37 °C. The labelled bacteria were opsonized with the anti-β-WTA-FRET probe by incubation for 1 h in HB buffer. Macrophages were washed once immediately before addition of the opsonized bacteria, and bacteria were added to cells at 1 × 107 bacteria per ml. For no-phagocytosis controls, the macrophages were pre-treated with 60 nM Latrunculin A (Calbiochem) for 30 min before and during phagocytosis. The slides were placed on the microscope immediately after addition of bacteria to the cells and movies were acquired with a Leica SP5 confocal microscope equipped with an environmental chamber with CO and temperature controllers from Ludin. The images were captured every minute for a total time of 30 min using a Plan APO CS ×40, N.A: 1.25, oil immersion lens, and the 488 nm and 543 nm laser lines to excite Alexa-488 and TAMRA, respectively. Phase images were also recorded using the 543 nm laser line. Primary murine peritoneal macrophages or RAW 264.7 cells (purchased from ATCC) were infected in 24-well tissue culture dishes as described later for the intracellular killing assay with MRSA opsonized with AAC at 100 μg ml−1 in HB. The RAW 264.7 cells were used without further authentication or testing for mycoplasma contamination. After phagocytosis was complete, the cells were washed and 250 μl of complete media plus gentamycin was added to wells and the cells were incubated for the indicated time points. At each time point, the supernatant and cellular fractions were collected followed by acetonitrile (ACN) addition to 75% final concentration and incubated for 30 min. Cell and supernatant extracts were lyophilized by evaporation under N2 (TurboVap; Biotage) and reconstituted in 100 μl of 50% ACN, filtered using a 0.45 glass fibre filter plate (Phenomenex) and analysed by LC/MS/MS as follows. The rifalogue was separated on an Acquity UPLC (Waters Corporation) under gradient elution using a Phenomenex Kinetex XB-C18 column (100 Å, 50 × 2.1 mm internal diameter, 2.6 μm particle size). The column was maintained at room temperature. The mobile phase was a mixture of 10 mM ammonium acetate in water containing 0.1% formic acid (A) and 90% acetonitrile (B) at a flow rate of 1 ml min−1. The rifalogue was eluted with a gradient of 3–98% B over 1 min, followed by 0.8 min at 98% B, then 0.7 min of 3% B to re-equilibrate the column. The injection volume was 10 μl. The Triple Quad 6500 mass spectrometer (Ab Sciex) was operated in a positive ion multiple reaction-monitoring (MRM) mode. The rifalogue precursor (Q1) ion monitored was 927.6 m/z and the product (Q3) ion monitored was 895.2 m/z with collision energy at 27 eV and declustering potential at 191 V. The MS/MS setting parameters were as follows: ion spray voltage, 5,500 V; curtain gas, 40 psi; nebulizer gas (GS1), 35 psi, (GS2), 50 psi; temperature, 600 °C; and dwell time, 150 ms. Linear calibration curves were obtained for 0.41–100 nM concentration range by spiking rifalogue into cell or supernatant fractions (lacking MRSA or AAC) that were treated similarly to samples. Concentrations of rifalogue were calculated with MultiQuant software (Ab Sciex). Non-phagocytic cell types. MG63 (CRL-1427) and A549 (CCL185) cell lines were obtained from ATCC and maintained in RPMI 1640 tissue culture media supplemented with 10 mM HEPES and 10% fetal calf serum (RPMI-10). HUVEC cells were obtained from Lonza and maintained in EGM endothelial cell complete media (Lonza). HBMEC cells (catalogue #1000) and ECM media (catalogue #1001) were obtained from ScienceCell Research Labs. The cells were used without further authentication or testing for mycoplasma contamination. Murine macrophages. Peritoneal macrophages were isolated from the peritoneum of 6–8-week-old Balb/c mice (Charles River Laboratories). To increase the yield of macrophages, mice were pre-treated by intraperitoneal injection with 1 ml of thioglycolate media (Becton Dickinson). The thioglycolate media was prepared at a concentration of 4% in water, sterilized by autoclaving, and aged for 20 days to 6 months before use. Peritoneal macrophages were harvested 4 days after treatment with thioglycolate by washing the peritoneal cavity with cold PBS. Macrophages were plated in DMEM supplemented with 10% fetal calf serum, and 10 mM HEPES, without antibiotics, at a density of 4 × 105 cells well−1 in 24-well culture dishes. Macrophages were cultured overnight to permit adherence to the plate. Human M2 macrophages. CD14+ monocytes were purified from normal human blood using a Monocyte Isolation Kit II (Miltenyi, catalogue 130-091-153) and plated at 1.5 × 105 cells cm−2 on tissue culture dishes pre-coated with fetal calf serum (FCS) and cultured in RPMI 1640 media with 20% FCS plus 100 ng ml−1 rhM-CSF. Media was refreshed on day 1 and on day 7, the media was changed to 5% serum plus 20 ng ml−1 IL-4. Macrophages were used 18 h later. Assay protocol. In all experiments bacteria were cultured in TSB. To assess intracellular killing with AACs, USA300 was taken from an exponentially growing culture and washed in HB. AACs or antibodies were diluted in HB (Hanks balanced salt solution supplemented with 10 mM HEPES and 0.1% BSA) and incubated with the bacteria for 1 h to permit antibody binding to the bacteria (opsonization), and the opsonized bacteria were used to infect macrophages at a ratio of 10–20 bacteria per macrophage (4 × 106 bacteria in 250 μl of HB per well). Macrophages were pre-washed with serum-free DMEM media immediately before infection, and infected by incubation at 37 °C in a humidified tissue culture incubator with 5% CO to permit phagocytosis of the bacteria. After 2 h, the infection mix was removed and replaced with normal growth media (DMEM supplemented with 10% FCS, 10 mM HEPES) and gentamycin was added at 50 μg ml−1 to prevent growth of extracellular bacteria45. At the end of the incubation period, the macrophages were washed with serum-free media, and the cells were lysed in HB supplemented with 0.1% Triton-X (lyses the macrophages without damaging the intracellular bacteria). Serial dilutions of the lysate were made in PBS solution supplemented with 0.05% Tween-20 (to disrupt aggregates of bacteria) and the total number of surviving intracellular bacteria was determined by plating on tryptic soy agar with 5% defibrinated sheep blood. Cell wall preparations (CWPs) were generated from protein-A-deficient S. aureus by incubating 40 mg of pelleted bacteria per ml of 10 mM Tris-HCl (pH 7.4) supplemented with 30% raffinose, 100 μg ml−1 of lysostaphin (Cell Sciences), and EDTA-free protease inhibitor cocktail (Roche), for 30 min at 37 °C. The lysates were centrifuged at 11,600g for 5 min, and the supernatants containing cell wall components were collected. ELISA experiments were performed using standard protocols. Briefly, plates were pre-coated with CWP and then incubated with human IgG preparations: purified human IGIV Immune Globulin (ASD Healthcare), pooled serum from healthy donors or from MRSA patients. The concentrations of anti-staphylococcal IgG present in the serum or purified IgG were calculated by using a calibration curve that was generated with known concentrations of anti-peptidoglycan mAb (4479) against peptidoglycan. Seven-week-old female mice, Balb/c, were obtained from Jackson West, or SCID mice were obtained from Charles River Laboratories. Infections were carried out by intravenous injection into the tail vein. SCID-huIgG model: CB17.SCID mice were reconstituted with IGIV Immune Globulin (ASD Healthcare) using a dosing regimen optimized to achieve constant serum levels of >10 mg ml−1 of human IgG. IGIV was administered with an initial intravenous dose of 30 mg per mouse followed by a second dose of 15 mg per mouse by intraperitoneal injection after 6 h, and subsequent daily dosings of 15 mg per mouse by intraperitoneal injection for 3 consecutive days. Mice were infected 4 h after the first dose of IGIV with 2 × 107 c.f.u. of MRSA diluted in PBS by intravenous injection. The wild-type USA300, protein-A-sufficient strain was used for all in vivo experiments. Mice that received vancomycin were treated with twice daily intraperitoneal injections of 110 mg kg−1 of vancomycin starting between 6 and 24 h after infection for the duration of the study. Experimental therapeutics (AAC, anti-MRSA antibodies or free rifalogue antibiotic) were diluted in PBS and administered with a single intravenous injection 30 min to 24 h after infection. All mice were killed on day 4 after infection, and kidneys were harvested in 5 ml of PBS. The tissue samples were homogenized using a GentleMACS dissociator (Miltenyi Biotec). The total number of bacteria recovered per mouse (two kidneys) was determined by plating serial dilutions of the tissue homogenate in PBS 0.05% Tween on tryptic soy agar with 5% defibrinated sheep blood. All experiments were performed on biological replicates. Sample size for each experimental group per condition is reported in appropriate figure legends and Methods. For cell culture experiments, sample size was not predetermined, and all samples were included in the analysis. In animal experiments no statistical methods were used to predetermine sample size (n = number of mice per group), and all animals were used for analysis unless the mice died or had to be euthanized when found moribund. These cases are annotated in the figures. The mice were not randomized after infection, and the investigators were not blinded to outcome assessment. When appropriate, statistically significant differences between control and experimental groups were determined using Mann–Whitney tests.

Mao X.,Northeastern University | Mao X.,Wuhan University | Wang J.,Geosyntec Consultants | Ciblak A.,Northeastern University | And 5 more authors.
Journal of Hazardous Materials | Year: 2012

Successful bioremediation of contaminated soils is controlled by the ability to deliver bioremediation additives, such as bacteria and/or nutrients, to the contaminated zone. Because hydraulic advection is not practical for delivery in clays, electrokinetic (EK) injection is an alternative for efficient and uniform delivery of bioremediation additive into low-permeability soil and heterogeneous deposits. EK-enhanced bioaugmentation for remediation of clays contaminated with chlorinated solvents is evaluated. Dehalococcoides (Dhc) bacterial strain and lactate ions are uniformly injected in contaminated clay and complete dechlorination of chlorinated ethene is observed in laboratory experiments. The injected bacteria can survive, grow, and promote effective dechlorination under EK conditions and after EK application. The distribution of Dhc within the clay suggests that electrokinetic transport of Dhc is primarily driven by electroosmosis. In addition to biodegradation due to bioaugmentation of Dhc, an EK-driven transport of chlorinated ethenes is observed in the clay, which accelerates cleanup of chlorinated ethenes from the anode side. Compared with conventional advection-based delivery, EK injection is significantly more effective for establishing microbial reductive dechlorination capacity in low-permeability soils. © 2012 Elsevier B.V.

Steffensen C.,Aarhus University Hospital | Maegbaek M.L.,Aarhus University Hospital | Laurberg P.,Aalborg Hospital | Andersen M.,University of Southern Denmark | And 4 more authors.
Journal of Clinical Endocrinology and Metabolism | Year: 2012

Background: Increased risk of heart valve disease during treatment with certain dopamine agonists, such as cabergoline, has been observed in patients with Parkinson's disease. The same compound is used to treat hyperprolactinemia, but it is unknown whether this also associates with heart valve disease. Objectives: The objective of the study was to assess the incidence of diagnosed heart valve disease and cardiac valve surgery among patients with hyperprolactinemia, compared with a general population cohort in Denmark. Design: This was a nationwide, population-based, cohort study based on a nationwide hospital registry. Methods: We identified 2381 hyperprolactinemia patients with a first-time diagnosis recorded from 1994 through 2010 in the registry, with no previous hospital diagnosis of heart valve disease. Each patient was compared with 10 age- and gender-matched comparison cohort members from the general population. The association between hyperprolactinemia and heart valve disease was analyzed with Cox's proportional hazards regression, controlling for potential confounding factors. To assess the risk of cardiac valve surgery and avoid ascertainment bias, a subanalysis was made in a cohort of 2,387 hyperprolactinemia patients with no previous cardiac valve surgery and 23,870 comparison cohort members. Results: Nineteen hyperprolactinemic patients (0.80%) were diagnosed with heart valve disease during a total of 17,759.8 yr of follow-up, compared with 75 persons (0.31%) in the comparison cohort during 179,940.6 yr of follow-up [adjusted hazard ratio 2.27 (95% confidence interval 1.35-3.82)]. Seven of the 10 patients treated with cabergoline and diagnosed with heart valve disease were asymptomatic and diagnosed on the basis of an echocardiography performed as a safety measure. However, only two patients with hyperprolactinemia (0.08%) underwent surgery, compared with 28 persons in the general population cohort (0.12%) [adjusted hazard ratio 0.55 (95% confidence interval 0.13-2.42)]. Conclusions: Data from the present register-based study do not support that hyperprolactinemia or its treatmentis-associated with an increased risk of clinically significant heart valve disease. Copyright © 2012 by The Endocrine Society.

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