Bereavement and marriage are associated with antibody response to influenza vaccination in the elderly

Stressful life events exposure including bereavement, an event commonly experienced by elderly people, social support, marital status and satisfaction were examined in relation to antibody response to the annual trivalent influenza vaccination in an elderly community sample (N = 184). Antibody response was assessed at baseline, and at one and 12 months following vaccination. Taking into account baseline antibody titer, overall life events exposure and social support were not associated with response to any of the influenza strains. However, bereavement in the year prior to vaccination was negatively associated with the one-month response to the A/Panama and B/Shangdong strains. Being married and having higher marital satisfaction was also associated with higher peak responses to the A/Panama influenza strain at one month. The positive association between marital satisfaction and A/Panama response was particularly evident in the younger half of the married sample. These associations largely withstood adjustment for potential confounders. Thus, in the elderly, peak antibody response was associated with bereavement and marriage, and not the more general factors, life events and social support, related to antibody response in student samples. This suggests the importance of taking a life course approach to examining relationships between psychosocial factors and immunity, and that interventions to modify the impact of these factors should address those most salient for each age group

Gut Microbiome Perturbations Induced by Bacterial Infection Affect Arsenic Biotransformation

Exposure to arsenic affects large human populations worldwide and has been associated with a long list of human diseases, including skin, bladder, lung, and liver cancers, diabetes, and cardiovascular disorders. In addition, there are large individual differences in susceptibility to arsenic-induced diseases, which are frequently associated with different patterns of arsenic metabolism. Several underlying mechanisms, such as genetic polymorphisms and epigenetics, have been proposed, as these factors closely impact the individuals’ capacity to metabolize arsenic. In this context, the role of the gut microbiome in directly metabolizing arsenic and triggering systemic responses in diverse organs raises the possibility that perturbations of the gut microbial communities affect the spectrum of metabolized arsenic species and subsequent toxicological effects. In this study, we used an animal model with an altered gut microbiome induced by bacterial infection, 16S rRNA gene sequencing, and inductively coupled plasma mass spectrometry-based arsenic speciation to examine the effect of gut microbiome perturbations on the biotransformation of arsenic. Metagenomics sequencing revealed that bacterial infection significantly perturbed the gut microbiome composition in C57BL/6 mice, which in turn resulted in altered spectra of arsenic metabolites in urine, with inorganic arsenic species and methylated and thiolated arsenic being perturbed. These data clearly illustrated that gut microbiome phenotypes significantly affected arsenic metabolic reactions, including reduction, methylation, and thiolation. These findings improve our understanding of how infectious diseases and environmental exposure interact and may also provide novel insight regarding the gut microbiome composition as a new risk factor of individual susceptibility to environmental chemicals.National Institute of Environmental Health Sciences (Massachusetts Institute of Technology. Center for Environmental Health Sciences Grant P30 ES002109)National Institute of Environmental Health Sciences (University of North Carolina. Center for Environmental Health and Susceptibility Grant P30 ES010126

Overturning established chemoselectivities : selective reduction of arenes over malonates and cyanoacetates by photoactivated organic electron donors

The prevalence of metal-based reducing reagents, including metals, metal complexes, and metal salts, has produced an empirical order of reactivity that governs our approach to chemical synthesis. However, this reactivity may be influenced by stabilization of transition states, intermediates, and products through substrate-metal bonding. This article reports that in the absence of such stabilizing interactions, established chemoselectivities can be overthrown. Thus, photoactivation of the recently developed neutral organic superelectron donor 5 selectively reduces alkyl-substituted benzene rings in the presence of activated esters and nitriles, in direct contrast to metal-based reductions, opening a new perspective on reactivity. The altered outcomes arising from the organic electron donors are attributed to selective interactions between the neutral organic donors and the arene rings of the substrates

Going to sleep in the supine position is a modifiable risk factor for late pregnancy stillbirth; findings from the New Zealand multicentre stillbirth case-control study

Objective: Our objective was to test the primary hypothesis that maternal non-left, in particular supine going-to-sleep position, would be a risk factor for late stillbirth (≥28 weeks of gestation). Methods: A multicentre case-control study was conducted in seven New Zealand health regions, between February 2012 and December 2015. Cases (n=164) were women with singleton pregnancies and late stillbirth, without congenital abnormality. Controls (n=569) were women with on-going singleton pregnancies, randomly selected and frequency matched for health region and gestation. The primary outcome was adjusted odds of late stillbirth associated with self-reported going-to-sleep position, on the last night. The last night was the night before the late stillbirth was thought to have occurred or the night before interview for controls. Going to- sleep position on the last night was categorised as: supine, left-side, right-side, propped or restless. Multivariable logistic regression adjusted for known confounders. Results: Supine going-to-sleep position on the last night was associated with increased late stillbirth risk (adjusted odds ratios (aOR) 3.67, 95% confidence interval (CI) 1.74 to 7.78) with a population attributable risk of 9.4%. Other independent risk factors for late stillbirth (aOR, 95% CI) were: BMI (1.04, 1.01 to 1.08) per unit, maternal age ≥40 (2.88, 1.31 to 6.32), birthweight <10th customised centile (2.76, 1.59 to 4.80), and <6 hours sleep on the last night (1.81, 1.14 to 2.88). The risk associated with supine-going-to sleep position was greater for term (aOR 10.26, 3.00 to 35.04) than preterm stillbirths (aOR 3.12, 0.97 to 10.05). Conclusions: Supine going-to-sleep position is associated with a 3.7 fold increase in overall late stillbirth risk, independent of other common risk factors. A public health campaign encouraging women not to go-to-sleep supine in the third trimester has potential to reduce late stillbirth by approximately 9%

Genome-Wide Progesterone Receptor Binding: Cell Type-Specific and Shared Mechanisms in T47D Breast Cancer Cells and Primary Leiomyoma Cells

Progesterone, via its nuclear receptor (PR), exerts an overall tumorigenic effect on both uterine fibroid (leiomyoma) and breast cancer tissues, whereas the antiprogestin RU486 inhibits growth of these tissues through an unknown mechanism. Here, we determined the interaction between common or cell-specific genome-wide binding sites of PR and mRNA expression in RU486-treated uterine leiomyoma and breast cancer cells.ChIP-sequencing revealed 31,457 and 7,034 PR-binding sites in breast cancer and uterine leiomyoma cells, respectively; 1,035 sites overlapped in both cell types. Based on the chromatin-PR interaction in both cell types, we statistically refined the consensus progesterone response element to G•ACA• • •TGT•C. We identified two striking differences between uterine leiomyoma and breast cancer cells. First, the cis-regulatory elements for HSF, TEF-1, and C/EBPα and β were statistically enriched at genomic RU486/PR-targets in uterine leiomyoma, whereas E2F, FOXO1, FOXA1, and FOXF sites were preferentially enriched in breast cancer cells. Second, 51.5% of RU486-regulated genes in breast cancer cells but only 6.6% of RU486-regulated genes in uterine leiomyoma cells contained a PR-binding site within 5 kb from their transcription start sites (TSSs), whereas 75.4% of RU486-regulated genes contained a PR-binding site farther than 50 kb from their TSSs in uterine leiomyoma cells. RU486 regulated only seven mRNAs in both cell types. Among these, adipophilin (PLIN2), a pro-differentiation gene, was induced via RU486 and PR via the same regulatory region in both cell types.Our studies have identified molecular components in a RU486/PR-controlled gene network involved in the regulation of cell growth, cell migration, and extracellular matrix function. Tissue-specific and common patterns of genome-wide PR binding and gene regulation may determine the therapeutic effects of antiprogestins in uterine fibroids and breast cancer

Association between Regulator of G Protein Signaling 9–2 and Body Weight

Regulator of G protein signaling 9–2 (RGS9–2) is a protein that is highly enriched in the striatum, a brain region that mediates motivation, movement and reward responses. We identified a naturally occurring 5 nucleotide deletion polymorphism in the human RGS9 gene and found that the mean body mass index (BMI) of individuals with the deletion was significantly higher than those without. A splicing reporter minigene assay demonstrated that the deletion had the potential to significantly decrease the levels of correctly spliced RGS9 gene product. We measured the weights of rats after virally transduced overexpression of RGS9–2 or the structurally related RGS proteins, RGS7, or RGS11, in the nucleus accumbens (NAc) and observed a reduction in body weight after overexpression of RGS9–2 but not RGS7 or 11. Conversely, we found that the RGS9 knockout mice were heavier than their wild-type littermates and had significantly higher percentages of abdominal fat. The constituent adipocytes were found to have a mean cross-sectional area that was more than double that of corresponding cells from wild-type mice. However, food intake and locomotion were not significantly different between the two strains. These studies with humans, rats and mice implicate RGS9–2 as a factor in regulating body weight.National Institute of Mental Health (U.S.) (R41MH78570 award)National Center for Research Resources (U.S.) (Rhode Island IDeA Network of Biomedical Research Excellence (RI-INBRE) Award P20RR016457-10

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L