Effect of Thiotriazinone Impurity on Insoluble Microparticle Generation Associated with Ceftriaxone-calcium Salt Precipitation in Original (Rocephin®) and Japanese Generic Ceftriaxone Products

This study examined the effect of thiotriazinone impurity on the generation of insoluble microparticles (IMPs) associated with ceftriaxone-calcium salt precipitation in original (Rocephin®) and Japanese generic ceftriaxone (A; Sawai, B; Nichi-Iko) products when mixed with Ca2＋ 4.3mEq/l. We found that the generation rate of IMPs associated with ceftriaxone-calcium salt precipitation among the three ceftriaxone products tested was in the order of generic (A)＜original＜generic (B), as assessed by light obscuration particle counting. Typically, after 60 min, one of the generic ceftriaxone (B)-calcium mixtures was highly opaque with numerous aggregates of milky-white precipitates, the original ceftriaxone-calcium mixture exhibited noticeable IMPs, and the second generic ceftriaxone (A)-calcium mixture was transparent. The levels of thiotriazinone contaminants, known to be a major impurity in ceftriaxone products, were determined by HPLC and found to be in the order of generic A＞original＞generic B. Moreover, the addition of a small amount of thiotriazinone into the generic ceftriaxone (B)-calcium mixture significantly decreased the amount of IMPs, suggesting that the impurity retards ceftriaxone-calcium crystal growth. We thus concluded that the thiotriazinone impurity acts as a suppressive factor of ceftriaxone-calcium salt precipitation, and that the high level of thiotriazinone impurity in the ceftriaxone (B) product could underlie its lowest rate of IMP generation when mixed with calcium. We thus recommend caution regarding the clinical risk of ceftriaxone-calcium compatibility due to impurity contamination in ceftriaxone products

Differences in coronary plaque characteristics between patients with and those without peripheral arterial disease.

INTRODUCTION Cardiovascular mortality of patients with combined peripheral arterial disease (PAD) and coronary artery disease (CAD) is twice as high as that in those with either disease alone. It is known that patients with PAD undergoing percutaneous coronary intervention have a higher incidence of adverse cardiac events such as myocardial infarction or target vessel revascularization. OBJECTIVE In this study, we compared the detailed characteristics of culprit and nonculprit plaques between patients with and those without PAD using optical coherence tomography. PATIENTS AND METHODS We performed propensity score matching using the following variables: (i) age; (ii) sex; (iii) clinical presentation; (iv) diabetes mellitus; (v) hyperlipidemia; (vi) smoking; (vii) hypertension; (viii) BMI; and (ix) coronary lesion location. Finally, we matched 34 culprit lesions and 30 nonculprit lesions in patients with PAD to 68 culprit lesions and 60 nonculprit lesions in patients without PAD (1 : 2 ratio). RESULTS In culprit lesions, PAD patients when compared with those without PAD had a higher prevalence of lipid-rich plaque (73.5 vs. 51.5%; P=0.033), higher lipid index (1744±1110 vs. 1246±656; P=0.043), calcification (79.4 vs. 58.8%; P=0.039), macrophage accumulation (70.6 vs. 48.5%; P=0.034), and cholesterol crystals (32.4 vs. 10.3%; P=0.006). In nonculprit lesions, PAD patients had a higher prevalence of calcification (76.7 vs. 55.0%; P=0.046), macrophage accumulation (63.3 vs. 38.3%; P=0.025), and cholesterol crystals (36.7 vs. 16.7%; P=0.034). CONCLUSION Our study suggests greater coronary plaque vulnerability in both culprit and nonculprit lesions in patients with PAD. This observation underscores the need for more aggressive risk management in patients with combined PAD and coronary artery disease

Pyridoxal 5′-phosphate and related metabolites in hypophosphatasia: Effects of enzyme replacement therapy

Objective To investigate the utility of serum pyridoxal 5′-phosphate (PLP), pyridoxal (PL), and 4-pyridoxic acid (PA) as a diagnostic marker of hypophosphatasia (HPP) and an indicator of the effect of, and patient compliance with, enzyme replacement therapy (ERT), we measured PLP, PL, and PA concentrations in serum samples from HPP patients with and without ERT. Methods Blood samples were collected from HPP patients and serum was frozen as soon as possible (mostly within one hour). PLP, PL, and PA concentrations were analyzed using high-performance liquid chromatography with fluorescence detection after pre-column derivatization by semicarbazide. We investigated which metabolites are associated with clinical phenotypes and how these metabolites change with ERT. Results Serum samples from 20 HPP patients were analyzed. The PLP-to-PL ratio and PLP concentration were elevated in all HPP patients. They correlated negatively with serum alkaline phosphatase (ALP) activity and showed higher values in more severe phenotypes (perinatal severe and infantile HPP) compared with other phenotypes. PL concentration was reduced only in perinatal severe HPP. ERT reduced the PLP-to-PL ratio to mildly reduced or low-normal levels and the PLP concentration was reduced to normal or mildly elevated levels. Urine phosphoethanolamine (PEA) concentration did not return to normal levels with ERT in most patients. Conclusions The serum PLP-to-PL ratio is a better indicator of the effect of ERT for HPP than serum PLP and urine PEA concentrations, and a PLP-to-PL ratio of <4.0 is a good indicator of the effect of, and patient compliance with, ERT

Clinical and laboratory predictors for plaque erosion in patients with acute coronary syndromes

Background-—Plaque erosion is responsible for 25% to 40% of patients with acute coronary syndromes (ACS). Recent studies suggest that anti-thrombotic therapy without stenting may be an option for this subset of patients. Currently, however, an invasive procedure is required to make a diagnosis of plaque erosion. The aim of this study was to identify clinical or laboratory predictors of plaque erosion in patients with ACS to enable a diagnosis of erosion without additional invasive procedures. Methods and Results-—Patients with ACS who underwent optical coherence tomography imaging were selected from 11 institutions in 6 countries. The patients were classified into plaque rupture, plaque erosion, or calcified plaque, and predictors were identified using multivariable logistic modeling. Among 1241 patients with ACS, 477 (38.4%) patients were found to have plaque erosion. Plaque erosion was more frequent in non–ST-segment elevation-ACS than in ST-segment–elevation myocardial infarction (47.9% versus 29.8%, P=0.0002). Multivariable logistic regression models showed 5 independent parameters associated with plaque erosion: age 15.0 g/dL, and normal renal function. When all 5 parameters are present in a patient with non–ST-segment elevation-ACS, the probability of plaque erosion increased to 73.1%. Conclusions-—Clinical and laboratory parameters associatedwith plaque erosion are explored in this retrospective registry study. These parametersmay be useful to identify the subset ofACS patients with plaque erosion and guide themto conservativemanagement without invasive procedures. The results of this exploratory analysis need to be confirmed in large scale prospective clinical studiesDr. Jang has received an educational grant from Abbott Vascular and Medicure. Dr. Adriaenssens has received grants and consulting fees from Abbott Vascula

Comparison of Serum HBsAg Quantitation by Four Immunoassays, and Relationships of HBsAg Level with HBV Replication and HBV Genotypes

BACKGROUND: The decline in hepatitis B virus surface antigen (HBsAg) may be an early predictor of the viral efficacy of Hepatitis B virus (HBV) therapy. The HBsAg levels obtained by different immunoassays now need comparing and the relationships between levels of HBsAg and HBV DNA alongside HBsAg and genotype must be evaluated. METHODOLOGY/PRINCIPAL FINDINGS: HBsAg levels were compared among 80 patients using the Abbott Architect assay, a commercial immunoassay approved for HBsAg detection and quantitation, and three other assays derived from immunoassays approved for HBsAg detection (manufactured by Diasorin, Bio-Rad and Roche). Good correlation was found between the Abbot vs. Diasorin, Bio-Rad and Roche assays with narrow 95% limits of agreement and small mean differences: -0.06 to 0.11, -0.09 log(10) IU/mL; -0.57 to 0.64, -0.04 log(10) IU/mL; -0.09 to 0.45, -0.27 log(10) IU/mL, respectively. These agreements were not affected by genotypes A or D. HBsAg was weakly correlated with HBV DNA, whatever the HBsAg assay used: Abbott, ρ = 0.36 p = 0.001, Diasorin ρ = 0.34, p = 0.002; Bio-Rad ρ = 0.37, p<0.001; or Roche ρ = 0.41, p<0.001. This relationship between levels of HBsAg and HBV DNA seemed to depend on genotypes. Whereas HBsAg (Abbott assay) tended to correlate with HBV DNA for genotype A (ρ = 0.44, p = 0.02), no such correlation was significant for genotypes D (ρ = 0.29, p = 0.15). CONCLUSION/SIGNIFICANCE: The quantitation of HBsAg in routine clinical samples is comparable between the reference assay and the adapted assays with acceptable accuracy limits, low levels of variability and minimum discrepancy. While HBsAg quantitation is not affected by HBV genotype, the observed association between levels of HBsAg and HBV DNA seems genotype dependent

A Patient with Type 3 Autoimmune Polyglandular Syndrome who Developed Systemic Lupus Erythematosus 8 years after the Diagnosis of Autoimmune Hepatitis

Eight years prior to her present admission, a 61-year-old Japanese woman was diagnosed with autoimmune hepatitis, slowly progressive insulin-dependent diabetes mellitus, and chronic thyroiditis; she had been treated with oral prednisolone (PSL). After she suddenly discontinued PSL, she newly developed systemic lupus erythematosus. A combination therapy of oral PSL and intravenous cyclophosphamide resulted in remission. She was finally diagnosed with autoimmune polyglandular syndrome (APS) type 3 (3A ,3B, 3D), complicated with four different autoimmune diseases. Since patients with type 3 APS may present many manifestations over a long period of time, they should be carefully monitored

Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome.

The evolution of land flora transformed the terrestrial environment. Land plants evolved from an ancestral charophycean alga from which they inherited developmental, biochemical, and cell biological attributes. Additional biochemical and physiological adaptations to land, and a life cycle with an alternation between multicellular haploid and diploid generations that facilitated efficient dispersal of desiccation tolerant spores, evolved in the ancestral land plant. We analyzed the genome of the liverwort Marchantia polymorpha, a member of a basal land plant lineage. Relative to charophycean algae, land plant genomes are characterized by genes encoding novel biochemical pathways, new phytohormone signaling pathways (notably auxin), expanded repertoires of signaling pathways, and increased diversity in some transcription factor families. Compared with other sequenced land plants, M. polymorpha exhibits low genetic redundancy in most regulatory pathways, with this portion of its genome resembling that predicted for the ancestral land plant. PAPERCLIP

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

Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216