An a posteriori verification method for generalized real-symmetric eigenvalue problems in large-scale electronic state calculations

An a posteriori verification method is proposed for the generalized real-symmetric eigenvalue problem and is applied to densely clustered eigenvalue problems in large-scale electronic state calculations. The proposed method is realized by a two-stage process in which the approximate solution is computed by existing numerical libraries and is then verified in a moderate computational time. The procedure returns intervals containing one exact eigenvalue in each interval. Test calculations were carried out for organic device materials, and the verification method confirms that all exact eigenvalues are well separated in the obtained intervals. This verification method will be integrated into EigenKernel (https://github.com/eigenkernel/), which is middleware for various parallel solvers for the generalized eigenvalue problem. Such an a posteriori verification method will be important in future computational science.Comment: 15 pages, 7 figure

Secretion of an immunoreactive single-chain variable fragment antibody against mouse interleukin 6 by Lactococcus lactis

Epub 2016 Oct 8.Interleukin 6 (IL-6) is an important pathogenic factor in development of various inflammatory and autoimmune diseases and cancer. Blocking antibodies against molecules associated with IL-6/IL-6 receptor signaling are an attractive candidate for the prevention or therapy of these diseases. In this study, we developed a genetically modified strain of Lactococcus lactis secreting a single-chain variable fragment antibody against mouse IL-6 (IL6scFv). An IL6scFv-secretion vector was constructed by cloning an IL6scFv gene fragment into a lactococcal secretion plasmid and was electroporated into L. lactis NZ9000 (NZ-IL6scFv). Secretion of recombinant IL6scFv (rIL6scFv) by nisin-induced NZ-IL6scFv was confirmed by western blotting and was optimized by tuning culture conditions. We found that rIL6scFv could bind to commercial recombinant mouse IL-6. This result clearly demonstrated the immunoreactivity of rIL6scFv. This is the first study to engineer a genetically modified strain of lactic acid bacteria (gmLAB) that produces a functional anti-cytokine scFv. Numerous previous studies suggested that mucosal delivery of biomedical proteins using gmLAB is an effective and low-cost way to treat various disorders. Therefore, NZ-IL6scFv may be an attractive tool for the research and development of new IL-6 targeting agents for various inflammatory and autoimmune diseases as well as for cancer.ArticleAPPLIED MICROBIOLOGY AND BIOTECHNOLOGY. 101(1):341-349 (2017)journal articl

Synergistic oligodeoxynucleotide strongly promotes CpG-induced interleukin-6 production

[Background] :Bacterial genomes span a significant portion of diversity, reflecting their adaptation strategies; these strategies include nucleotide usage biases that affect chromosome configuration. Here, we explore an immuno-synergistic oligodeoxynucleotide (iSN-ODN, named iSN34), derived from Lactobacillus rhamnosusGG (LGG) genomic sequences, that exhibits a synergistic effect on immune response to CpG-induced immune activation. [Methods]: The sequence of iSN34 was designed based on the genomic sequences of LGG. Pathogen-free mice were purchased from Japan SLC and maintained under temperature- and light-controlled conditions. We tested the effects of iSN34 exposure in vitro and in vivo by assessing effects on mRNA expression, protein levels, and cell type in murine splenocytes. [Results]: We demonstrate that iSN34 has a significant stimulatory effect when administered in combination with CpGODN, yielding enhanced interleukin (IL)-6 expression and production. IL-6 is a pleotropic cytokine that has been shown to prevent epithelial apoptosis during prolonged inflammation. [Conclusions]: Our results are the first report of a bacterial-DNA-derived ODN that exhibits immune synergistic activity.The potent over-expression of IL-6 in response to treatment with the combination of CpG ODN and iSN34 suggests anew approach to immune therapy.This finding may lead to novel clinical strategies for the prevention or treatment of dysfunctions of the innate and adaptive immune systems.This work was supported by A-STEP (Adaptable and Seamless Technology Transfer Program through Target-driven R&D)

Impact of admission glycemia and glycosylated hemoglobin A1c on long-term clinical outcomes of non-diabetic patients with acute coronary syndrome

AbstractBackgroundAdmission glucose levels have proven to be a predictor in patients with acute myocardial infarction and elevated glycosylated hemoglobin A1c (HbA1c) is associated with an increased risk of cardiovascular disease, even in patients without diabetes. However, the effect of both admission glucose and HbA1c levels on clinical outcomes in non-diabetic patients with acute coronary syndrome (ACS) has not been fully elucidated. We evaluated the combined effect of admission glucose and HbA1c values on long-term clinical outcomes in non-diabetic patients with ACS treated with percutaneous coronary intervention (PCI).Methods and resultsThis was an observational study of 452 consecutive non-diabetic patients with ACS who underwent PCI between January 1997 and December 2006. The patients were assigned to four groups according to the median values of admission glucose and HbA1c. The primary endpoint comprising a composite of all-cause death and non-fatal MI was compared among the four groups. The primary endpoint occurred in 13.3% of the participants during a median follow-up period of 4.7 years. The cumulative incidence rate of primary endpoint significantly differed among the groups (p=0.048). Multivariable Cox regression analysis showed that the combination of elevated admission glucose and HbA1c was independently associated with long-term clinical outcomes.ConclusionsCombined admission glucose and HbA1c values were independently associated with clinical outcomes in non-diabetic patients with ACS treated with PCI

White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing

In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy and reproducibility). However, precision generally plays a contrary role for both. Therefore, the ultimate concept for maximizing both at the same time is the minimal-precision computing through precision-tuning, which adjusts the optimal precision for each operation and data. Several studies have been already conducted for it so far (e.g. Precimoniuos and Verrou), but the scope of those studies is limited to the precision-tuning alone. Hence, we aim to propose a broader concept of the minimal-precision computing system with precision-tuning, involving both hardware and software stack. In 2019, we have started the Minimal-Precision Computing project to propose a more broad concept of the minimal-precision computing system with precision-tuning, involving both hardware and software stack. Specifically, our system combines (1) a precision-tuning method based on Discrete Stochastic Arithmetic (DSA), (2) arbitrary-precision arithmetic libraries, (3) fast and accurate numerical libraries, and (4) Field-Programmable Gate Array (FPGA) with High-Level Synthesis (HLS). In this white paper, we aim to provide an overview of various technologies related to minimal- and mixed-precision, to outline the future direction of the project, as well as to discuss current challenges together with our project members and guest speakers at the LSPANC 2020 workshop; https://www.r-ccs.riken.jp/labs/lpnctrt/lspanc2020jan/

Renritsu ichiji hoteishiki no suchikai no kosoku seido hosho ni kansuru kenkyu

制度:新 ; 文部省報告番号:甲1748号 ; 学位の種類:博士(情報科学) ; 授与年月日:2003-03-15 ; 早大学位記番号:新3511早稲田大