Amphiphilic peptide-tagged N-cadherin forms radial glial-like fibers that enhance neuronal migration in injured brain and promote sensorimotor recovery

The mammalian brain has very limited ability to regenerate lost neurons and recover function after injury. Promoting the migration of young neurons (neuroblasts) derived from endogenous neural stem cells using biomaterials is a new and promising approach to aid recovery of the brain after injury. However, the delivery of sufficient neuroblasts to distant injured sites is a major challenge because of the limited number of scaffold cells that are available to guide neuroblast migration. To address this issue, we have developed an amphiphilic peptide [(RADA)3-(RADG)] (mRADA)-tagged N-cadherin extracellular domain (Ncad-mRADA), which can remain in mRADA hydrogels and be injected into deep brain tissue to facilitate neuroblast migration. Migrating neuroblasts directly contacted the fiber-like Ncad-mRADA hydrogel and efficiently migrated toward an injured site in the striatum, a deep brain area. Furthermore, application of Ncad-mRADA to neonatal cortical brain injury efficiently promoted neuronal regeneration and functional recovery. These results demonstrate that self- assembling Ncad-mRADA peptides mimic both the function and structure of endogenous scaffold cells and provide a novel strategy for regenerative therapy

Hitomi (ASTRO-H) X-ray Astronomy Satellite

The Hitomi (ASTRO-H) mission is the sixth Japanese x-ray astronomy satellite developed by a large international collaboration, including Japan, USA, Canada, and Europe. The mission aimed to provide the highest energy resolution ever achieved at E  >  2  keV, using a microcalorimeter instrument, and to cover a wide energy range spanning four decades in energy from soft x-rays to gamma rays. After a successful launch on February 17, 2016, the spacecraft lost its function on March 26, 2016, but the commissioning phase for about a month provided valuable information on the onboard instruments and the spacecraft system, including astrophysical results obtained from first light observations. The paper describes the Hitomi (ASTRO-H) mission, its capabilities, the initial operation, and the instruments/spacecraft performances confirmed during the commissioning operations for about a month

THE RELATIONSHIP OF WATER QUALITY RESTORATION AND PLANTS RE-ESTABLISHMENT IN BOG MIRE CONSERVATION

第12回衛生工学シンポジウム（平成16年11月4日（木）-5日（金） 北海道大学クラーク会館） . 一般セッション . 2 水環境 . P2-

Concordance of two diabetes diagnostic criteria using fasting plasma glucose and hemoglobin A1c: the Yuport Medical Checkup Centre study.

We tested the concordance of the two diagnostic criteria for diabetes using fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) by the Japan Diabetes Society (JDS) and American Diabetes Association (ADA).We used data from 7,328 subjects without known diabetes who participated in a voluntary health checkup program at least twice between 1998 and 2006, at intervals ≤ 2 years. For repeat participants who attended the screening over two times, data from the first and second checkups were used for this study. At the first visit, diabetes was diagnosed both at FPG ≥ 7.0 mmol/L and HbA1c ≥ 6.5% using the JDS criteria. In addition, diabetes was diagnosed using two ADA criteria; ADA-FPG diabetes for persistent fasting hyperglycemia (FPG ≥ 7.0 mmol/L) or ADA-HbA1c diabetes for hyper-glycated hemoglominemia (HbA1c ≥ 6.5%), both at the first and second checkups. Subsequently, the concordance of diagnosis between the JDS and the ADA criteria was evaluated.At the first checkup, 153 (2.1%) persons were diagnosed with diabetes by the JDS criteria. They had higher levels of risk factors for diabetes than non-diabetic subjects. Using the first and second checkups, 174 (2.4%) and 175 (2.4%) were diagnosed with diabetes by the ADA-FPG criteria, respectively. Among 153 subjects diagnosed with diabetes by the JDS criteria, 125 (81.7%) and 129 (84.3%) had ADA-FPG and ADA-HbA1c diabetes, respectively. The kappa coefficients of the JDS criteria with ADA-FPG and ADA-HbA1c criteria were 0.759 and 0.782 (P<0.001), respectively. In the subgroup analysis stratified by sex, the concordance was well preserved at the kappa coefficients around 0.8 (between 0.725 and 0.836).The JDS diagnostic criteria for diabetes have a substantial and acceptable concordance with the ADA criteria. The JDS criteria may be a practical method for diagnosing diabetes that maintains compatibility with the ADA criteria

Baseline characteristics of the 9,989 study subjects.

<p>Data are expressed as mean ± standard deviation, median (25 percentile, 75 percentile) or number (%).</p><p>HDL, high-density lipoprotein; LDL, low-density lipoprotein.</p

Area under the receiver operating characteristics and predictabilities of single markers for progression of diabetes.^a

<p>AUC, area under the receiver operating characteristic curve; CI, confidence interval; HDL, high-density lipoprotein; LDL, low-density lipoprotein.</p>a<p>Diabetes was defined as FPG ≥7.00 mmol/L or known diabetes at follow-up.</p>b<p>The units of each optimal cutoff point was shown in Table2, respectively.</p

Enrollment of the study subjects.

<p>FPG, fasting plasma glucose; HbA1c, hemoglobin A1c.</p

The area under the receiver operating characteristics and predictabilities of multiple markers for progression of diabetes^a by logistic regression models.^b

<p>ALT, alanine aminotransferase; AST, asparate aminotransferase; AUC, area under the receiver operating characteristic curve; CI, confidence interval; FPG, fasting plasma glucose; GGT, gamma-glutamyltranspeptidase; HbA1c, hemoglobin A1c; HDL, high-density lipoprotein; LDL, low-density lipoprotein.</p>a<p>Diabetes was defined as FPG ≥7.00 mmol/L or from known diabetes.</p>b<p>FPG and HbA1c are placed into all models as the basic predictors.</p>c<p><i>P</i> value was for comparing the AUC between base model (FPG+HbA1c) and additional models with multiple markers (FPG+HbA1c+non-glycaemic- non-blood biomarker).</p>d<p>Incremental AUC above 0.5 was incremental AUC above 0.5 over base model (FPG+HbA1c).</p

Receiver operating characteristic curves for variables predicting diabetes.

<p>The graphs only show glycaemic biomarkers (FPG and HbA1c), and the non-glycaemic biomarker, alanine aminotransferase, which had the highest area under the receiver operating characteristic curves in the additional models. FPG, fasting plasma glucose; HbA1c, hemoglobin A1c.</p