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Institution

Kumamoto University

EducationKumamoto, Kumamoto, Japan
About: Kumamoto University is a education organization based out in Kumamoto, Kumamoto, Japan. It is known for research contribution in the topics: Cancer & Population. The organization has 19602 authors who have published 35513 publications receiving 901260 citations. The organization is also known as: Kumamoto Daigaku.
Topics: Cancer, Population, Gene, Cell culture, Receptor


Papers
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Journal ArticleDOI
TL;DR: The findings indicate that there is a multifunctional Ca2+‐ and calmodulin‐dependent protein kinase in the brain and that this enzyme may regulate the reactions of various endogenous proteins.
Abstract: A Ca2+- and calmodulin-dependent protein kinase was purified from rat brain cytosol fraction to apparent homogeneity at approximately 800-fold and with a 5% yield. The purified enzyme had a molecular weight of 640,000 as determined by gel filtration analysis on Sephacryl S-300 and a sedimentation coefficient of 15.3 S by sucrose density gradient centrifugation, and resulted in a single protein band of MW 49,000 by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. These results suggest that the native enzyme has a large molecular weight and consists of 11 to 14 identical subunits. The purified enzyme exhibited Km values of 109 and 30 microM for ATP and chicken gizzard myosin light chain, respectively, and Ka values of 12 nM and 1.9 microM for brain calmodulin and Ca2+, respectively. In addition to myosin light chain, myelin basic protein, casein, arginine-rich histone, microtubule protein, and synaptosomal proteins were phosphorylated by the enzyme in a CA2+- and calmodulin-dependent manner. The purified enzyme was phosphorylated without the addition of the catalytic subunits of cyclic AMP-dependent protein kinase. Our findings indicate that there is a multifunctional Ca2+- and calmodulin-dependent protein kinase in the brain and that this enzyme may regulate the reactions of various endogenous proteins.

226 citations

Journal ArticleDOI
TL;DR: The presence of a CD27−CD28+ subset with a CCR5+CCR7− phenotype implies a specialized role for this subset in the differentiation of CD8+ T cells.
Abstract: Previous studies of perforin expression and cytokine production in subsets of peripheral human CD45RA(-)CD8(+) T cells with different CD28/CD27 phenotypes showed that CD28(+)CD45RA(-)CD8(+) and CD27(+)CD45RA(-)CD8(+) T cells have characteristics of memory T cells, whereas CD28(-)CD45RA(-)CD8(+) and CD27(-)CD45RA(-)CD8(+) T cells have characteristics of both memory and effector T cells However, the differentiation pathway from memory CD8(+) T cells into memory/effector CD8(+) T cells has not been completely clarified We investigated this differentiation pathway using EBV- and human CMV (HCMV)-specific CD8(+) T cells Three subsets of CD45RA(-)CD8(+) T cells were observed in both total CD8(+) T cells and EBV- or HCMV-specific CD8(+) T cells: CD27(+)CD28(+), CD27(+)CD28(-), and CD27(-)CD28(-) A significant number of the CD27(-)CD28(+) subset was observed in total CD8 T cells However, this subset was barely detectable in EBV- or HCMV-specific CD8(+) T cells Analysis of perforin expression and cytotoxic activity in the first three subsets suggested the following differentiation pathway: CD27(+)CD28(+)CD45RA(-)-->CD27(+)CD28(-)CD45RA(-)-->CD27(-)CD28(-)CD45RA(-) This was supported by the observation that the frequency of CCR5(+) cells and CCR7(+) cells decreased during this sequence Analysis of CCR5 and CCR7 expression in the CD27(+)CD28(+) memory cell subset demonstrated the presence of three CCR5/CCR7 populations: CCR5(-)CCR7(+), CCR5(+)CCR7(+), and CCR5(+)CCR7(-) These findings suggested the following differentiation pathway: CD27(+)CD28(+)CD45RA(-) (CCR5(-)CCR7(+)-->CCR5(+)CCR7(+)-->CCR5(+)CCR7(-))-->CD27(+)CD28(-)CD45RA(-)-->CD27(-)CD28(-)CD45RA(-) The presence of a CD27(-)CD28(+) subset with a CCR5(+)CCR7(-) phenotype implies a specialized role for this subset in the differentiation of CD8(+) T cells

225 citations

Journal ArticleDOI
TL;DR: This work has shown that maternally methylated genes are first erased in primordial germ cells (PGCs) and then re‐established during oocyte growth, suggesting that their methylation imprints have to be reprogrammed following each passage through the germline.
Abstract: Background Germline-specific differential DNA methylation that persists through fertilization and embryonic development is thought to be the ‘imprint’ distinguishing the parental alleles of imprinted genes. If such methylation is to work as the imprinting mechanism, however, it has to be reprogrammed following each passage through the germline. Previous studies on maternally methylated genes have shown that their methylation imprints are first erased in primordial germ cells (PGCs) and then re-established during oocyte growth. Results We have examined the timing of the reprogramming of the paternal methylation imprint of the mouse H19 gene during germ cell development. In both male and female PGCs, the paternal allele is partially methylated whereas the maternal allele is unmethylated. This partial methylation is completely erased in the female germline by entry into meiosis, establishing the oocyte methylation pattern. In the male germline, both alleles become methylated, mainly during the gonocyte stage, establishing the sperm methylation pattern. Conclusion The paternal methylation imprint of H19 is established in the male germline and erased in the female germline at specific developmental stages. The identification of the timings of the methylation and demethylation should help to identify and characterize the biochemical basis of the reprogramming of imprinting.

225 citations

Journal ArticleDOI
TL;DR: Artificial neural network (ANN) is proposed as a method to improve accurate RUL prediction of bearing failure and shows that better performance is achieved in order to predict bearing failure.
Abstract: Accurate remaining useful life (RUL) prediction of machines is important for condition based maintenance (CBM) to improve the reliability and cost of maintenance. This paper proposes artificial neural network (ANN) as a method to improve accurate RUL prediction of bearing failure. For this purpose, ANN model uses time and fitted measurements Weibull hazard rates of root mean square (RMS) and kurtosis from its present and previous points as input. Meanwhile, the normalized life percentage is selected as output. By doing that, the noise of a degradation signal from a target bearing can be minimized and the accuracy of prognosis system can be improved. The ANN RUL prediction uses FeedForward Neural Network (FFNN) with Levenberg Marquardt of training algorithm. The results from the proposed method shows that better performance is achieved in order to predict bearing failure.

225 citations

Journal ArticleDOI
TL;DR: Results support a model in which the cilia act as a brake to prevent cell cycle progression, and show the involvement of actin dynamics in Tctex-1-regulated cilium resorption.
Abstract: Primary cilia are displayed during the G(0)/G(1) phase of many cell types. Cilia are resorbed as cells prepare to re-enter the cell cycle, but the causal and molecular link between these two cellular events remains unclear. We show that Tctex-1 phosphorylated at Thr 94 is recruited to ciliary transition zones before S-phase entry and has a pivotal role in both ciliary disassembly and cell cycle progression. However, the role of Tctex-1 in S-phase entry is dispensable in non-ciliated cells. Exogenously adding a phospho-mimic Tctex-1(T94E) mutant accelerates cilium disassembly and S-phase entry. These results support a model in which the cilia act as a brake to prevent cell cycle progression. Mechanistic studies show the involvement of actin dynamics in Tctex-1-regulated cilium resorption. Tctex-1 phosphorylated at Thr 94 is also selectively enriched at the ciliary transition zones of cortical neural progenitors, and has a key role in controlling G(1) length, cell cycle entry and fate determination of these cells during corticogenesis.

225 citations


Authors

Showing all 19645 results

NameH-indexPapersCitations
Fred H. Gage216967185732
George D. Yancopoulos15849693955
Kenji Kangawa1531117110059
Tasuku Honjo14171288428
Hideo Yagita13794670623
Masashi Yanagisawa13052483631
Kazuwa Nakao128104170812
Kouji Matsushima12459056995
Thomas E. Mallouk12254952593
Toshio Hirano12040155721
Eisuke Nishida11234945918
Hiroaki Shimokawa11194948822
Bernd Bukau11127138446
Kazuo Tsubota105137948991
Toshio Suda10458041069
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202297
20211,701
20201,654
20191,511
20181,330