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Institution

Kyoto University

EducationKyoto, Japan
About: Kyoto University is a education organization based out in Kyoto, Japan. It is known for research contribution in the topics: Population & Catalysis. The organization has 85837 authors who have published 217215 publications receiving 6526826 citations. The organization is also known as: Kyōto University & Kyōto daigaku.


Papers
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Journal ArticleDOI
20 Nov 1997-Nature
TL;DR: It is shown that p110 is CRM1, which is an evolutionarily conserved protein originally found as an essential nuclear protein in fission yeast and known as a likely target of LMB, which indicates that CRM 1 is an essential mediator of the NES-dependent nuclear export of proteins in eukaryotic cells.
Abstract: The discovery of nuclear export signals (NESs) in a number of proteins revealed the occurrence of signal-dependent transport of proteins from the nucleus to the cytoplasm. Although the consensus motif of the NESs has been shown to be a leucine-rich, short amino-acid sequence, its receptor has not been identified. A cytotoxin leptomycin B (LMB) has recently been suggested to inhibit the NES-mediated transport of Rev protein. Here we show that LMB is a potent and specific inhibitor of the NES-dependent nuclear export of proteins. Moreover, we have found a protein of relative molecular mass 110K (p110) in Xenopus oocyte extracts that binds to the intact NES but not to the mutated, non-functional NES. The binding of p110 to NES is inhibited by LMB. We show that p110 is CRM1, which is an evolutionarily conserved protein originally found as an essential nuclear protein in fission yeast and known as a likely target of LMB. We also show that nuclear export of a fission yeast protein, Dsk1, which has a leucine-rich NES, is disrupted in wild-type yeast treated with LMB or in the crm1 mutant. These results indicate that CRM1 is an essential mediator of the NES-dependent nuclear export of proteins in eukaryotic cells.

1,193 citations

Journal ArticleDOI
27 Aug 1998-Nature
TL;DR: The results of asking subjects to choose the most attractive faces from continua that enhanced or diminished differences between the average shape of female and male faces indicate a selection pressure that limits sexual dimorphism and encourages neoteny in humans.
Abstract: Testosterone-dependent secondary sexual characteristics in males may signal immunological competence1 and are sexually selected for in several species2,3. In humans, oestrogen-dependent characteristics of the female body correlate with health and reproductive fitness and are found attractive4,5,6. Enhancing the sexual dimorphism of human faces should raise attractiveness by enhancing sex-hormone-related cues to youth and fertility in females5,7,8,9,10,11, and to dominance and immunocompetence in males5,12,13. Here we report the results of asking subjects to choose the most attractive faces from continua that enhanced or diminished differences between the average shape of female and male faces. As predicted, subjects preferred feminized to average shapes of a female face. This preference applied across UK and Japanese populations but was stronger for within-population judgements, which indicates that attractiveness cues are learned. Subjects preferred feminized to average or masculinized shapes of a male face. Enhancing masculine facial characteristics increased both perceived dominance and negative attributions (for example, coldness or dishonesty) relevant to relationships and paternal investment. These results indicate a selection pressure that limits sexual dimorphism and encourages neoteny in humans.

1,186 citations

Journal ArticleDOI
26 Aug 1999-Nature
TL;DR: Evidence is provided that ngn3 acts as pro-endocrine gene and that Notch signalling is critical for the decision between theendocrine and progenitor/exocrine fates in the developing pancreas.
Abstract: The pancreas contains both exocrine and endocrine cells, but the molecular mechanisms controlling the differentiation of these cell types are largely unknown. Despite their endodermal origin, pancreatic endocrine cells share several molecular characteristics with neurons, and, like neurons in the central nervous system, differentiating endocrine cells in the pancreas appear in a scattered fashion within a field of progenitor cells. This indicates that they may be generated by lateral specification through Notch signalling. Here, to test this idea, we analysed pancreas development in mice genetically altered at several steps in the Notch signalling pathway. Mice deficient for Delta-like gene 1 (Dll1) or the intracellular mediator RBP-JK showed accelerated differentiation of pancreatic endocrine cells. A similar phenotype was observed in mice over-expressing neurogenin 3(ngn 3) or the intracellular form of Notch3 (ref. 13) (a repressor of Notch signalling). These data provide evidence that ngn3 acts as pro-endocrine gene and that Notch signalling is critical for the decision between theendocrine and progenitor/exocrine fates in the developing pancreas.

1,185 citations

Journal ArticleDOI
20 Apr 2006-Oncogene
TL;DR: Analysis of miRNA expression profiles in hepatocellular carcinoma and adjacent non-tumorous tissue specimens may help clarify the molecular mechanisms involved in the progression of liver disease, potentially serving as a diagnostic tool of HCC.
Abstract: MicroRNAs (miRNAs) are a non-coding family of genes involved in post-transcriptional gene regulation. These transcripts are associated with cell proliferation, cell differentiation, cell death and carcinogenesis. We analysed the miRNA expression profiles in 25 pairs of hepatocellular carcinoma (HCC) and adjacent non-tumorous tissue (NT) and nine additional chronic hepatitis (CH) specimens using a human miRNA microarray. Targets and references samples were co-hybridized to a microarray containing whole human mature and precursor miRNA sequences. Whereas three miRNAs exhibited higher expression in the HCC samples than that in the NT samples, five miRNAs demonstrated lower expression in the HCC samples than in the NT samples (P<0.0001). Classification of samples as HCC or NT by using support vector machine algorithms based on these data provided an overall prediction accuracy of 97.8% (45/46). In addition, the expression levels of four miRNAs were inversely correlated with the degree of HCC differentiation (P<0.01). A comparison of CH and liver cirrhosis samples revealed significantly different pattern of miRNA expression (P<0.01). There were no differences, however, between hepatitis B-positive and hepatitis C-positive samples. This information may help clarify the molecular mechanisms involved in the progression of liver disease, potentially serving as a diagnostic tool of HCC.

1,184 citations

Journal ArticleDOI
TL;DR: The relationship between the moments of a time-course curve and pharmacokinetic profiles of drug disposition, i.e., absorption, distribution, metabolism, and excretion, is described and it is shown that they can be effectively applied to the deconvolution operation.
Abstract: Statistical moments are parameters that describe the characteristics of the time courses of plasma concentration (area, mean residence time, and variance of residence time) and of the urinary excretion rate that follow administration of a single dose of a drug. The relationship between the moments of a time-course curve and pharmacokinetic profiles of drug disposition, i.e., absorption, distribution, metabolism, and excretion, is described. The moments are related to the extent and rate of bioavailability, and it is shown that they can be effectively applied to the deconvolution operation.

1,179 citations


Authors

Showing all 86225 results

NameH-indexPapersCitations
Kari Alitalo174817114231
Ralph M. Steinman171453121518
Masayuki Yamamoto1711576123028
Karl Deisseroth160556101487
Kenji Kangawa1531117110059
Takashi Taniguchi1522141110658
Ben Zhong Tang1492007116294
Takeo Kanade147799103237
Yuji Matsuzawa143836116711
Tasuku Honjo14171288428
Kenneth M. Yamada13944672136
Y. B. Hsiung138125894278
Shuh Narumiya13759570183
Kevin P. Campbell13752160854
Junji Tojo13587884615
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023234
2022679
20218,533
20208,740
20198,050
20187,932