Exosomes in mammals with greater habitat variability contain more proteins and RNAs

Takemoto, Kazuhiro; Miku, Imoto

doi:10.1098/rsos.170162

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…In this study, we could not use a direct regression model for all 88 explanatory variables (i.e., age, sex, 3 global network measures, and the BET values of the 83 nodes) because of the combinational explosion in the model selection and the multicollinearity that mainly arises from feature overlap among network measures. Thus, following a previous study 32 , to avoid this problem as much as possible, we considered the parameter selection using the least absolute shrinkage and selection operator (LASSO) method, which is thought to be useful for regularization, to increase the interpretability of the regression model for finding significant variables 33 .…”

Section: Methodsmentioning

confidence: 99%

Brain structural connectivity and neuroticism in healthy adults

Ueda

Kakeda

Watanabe

et al. 2018

Sci Rep

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Understanding the neural correlates of the neurotic brain is important because neuroticism is a risk factor for the development of psychopathology. We examined the correlation between brain structural networks and neuroticism based on NEO Five-Factor Inventory (NEO-FFI) scores. Fifty-one healthy participants (female, n = 18; male, n = 33; mean age, 38.5 ± 11.7 years) underwent the NEO-FFI test and magnetic resonance imaging (MRI), including diffusion tensor imaging and 3D T1WI. Using MRI data, for each participant, we constructed whole-brain interregional connectivity matrices by deterministic tractography and calculated the graph theoretical network measures, including the characteristic path length, global clustering coefficient, small-worldness, and betweenness centrality (BET) in 83 brain regions from the Desikan-Killiany atlas with subcortical segmentation using FreeSurfer. In relation to the BET, neuroticism score had a negative correlation in the left isthmus cingulate cortex, left superior parietal, left superior temporal, right caudal middle frontal, and right entorhinal cortices, and a positive correlation in the bilateral frontal pole, left caudal anterior cingulate cortex, and left fusiform gyrus. No other measurements showed significant correlations. Our results imply that the brain regions related to neuroticism exist in various regions, and that the neuroticism trait is likely formed as a result of interactions among these regions. This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas (Comprehensive Brain Science Network) from the Ministry of Education, Science, Sports and Culture of Japan.

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Section: Methodsmentioning

confidence: 99%

Brain structural connectivity and neuroticism in healthy adults

Ueda

Kakeda

Watanabe

et al. 2018

Sci Rep

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“…The findings of this study depend significantly on the quality of genome annotation. Moreover, as previously mentioned [40], there are limitations to the phylogenetic comparative analysis. This type of analysis assumes a Brownian motion-like evolution of biological traits on a phylogenetic tree with accurate branch lengths, which may lead to a misleading conclusion.…”

Section: Discussionmentioning

confidence: 99%

Revisiting the hypothesis of an energetic barrier to genome complexity between eukaryotes and prokaryotes

Chiyomaru

Takemoto

2020

R. Soc. open sci.

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The absence of genome complexity in prokaryotes, being the evolutionary precursors to eukaryotic cells comprising all complex life (the prokaryote–eukaryote divide), is a long-standing question in evolutionary biology. A previous study hypothesized that the divide exists because prokaryotic genome size is constrained by bioenergetics (prokaryotic power per gene or genome being significantly lower than eukaryotic ones). However, this hypothesis was evaluated using a relatively small dataset due to lack of data availability at the time, and is therefore controversial. Accordingly, we constructed a larger dataset of genomes, metabolic rates, cell sizes and ploidy levels to investigate whether an energetic barrier to genome complexity exists between eukaryotes and prokaryotes while statistically controlling for the confounding effects of cell size and phylogenetic signals. Notably, we showed that the differences in bioenergetics between prokaryotes and eukaryotes were less significant than those previously reported. More importantly, we found a limited contribution of power per genome and power per gene to the prokaryote–eukaryote dichotomy. Our findings indicate that the prokaryote–eukaryote divide is hard to explain from the energetic perspective. However, our findings may not entirely discount the traditional hypothesis; in contrast, they indicate the need for more careful examination.

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Data from: Exosomes in mammals with greater habitat variability contain more proteins and RNAs

Takemoto,

Imoto

2017

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Exosomes in mammals with greater habitat variability contain more proteins and RNAs

Cited by 3 publications

References 41 publications

Brain structural connectivity and neuroticism in healthy adults

Brain structural connectivity and neuroticism in healthy adults

Revisiting the hypothesis of an energetic barrier to genome complexity between eukaryotes and prokaryotes

Data from: Exosomes in mammals with greater habitat variability contain more proteins and RNAs

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