Hydraulic Strategy of Cactus Trichome for Absorption and Storage of Water under Arid Environment

Being an essential component in various metabolic activities, water is important for the survival of plants and animals. Cacti grown in arid areas have developed intrinsic water management systems, such as water collection through spines, water absorption through trichome, and water storage using mucilage. The water collection method of cactus is well-documented, but its water absorption and storage strategies remain to be elucidated. Thus, this study analyzed the morphology and wettability of cactus trichomes by using advanced bio-imaging techniques and by performing in vitro experiments on an artificial system mimicking these structures, respectively. In addition, the in situ water absorption process through the trichome cluster was quantitatively visualized. This paper proposes a new bio-inspired technique for dew collection based on information about the water management strategies of cactus. This study discusses the underlying water absorption and storage strategies of cactus and provides the experimental database required to develop a biomimetic water management device.114Ysciescopu

STAT1 and Nmi are downstream targets of Ets-1 transcription factor in MCF-7 human breast cancer cell

AbstractEts-1 is a cellular homologue of the product of the viral ets oncogene of the E26 virus, and it functions as a tissue-specific transcription factor. It plays an important role in cell proliferation, differentiation, lymphoid cell development, transformation, angiogenesis, and apoptosis. Ets-1 controls the expression of critical genes involved in these processes by binding to ets binding sites present in the transcriptional regulatory regions. Here, we transiently overexpressed Ets-1 in MCF-7 and comprehensively searched for potential downstream targets of Ets-1 by cDNA microarray analysis. The expressions of several interferon-related genes including STAT1 and Nmi were augmented by the overexpression of Ets-1. RT-PCR and Western blotting confirmed the increase in the levels of STAT1 and Nmi mRNA and protein. In contrast, Ets-1 siRNA decreased the expression of STAT1 and Nmi proteins. As in our transient transfection experiments, stable overexpression of Ets-1, also increased the protein expression of STAT1 and Nmi in MCF-7 cells. Taken together, our results indicate that STAT1 and Nmi are downstream targets of Ets-1 in MCF-7 human breast cancer cells

Interbrain phase synchronization during turn-taking verbal interaction-a hyperscanning study using simultaneous EEG/MEG: Synchronization During Turn-Taking Verbal Interaction

Recently, neurophysiological findings about social interaction have been investigated widely, and hardware has been developed that can measure multiple subjects' brain activities simultaneously. These hyperscanning studies have enabled us to discover new and important evidences of interbrain interactions. Yet, very little is known about verbal interaction without any visual input. Therefore, we conducted a new hyperscanning study based on verbal, interbrain turn-taking interaction using simultaneous EEG/MEG, which measures rapidly changing brain activities. To establish turn-taking verbal interactions between a pair of subjects, we set up two EEG/MEG systems (19 and 146 channels of EEG and MEG, respectively) located ∼100 miles apart. Subjects engaged in verbal communication via condenser microphones and magnetic-compatible earphones, and a network time protocol synchronized the two systems. Ten subjects participated in this experiment and performed verbal interaction and noninteraction tasks separately. We found significant oscillations in EEG alpha and MEG alpha/gamma bands in several brain regions for all subjects. Furthermore, we estimated phase synchronization between two brains using the weighted phase lag index and found statistically significant synchronization in EEG and MEG data. Our novel paradigm and neurophysiological findings may foster a basic understanding of the functional mechanisms involved in human social interactions. Hum Brain Mapp 39:171-188, 2018. © 2017 Wiley Periodicals, Inc

Steady-State Somatosensory Evoked Potential for Brain-Computer Interface–Present and Future

Brain-computer interface (BCI) performance has achieved continued improvement over recent decades, and sensorimotor rhythm-based BCIs that use motor function have been popular subjects of investigation. However, it remains problematic to introduce them to the public market because of their low reliability. As an alternative resolution to this issue, visual-based BCIs that use P300 or steady-state visually evoked potentials seem promising; however, the inherent visual fatigue that occurs with these BCIs may be unavoidable. For these reasons, steady-state somatosensory evoked potential (SSSEP) BCIs, which are based on tactile selective attention, have gained increasing attention recently. These may reduce the fatigue induced by visual attention and overcome the low reliability of motor activity. In this literature survey, recent findings on SSSEP and its methodological uses in BCI are reviewed. Further, existing limitations of SSSEP BCI and potential future directions for the technique are discussed

Super-Resolution for Improving EEG Spatial Resolution using Deep Convolutional Neural Network—Feasibility Study

Electroencephalography (EEG) has relatively poor spatial resolution and may yield incorrect brain dynamics and distort topography; thus, high-density EEG systems are necessary for better analysis. Conventional methods have been proposed to solve these problems, however, they depend on parameters or brain models that are not simple to address. Therefore, new approaches are necessary to enhance EEG spatial resolution while maintaining its data properties. In this work, we investigated the super-resolution (SR) technique using deep convolutional neural networks (CNN) with simulated EEG data with white Gaussian and real brain noises, and experimental EEG data obtained during an auditory evoked potential task. SR EEG simulated data with white Gaussian noise or brain noise demonstrated a lower mean squared error and higher correlations with sensor information, and detected sources even more clearly than did low resolution (LR) EEG. In addition, experimental SR data also demonstrated far smaller errors for N1 and P2 components, and yielded reasonable localized sources, while LR data did not. We verified our proposed approach’s feasibility and efficacy, and conclude that it may be possible to explore various brain dynamics even with a small number of sensors

Hydraulic Strategy of Cactus Trichome for Absorption and Storage of Water under Arid Environment

Being an essential component in various metabolic activities, water is important for the survival of plants and animals. Cacti grown in arid areas have developed intrinsic water management systems, such as water collection through spines, water absorption through trichome, and water storage using mucilage. The water collection method of cactus is well-documented, but its water absorption and storage strategies remain to be elucidated. Thus, this study analyzed the morphology and wettability of cactus trichomes by using advanced bio-imaging techniques and by performing in vitro experiments on an artificial system mimicking these structures, respectively. In addition, the in situ water absorption process through the trichome cluster was quantitatively visualized. This paper proposes a new bio-inspired technique for dew collection based on information about the water management strategies of cactus. This study discusses the underlying water absorption and storage strategies of cactus and provides the experimental database required to develop a biomimetic water management device

Gamma band activity associated with BCI performance – Simultaneous MEG/EEG study

While brain computer interface (BCI) can be employed for patients and healthy subjects, there are problems that must be resolved before BCI can be useful to the public. In the most popular motor imagery BCI system, a significant number of target users (called BCI-Illiterates) cannot modulate their neuronal signals enough to use the BCI system. This causes performance variability among subjects and even among sessions within a subject. The mechanism of such BCI-Illiteracy and possible solutions still remain to be determined. Gamma oscillation is known to be involved in various fundamental brain functions, and may play a role in motor imagery. In this study, we investigated the association of gamma activity with motor imagery performance among subjects. Ten simultaneous MEG/EEG experiments were conducted; motor imagery performance for each was estimated by EEG data, and the gamma activity associated with BCI performance was investigated with MEG data. Our results showed that gamma activity had a high positive correlation with motor imagery performance in the prefrontal area. This trend was also found across sessions within one subject. In conclusion, gamma rhythms generated in the prefrontal area appears to play a critical role in BCI performance