Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery

Copyright @ 2014 Booth et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.When the nucleolus disassembles during open mitosis, many nucleolar proteins and RNAs associate with chromosomes, establishing a perichromosomal compartment coating the chromosome periphery. At present nothing is known about the function of this poorly characterised compartment. In this study, we report that the nucleolar protein Ki-67 is required for the assembly of the perichromosomal compartment in human cells. Ki-67 is a cell-cycle regulated protein phosphatase 1-binding protein that is involved in phospho-regulation of the nucleolar protein B23/nucleophosmin. Following siRNA depletion of Ki-67, NIFK, B23, nucleolin, and four novel chromosome periphery proteins all fail to associate with the periphery of human chromosomes. Correlative light and electron microscopy (CLEM) images suggest a near-complete loss of the entire perichromosomal compartment. Mitotic chromosome condensation and intrinsic structure appear normal in the absence of the perichromosomal compartment but significant differences in nucleolar reassembly and nuclear organisation are observed in post-mitotic cells

[技術・研究報告] アンドロイド・ロボットを用いた大学図書館司書のためのヘルプデスク遠隔対応システムの開発

本稿では，アンドロイド・ロボットを用いた大学図書館司書のためのヘルプデスク遠隔対応システムの開発について述べる．大学図書館ヘルプデスクの業務には受付での接客業務だけでなく，図書館書架の整理や事務所での作業などがあり，受付から離れて業務を行う必要がある．その際には，受付が無人となってしまい，利用客にとって図書館の利便性を損なってしまう．また，専門知識が必要な場でロボットによる自動対話を行う場合，利用者の多様な要望に対応することが難しく，利用客に不快な感情を抱かせてしまう．本稿では，それらの問題点の解決に向けて，これまでに開発されたアンドロイド・ロボットを用いたビデオ通話システムを拡張し，ビデオ通話時のミュート機能と会話音声の録音，音声文字化による図書館司書のための記録機能を構築する．構築したシステムを図書館ヘルプデスクの実業務にて長時間運用することで本システムの可能性，有用性を示す

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

A new brain-computer interface design using fuzzy ARTMAP

This paper proposes a new brain-computer interface (BCI) design using fuzzy ARTMAP (FA) neural network, as well as an application of the design. The objective of this BCI-FA design is to classify the best three of the five available mental tasks for each subject using power spectral density (PSD) values of electroencephalogram (EEG) signals. These PSD values are extracted using the Wiener-Khinchine and autoregressive methods. Ten experiments employing different triplets of mental tasks are studied for each subject. The findings show that the average BCI-FA outputs for four subjects gave less than 6% of error using the best triplets of mental tasks identified from the classification performances of FA. This implies that the BCI-FA can be successfully used with a tri-state switching device. As an application, a proposed tri-state Morse code scheme could be utilized to translate the outputs of this BCI-FA design into English letters. In this scheme, the three BCI-FA outputs correspond to a dot and a dash, which are the two basic Morse code alphabets and a space to denote the end (or beginning) of a dot or a dash. The construction of English letters using this tri-state Morse code scheme is determined only by the sequence of mental tasks and is independent of the time duration of each mental task. This is especially useful for constructing letters that are represented as multiple dots or dashes. This combination of BCI-FA design and the tri-state Morse code scheme could be developed as a communication system for paralyzed patients

Autoregressive spectral analysis and model order selection criteria for EEG signals

The advantages of autoregressive (AR) modelling over the classical Fourier Transform methods have been centre staged in the recent years. But a problem with AR method lies with the appropriate model order selection. In this paper, we address this problem by studying the performance of three different types of order selection criteria for AR models to represent electroencephalogram signals. We perform this by extracting EEG signals for different mental tasks and obtaining the appropriate model order given by the different criteria. From this, we derive the spectral density function. Using the spectral values, we train a neural network and classify the tasks into their respective categories. In this way, we show the difference in the performance level of the different model order selection criteria for EEG signals

Fuzzy Artmap classification of mental tasks using segmented and overlapped EEG signals

Visual inspection of EEG signals in their unprocessed form is still the predominant way of discriminating EEG patterns in the medical community and requires highly trained medical professionals. To overcome this problem, automatic EEG analysis using Fourier Transform methods are popular since most EEG signals consist of spectral power in the range of δ, θ, α and β i.e from 0 to 30 Hz. But this method suffers from high noise sensitivity and is not suitable for short and variable length of signal segments. In this paper, we analyze EEG signals with time series analysis using autoregression techniques. We classify these extracted features for different mental tasks using a Fuzzy ARTMAP classifier. We study the effects of different EEG segment or window lengths and different overlapping lengths on the overall performance of the classifier. Our results show that the segment length affects the performance and that overlapping the segments improves the performance greatly