Biology subjects

Nakajima, M.

Publications and source records attributed to Nakajima, M..

5 recordsLinked to original sources

bioRxiv2021

Epileptic Spike Detection by Recurrent Neural Networks with Self-Attention Mechanism

ObjectiveBecause of the lack of highly skilled experts, automated technologies that support electroencephalogram (EEG)-based in epilepsy diagnosis are advancing. Deep convolutional neural network-based models have been used successfully for detecting epileptic spikes, one of the biomarkers, from EEG. However, a sizeable number of supervised EEG records are required for training. ApproachThis study introduces the Satelight model, which uses the self-attention (SA) mechanism. The model was trained using a clinical EEG dataset labeled by five specialists, including 16,008 epileptic spikes and 15,478 artifacts from 50 children. The SA mechanism is expected to reduce the number of parameters and efficiently extract features from a small amount of EEG data. To validate the effectiveness, we compared various spike detection approaches with the clinical EEG data. Main resultsThe experimental results showed that the proposed method detected epileptic spikes more effectively than other models (accuracy = 0.876 and false positive rate = 0.133). SignificanceThe proposed model had only one-tenth the number of parameters as the other effective model, despite having such a high detection performance. Further exploration of the hidden parameters revealed that the model automatically attended to the EEGs characteristic waveform locations of interest.

bioengineering↗

bioRxiv2021

Comparative analyses of gene expression in common marmoset and human pluripotent stem cells (PSCs) identify factors enhancing homologous recombination efficiency in the HPRT locus of human PSCs

A previous study assessing the efficiency of the genome editing technology CRISPR-Cas9 for knock-in gene targeting in common marmoset (marmoset; Callithrix jacchus) embryonic stem cells (ESCs) unexpectedly identified innately enhanced homologous recombination (HR) activity in marmoset ESCs (cmESCs). Here, we compared gene expression in marmoset and human pluripotent stem cells (PSCs) using transcriptomic and quantitative PCR (qPCR) analyses and found that five HR-related genes (BRCA1, BRCA2, RAD51C, RAD51D and RAD51) were upregulated in marmoset cells. Four of these upregulated genes enhanced HR efficiency with CRISPR-Cas9 in human pluripotent stem cells. Thus, the present study provides a novel insight into species-specific mechanisms for the choice of DNA repair pathways.

cell biology↗

bioRxiv2020

Basis for the phototaxis sign reversal in the green alga Chlamydomonas reinhardtii studied by high-speed observation

For organisms that respond to environmental stimuli using taxes, reversal of the tactic sign should be tightly regulated for survival. The biciliate green alga Chlamydomonas reinhardtii is an excellent model for studying reversal between positive and negative phototaxis. C. reinhardtii cells change swimming direction by modulating the balance of beating forces between their two cilia after photoreception at the eyespot; however, it remains unknown how they reverse phototactic sign. In this study, we observed cells undergoing phototactic turns with a high-speed camera and found that two key factors determine the phototactic sign: which of the two cilia beats more strongly for phototactic turning and when the strong beating starts. The timing of the strong ciliary beating is suggested to be regulated by ROS-regulated switching between the light-on and light-off responses at the eyespot, which leads to the switching between positive and negative phototaxis. This idea is supported by a mathematical model that introduces the timing of the strong ciliary beating after photoreception.

cell biology↗

bioRxiv2020

Epileptic Spike Detection by Using a Linear-Phase Convolutional Neural Network

To cope with the lack of highly skilled professionals, machine learning with proper signal processing is key for establishing automated diagnostic-aid technologies with which to conduct epileptic electroencephalogram (EEG) testing. In particular, frequency filtering with the appropriate passbands is essential for enhancing the biomarkers--such as epileptic spike waves--that are noted in the EEG. This paper introduces a novel class of neural networks (NNs) that have a bank of linear-phase finite impulse response filters at the first layer as a preprocessor that can behave as bandpass filters that extract biomarkers without destroying waveforms because of a linear-phase condition. Besides, the parameters of the filters are also data-driven. The proposed NNs were trained with a large amount of clinical EEG data, including 15,833 epileptic spike waveforms recorded from 50 patients, and their labels were annotated by specialists. In the experiments, we compared three scenarios for the first layer: no preprocessing, discrete wavelet transform, and the proposed data-driven filters. The experimental results show that the trained data-driven filter bank with supervised learning behaves like multiple bandpass filters. In particular, the trained filter passed a frequency band of approximately 10-30 Hz. Moreover, the proposed method detected epileptic spikes, with the area under the receiver operating characteristic curve of 0.967 in the mean of 50 intersubject validations.

neuroscience↗

bioRxiv2019

Inverse correlation between heme synthesis and the Warburg effect in cancer cells

AbstractsCancer cells show a bias toward the glycolytic system over the conventional mitochondrial electron transfer system for obtaining energy. This biased metabolic adaptation is called the Warburg effect. Cancer cells also exhibit a characteristic metabolism, a decreased heme synthesizing ability. Here we show that heme synthesis and the Warburg effect are inversely correlated. We used human gastric cancer cell lines to investigate glycolytic metabolism and electron transfer system toward promotion/inhibition of heme synthesis. Under hypoxic conditions, heme synthesis was suppressed and the glycolytic system was enhanced. Addition of a heme precursor for the promotion of heme synthesis led to an enhanced electron transfer system and inhibited the glycolytic system and vice versa. Enhanced heme synthesis leads to suppression of cancer cell proliferation by increasing intracellular reactive oxygen species levels. Collectively, the promotion of heme synthesis in cancer cells eliminated the Warburg effect by shifting energy metabolism from glycolysis to oxidative phosphorylation.

biochemistry↗