Biology subjects

Kojima, K.

Publications and source records attributed to Kojima, K..

25 records · Page 2Linked to original sources

bioRxiv2021

Mesenchymal Stromal Cell Aging Impairs the Self-Organizing Capacity of Lung Alveolar Epithelial Stem Cells

Multicellular organisms maintain structure and function of tissues/organs through emergent, self-organizing behavior. In this report, we demonstrate a critical role for lung mesenchymal stromal cell (L-MSC) aging in determining the capacity to form 3-dimentional organoids or "alveolospheres " with type 2 alveolar epithelial cells (AEC2s). In contrast to L-MSCs from aged mice, young L-MSCs support the efficient formation of alveolospheres when co-cultured with young or aged AEC2s. Aged L-MSCs demonstrated features of cellular senescence, altered bioenergetics, and a senescence-associated secretory profile (SASP). The reactive oxygen species generating enzyme, NADPH oxidase 4 (Nox4), was highly activated in aged L-MSCs and Nox4 downregulation was sufficient to, at least partially, reverse this age-related energy deficit, while restoring the self-organizing capacity of alveolospheres. Together, these data indicate a critical role for cellular bioenergetics and redox homeostasis in an organoid model of self-organization, and supports the concept of thermodynamic entropy in aging biology.

cell biology↗

bioRxiv2020

Collection of 2429 constrained headshots of 277 volunteers for deep learning

Deep learning has rapidly been filtrating many aspects of human lives. In particular, image recognition by convolutional neural networks has inspired numerous studies in this area. Hardware and software technologies as well as large quantities of data have contributed to the drastic development of the field. However, the application of deep learning is often hindered by the need for big data and the laborious manual annotation thereof. To experience deep learning using the data compiled by us, we collected 2429 constrained headshot images of 277 volunteers. The collection of face photographs is challenging in terms of protecting personal information; we established an online procedure in which both the informed consent and image data could be obtained. We did not collect personal information, but issued agreement numbers to deal with withdrawal requests. Gender and smile labels were manually and subjectively annotated only from the appearances, and final labels were determined by majority among our team members. Rotated, trimmed, resolution-reduced, decolorized, and matrix-formed data were allowed to be publicly released. Moreover, simplified feature vectors for data sciences were released. We performed gender recognition by building convolutional neural networks based on the Inception V3 model with pre-trained ImageNet data to demonstrate the usefulness of our dataset.

animal behavior and cognition↗

bioRxiv2020

Low-frequency neural tracking of speech envelope reflects evoked responses to acoustic edges

The amplitude envelope of speech is crucial for accurate comprehension. Considered a key stage in speech processing, the phase of neural activity in the theta-delta bands (1 - 10 Hz) tracks the phase of the speech amplitude envelope during listening. However, the mechanisms underlying this envelope representation have been heavily debated. A dominant model posits that envelope tracking reflects entrainment of endogenous low-frequency oscillations to the speech envelope. Alternatively, envelope tracking reflects a series of evoked responses to acoustic landmarks within the envelope. It has proven challenging to distinguish these two mechanisms. To address this, we recorded magnetoencephalography while participants listened to natural speech, and compared the neural phase patterns to the predictions of two computational models: An oscillatory entrainment model and a model of evoked responses to peaks in the rate of envelope change. Critically, we also presented speech at slowed rates, where the spectrotemporal predictions of the two models diverge. Our analyses revealed transient theta phase-locking in regular speech, as predicted by both models. However, for slow speech we found transient theta and delta phase-locking, a pattern that was fully compatible with the evoked response model but could not be explained by the oscillatory entrainment model. Furthermore, encoding of acoustic edge magnitudes was invariant to contextual speech rate, demonstrating speech rate normalization of acoustic edge representations. Taken together, our results suggest that neural phase locking to the speech envelope is more likely to reflect discrete representation of transient information rather than oscillatory entrainment.

neuroscience↗

bioRxiv2019

A Recurrent Neural Network Based Method for Genotype Imputation on Phased Genotype Data

Genotype imputation estimates genotypes of unobserved variants from genotype data of other observed variants, and such estimation is enabled using haplotype data of a large number of other individuals. Although existing imputation methods explicitly use haplotype data, the accessibility of haplotype data is often limited because the agreement is necessary from donors of genome data. We propose a new imputation method that uses bidirectional recurrent neural network, and haplotype data of a large number of individuals are encoded as its model parameters through the training step, which can be shared publicly due to the difficulty in restoring genotype data at the individual-level. In the performance evaluation using the phased genotype data in the 1000 Genomes Project, the imputation accuracy of the proposed method in R2 is comparative with existing methods for variants with MAF [≥] 0.05 and is slightly worse than those of the existing methods for variants with MAF < 0.05. In a scenario of limited availability of haplotype data to the existing methods, the accuracy of the proposed method is higher than those of the existing methods at least for variants with MAF [≥] 0.005. Python code of our implementation for imputation is available at https://github.com/kanamekojima/rnnimp/.

bioinformatics↗

bioRxiv2019

A Pro-Diabetogenic mtDNA Polymorphism in the Mitochondrial-Derived Peptide, MOTS-c

Type 2 Diabetes (T2D) is an emerging public health problem in Asia. An Asian mitochondrial DNA variation m.1382A>C (rs111033358) leads to a K14Q amino acid replacement in MOTS-c, an insulin sensitizing mitochondrial-derived peptide. Meta-analysis of three cohorts (n=27,527, J-MICC, MEC, and TMM) showed that males but not females with the C-allele exhibit a higher prevalence of T2D. Furthermore, in J-MICC, only males with the C-allele in the lowest tertile of physical activity increased their prevalence of T2D, demonstrating a kinesio-genomic interaction. High-fat fed, male mice injected with MOTS-c showed reduced weight and improved glucose tolerance, but not K14Q-MOTS-c treated mice. Like the human data, female mice were unaffected. Mechanistically, K14Q-MOTS-c leads to diminished insulin-sensitization in vitro. Thus, the m.1382A>C polymorphism is associated with susceptibility to T2D in men, possibly interacting with exercise, and contributing to the risk of T2D in sedentary males by reducing the activity of MOTS-c.

genetics↗

bioRxiv2019

3.5KJPNv2, An allele frequency panel of 3,552 Japanese Individuals

The first step towards realizing personalized healthcare is to catalog the genetic variations in a population. Since the dissemination of individual-level genomic information is strictly controlled, it will be useful to construct population-level allele frequency panels and to provide them through easy-to-use interfaces. In the Tohoku Medical Megabank Project, we have sequenced nearly 4,000 individuals from a Japanese population, and constructed an allele frequency panel of 3,552 individuals after removing related samples. The panel is called the 3.5KJPNv2. It was constructed by using a standard pipeline including the 1KGP and gnomAD algorithms to reduce technical biases and to allow comparisons to other populations. Our database is the first largescale panel providing the frequencies of variants present on the X chromosome and on the mitochondria in the Japanese population. All the data are available on our original database at https://jmorp.megabank.tohoku.ac.jp.

genomics↗

bioRxiv2018

Changes choroidal area following trabeculectomy: long-term effect of intraocular pressure reduction

PurposeTo investigate the long-term effects of intraocular pressure (IOP) changes after trabeculectomy on the macular and peripapillary choroidal areas.\n\nMethodsThis prospective longitudinal study examined 30 eyes of 30 patients with glaucoma that was uncontrolled by medical therapy. At 1 day before and at 1 year after the trabeculectomy surgery, macular and peripapillary choroidal images were recorded by enhanced depth imaging optical coherence tomography (EDI-OCT). Luminal and interstitial areas were converted to binary images using the Niblack method. Factors influencing the macular choroidal and peripapillary area were examined by multivariate analysis.\n\nResultsAfter trabeculectomy, the mean IOP was 10.8{+/-}3.2 mmHg compared to 17.8{+/-}7.2 mmHg at baseline (P < 0.001). The total macular choroidal area after the surgery increased from 317,735{+/-}77,380 to 338,120{+/-}90,700 m2, while the interstitial area increased from 108,598{+/-}24,502 to 119,172{+/-}31,495 m2 (all P < 0.05). The total peripapillary choroidal area after the surgery also increased from 1,557,487{+/-}431,798 to 1,650,253{+/-}466,672 m2, while the interstitial area increased from 689,891{+/-}149,476 to 751,816{+/-}162,457 m2 (all P < 0.05). However, there were no significant differences observed in the luminal area before and after the surgery. A decrease in the IOP was among the factors associated with the changes in the peripapillary choroidal area.\n\nConclusionsIOP reductions after trabeculectomy led to increases in the macular and peripapillary choroidal areas for at least 1 year postoperative. Increases in the interstitial areas were the primary reason for observed changes in the choroidal area after trabeculectomy.

pathology↗