Biology subjects

Ueda, N.

Publications and source records attributed to Ueda, N..

10 recordsLinked to original sources

bioRxiv2026

microRNA expression during early development in the coral Acropora digitifera

Acropora spp. are the dominant reef-builders of the Indo-Pacific but are also amongst the most stress-sensitive corals. For these reasons, Acropora spp. have become the most studied of corals, two species (A. digitifera and A. millepora) often essentially serving as the basis for understanding molecular responses and processes across the sub-order Refertina and corals in general. The early development of these species has been well-characterised in terms of morphology and gene expression but as yet we have a limited understanding of how transcription is regulated during development. In "higher" animals (bilaterians) microRNAs (miRNAs) are critical regulators of gene expression but until now their involvement in coral development has not been investigated. Building on the existing developmental data for Acropora spp., we catalogued microRNAs (miRNAs) expressed during the early development of Acropora digitifera and profiled their expression in 21 stages from unfertilised eggs to 24h after treatment with a natural settlement cue (CCA chips). 157 miRNAs were recognised, many of which ([~]60%) were novel. These fell into three distinct groups, corresponding to three distinct developmental phases: (1) those present in eggs through to gastrulation (2) a larvally expressed group and (3) those expressed following settlement induction. Exposure of competent larvae to a natural settlement inducer resulted in major changes in the miRNA profile within 10 minutes, indicating that miRNAs may be particularly important in mediating the larva/polyp transition but are also likely to play important regulatory roles throughout early coral development in addition to possible roles in disease resistance.

developmental biology↗

bioRxiv2025

Non-linear gene sets for digital biomarkers of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease caused by the loss of motor neurons. Accurate and accessible blood-based diagnosis of neurodegenerative diseases, including ALS, is becoming increasingly critical. It would be of a major clinical advantage to be able to distinguish ALS based on gene expression profiles of blood cells, but this still remains to be established. We analyzed existing data of peripheral blood mononuclear cells (PBMCs) of ALS patients by machine learning, the Maximum Mean Discrepancy (MMD), minimizing the issue of multi-collinearity shown in a multiple regression model, and identified a non-linear combination of gene sets to classify healthy controls and ALS, since non-linear approaches can capture intricate gene-gene interactions and threshold effects, which are often critical for accurately distinguishing disease from healthy states. In the gene expression profiles of PBMCs, a combination of expression levels in 3 genes, PRKAR1A, QPCT, and TMEM71, enabled us to classify ALS with an area under the curve (AUC) accuracy of 0.83 from the public database, which were then confirmed by laboratory blood samples with an AUC accuracy of 0.85. Furthermore, we found the expression levels of PRKAR1A, QPCT, and TMEM71 in motor neurons derived from induced pluripotent stem cells (iPSCs), the cell type at the core of the pathology, classified ALS with an accuracy of AUC 0.79. This approach of discriminating ALS with non-linear gene combinations may be useful for identifying ALS molecular biomarkers for blood-based diagnosis as well as for arriving at a completely new perspective of ALS pathogenesis.

molecular biology↗

bioRxiv2023

Nitric oxide feedback to ciliary photoreceptor cells gates a UV avoidance circuit

Nitric oxide (NO) produced by nitric-oxide synthase (NOS) is a key regulator of animal physiology. Here we uncover a function for NO in the integration of UV exposure and the gating of a UV-avoidance circuit. We studied UV/violet avoidance mediated by brain ciliary photoreceptors (cPRCs) in larvae of the annelid Platynereis dumerilii. In the larva, NOS is expressed in interneurons (INNOS) postsynaptic to cPRCs. UV stimulation of cPRCs triggers INNOS activation and NO production. NO signals retrogradely to cPRCs to induce their sustained post-stimulus activation through an unconventional guanylate cyclase. This late activation drives ciliary beating through serotonergic ciliomotor neurons during UV avoidance. In NOS mutants, retrograde signalling, ciliary activation and UV avoidance are defective. By mathematical modelling, we recapitulate phototransduction and circuit dynamics in wild-type and mutant larvae. Our results reveal how NO-mediated retrograde signalling gates a synaptic circuit and induces short-term memory of UV exposure to orchestrate light-avoidance behaviour.

neuroscience↗

bioRxiv2022

Single-hit genome edition for expression of single-chain immunoglobulins by edited B cells

Lymphocytes have become attractive agents for adoptive immunotherapy but only the reformatting of T cells is efficiently mastered. Despite some recent breakthroughs, B cells remain challenging targets, with regard to both their long-term survival after in vitro manipulation and the rewiring of immunoglobulin (Ig) expression. Working on these two aspects, we have designed a new format of single-chain Ig ("scFull-Ig") coding cassette, the insertion of which at a single genomic position can redirect B cells toward a new antigen specificity, while preserving all functional domains of the B cell receptor. Precise genomic edition at a single locus then provides the most efficient and safe strategy to both disrupt endogenous Ig expression while encoding a new Ig paratope. As proofs of concept, functionality of such scFull BCR was validated by checking specific binding of two different classical targets of tumor immunotherapy, HER2 and CD20. Once the strategy validated in cell lines, it was also validated in primary B cells, again showing successful engineering of BCR expression. These results contribute to pave the way for future B cell-based adoptive cell therapy.

immunology↗

bioRxiv2020

Effects of species traits and ecosystem characteristics on species detection by eDNA metabarcoding in lake fish communities

Although environmental DNA (eDNA) metabarcoding is acknowledged to be an exceptionally useful and powerful tool for monitoring surveys, it has limited applicability, particularly for nationwide surveys. To evaluate the performance of eDNA metabarcoding in broad-scale monitoring, we examined the effects of species ecological/biological traits and ecosystem characteristics on species detection rates and the consequences for community analysis. We conducted eDNA metabarcoding on fish communities in 18 Japanese lakes on a country-wide scale. By comparing species records, we found that certain species traits, including body size, body shape, saltwater tolerance, and habitat preferences, influenced eDNA detection. We also found that the proportion of species detected decreased significantly with an increase in lake surface area, owing to an ecosystem-size effect on species detection. We conclude that species traits, including habitat preferences and body size, and ecosystem size should be taken into consideration when assessing the performance of eDNA metabarcoding in broad-scale monitoring.

ecology↗

bioRxiv2020

Whole-animal connectome and cell-type complement of the three-segmented Platynereis dumerilii larva

Nervous systems coordinate effectors across the body during movements. We know little about the cellular-level structure of synaptic circuits for such body-wide control. Here we describe the whole-body synaptic connectome and cell-type complement of a three-segmented larva of the marine annelid Platynereis dumerilii. We reconstructed and annotated over 1,500 neurons and 6,500 non-neuronal cells in a whole-body serial electron microscopy dataset. The differentiated cells fall into 180 neuronal and 90 non-neuronal cell types. We analyse the modular network architecture of the entire nervous system and describe polysynaptic pathways from 428 sensory neurons to four effector systems - ciliated cells, glands, pigment cells and muscles. The complete somatic musculature and its innervation will be described in a companion paper. We also investigated intersegmental differences in cell-type complement, descending and ascending pathways, and mechanosensory and peptidergic circuits. Our work provides the basis for understanding whole-body coordination in annelids.

neuroscience↗

bioRxiv2020

Quantitative detection of sleep apnea with wearable watch device

The spread of wearable watch devices with photoplethysmography (PPG) sensors has made it possible to use continuous pulse wave data during daily life. We examined if PPG pulse wave data can be used to detect sleep apnea, a common but underdiagnosed health problem associated with impaired quality of life and increased cardiovascular risk. In 41 patients undergoing diagnostic polysomnography (PSG) for sleep apnea, PPG was recorded simultaneously with a wearable watch device. The pulse interval data were analyzed by an automated algorithm called auto-correlated wave detection with adaptive threshold (ACAT) which was developed for electrocardiogram (ECG) to detect the cyclic variation of heart rate (CVHR), a characteristic heart rate pattern accompanying sleep apnea episodes. The median (IQR) apnea-hypopnea index (AHI) was 17.2 (4.4-28.4) and 22 (54%) subjects had AHI [≥]15. The hourly frequency of CVHR (Fcv) detected by the ACAT algorithm closely correlated with AHI (r = 0.81), while none of the time-domain, frequency-domain, or non-linear indices of pulse interval variability showed significant correlation. The Fcv was greater in subjects with AHI [≥]15 (19.6 {+/-} 12.3 /h) than in those with AHI <15 (6.4 {+/-} 4.6 /h), and was able to discriminate them with 82% sensitivity, 89% specificity, and 85% accuracy. The classification performance was comparable to that obtained when the ACAT algorithm was applied to ECG R-R intervals during the PSG. The analysis of wearable watch PPG by the ACAT algorithm could be used for the quantitative screening of sleep apnea.

bioengineering↗

bioRxiv2019

Novel application method for mesenchymal stem cell therapy utilizing its attractant-responsive accumulation property

ObjectivesIt remains difficult to control the delivery of appropriate amounts of mesenchymal stem cell (MSC)-based cell therapies. To examine the ability of MSCs to accumulate at sites of damage and potential therapeutic benefit of providing continuous migration of MSCs to these sites, we observed the effect of MSCs administered in a collagen gel scaffold on healing of a tooth extraction site.\n\nMaterials and MethodsMSCs isolated from the bone marrow of green fluorescent protein (GFP)-expressing donor mice were expanded for 3 weeks in three-dimensional (3-D) culture using a collagen gel scaffold, and evaluated to confirm the efficacy of the scaffold. Next, MSCs suspended in collagen gel were subcutaneously administered into the backs of mice. Two days later, extraction of the maxillary first molar was carried out. Numbers of MSCs in scaffolds, migration and accumulation around the extracted tooth cavity, extraction site healing, and presence of MSCs in vital organs were evaluated.\n\nResultsMSCs cultured in the collagen gel scaffold maintained stemness for 2 weeks. After subcutaneous administration, numbers of MSCs in scaffolds slightly decreased over time, but cells survived for at least 2 weeks. After tooth extraction, GFP-expressing MSCs were confirmed in the surrounding mucosa of the extracted tooth cavity; in the scaffold group, numbers of MSCs increased over time and fewer were observed in lung tissue. Wound healing was enhanced by injection of MSCs via the tail vein or into the back compared with the untreated control group.\n\nConclusionsDelivery in a collagen gel could maintain the characteristics of MSCs, which migrated to the damaged area and promoted wound healing without side effects occurring with conventional administration methods.

cell biology↗

bioRxiv2019

Automated acquisition of knowledge beyond pathologists

Deep learning algorithms have been successfully used in medical image classification and cancer detection. In the next stage, the technology of acquiring explainable knowledge from medical images is highly desired. Herein, fully automated acquisition of explainable features from annotation-free histopathological images is achieved via revealing statistical distortions in datasets by introducing the way of pathologists examination into a set of deep neural networks. As validation, we compared the prediction accuracy of prostate cancer recurrence using our algorithm-generated features with that of diagnosis by an expert pathologist using established criteria on 13,188 whole-mount pathology images. Our method found not only the findings established by humans but also features that have not been recognized so far, and showed higher accuracy than human in prognostic prediction. This study provides a new field to the deep learning approach as a novel tool for discovering uncharted knowledge, leading to effective treatments and drug discovery.

bioinformatics↗

bioRxiv2017

Ciliomotor circuitry underlying whole-body coordination of ciliary activity in the Platynereis larva

Ciliated surfaces harbouring synchronously beating cilia can generate fluid flow or drive locomotion. In ciliary swimmers, ciliary beating, arrests, and changes in beat frequency are often coordinated across extended or discontinuous surfaces. To understand how such coordination is achieved, we studied the ciliated larvae of Platynereis dumerilii, a marine annelid. Platynereis larvae have segmental multiciliated cells that regularly display spontaneous coordinated ciliary arrests. We used whole-body connectomics, activity imaging, transgenesis, and neuron ablation to characterize the ciliomotor circuitry. We identified cholinergic, serotonergic, and catecholaminergic ciliomotor neurons. The synchronous rhythmic activation of cholinergic cells drives the coordinated arrests of all cilia. The serotonergic cells are active when cilia are beating. Serotonin inhibits the cholinergic rhythm, and increases ciliary beat frequency. Based on their connectivity and alternating activity, the catecholaminergic cells may generate the rhythm. The ciliomotor circuitry thus constitutes a stop-and-go pacemaker system for the whole-body coordination of ciliary locomotion.

neuroscience↗