Biology subjects

Tsutsumi, M.

Publications and source records attributed to Tsutsumi, M..

14 recordsLinked to original sources

bioRxiv2026

Confidence: Its Measurement, Relation to Behavior, and Neural Representation

Confidence (certainty/uncertainty about one's own decision) has attracted considerable attention in psychology, neuroscience, and artificial intelligence. Yet its relation to behavior remains unclear: Some treat confidence as a cause of behavior whereas others view it as a state controlled by environmental variables. The unobservable nature of confidence makes its measurement validation and analyses difficult. To tackle these issues, we developed a novel procedure combining a decision-making task, risk choices, and a post-task open-ended questionnaire. Point-gain/loss amounts for correct/incorrect decisions varied depending on choices between high-risk/high-return and low-risk/low-return. In the questionnaire, 90% of 16 participants reported feelings interpretable as certainty/uncertainty when making those risk choices despite no instruction about confidence, whereas 8% did so when the choices led to identical outcomes/returns. This suggests confidence is a state controlled by environmental contingencies rather than a cause of behavior. We also decoded changes in the state from electroencephalography and functional magnetic resonance imaging.

neuroscience↗

bioRxiv2026

In vivo brain temperature measurement using quantum dot imaging temperature sensors

Temperature regulation in the brain is essential for maintaining neuronal function and preventing thermally induced damage. Here, we report the development and in vivo application of quantum dots (QDs) to high-resolution thermometry in the mouse brain using two-photon excitation microscopy. These QDs, via the red-to-green photoluminescence (PL) intensity ratios, enabled stable temperature measurements in both normal and chronically hypo-perfused cerebral tissue. Our findings show that localized neuronal activity leads to transient heat generation, which is rapidly dissipated by cerebrovascular responses. In a chronic hypoperfusion model, impaired vascular function resulted in exaggerated and prolonged brain temperature elevations. This thermometry system provides unprecedented insight into the mechanisms of cerebral thermoregulation and highlights the importance of vascular cooling in protecting the brain from heat-induced stress, particularly in pathological conditions such as stroke.

bioengineering↗

bioRxiv2026

Mind the gap: quantifying population-individual gap in depressive symptom dynamics through energy landscapes

People do not always feel as they appear. Someone who seems stable may struggle internally, whereas someone who appears distressed may experience it differently. This gap matters in psychiatry, where assessment relies on symptom scales and external evaluation. Here we developed mindGAP (Measuring INDividual-population GAPs in psychiatric energy landscapes), a hierarchical variational Bayesian framework that uses longitudinal questionnaire data to estimate population-level and individual-level pairwise maximum entropy models (pMEMs). We applied mindGAP to time-series PHQ-9 data from 248 participants. The population landscape contained three major states, whereas individual-level landscapes often diverged from this shared structure. We quantified this gap as individual-population landscape divergence, which was associated not only with depressive severity but also with modern-type depression-related traits (TACS-22) and interpersonal sensitivity-self traits (IPS-22). Thus, mindGAP opens a route to quantifying a previously unquantified gap between population-level and individual-level symptom organization.

bioinformatics↗

bioRxiv2026

Decoding Anadara shell morphology with deep learning

Accurate shell shape quantification is critical for studying biodiversity and evolution, yet intraspecific variability in bivalves makes morphology-based identification difficult. Traditional methods, including landmark-based analyses and elliptic Fourier descriptors, suffer either from subjectivity in homologous point selection or from limited use of contour information. Here, we introduce Morpho-VAE, a deep generative framework integrating a variational autoencoder with a supervised classifier, to analyze shell images of five Anadara species. Morpho-VAE outperforms conventional approaches in species classification by embedding morphological variation into a low-dimensional space where species cluster distinctly. To highlight species-specific morphological patterns, we develop a patch masking assay, revealing the hinge line as a shared morphological marker across species and species-specific regions near the umbo and anterior ventral margin. The decoder further enables morphological visualization via image reconstruction and interpolation. Our results show that Morpho-VAE can automatically extract species-defining morphological patterns from raw images, providing complementary or novel insights beyond traditional morphometric methods.

biophysics↗

bioRxiv2025

Sequence-encoded conformational biases shape self-assembly modes of intrinsically disordered proteins

Self-assembly of intrinsically disordered proteins (IDPs) underlies cellular functions and disease pathogenesis. This process is mediated by two intermolecular interaction modes: transient point-to-point contacts described by the sticker-and-spacer framework, and persistent surface-to-surface contacts proposed in the cross-{beta} hypothesis. We investigated the molecular basis of these modes in the context of conformational biases, defined as sequence-encoded structural preferences of local segments. Using a five-residue model, we generated lag-series IDPs from the TIA-1 prion-like domain by systematically modulating conformational biases while preserving amino acid composition. The lag-series IDPs demonstrated distinct condensate properties and varying capacities for amyloid fibril formation. Their structural analyses revealed that strongly biased regions preferentially adopt extended structures, including {beta}-strands, and the spacing between these regions influences metastable {beta}-sheet formation. Our findings demonstrate that local conformational biases shape interaction modes of IDPs, thereby linking sequence to condensate properties and amyloid fibril formation. Significance StatementProteins fold into three-dimensional structures defined by their amino acid sequences. In contrast, intrinsically disordered proteins (IDPs) lack stable structures, yet their sequences encode unique self-assembly behaviors, including phase separation and amyloid fibril formation. Can such behaviors be explained within structure-based frameworks? Using a five-residue model, we showed that IDP sequences encode local structural preferences, termed conformational biases, within short segments. These biases determine whether segments engage in transient point-to-point interactions driving phase separation or persistent surface-to-surface interactions leading to amyloid fibril formation. By bridging sequence, structure, and interaction modes, our work provides a comprehensive mechanism for self-assembly and conceptual tools for understanding IDP-related biological functions and disease mechanisms.

biophysics↗

bioRxiv2025

Emergence of cell polarity by reciprocal interactions between Wnt and core PCP components

Planar cell polarity (PCP) is established by asymmetric localization of core PCP components in each cell. Since some Wnt proteins can induce PCP in vertebrates, it has been proposed that Wnt concentration gradients provide spatial cues for polarization. Here, however, we present evidence that Wnt11 can regulate PCP in a gradient-independent manner. In the neural plate of Xenopus embryos, endogenous Wnt11 does not form an obvious gradient in the direction of PCP, but is polarized at cell boundaries together with core PCP components. Wnt11 polarization is dependent on core PCP components, while polarization of core PCP components can also be induced by Wnt11, indicating a mutual amplification loop between Wnt11 and core PCP components in PCP formation. Furthermore, Wnt11 and core PCP components compose an intercellular loop to coordinate the direction of polarity. Thus, we propose that local and reciprocal interactions between Wnt11 and core PCP components can generate PCP.

developmental biology↗

bioRxiv2025

In vivo deep-brain microscopy at submicrometer resolution with refractive index-matched prism interfaces

The mammalian brain is a thick and densely layered structure comprising a huge number of neurons that work together to process information and regulate brain functions. Although various optical methods have been developed to investigate deep brain dynamics, they are limited by technical constraints, invasiveness, suboptimal spatial resolution, and/or a restricted field of view. To overcome these limitations, we developed an implantable, optically optimized microprism interface with a refractive index matched to that of brain tissue and water, enabling minimally-invasive, wide-field two-photon imaging method with enhanced brightness and sub-micron resolution in deep prefrontal areas.

neuroscience↗

bioRxiv2025

Disentanglement of batch effects and biological signals across conditions in the single-cell transcriptome

Batch effects, which arise due to technical variations across different experimental factors, pose a significant challenge for single-cell transcriptomic analysis. Although various batch correction methods have been developed to mitigate these effects, they often indiscriminately mix data from different batches, leading to the removal of biologically meaningful signals. This limitation hinders comparative analyses across multiple conditions, an essential aspect of scientific research. Recent approaches attempt to address this issue by mapping data to separate spaces, but they prevent direct comparisons between conditions. Here, we propose Kanade, a batch correction method based on a variational autoencoder. Kanade explicitly disentangles batch effects from biological signals by specializing latent variables for different types of information. Using both simulated and real datasets, we demonstrate that Kanade selectively correct batch effects while preserving essential biological features, enabling more accurate comparative analyses in single-cell transcriptomics.

bioinformatics↗

bioRxiv2025

Cellular Responses to Photothermal Therapy: Heat-Induced ERK Signaling and Intercellular Communication in Solid Tumors

Nanoparticle-mediated photothermal therapy (PTT) shows promise as a standalone cancer treatment but faces clinical challenges due to inconsistent efficacy. Its translation is further hindered by a limited understanding of plasmon-induced heat effects, such as stress responses and intercellular signaling. Here, we investigate how plasmon-induced local heating affects cellular behavior and fate within tumor spheroids by focusing on the activity of the extracellular signal-regulated kinase (ERK). Spheroids were prepared from HeLa cells that express a FRET-based ERK sensor, and ERK activity changes under photothermal stimuli were tracked using a deep-learning program, 3DeeCellTracker. Gold nanostars were used as highly efficient photothermal transducers. Our results revealed significant alterations in ERK signaling patterns upon photothermal stimulation compared to spontaneous ERK activity in untreated spheroids, including changes in the activation frequency, timing, and duration. Notably, photothermal-induced ERK activity propagated across neighboring cells within the spheroid, suggesting intercellular communication. Furthermore, analysis of cell death and division further demonstrated that laser power modulates cellular fate during photothermal therapy. This study provides insights for predicting the therapeutic effects of PPT and guides the rational design of next-generation photothermal strategies. Additionally, our approach demonstrates the potential of FRET-based biosensors and deep-learning tools as powerful methods to study the effects of various therapeutic stimuli on solid tumors at the single-cell level.

cancer biology↗

bioRxiv2024

Amyloid-β-induced Alteration of Fast and Localized Calcium Elevations in Cultured Astrocytes

Alzheimers disease (AD) is a progressive neurodegenerative disorder that causes cognitive decline. Uncovering the mechanisms of neurodegeneration in the early stages is essential to establish a treatment for AD. Recent research has proposed the hypothesis that amyloid-{beta} (A{beta}) oligomers elicit an excessive glutamate release from astrocytes toward synapses through intracellular free Ca2+ ([Ca2+]i) elevations in astrocytes, finally resulting in neuronal dendritic spine loss. Under physiological conditions, astrocytic [Ca2+]i elevations range spatially from microdomains to network-wide propagation and temporally from milliseconds to tens of seconds. Astrocytic localized and fast [Ca2+]i elevations might correlate with glutamate release; however, the A{beta}-induced alteration of localized, fast astrocytic [Ca2+]i elevations remains unexplored. In this study, we quantitatively investigated the A{beta} dimers-induced changes in the spatial and temporal patterns of [Ca2+]i in a primary culture of astrocytes by two-photon excitation spinning-disk confocal microscopy. The frequency of fast [Ca2+]i elevations occurring locally in astrocytes ([≤]0.5 s, [≤]35 {micro}m2) and [Ca2+]i event occupancy relative to cell area significantly increased after exposure to A{beta} dimers. The effect of A{beta} dimers appeared dose-dependently above 500 nM, and these A{beta} dimers-induced [Ca2+]i elevations were primarily mediated by a metabotropic purinergic receptor (P2Y1 receptor) and Ca2+ release from the endoplasmic reticulum. Our findings suggest that the A{beta} dimers-induced alterations and hyperactivation of astrocytic [Ca2+]i is a candidate cellular mechanism in the early stages of AD.

neuroscience↗

bioRxiv2023

Actin dynamics switches two distinct modes of endosomal fusion in yolk sac visceral endoderm cells

Membranes undergo various patterns of deformation during vesicle fusion, but how this membrane deformation is regulated and contributes to fusion remains unknown. In this study, we developed a new method of observing the fusion of individual late endosomes and lysosomes by using yolk sac visceral endoderm cells that have huge endocytic vesicles. We found that there were two distinct fusion modes that were differently regulated. In homotypic fusion, two late endosomes fused quickly, whereas in heterotypic fusion they fused to lysosomes slowly. Mathematical modeling showed that vesicle size is a critical determinant of these fusion types and that membrane fluctuation forces can overcome the vesicle size effects. We found that actin filaments were bound to late endosomes and forces derived from dynamic actin remodeling were necessary for quick fusion during homotypic fusion. Furthermore, cofilin played a role in endocytic fusion by regulating actin turnover. These data suggest that actin promotes vesicle fusion for efficient membrane trafficking in visceral endoderm cells.

cell biology↗

bioRxiv2023

Ether phospholipids modulate somatosensory responses by tuning multiple receptor functions in Drosophila

Transient receptor potential (TRP) and PIEZO channels are known receptors for physical stimuli, such as temperature and mechanical touch, respectively, in sensory nerves. As these receptors are localized in the plasma membrane, the modulation of sensory receptor activity by plasma membrane lipids has recently attracted attention. In this study, we focused on ether phospholipids (ePLs), which are abundant in neurons, and analyzed their role in somatosensation using Drosophila as a model. Reduced mechanosensory behavior was observed with ePL synthesizing gene knockout or knockdown in mechano-sensitive PIEZO-expressing neurons. The activation of PIEZO channels was significantly augmented in the presence of ePLs. Furthermore, we observed that ePLs modulate the thermosensory behavior and reduce thermal threshold of the thermosensitive TRPA1 channels. Finally, we revealed that ePLs affect membrane tension and lipid order of the plasma membrane in culture cells. Our study identified ePLs as a modulator of multiple somatosensation modalities in Drosophila, which underscore the significance of functional interaction between membrane lipid and sensory channel proteins.

molecular biology↗

bioRxiv2023

Tight junction membrane proteins regulate the mechanical resistance of the apical junctional complex

Epithelia must be able to resist mechanical force to preserve tissue integrity. While intercellular junctions are known to be important for the mechanical resistance of epithelia, the roles of tight junctions (TJs) remain to be established. We previously demonstrated that epithelial cells devoid of the TJ membrane proteins claudins and JAM-A completely lack TJs and exhibit focal breakages of their apical junctions. Here, we demonstrate that apical junctions undergo spontaneous fracture when claudin/JAM-A-deficient cells are exposed to mechanical stress. The junction fracture was accompanied by actin disorganization, and actin polymerization was required for apical junction integrity in the claudin/JAM-A-deficient cells. Further deletion of CAR resulted in the disruption of ZO-1 molecule ordering at cell junctions, accompanied by severe defects in apical junction integrity. These results demonstrate that TJ membrane proteins regulate the mechanical resistance of the apical junctional complex in epithelial cells. SummaryTight junction membrane proteins claudins, JAM, and CAR coordinately regulate the nanometer-scale organization of ZO-1 molecules, and are required for the mechanical resistance of apical junctions in epithelial cells.

cell biology↗

bioRxiv2022

A method for morphological feature extraction based on variational auto-encoder : an application to mandible shape

Shape analysis of biological data is crucial for investigating the morphological variations during development or evolution. However, conventional approaches for quantifying shapes are difficult as exemplified by the ambiguity in the landmark-based method in which anatomically prominent "landmarks" are manually annotated. In this study, a morphological regulated variational autoencoder (Morpho-VAE) is proposed that conducts image-based shape analysis using imaging processing through a deep-learning framework, thereby removing the need for defining landmarks. The proposed architecture comprises a VAE combined with a classifier module. This integration of unsupervised and supervised learning models (i.e., VAE and classifier modules) is designed to reduce dimensionality by focusing on the morphological features in which the differences between data with different labels are best distinguished. The proposed method is applied to the image dataset of the primate mandible to extract morphological features, which allow us to distinguish different families in a low dimensional latent space. Furthermore, the visualization analysis of decision-making of Morpho-VAE clarifies the area of the mandibular joint that is important for family-level classification. The generative nature of the proposed model is also demonstrated to complement a missing image segment based on the remaining structure. Therefore, the proposed method, which flexibly performs landmark-free feature extraction from complete and incomplete image data is a promising tool for analyzing morphological datasets in biology. AUTHOR SUMMARYShape is the most intuitive visual characteristic; however, shape is generally difficult to measure using a small number of variables. Specifically, for biological data, shape is sometimes highly diverse as it has been acquired through a long evolutionary process, adaptation to environmental factors, etc., which limits the straightforward approach to shape measurement. Therefore, a systematic method for quantifying such a variety of shapes using a low-dimensional quantity is needed. To this end, we propose a novel method that extracts low-dimensional features to describe shapes from image data using machine learning. The proposed method is applied to the primate mandible image data to extract morphological features that reflect the characteristics of the groups to which the organisms belong and then those features are visualized. This method also reconstructs a missing image segment from an incomplete image based on the remaining structure. To summarize, this method is applicable to the shape analysis of various organisms and is a useful tool for analyzing a wide variety of image data, even those with a missing segment.

bioinformatics↗