Biology subjects

Miura, T.

Publications and source records attributed to Miura, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Spectral fingerprints distinguish buckling from angiogenesis in tortuous blood vessels

HighlightsO_LIBuckling and angiogenesis yield distinct vessel power spectra C_LIO_LIDominant buckling wavelength vs k-2 angiogenic scaling C_LIO_LITwo-phase CA+EB model matches real retinal vessel morphology C_LIO_LIOCTA500 segments show morphology beyond single-mechanism models C_LI Physiological blood vessels are generally straight, but tortuous curvature is observed under pathological conditions across spatial scales, from large arteries to retinal microvasculature and tumor-associated vessels. Here, we compare two theoretical mechanisms of curved vessel formation--mechanical buckling and angiogenic biased random walk--by analyzing the vessel centerline height function in Fourier space. We simplify the Chaplain-Anderson angiogenesis model and an Euler-Bernoulli buckling model with surrounding-tissue support, reproduce curvature numerically, and analyze the power spectra of the resulting patterns. Buckling yields a single characteristic peak in the power spectrum, whereas angiogenesis yields k-2 scaling in the low-frequency range. Mathematical analysis explains the selective growth of a dominant buckling wavelength in the buckling model and the origin of the scaling in the Chaplain-Anderson model. We further analyze OCTA500 segments using morphological descriptors (power spectrum, autocorrelation, and mean squared displacement); neither single-mechanism prediction alone accounts for the observed morphology, motivating a two-phase model in which angiogenic structure generation is followed by mechanical remodeling. Based on this two-phase hypothesis (a Chaplain-Anderson (CA)-like scaling background plus mechanical remodeling), we introduce quantitative indices--residual low-to-high wavenumber power ratio (rLHP) and slope reversal density (SRD)--to quantify Euler-Bernoulli-like buckling contributions in vessel segments. These results suggest that spectral fingerprints and complementary metrics may help distinguish mechanically driven tortuosity from angiogenesis-driven tortuosity in vascular images.

Systems Biology↗

bioRxiv2026

Box-Counting Fractal Dimensions of Cranial Suture: Effects of Measurement Conditions and Model-Based Reproduction of Fractal-Like Patterns

Cranial sutures are important structures associated with skull growth, and it is widely believed that cranial sutures exhibit fractal structure. However, measurement conditions and analytical procedures have varied among studies, making direct comparison and interpretation difficult. In this study, by reviewing previous work, we established a standardized box-counting protocol for quantifying the fractal dimension (FD) of cranial sutures. Using this protocol, we quantified FD in 45 digitized images of human lambdoid sutures and in eight structure-formation model variants designed to generate fractal-like patterns via distinct kernel designs (step, Gaussian, Mexican-hat, and time-dependent/dual-stage), spatially inhomogeneous inhibition (Fbase), low-frequency noise, and time-dependent change of differentiation. We tested whether each model can generate structures with FD values at least as high as those of real sutures using one-sided Welch t-tests with Bonferroni correction for eight comparisons (adj = 0.00625), and found that six of eight model variants satisfied this criterion. Analysis of scale-dependent FD further revealed that FD is close to 1 at fine scales and approaches 2 at coarse scales in both real and model-generated patterns, indicating that cranial sutures are better described as finite-range fractal-like structures than as strict fractals, and that the box-counting FD is a scale-conditioned descriptor sensitive to preprocessing choices.

systems biology↗

bioRxiv2026

Axial Patterning Beyond the Individual: Colony-level Organization in a Siphonophore Colony

Colonial animals composed of clonally produced units can achieve a high degree of functional integration, challenging the distinction between an individual and a higher-order organism. Siphonophores (Cnidaria: Hydrozoa) exemplify this condition, forming highly organized colonies in which genetically identical zooids are specialized for functions such as locomotion, feeding, and reproduction, and are precisely arranged along a shared stem. All zooids arise from two spatially separated budding zones, the nectosomal and siphosomal growth zones, suggesting that positional information along the stem patterns colony organization at the level of the colony rather than individual zooids. However, the molecular basis of this colony-level axial patterning remains poorly understood. Here, we analyze gene expression along the stem of the siphonophore Agalma okenii using RNA sequencing and in situ hybridization chain reaction (HCR). We show that conserved developmental regulators, including Hox and Wnt pathway genes, exhibit region-specific expression corresponding to distinct budding zones and zooid distributions. These results indicate that canonical axial patterning systems are deployed at the level of the colony axis. Our findings demonstrate that developmental gene networks classically associated with anterior-posterior patterning can operate at a higher level of biological organization, providing a mechanistic framework for the evolution of integrated, superorganism-like body plans in colonial animals.

developmental biology↗

bioRxiv2026

Improved adenine-HPLC method for quantifying yeast based on cellular DNA content

Accurate quantification of fungi is important for a myriad of applications but remains challenging. Previously, we demonstrated that an approach called the adenine-HPLC method can quantify bacteria, including those with aggregating properties that are difficult to quantify using conventional methods, by measuring cellular adenine derived from DNA and converting the adenine amount to genome copy number, without being influenced by cell morphology. However, in this study, when this adenine-HPLC method was applied to the quantification of budding yeast as a model fungus, accurate measurement proved impossible. This limitation was attributed to adenine release from other adenine-containing biomolecules, such as RNA and ATP, and we therefore developed a method that suppresses adenine release from these molecules. This method involves reducing the temperature of the acid treatment and prewashing the cells before acid treatment. In addition, we incorporated a process that corrects for the naturally occurring free adenine level as background during total adenine measurement. The improved adenine-HPLC method based on these modifications enables accurate quantification of budding yeast using genomic DNA content in whole cells as the quantification unit.

microbiology↗

bioRxiv2026

Segmented wavetrains and sites of reversal in the mouse seminiferous tubules

Mammalian spermatogenesis occurs in the seminiferous tubules, which exhibit unique spatiotemporal differentiation patterns known as cellular association patterns. In mice, these patterns can be regarded as one-dimensional wavetrains that consistently propagate inward from both ends, resulting in one or more "sites of reversal." Segmented wavetrain pattern, in which the wave propagation direction spatially switches, was observed in our previous three-species reaction-diffusion model for interspecific species difference in spermatogenic waves (Kawamura et al., 2021). However, the biological mechanisms of the formation of sites of reversal and of this directional bias, as well as the principle of pattern formation, remain unknown. Here, we refined our previous model to match the actual biological spatiotemporal scale and examined its dynamics through extensive numerical simulations. The modified model frequently generated segmented wavetrain patterns, corresponding to the sites of reversal, but without directional bias. We systematically examined possible biological mechanisms for the bias and found that tubule elongation, especially near the rete testis, most effectively accounts for the bias among the tested. Extensive simulations revealed that the segmented pattern is numerically stable, emerges more frequently in longer domains, and shows an exponential segment size distribution with a lower limit for the stably existing segment length. These explorations imply that locally emerged unidirectional wavetrains serve as building blocks to generate the stable segmented wavetrains through their interactions. HighlightsO_LISegmented wavetrains reflect sites of reversal in seminiferous tubules. C_LIO_LISegmented patterns frequently emerge but show no inherent directional bias. C_LIO_LITubule elongation may contribute to inward propagation near the rete testis. C_LIO_LISegmented wavetrains are numerically stable and more frequent in longer domains. C_LIO_LIInteractions of local unidirectional wavetrains generate stable segmented structures. C_LI

developmental biology↗

bioRxiv2025

Postembryonic Development and Morphology of the Reproductive System in the Acoel Hofstenia atroviridis

Reconstructing ancestral reproductive systems is essential for understanding the evolution of bilaterian body plans, yet the origin and development of reproductive organs remain poorly characterized. Here, we investigate postembryonic sexual development in the xenacoelomorph Hofstenia atroviridis, a basal acoel species, to gain insight into early bilaterian reproductive evolution. Individuals were reared from eggs to adulthood, and the ontogeny of reproductive organs was examined using histology and immunohistochemistry with muscle and neural markers. H. atroviridis is a protandrous simultaneous hermaphrodite, with sexual maturity correlated with body size rather than age. The male copulatory system comprises a seminal vesicle, granular vesicle, penis with a penile bulb, and a single copulatory stylet, accompanied by regionally specialized musculature and innervation. In contrast, the female reproductive system consists of paired, asaccate ovaries containing large, follicle cell-bound oocytes and lacks a discrete gonopore or copulatory organ. Fertilization occurs via traumatic insemination, and eggs are likely released through the mouth. Despite the organisms overall morphological simplicity, the male reproductive system exhibits pronounced structural differentiation. These findings suggest that sexual selection acting on a hermaphroditic ancestor may have contributed to the early diversification of bilaterian copulatory organs and establish H. atroviridis as a useful model for studying the evolutionary origins of animal reproductive systems.

evolutionary biology↗

bioRxiv2025

Histological transition during ovotestis formation in a female-to-male sex-change fish, the harlequin sandsmelt (Parapercis pulchella)

Many teleost fishes are capable of sex change, and some species possess intersex gonads known as ovotestes, which contain both ovarian and testicular tissues. Uncovering the developmental processes in ovotestis formation is critical for elucidating the mechanisms of intersexuality in vertebrates. However, such developmental processes have been described in only a limited number of species. In this study, we examined the histological structure of juvenile gonads in the harlequin sandsmelt (Parapercis pulchella), a female-to-male sex-change fish in which mature females possess ovotestes. Juveniles measuring up to 32.2 mm in total length exhibited gonads containing cyst-formed developing oogonia and a small number of oocytes. In contrast, larger juveniles possessed more developed ovaries but showed no detectable spermatogenic germ cells. These results suggest that gonads initially differentiate as ovaries and subsequently develop into ovotestes through the emergence of male germ cells. Together with previous studies, our results also indicate that a similar developmental sequence may be shared among sex-change fishes.

zoology↗

bioRxiv2024

Integrating qualitative and quantitative data across multiple labs for model calibration

The integration of computational models with experimental data is a cornerstone for gaining insight into biomedical applications. However, parameter fitting procedures often require a vast availability and frequency of data that are challenging to obtain from a single source. Here, we present a novel methodology "CrossLabFit" designed to integrate qualitative data from multiple laboratories, overcoming the constraints of single-lab data collection. Our approach harmonizes disparate qualitative assessments--ranging from different experimental labs to categorical observations--into a unified framework for parameter estimation. By using machine learning algorithms, these qualitative constraints are represented as dynamic "qualitative windows" that capture significant trends to which models must adhere. For numerical implementation, we developed a GPU-accelerated version of differential evolution to navigate in the cost function that integrated quantitative and qualitative data. We validate our approach across a series of case studies, demonstrating significant improvements in model accuracy and parameter identifiability. This work opens a new paradigm for collaborative science, enabling a methodological road to combine and compare findings between studies to improve our understanding of biological systems and beyond.

systems biology↗

bioRxiv2024

BayesianSSA: a Bayesian statistical model based on structural sensitivity analysis for predicting responses to enzyme perturbations in metabolic networks

BackgroundChemical bioproduction has attracted attention as a key technology in a decarbonized society. In computational design for chemical bioproduction, it is necessary to predict changes in metabolic fluxes when up-/down-regulating enzymatic reactions, that is, responses of the system to enzyme perturbations. Structural sensitivity analysis (SSA) was previously developed as a method to predict qualitative responses to enzyme perturbations on the basis of the structural information of the reaction network. However, the network structural information can sometimes be insufficient to predict qualitative responses unambiguously, which is a practical issue in bioproduction applications. To address this, in this study, we propose BayesianSSA, a Bayesian statistical model based on SSA. BayesianSSA extracts environmental information from perturbation datasets collected in environments of interest and integrates it into SSA predictions. ResultsWe applied BayesianSSA to synthetic and real datasets of the central metabolic pathway of Escherichia coli. Our result demonstrates that BayesianSSA can successfully integrate environmental information extracted from perturbation data into SSA predictions. In addition, the posterior distribution estimated by BayesianSSA can be associated with the known pathway reported to enhance succinate export flux in previous studies. ConclusionsWe believe that BayesianSSA will accelerate the chemical bioproduction process and contribute to advancements in the field.

bioinformatics↗

bioRxiv2023

Mesoscale regulatory mechanisms of branch formation generating hierarchical structure of the lung

The lung airways exhibit distinct features with long, wide proximal branches and short, thin distal branches, crucial for optimal respiratory function. In this study, we investigated the mechanism behind this hierarchical structure through experiments and modeling, focusing on the regulation of branch length and width during the pseudoglandular stage. To evaluate the response of mouse lung epithelium to fibroblast growth factor 10 (FGF10), we monitored the activity of extracellular signal-regulated kinase (ERK). ERK activity exhibited an increase dependent on the curvature of the epithelial tissue, which gradually decreased with the progression of development. We then constructed a computational model that incorporates curvature-dependent growth to predict its impact on branch formation. It was demonstrated that branch length is determined by the curvature dependence of growth. Next, in exploring branch width regulation, we considered the effect of apical contraction, a mechanism we had previously proposed to be regulated by Wnt signaling. Analysis of a mathematical model representing apical constriction showed that branch width is determined by cell shape. Finally, we constructed an integrated computational model that includes curvature-dependent growth and cell shape controls, confirming their coordination in regulating branch formation. This study proposed that changes in the autonomous property of the epithelium may be responsible for the progressive branch morphology.

biophysics↗

bioRxiv2021

Genomic and transcriptomic analyses of the subterranean termite Reticulitermes speratus: gene duplication facilitates social evolution

Termites are model social organisms characterized by a polyphenic caste system. Subterranean termites (Rhinotermitidae) are ecologically and economically important species, including acting as destructive pests. Rhinotermitidae occupies an important evolutionary position within the clade representing an intermediate taxon between the higher (Termitidae) and lower (other families) termites. Here, we report the genome, transcriptome and methylome of the Japanese subterranean termite Reticulitermes speratus. The analyses highlight the significance of gene duplication in social evolution in this termite. Gene duplication associated with caste-biased gene expression is prevalent in the R. speratus genome. Such duplicated genes encompass diverse categories related to social functions, including lipocalins (chemical communication), cellulases (wood digestion and social interaction), lysozymes (social immunity), geranylgeranyl diphosphate synthase (social defense) and a novel class of termite lineage-specific genes with unknown functions. Paralogous genes were often observed in tandem in the genome, but the expression patterns were highly variable, exhibiting caste biases. Some duplicated genes assayed were expressed in caste-specific organs, such as the accessory glands of the queen ovary and frontal glands in soldier heads. We propose that gene duplication facilitates social evolution through regulatory diversification leading to caste-biased expression and subfunctionalization and/or neofunctionalization that confers caste-specialized functions. Significance StatementTermites are model social organisms characterized by a sophisticated caste system, where distinct castes arise from the same genome. Our genomics data of Japanese subterranean termite provides insights into the evolution of the social system, highlighting the significance of gene duplication. Gene duplication associated with caste-biased gene expression is prevalent in the termite genome. Many of the duplicated genes were related to social functions, such as chemical communication, social immunity and defense, and they often expressed in caste-specific organs. We propose that gene duplication facilitates social evolution through regulatory diversification leading to caste-biased expression and functional specialization. In addition, since subterranean termites are ecologically and economically important species including destructive pests in the world, our genomics data serves as a foundation for these studies.

genomics↗

bioRxiv2021

Quantitative modeling of regular retinal microglia distribution

1Microglia are resident immune cells in the central nervous system (CNS), showing a regular distribution. Advancing microscopy and image processing techniques have contributed to elucidating microglias morphology, dynamics, and distribution. However, the mechanism underlying the regular distribution of microglia remains to be elucidated. First, we quantitatively confirmed the regularity of the distribution pattern of microglial soma. Second, we formulated a mathematical model that includes factors that may influence regular distribution. Next, we experimentally quantified the model parameters (cell movement, process formation, and ATP dynamics). The resulting model simulation from the measured parameters showed that direct cell-cell contact is most important in generating regular cell spacing. Finally, we tried to specify the molecular pathway responsible for the repulsion between neighboring microglia. Author summaryMicroglia are resident immune cells in the central nervous system. It is known that the microglia cells show a regular distribution, but the mechanism underlying the regular distribution remains to be elucidated. In the present study, we quantitatively assayed the regularity of the microglia soma distribution using the image processing technique. Next, we formulated a mathematical model of cell distribution that includes factors that may influence regular distribution. Next, we experimentally quantified the model parameters using organ culture. As a result, we obtained parameters for cell migration, cell process dynamics, and extracellular ATP dynamics. Then we undertook numerical simulation of the mathematical model using the parameters obtained by the experiments. The resulting model simulations showed that direct cell-cell contact is the most important factor in generating regular spacing. Finally, we screened possible molecular pathways involved in the regular spacing of microglia, which confirmed the validity of the model.

cell biology↗

bioRxiv2021

Chronic exercise protects against the progression of renal cyst growth and dysfunction in rats with polycystic kidney disease

IntroductionPolycystic kidney disease (PKD) is a genetic disorder characterized by the progressive enlargement of renal epithelial cysts and renal dysfunction. Previous studies have reported the beneficial effects of chronic exercise on chronic kidney disease. However, the effects of chronic exercise have not been fully examined in PKD patients or models. The effects of chronic exercise on the progression of PKD were investigated in a polycystic kidney (PCK) rat model. MethodsSix-week-old male PCK rats were divided into a sedentary group and an exercise group. The exercise group underwent forced treadmill exercise for 12 weeks (28 m/min, 60 min/day, 5 days/week). After 12 weeks, kidney function and histology were examined, protein expressions were analyzed, and signaling cascades of PKD were examined. ResultsChronic exercise reduced the excretion of urinary protein, liver-type fatty acid-binding protein, plasma creatinine, urea nitrogen, and increased plasma irisin and urinary arginine vasopressin (AVP) excretion. Chronic exercise also slowed renal cyst growth, glomerular damage, and interstitial fibrosis, and led to reduced Ki-67 expression. Chronic exercise had no effect on cAMP content but decreased the renal expression of B-Raf and reduced the phosphorylation of extracellular signal-regulated kinase (ERK), mammalian target of rapamycin (mTOR), and S6. ConclusionChronic exercise slows renal cyst growth and damage in PCK rats, despite increasing AVP, with down-regulation of the cAMP/B-Raf/ERK and mTOR/S6 pathways in the kidney of PCK rats.

physiology↗

bioRxiv2020

Noise-induced scaling in skull suture interdigitation

Sutures, the thin, soft tissue between skull bones, serve as the major craniofacial growth centers during postnatal development. In a newborn skull, the sutures are straight; however, as the skull develops, the sutures wind dynamically to form an interdigitation pattern. Moreover, the final winding pattern had been shown to have fractal characteristics. Although various molecules involved in suture development have been identified, the mechanism underlying the pattern formation remains unknown. In a previous study, we reproduced the formation of the interdigitation pattern in a mathematical model combining an interface equation and a convolution kernel. However, the generated pattern had a specific characteristic length, and the model was unable to produce a fractal structure with the model.In the present study, we focused on the anterior part of the sagittal suture and formulated a new mathematical model with time–space-dependent noise that was able to generate the fractal structure. We reduced our previous model to represent the linear dynamics of the centerline of the suture tissue and included a time–space-dependent noise term. We showed theoretically that the final pattern from the model follows a scaling law due to the scaling of the dispersion relation in the full model, which we confirmed numerically. Furthermore, we observed experimentally that stochastic fluctuation of the osteogenic signal exists in the developing skull, and found that actual suture patterns followed a scaling law similar to that of the theoretical prediction.Author summary Skull sutures (thin, undifferentiated tissue between bones) act as the growth centers for the skull. Sutures are straight at birth but later develop an interdigitated pattern that ultimately becomes a fractal structure. While our previous mathematical model of sutures generated a periodic pattern, the mechanism underlying the fractal structure formation remained to be elucidated. Here, we focused only on the anterior part of the sagittal suture and formulated a reduced model representing the initial linear phase of pattern formation with the addition of a time–space-dependent noise term. We showed analytically that the model generates patterns with a scaling law. This result was confirmed numerically and experimentally.View Full Text

developmental biology↗

bioRxiv2020

Remodeling mechanisms determine size distributions in developing retinal vasculature

The development of retinal blood vessels has extensively been used as a model to study vascular pattern formation. To date, various quantitative measurements, such as size distribution have been performed, but the relationship between pattern formation mechanisms and these measurements remains unclear. In the present study, we first quantitatively measured the island size distribution in the retinal vascular network and found that it tended to exhibit an exponential distribution. We were able to recapitulate this distribution pattern in a theoretical model by implementing the stochastic disappearance of vessel segments around arteries could reproduce the observed exponential distribution of islands. Second, we observed that the diameter distribution of the retinal artery segment obeyed a power law;. We theoretically showed that an equal bifurcation branch pattern and Murrays law could reproduce this pattern. This study demonstrates the utility of examining size distribution for understanding the mechanisms of vascular pattern formation.

developmental biology↗

bioRxiv2020

A new microcirculation culture method with a self-organized capillary network

A lack of microcirculation has been one of the most significant obstacles for three-dimensional culture systems of organoids and embryonic tissues. Here, we developed a simple and reliable method to implement a perfusable capillary network in vitro. The method employed the self-organization of endothelial cells to generate a capillary network and a static pressure difference for culture medium circulation, which can be easily introduced to standard biological laboratories and enables long-term cultivation of vascular structures. Using this culture system, we perfused the lumen of the self-organized capillary network and observed a flow-induced vascular remodeling process, cell shape changes, and collective cell migration. We also observed an increase in cell proliferation around the synthetic vasculature induced by flow, indicating functional perfusion of the culture medium. We also reconstructed extravasation of tumor and inflammatory cells, and circulation inside spheroids including endothelial cells and human lung fibroblasts. In conclusion, this system is a promising tool to elucidate the mechanisms of various biological processes related to vascular flow.

cell biology↗

bioRxiv2020

Virtual-freezing fluorescence imaging flow cytometry

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. For example, at high flow speed (i.e., high throughput), the integration time of the image sensor becomes short, resulting in reduced sensitivity or pixel resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually "freezing" the motion of flowing cells on the image sensor to effectively achieve 1,000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells/s without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

cell biology↗

bioRxiv2018

Deep-learning-based flexible pipeline for segmenting and tracking cells in 3D image time series for whole brain imaging

The brain is a complex system that operates based on coordinated neuronal activities. Brain-wide cellular calcium imaging techniques have quickly advanced in recent years and become powerful tools for understanding the neuronal activities of small animal models. The whole brain imaging generally requires to extract the neuronal activities from three-dimensional (3D) image series. Unfortunately, the 3D image series are obtained under imaging conditions different among laboratories and extracting neuronal activities from the data requires multiple processes. Therefore researchers need to develop their own software, which has prevented the application of whole-brain imaging experiments in more laboratories. Here, we combined traditional image processing techniques with the powerful deep-learning method which can be flexibly modified to fit 3D image data in the nematode Caenorhabditis elegans obtained under different conditions. We first trained the 3D U-net deep network to classify each pixel into cell and non-cell categories. Cells merged as a whole region were further separated into individual cells by watershed segmentation. The cells were then tracked in 3D space over time with the combination of a feedforward network and a point set registration method to use local and global relative positions of the cells, respectively. Remarkably, one manually annotated 3D image combined with data augmentation was sufficient for training the deep networks to obtain satisfactory tracking results. Our method correctly tracked more than 98% of neurons in three different image datasets and successfully extracted brain-wide neuronal activities. Our method worked well even when the sampling rate was reduced: 86% correct in case 4/5 frames were removed, and when artificial noise was added into the raw images: 91% correct in case 35 times of background-level noise was added. Our results proved that deep learning is widely applicable to different datasets and can help us in establishing a flexible pipeline for extracting whole brain activities.

bioinformatics↗