Biology subjects

Inada, H.

Publications and source records attributed to Inada, H..

10 recordsLinked to original sources

bioRxiv2026

Desialylated platelets promote hepatocyte proliferation via the ERK1/2 signaling pathway

Platelets are increasingly recognized as active regulators of tissue repair and liver regeneration beyond their classical roles in hemostasis and thrombosis. Loss of terminal sialic acid from platelet surface glycoproteins, a process known as desialylation, occurs during platelet aging or activation and has been linked to platelet clearance via the asialoglycoprotein receptor (ASGPR) on hepatocytes. However, the mechanisms by which desialylated platelets (D-plts) directly stimulate hepatocyte proliferation remain poorly understood. This study aimed to elucidate the proliferative effects of D-plts on hepatocytes and to identify the underlying signaling mechanisms. D-plts were generated and co-cultured with hepatocyte models exhibiting low or absent levels of asialoglycoprotein receptor 1 (ASGPR1) expression, including HepG2 cells, HuH-7 cells, and human chemically induced liver progenitors. Hepatocyte proliferation was assessed, and the roles of platelet-derived factors and downstream signaling pathways were investigated. Co-culture with D-plts significantly increased hepatocyte proliferation in all three cell models compared with the corresponding controls. Moreover, supernatants derived from stimulated D-plts also significantly enhanced hepatocyte proliferation, suggesting that soluble platelet-derived factors contribute to this effect. Mechanistically, the proliferative effects were mediated predominantly through the ERK1/2 signaling pathway rather than the JAK-STAT pathway in both hepatocytes co-cultured with D-plts and those treated with D-plt-derived supernatants. In conclusion, our findings demonstrate that D-plts directly promote hepatocyte proliferation through an ASGPR-independent pathway, in which ERK1/2 signaling plays a central role. These results highlight a novel mechanism through which platelet desialylation may contribute to liver regeneration. Graphical Abstract(A) Desialylated platelets are readily activated and release increased amounts of EGF, promoting hepatocyte proliferation via the EGF-ERK signaling pathway. (B) Normal platelets show lower reactivity and reduced EGF release than desialylated platelets, resulting in weaker hepatocyte proliferation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/740293v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@d8eb25org.highwire.dtl.DTLVardef@135e644org.highwire.dtl.DTLVardef@1a0a924org.highwire.dtl.DTLVardef@c092e9_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

IntelliProfiler 2.0: An integrated R pipeline for long-term home-cage behavioral profiling in group-housed mice using eeeHive 2D

BackgroundLong-term home-cage monitoring is essential to quantify spontaneous locomotor and social behaviors in group-housed mice, but analysis of high-density RFID tracking data remains a barrier to reproducibility. New methodsWe developed IntelliProfiler 2.0, a fully R-based pipeline tailored to the eeeHive 2D floor-mounted RFID array. The workflow performs data import from text logs, preprocessing, coordinate reconstruction, missing-value handling, feature extraction, statistical testing, and visualization in a single environment. Behavioral metrics include travel distance, close contact ratio (CCR), and a newly implemented inter-individual distance metric. ResultsIn four-day recordings of group-housed C57BL/6J mice (8 males and 8 females), IntelliProfiler 2.0 captured circadian phase-dependent locomotion and proximity patterns and reproduced sex-dependent differences consistent with prior analyses while incorporating updated hardware specifications. Radar-chart summaries enabled intuitive comparison of multidimensional behavioral profiles and inter-individual variability across light/dark phases. Comparison with existing methodsCompared with IntelliProfiler 1.0 and multi-tool workflows, IntelliProfiler 2.0 consolidates analysis into a single, script-based R pipeline, reducing operational complexity and improving reproducibility. The updated implementation supports recent manufacturer-driven changes, including antenna renumbering and multi-USB data export. ConclusionsIntelliProfiler 2.0 provides a reproducible, extensible framework for high-throughput behavioral phenotyping of group-housed mice and is scalable across hardware configurations, including simplified single-board recordings. HighlightsO_LIEnd-to-end R pipeline for eeeHive 2D floor-based RFID tracking analysis C_LIO_LIStandardized setup with comprehensive manuals and protocols C_LIO_LIInter-individual distance metric to quantify group spatial structure C_LIO_LICircadian- and sex-dependent behavioral profiling in group-housed mice C_LIO_LIRadar-charts summarize multidimensional behavioral profiles and variability C_LI

animal behavior and cognition↗

bioRxiv2026

Neonatal social communication and single genes predict the variability of post-pubertal social behavior in a mouse model of paternal 15q11-13 duplication

Mental illnesses associated with high-risk copy number variations (CNVs) are characterized by incomplete penetrance and variable severity, with their underlying mechanisms remaining inadequately understood. We hypothesized that such phenotypic variability is evident from the neonatal stage and is, at least in part, attributable to individual differences in the expression levels of CNV-encoded genes in the brain. We conducted an analysis of the quantitative and functional structure of neonatal social communication, assessed post-pubertal social interaction, and evaluated the brain expression levels of genes within the same cohort of a mouse model of paternal human 15q11-13 duplication, a high-risk factor variably associated with neurodevelopmental disorders. Subsequently, computational methods were utilized to identify predictive variables for the variability of post-pubertal social interaction. Mice harboring the 15q11-13 duplication exhibited distinctive call sequences characterized by diverse connections, which lacked the incentive value necessary for effective social communication with mother mice. The neonatal call sequences and the expression levels of Magel2, along with, to a lesser extent, Herc2 and Ndn, in the prefrontal cortex of the 15q11-13 duplication model were predictive of post-pubertal social interaction. Our findings demonstrate that variability in post-pubertal social interaction--a dimensional characteristic of neurodevelopmental disorders--can be predicted by the variability of neonatal social communication and is influenced by the expression levels of specific CNV-encoded genes in the prefrontal cortex. This computational approach has the potential to predict the developmental trajectories of various dimensions of mental illness among CNV carriers in humans and to identify CNV-encoded driver genes in preclinical models, thereby providing potential mechanistic bases for the development of gene-based therapeutic strategies.

neuroscience↗

bioRxiv2024

IntelliProfiler: a novel analytic tool for behavior dynamics of multiple animals in a home cage

Unbiased, scalable behavioral phenotyping that captures multi-animal interactions in home-cage settings is increasingly needed. Here we present "IntelliProfiler", a research workflow consisting of data processing scripts that extract locomotor activity and pairwise proximity from a commercially available, previously validated, high-resolution radio frequency identification (RFID) floor plate. IntelliProfiler is not a standalone system; it operates on data acquired with the Phenovance floor plate and is not yet validated with other hardware configurations. The workflow reconstructs individual trajectories and positions of multiple mice, enabling long-term assessment of locomotor and social spacing. In proof-of-concept analyses, male mice placed in a novel cage environment maintained greater inter-animal distances than female mice, an effect that strengthened as group size increased. Aging reduced locomotor activity in a group size-dependent manner and altered proximity patterns. In addition, offspring of aged fathers (a paternal-aging autism spectrum disorder (ASD) model) exhibited hyperactivity and increased social distance relative to controls, consistent with ASD-related phenotypes and motivating further investigations. Together, these findings demonstrate that IntelliProfiler workflow provides a practical and versatile approach for screening group dynamics and quantifying complex social behaviors in neuroscience research.

animal behavior and cognition↗

bioRxiv2024

Neuronal migration depends on blood flow in the adult brain

In animal tissues, several cell types migrate along blood vessels, raising the possibility that blood flow influences cell migration. Here, we show that blood flow promotes the migration of new olfactory-bulb neurons in the adult brain. Neuronal migration is facilitated by blood flow, leading to accumulation of new neurons near blood vessels with abundant blood flow. Blood flow inhibition attenuates blood vessel-guided neuronal migration, suggesting that blood contains factors beneficial to neuronal migration. We found that ghrelin, which is increased in blood by hunger, directly influences neuronal migration. Ghrelin signaling promotes somal translocation by activating actin cytoskeleton contraction at the rear of the cell soma. New neurons mature in the olfactory bulb and contribute to the olfactory function for sensing odorants from food. Finally, we show that neuronal migration is increased by calorie restriction, and that ghrelin signaling is involved in the process. This study suggests that blood flow promotes neuronal migration through blood-derived ghrelin signaling in the adult brain, which could be one of the mechanisms that improves the olfactory function for food-seeking behavior during starvation.

neuroscience↗

bioRxiv2023

Clustering temporal step-counting patterns for 24 hours with machine learning revealed potential heterogeneity in the categorization by a traditional tertile procedure

ObjectivesPhysical activity is a crucial aspect of health benefits in the public society. Although studies on the temporal physical activity patterns might lead to the protocol for efficient intervention/program, a standardized procedure to determine and analyze the temporal physical activity patterns remains to be developed. Here, we attempted to develop a procedure to cluster 24-hour patterns of physical activity as step counts measured with an accelerometer-based wearable sensor. MethodsData was collected from 42 healthy participants, comprising 35 males and 7 females, at the Sendai Oroshisho center in 2008. Using unsupervised machine learning, specifically the kernel k-means algorithm with the global alignment kernel was applied on a total of 815 days from 42 participants, and 6 activity patterns were identified. Further, the probability of each 24-hour step-counting pattern was calculated for every participant., and was used in MATLAB to apply spectral clustering, and 5 activity behaviors were identified. ResultsWe could identify six 24-hour step-counting patterns and five daily step-behavioral clusters. When the amount of physical activity was categorized into tertile groups reflecting highly active, moderately active, and low active, each tertile group consisted of different proportions of six 24-hour step-counting patterns. ConclusionsOur study introduces a novel approach using an unsupervised machine learning method to categorize daily hourly activity, revealing six distinct step counting patterns and five clusters representing daily step behaviors. Our procedure would be reliable for finding and clustering physical activity patterns/behaviors and reveal heterogeneity in the categorization by a traditional tertile procedure using total step amount.

animal behavior and cognition↗

bioRxiv2019

Identification of FMRP target genes expressed in corticogenesis: implication for common phenotypes among neurodevelopmental disorders

Fragile X mental retardation protein (FMRP) is encoded by FMR1 gene that is responsible for Fragile X Syndrome (FXS) showing intellectual disability and autism spectrum disorder. FMRP is an RNA binding protein highly expressed in the brain. Although several target genes for FMRP have been identified, limited studies have suggested the role of FMRP in corticogenesis. Here we performed RNA immunoprecipitation sequencing against the murine embryonic neocortex, and identified 124 genes as potential FMRP mRNA targets. We found 48 of these genes as overlapped with autism-related genes, which were categorized in four functional groups: \"transcriptional regulation\", \"regulation of actin cytoskeleton\", \"ubiquitin-mediated proteolysis\" and \"calcium signaling pathway\". Four of these genes showed significant difference in expression in the cortical primordium of Fmr1-KO mice; Huwe1 and Kat6a increased, while Kmt2c and Apc decreased. Although the change in expression of these four genes was relatively small, these subtle changes due to dysregulated transcription could collectively contribute to impaired corticogenesis to cause phenotypes of FXS. Investigating the transcriptional control of FMRP on its mRNA targets may provide new insight to understand neurodevelopmental pathogenesis of FXS.

neuroscience↗

bioRxiv2019

Paternal aging affects the developmental patterns of ultrasonic vocalization induced by maternal separation in neonatal mice individually

Infant crying is an innate communicative behavior that is frequently impaired in certain neurodevelopmental disorders (NDDs). Since advanced paternal age is a reported risk factor for NDDs in offspring, we evaluated the impact of a fathers age on early vocal development in C57BL/6J mice. We recorded and applied a unique combination of computational analyses to ultrasonic vocalizations (USVs) emitted by mouse pups sired by young and aged fathers. Our data showed that advanced paternal age reduced the number and duration of USVs, and altered the syllable composition in pups. Moreover, pups born to young fathers showed convergent vocal characteristics with a rich repertoire during postnatal development, while those born to aged fathers exhibited more divergent vocal patterns with limited repertoire. Principal component analysis in conjunction with clustering analysis demonstrated that pups from aged fathers deviated from typical trajectories of vocal development, which were considered as atypical individuals. Thus, our study indicates that advanced paternal age has a significant effect on offsprings early vocal development. It is suggested that the trajectories of vocal development could be a useful marker of the NDD-like phenotype associated with the advanced paternal age. In addition, our comprehensive computational analysis described here is an effective approach to characterize the altered individual diversity relevant to neurodevelopmental disorders. One Sentence SummaryAdvanced paternal age affects vocal development in early postnatal mice, with more pups showing atypical developmental trajectories.

neuroscience↗

bioRxiv2019

Paternal age affects offspring's behavior possibly via an epigenetic mechanism recruiting a transcriptional repressor REST

Advanced paternal age has deleterious effects on mental health of next generation. Using a mouse model, we have confirmed that offspring derived from aged fathers showed impairments in behavior and abnormalities in the brain structure and activity. Comprehensive target DNA methylome analyses revealed in aged sperm more hypo-methylated genomic regions, in which REST/NRSF binding motif was enriched. Gene set enrichment analyses also identified enrichment of "REST/NRSF target genes", in addition to "Late-fetal genes" and autism spectrum disorder-related "SFARI genes", in up-regulated genes of developing brains from aged father. Indeed, gene sets near hypo-methylated genomic regions with REST/NRSF binding motif were also enriched in up-regulated genes of developing brains. Taken altogether, DNA hypo-methylation due to paternal aging in sperm will induce leaky expression of REST/NRSF target genes in the developing brain, thereby causing neuronal abnormalities and subsequent behavioral alteration in offspring.

neuroscience↗

bioRxiv2018

Conditional upregulation of KCC2 selectively enhances neuronal inhibition during seizures

Abstract/SummaryEfficacious neuronal inhibition is sustained by the neuronal K+Cl- co-transporter KCC2, and loss of KCC2 function through injury or mutation is associated with altered GABAergic signalling and neuronal seizures. Here we report a transgenic mouse with conditional KCC2 overexpression that results in increased membrane transport function. Increased KCC2 has little impact on behavioural and in vitro assays of neuronal excitability and GABAA receptor responses under resting conditions. In contrast, increased KCC2 imparts resistance to seizure-like neuronal activity in hippocampal slices and prevents the progression of mice into behavioural status epilepticus following multiple kainic acid doses. Our results demonstrate a transgenic mouse to facilitate investigations into the role of KCC2 in brain function, and provide a proof of principle that targeting KCC2 may be an effective way to selectively enhance neuronal inhibition to mitigate against diseases that involve an imbalance between excitation and inhibition.

neuroscience↗