Biology subjects

Murai, T.

Publications and source records attributed to Murai, T..

13 recordsLinked to original sources

bioRxiv2026

Predicted structure of the 89-kDa invasion-tip protein of Holospora obtusa, an endonuclear symbiont of Paramecium caudatum, suggests a pH-dependent conformational change

The endonuclear symbiont Holospora obtusa invades the macronucleus of Paramecium caudatum using an infectious-form invasion-tip containing a major 89-kDa periplasmic protein implicated in escape from the host digestive vacuole and macronuclear invasion. Sequence-based analyses placed this protein within a Holospora-specific family and predicted an N-terminal membrane-anchoring module and a long alpha-helical C-terminal region. AlphaFold2 modeling followed by molecular dynamics indicated that the C-terminal region forms an antiparallel, spectrin-repeat-like helical solenoid containing a localized three-helix coiled-coil. The protein exhibits a large pH-dependent charge difference, becoming 55 units more positive at pH 4 than at pH 7. Independent simulations at these pH values differed mainly in the relative orientation of the N-terminal core and C-terminal rod, described by DynDom as an approximately 35 degrees rigid-body rotation about a hinge centered on Gly291. However, none of the nearby glutamates (Glu273, Glu275, and Glu302) formed a pH-dependent salt bridge, and no specific protonation-dependent interaction responsible for the conformational difference was identified. We nonetheless propose, as a testable hypothesis, that acidification of the digestive vacuole may promote this reorientation, thereby repositioning the N-terminal membrane-anchoring module at the bacterial surface as an early step toward escape from the vacuole.

microbiology↗

bioRxiv2026

Identity-state expression and switching in co-conscious dissociative identity disorder: a non-traumatic proof-of-concept fMRI study

Dissociative identity disorder (DID) remains debated because identity-state phenomena are privately experienced and may be attributed to suggestion, simulation or role enactment. Most neuroimaging studies rely on symptom provocation or traumatic recall, which complicates interpretation and is poorly suited to co-conscious presentations where simultaneous awareness should make state differences hardest to detect. We applied Identity-State Characterization and Analysis (ID-SCAN), a non-traumatic, identity-cued functional magnetic resonance imaging protocol, to a DSM-5-diagnosed woman with persistent co-consciousness between Adult and Adolescent identity-states. One task used identical insect images that evoked opposite preferences across identity-states; the other used trait judgments about self, the other identity-state and a shared intimate other. Analyses combined Bayesian single-case general linear modelling, generalized psychophysiological interaction connectivity and searchlight representational similarity analysis. Identity-instruction cue epochs were pooled across tasks to assess switch direction. The same insect stimuli engaged different valuation-related configurations across identity-states: Adolescent-selective effects centred on striato-thalamic regions, whereas Adult-selective effects extended to amygdala and orbitofrontal/medial prefrontal cortex, with distinct task-evoked coupling. Adult-as-self and Adolescent-as-self occupied separable positions within canonical self-referential regions. Cue-locked activity differed by switch direction across tasks, with larger reconfiguration when switching to Adult (mean between-cluster beta separation 4.30 versus 0.85; permutation p = 0.0001). Cross-task overlap localized a limited shared task-related substrate mainly to posterior visual and dorsal parietal cortex. Even under persistent co-consciousness and without trauma provocation, identity-state expression and switching showed convergent within-person neural signatures. The findings support non-traumatic mechanistic phenotyping of dissociative presentations and motivate cohort and longitudinal studies, including treatment-tracking work.

neuroscience↗

bioRxiv2025

Neural Underpinnings of Olfactory Dysfunction across Parkinson's and Alzheimer's Spectra

Olfactory dysfunction is a frequent yet understudied feature of neurodegenerative spectrum disorders, including Alzheimers disease (AD) and Parkinsons disease (PD). To disentangle the neural substrates of hyposmia across disease spectra, we examined 222 participants from the Parkinsons and Alzheimers disease Dimensional Neuroimaging Initiative cohort. Participants were classified according to the presence of cognitive disturbance, movement disorder, or both. Olfactory testing disclosed that cognitive disturbance and movement disorder were independently associated with hyposmia, and having both cognitive disturbance and movement disorder was associated with severe hyposmia. Whole-brain voxel-based morphometry revealed that hyposmia was associated with atrophy in the medial temporal lobe (MTL) in individuals with cognitive disturbance, whereas an artificial intelligence-based segmentation model identified olfactory bulb atrophy in those with movement disorder. Regression analysis and structural equation modeling further confirmed that the MTL and olfactory bulb volume contributed to olfactory performance through distinct processes. Individuals with cognitive disturbance and movement disorder had atrophy in both the MTL and olfactory bulb ("double hit"). We identified dual processes underlying hyposmia in the AD and PD spectra: a process linking MTL degeneration to cognitive disturbance and a process linking olfactory bulb degeneration to movement disorder. Our transdiagnostic approach enhances strategy in identifying specific neural correlates underlying hyposmia, lending support to the development of biomarkers for early intervention in AD and PD.

neuroscience↗

bioRxiv2025

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

neuroscience↗

bioRxiv2024

An Open Access Resource for Marmoset Neuroscientific Apparatus

The use of the common marmoset (Callithrix jacchus) for neuroscientific inquiry has grown precipitously over the past two decades. Despite windfalls of grant support from funding initiatives in North America, Europe, and Asia to model human brain diseases in the marmoset, marmoset- specific apparatus are of sparse availability from commercial vendors and thus are often developed and reside within individual laboratories. Through our collective research efforts, we have designed and vetted myriad designs for awake or anesthetized magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), as well as focused ultrasound (FUS), electrophysiology, optical imaging, surgery, and behavior in marmosets across the age- span. This resource makes these designs openly available, reducing the burden of de novo development across the marmoset field. The computer-aided-design (CAD) files are publicly available through the Marmoset Brain Connectome (MBC) resource (https://www.marmosetbrainconnectome.org/apparatus/) and include dozens of downloadable CAD assemblies, software and online calculators for marmoset neuroscience. In addition, we make available a variety of vetted touchscreen and task-based fMRI code and stimuli. Here, we highlight the online interface and the development and validation of a few yet unpublished resources: Software to automatically extract the head morphology of a marmoset from a CT and produce a 3D printable helmet for awake neuroimaging, and the design and validation of 8-channel and 14- channel receive arrays for imaging deep structures during anatomical and functional MRI.

bioengineering↗

bioRxiv2024

Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile

Resting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiatric disorders. Despite progress, development of the reliable and practical FC biomarker remains an unmet goal, particularly one that is clinically predictive at the individual level with generalizability, robustness, and accuracy. In this study, we propose a new approach to profile each connectivity from diverse perspective, encompassing not only disorder-related differences but also disorder-unrelated variations attributed to individual difference, within-subject across-runs, imaging protocol, and scanner factors. By leveraging over 1500 runs of 10-minute resting-state data from 84 traveling-subjects across 29 sites and 900 participants of the case-control study with three psychiatric disorders, the disorder-related and disorder-unrelated FC variations were estimated for each individual FC. Using the FC profile information, we evaluated the effects of the disorder-related and disorder-unrelated variations on the output of the multi-connectivity biomarker trained with ensemble sparse classifiers and generalizable to the multicenter data. Our analysis revealed hierarchical variations in individual functional connectivity, ranging from within-subject across-run variations, individual differences, disease effects, inter-scanner discrepancies, and protocol differences, which were drastically inverted by the sparse machine-learning algorithm. We found this inversion mainly attributed to suppression of both individual difference and within-subject across-runs variations relative to the disorder-related difference by weighted-averaging of the selected FCs and ensemble computing. This comprehensive approach will provide an analytical tool to delineate future directions for developing reliable individual-level biomarkers.

neuroscience↗

bioRxiv2023

The multilevel society of proboscis monkeys with a possible patrilineal basis

Multilevel societies (MLS), which are characterized by two or more levels of social organization, are among the most complex primate social systems. MLS have only been recorded in a limited number of primates, including humans. The aim of this study was to investigate whether proboscis monkeys (Nasalis larvatus) form MLS in Sabah, Malaysia, and to genetically characterize their dispersal patterns. Association data were obtained through direct observation (35 months) and kinship data through genetic analysis, based on feces collected from [~]200 individuals. The results strongly suggest that proboscis monkeys exhibit a form of MLS, with several core reproductive units and a bachelor group woven together into a higher-level band. Genetic analysis revealed that the females migrated randomly over short and long distances; however, the males tended to migrate relatively shorter distances than females. Furthermore, male-male dyads showed a slightly higher average relatedness than female-female dyads. Combined with the results of direct observations, we conclude that proboscis monkeys form a MLS with at least two layers and a patrilineal basis. Since patrilineal MLS have been identified as an important step in the evolution of human societies, their convergent appearance in proboscis monkeys may help us understand of the drivers of human social evolution. Significance StatementThe aim of this study was to determine the social organization of proboscis monkeys by direct observation and genetic analysis. The results revealed that their social system exhibited a form of multilevel society with a possible patrilineal basis. Since humans exhibit a similar constellation of social features, proboscis monkeys may offer insightful clues about human social evolution.

animal behavior and cognition↗

bioRxiv2022

Formation of secondary allo-bile acids by novel enzymes from gut Firmicutes

The gut microbiome of vertebrates is capable of numerous biotransformations of bile acids, which are responsible for intestinal lipid digestion and function as key nutrient-signaling molecules. The human liver produces bile acids from cholesterol predominantly in the A/B-trans orientation in which the sterol rings are "kinked", as well as small quantities of A/B-cis oriented "flat" stereoisomers known as "primary allo-bile acids". While the complex multi-step bile acid 7-dehydroxylation pathway has been well-studied for conversion of "kinked" primary bile acids such as cholic acid (CA) and chenodeoxycholic acid (CDCA) to deoxycholic acid (DCA) and lithocholic acid (LCA), respectively, the enzymatic basis for the formation of "flat" stereoisomers allo-deoxycholic acid (allo-DCA) and allo-lithocholic acid (allo-LCA) by Firmicutes has remained unsolved for three decades. Here, we present a novel mechanism by which Firmicutes generate the "flat" bile acids allo-DCA and allo-LCA. The BaiA1 was shown to catalyze the final reduction from 3-oxo-allo-DCA to allo-DCA and 3-oxo-allo-LCA to allo-LCA. Phylogenetic and metagenomic analyses of human stool samples indicate that BaiP and BaiJ are encoded only in Firmicutes and differ from membrane-associated bile acid 5-reductases recently reported in Bacteroidetes that indirectly generate allo-LCA from 3-oxo-{Delta}4-LCA. We further map the distribution of baiP and baiJ among Firmicutes in human metagenomes, demonstrating an increased abundance of the two genes in colorectal cancer (CRC) patients relative to healthy individuals. SIGNIFICANCE STATEMENTBile acid synthesis by vertebrates is central to digestion and nutrient signaling. Gut bacteria have evolved enzymes capable of converting primary bile acids to hundreds of secondary bile acids. While bile acid microbiology has been focused on the metabolism of ring hydroxyl groups and the carboxylated side-chain, very little is known about how bacteria alter the shape of the steroid ring system. Here, we describe enzymes expressed by Firmicutes that convert the "kinked" primary bile acid into "flat" secondary bile acids. Decades of research indicate that increased levels of secondary bile acids are risk factors for colorectal cancer. Hidden Markov Models developed from the BaiP and BaiJ enzyme sequences revealed significant enrichment in metagenomes of subjects with colorectal cancer.

biochemistry↗

bioRxiv2020

Three-dimensional convolutional autoencoder extracts features of structural brain images with a diagnostic label-free approach: Application to schizophrenia datasets

There has been increasing interest in performing psychiatric brain imaging studies using deep learning. However, most studies in this field disregard three-dimensional (3D) spatial information and targeted disease discrimination, without considering the genetic and clinical heterogeneity of psychiatric disorders. The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (CAE) for extracting features related to psychiatric disorders without diagnostic labels. The network was trained using a Kyoto University dataset including 82 patients with schizophrenia (SZ) and 90 healthy subjects (HS), and was evaluated using Center for Biomedical Research Excellence (COBRE) datasets including 71 SZ patients and 71 HS. The proposed 3D-CAEs were successfully reconstructed into high-resolution 3D structural magnetic resonance imaging (MRI) scans with sufficiently low errors. In addition, the features extracted using 3D-CAE retained the relevant clinical information. We explored the appropriate hyper parameter range of 3D-CAE, and it was suggested that a model with eight convolution layers might be relevant to extract features for predicting the dose of medication and symptom severity in schizophrenia.

neuroscience↗

bioRxiv2020

Maternal immune activation during pregnancy alters early neurobehavioral development in nonhuman primate offspring

BackgroundHuman epidemiologic studies have implicated exposure to infectious or inflammatory insults during gestation in the etiology of neurodevelopmental disorders. Rodent models of maternal immune activation (MIA) have identified the maternal immune response as the critical link between maternal infection and aberrant brain and behavior development in offspring. The nonhuman primate MIA model provides an opportunity to maximize the translational utility of this model in a species more closely related to humans. MethodsHere we evaluate the effects of MIA on brain and behavioral development in the rhesus monkey (Macaca mulatta). A modified form of the viral mimic, Polyinosinic-polycytidylic acid (PolyIC), was delivered to pregnant rhesus monkeys (n=14) in the late first trimester to stimulate a maternal immune response. Control dams received saline injections at the same gestational time points (n=10) or were untreated (n=4). ResultsMIA-treated dams exhibited a strong immune response as indexed by transient increases in sickness behavior, temperature and inflammatory cytokines. MIA-exposed offspring developed species typical milestones and demonstrate subtle changes in early in social development. However, magnetic resonance imaging demonstrated significant gray matter volume reductions in prefrontal and frontal cortices at 6, 12 and 24 months of age. ConclusionsThese findings provide new insights into the emergence of neuropathology in MIA-exposed primates and have implications for the pathophysiology of human psychiatric disorders associated with maternal gestational infection.

neuroscience↗

bioRxiv2020

Epidynamics characterize and navigate the map of seizure dynamics

Seizures are a disruption of normal brain activity present across a vast range of species, diseases, and conditions. Here we introduce an organizing principle that leads to the first objective Taxonomy of Seizure Dynamics (TSD) based on bifurcation theory, and applied it to the analysis of EEG data. The "dynamotype" of a seizure is the part of its dynamic composition that defines its observable characteristics, including how it starts, evolves and terminates. Analyzing over 2000 focal-onset seizures recorded from 7 epilepsy centers on five continents, we find evidence of all 16 dynamotypes predicted in TSD. We demonstrate that patients dynamotypes evolve during their lifetime and display complex but systematic variations including hierarchy (certain dynamotypes are more common), non-bijectivity (a patient may display multiple dynamotypes) and pairing preference (multiple dynamotypes may occur during one seizure). TSD not only provides a way to stratify patients in complement to present practical classifications but also guides biophysically based mechanistic approaches and provides a language to describe the most critical features of seizure dynamics. Impact statementTaxonomy of Seizure Dynamics (TSD) provides a rigorous method for classifying and quantifying seizures and a principled framework for understanding seizure initiation and propagation.

bioinformatics↗

bioRxiv2019

Axial variation of deoxyhemoglobin density as a source of BOLD low-frequency time lag structure.

Perfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the \"perfusion lag structure,\" a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S0, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.

biophysics↗

bioRxiv2018

Overlapping but asymmetrical relationships between schizophrenia and autism revealed by brain connectivity

(Abstract included 248 words)Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. To address this issue, we took advantage of dual (ASD and SSD) classifiers that discriminate patients from their controls based on resting state brain functional connectivity. An SSD classifier using sophisticated machine-learning algorithms that automatically selected SSD- specific functional connections was applied to Japanese datasets including adult patients with SSD in a chronic stage. We demonstrated good performance of the SSD classification for independent validation cohorts. The generalizability was tested by USA and European cohorts in a chronic stage, and one USA cohort including first episode schizophrenia. The specificity was tested by two adult Japanese cohorts of ASD and major depressive disorder, and one European cohort of attention-deficit hyperactivity disorder. The weighted linear summation of the classifiers functional connections constituted the biological dimensions representing neural liability to the disorders. Our previously developed robust ASD classifier constituted the ASD dimension. Distributions of individuals with SSD, ASD and healthy controls were examined on the SSD and ASD biological dimensions. The SSD and ASD populations exhibited overlapping but asymmetrical patterns on the two biological dimensions. That is, the SSD population showed increased liability on the ASD dimension, but not vice versa. Furthermore, the two dimensions were correlated within the ASD population but not the SSD population. Using the two biological dimensions based on resting-state functional connectivity enabled us to quantify and visualize the relationships between SSD and ASD.

neuroscience↗