Biology subjects

Ishihara, T.

Publications and source records attributed to Ishihara, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Multispecies translational evaluation of an NMDA receptor modulator reveals analgesic, autonomic-stabilizing, and stress mitigating effects without evidence of abuse liability

CNS4 is an agonist concentration-biased NMDAR modulator exhibiting GluN2 subtype-dependent activity. Here we evaluated the translational pharmacology of CNS4 across mice, rats, and client-owned surgical oncology dogs. In mice, CNS4 did not produce conditioned place preference, indicating lack of reward liability. CNS4 produced dose-dependent reductions in locomotor activity without motor impairment on accelerating rotarod testing. CNS4 also maintained body temperature 0.5 to 1 degree Celsius above the vehicle group in mice and dogs, consistent with NMDAR-dependent thermoregulatory activity and contrasting with hypothermic effects reported for NMDAR channel blockers such as ketamine. In fear-conditioning paradigms, CNS4 did not impair fear learning, memory consolidation, or fear expression. CNS4 reduced acute stress-induced sucrose preference, suggesting modulation of stress-responsive neural circuits. In a rat spinal nerve ligation model of neuropathic pain, both single-dose and three-day repeated CNS4 administration significantly reversed mechanical, pressure, and thermal hypersensitivity, supporting analgesic efficacy with no apparent evidence of rapid tolerance development. In client-owned surgical oncology dogs undergoing standard veterinary procedures, preliminary findings from 14 dogs (8 CNS4-treated, 6 vehicle-treated) demonstrated stable intraoperative mean arterial pressure and heart rate. Postoperatively, CNS4-treated dogs exhibited normal physiological recovery, with respiratory rate, heart rate, and body temperature returning toward the normal canine range, and required approximately 8% less propofol for anesthetic induction. Collectively, these findings support CNS4 as a novel NMDAR modulator with thermoregulatory, anti-agitative, analgesic, and autonomic-stabilizing properties without evidence of abuse liability, supporting continued translational development for neuropathic pain and possibly neuropsychiatric disorders.

pharmacology and toxicology↗

bioRxiv2026

Estimation of the curved body length of tuna larvae from microscope images using a zero-shot model and image processing techniques

Fixed larval specimens often shrink and curve, making length measurement labor-intensive. Although recent studies have demonstrated efficient fish-length estimation from images using deep learning, methods for estimating curved length remain limited. Furthermore, although deep learning is a powerful method for object detection in images, an essential step for length measurement, it requires preparing large amounts of training data, which can hinder practical implementation. In this study, we used a zero-shot model that requires no training to detect fish in an image. The curved length was then estimated using an image-processing approach that combines image thinning with Bezier curve approximation, and its accuracy was evaluated. We analyzed 1,040 larvae from five tuna species captured in stereomicroscope images. Manual measurements (notochord length or standard length; 1.5-8.5 mm) were conducted by two measurers and served as reference values. Fish regions were detected using GroundedSAM, and curved body centerlines were extracted through image thinning and approximated with Bezier curves. The curve length was used as the estimated body length. Estimation accuracy was assessed using bias and standard deviation between estimated and manual measurements. GroundedSAM detected all 1,040 fish, although there were 49 overdetections. Overdetection was caused by the double-detection of a single fish or by the misidentification of debris and light reflections as fish. Although the standard deviation of the differences between manual measurements and the image analysis-based (IAB) method was larger than the inter-measurer differences, the bias for [≤]5 mm was comparable to or smaller than the inter-measurer bias. According to the strength-of-agreement criteria for the concordance correlation coefficient, the IAB method demonstrated substantial agreement in the [≤]5.0-mm range. The IAB method accurately measured most curved tuna larvae without prior training, particularly in the [≤]5.0-mm range. Combining the IAB method with manual remeasuring can improve the efficiency of curved-length measurement tasks.

ecology↗

bioRxiv2026

Image-scanning light-sheet microscopy for high-speed volumetric imaging of complex biological dynamics

Volumetric fluorescence microscopy is a powerful method for studying complex biological systems because it enables comprehensive observation of structural and physiological dynamics. In particular, light-sheet microscopy (LSM) is a leading option for real-time volumetric fluorescence imaging as it combines high imaging speed, low phototoxicity, minimal photobleaching, high spatiotemporal resolution, and low computational burden. To capture fast biological events, various efforts have been made to improve the imaging speed of volumetric fluorescence microscopy, including LSM. However, existing approaches entail significant trade-offs that make routine volumetric imaging at and beyond video rates challenging under practical conditions. Here, we introduce image-scanning LSM, a method that substantially increases the volumetric imaging speed achievable with LSM while preserving key performance metrics, such as spatial resolution and photon efficiency, as well as accessibility. Our implementation, termed image-scanning oblique plane (ISOP) microscopy, enables volumetric fluorescence imaging at up to 1,000 volumes per second with submicrometer lateral spatial resolution. We demonstrate the broad utility of ISOP microscopy by recording and analyzing the dynamics of behaving and rapidly moving organisms.

bioengineering↗

bioRxiv2025

Hydrodynamic coupling drives bacterial flagellar synchrony

Synchronization is a fundamental phenomenon observed across a wide range of physical, chemical, and biological systems. Even under the low-Reynolds-number conditions that govern microbial motility, synchronization of rhythmic processes is considered essential for diverse activities ranging from single cells to populations, yet experimental evidence remains scarce. Here, we performed rotation measurements of microbeads attached to two truncated bacterial flagella and observed the emergence of phase synchronization between these nanoscale active motors. The resulting intermittent in-phase synchronization was analyzed using a hydrodynamic model incorporating elastic deformation of the flagella, showing that stronger hydrodynamic coupling promotes more stable phase-locking. This study experimentally demonstrates fluid-mediated biological synchronization using bacterial rotary machinery, deepening our understanding of the physical principles underlying rhythmic phenomena and self-organization in living systems.

biophysics↗

bioRxiv2025

An anterior-posterior gradient in hippocampal subfield volumes linking sleep health to cognition in young adults

Sleep plays a critical role in maintaining hippocampal integrity and supporting cognitive function. However, it remains unclear how variations in sleep are associated with the structurally heterogeneous subfields of the hippocampus and how this association relates to cognition in healthy young adults. This study aimed to elucidate the multivariate relationships among sleep duration, quality, and timing, the specific hippocampal subfield volumes, and cognitive functions in a large sample of healthy young adults. We applied multiset canonical correlation analysis to data from 942 young adults (ages 22-37) from the Human Connectome Project. We examined relationships among self-reported sleep parameters (via the Pittsburgh Sleep Quality Index), high-resolution hippocampal subfield volumes, and a broad set of cognitive performance measures. We identified a single significant mode of covariation, wherein better sleep health--characterized by a moderate sleep duration (reflecting a nonlinear, inverted U-shaped relationship), higher sleep quality (e.g., fewer awakenings, less discomfort), and optimal sleep timing--was robustly associated with larger hippocampal volumes, particularly in the anterior subfields. This sleep-hippocampus pattern was also associated with enhanced cognitive performance. Our findings reveal a specific link among sleep, an anterior-dominant pattern of hippocampal structure, and cognition in healthy young adulthood. The anterior hippocampus may serve as a key neural hub through which the cognitive benefits of healthy sleep are manifested early in life.

neuroscience↗

bioRxiv2025

Modulation of prefrontal functional connectivity by anodal tDCS over left DLPFC predicts performance enhancement in competitive swimmers: A simultaneous tDCS-fNIRS, double-blind, sham-controlled crossover study

While transcranial direct current stimulation (tDCS) has been proposed as a method to enhance physical performance in athletes, the underlying neural mechanisms and the reasons for the widely reported individual variability in its effects remain unclear. This study investigated whether prefrontal hemodynamic responses, measured by functional near-infrared spectroscopy (fNIRS), are associated with the effects of anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC) on swimming performance. In a double-blind, sham-controlled, crossover design, eight trained male swimmers performed 100 m freestyle trials under both anodal tDCS and sham conditions. We recorded prefrontal cortical activation and functional connectivity using fNIRS during a resting-state period and a subsequent stimulation period. While tDCS led to a numerical improvement in 100 m freestyle time, the overall effect was not statistically significant. The fNIRS analyses revealed that tDCS significantly reduced intra-hemispheric functional connectivity, especially in the stimulated left prefrontal cortex. Crucially, the magnitude of this connectivity reduction correlated with the degree of performance improvement, suggesting a direct brain-behavior link. Exploratory analyses further suggested that baseline functional connectivity could predict an individuals neural response to tDCS, with those having higher baseline connectivity showing a greater reduction. These findings suggest that tDCS over the left DLPFC may enhance physical performance by increasing the neural efficiency of prefrontal networks. Therefore, baseline functional connectivity is a promising physiological biomarker that could be used to personalize neuromodulation protocols in athletes.

neuroscience↗

bioRxiv2024

Deuterium-reinforced polyunsaturated fatty acids protect against muscle atrophy induced by type 1 diabetes in mice

HIGHLIGHTSO_LID-PUFA diet prevents muscle atrophy in STZ-induced diabetic mice. C_LIO_LID-PUFA diet prevents muscle weakness depending on increased calcium release in STZ-induced diabetic mice. C_LIO_LID-PUFA diet may show a trend to decrease blood glucose in STZ-induced diabetic mice. C_LIO_LID-PUFA diet does not alter ferroptosis-related protein profiles including ACSL4, LPCAT3, ALOX12, and Gpx4. C_LI Oxidative stress and reactive oxygen species (ROS) have been linked to muscle atrophy and weakness. Diabetes increases the oxidative status of lipoproteins in nearly all tissues, including muscle tissues, but the role of lipid ROS on diabetes-induced muscle atrophy is not fully understood. Deuterium reinforced polyunsaturated fatty acids (D-PUFA) are more resistant to ROS-initiated chain reaction of lipid peroxidation than regular hydrogenated PUFA (H-PUFA). In this study, we tested the hypothesis that D-PUFA would protect muscle atrophy induced by diabetes driven by an accumulation of lipid hydroperoxides (LOOH). C57BL/6J mice were dosed with H-PUFA or D-PUFA for four weeks through dietary supplementation and then injected with streptozotocin (STZ) to induce insulin-deficient diabetes. After two weeks, muscles tissues were analyzed for individual muscle mass, force generating capacity and cross-sectional area. Skeletal muscle fibers from diabetic mice exhibited increased total ROS and LOOH. This was abolished by the D-PUFA supplementation regardless of accumulated iron. D-PUFA were found to be protective against muscle atrophy and weakness from STZ-induced diabetes. Prevention of muscle atrophy and weakness by D-PUFA might be independent of ACSL4/LPCAT3/15-LOX pathway. These findings provide novel insights into the role of LOOH in the mechanistic link between oxidative stress and diabetic myopathy and suggest a novel therapeutic approach to diabetes-associated muscle weakness.

pathology↗

bioRxiv2024

Enabling Epitope Analysis of Glycoproteins via HDX-MS Using Antigens with Uni-formed N-linked Glycans

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is widely used for epitope analysis of the antibodies. However, epitope analysis of glycoproteins is challenging because of the heterogeneity of attached N-linked glycans. Recent studies have reported methods where N-linked glycans were removed at low pH following hydrogen deuterium exchange reactions, but the methods for glycoproteins remain controversial. Here, we demonstrate the utility of using antigens with uniformed N-linked glycans in glycoprotein epitope analysis by HDX-MS. By treating HEK293 cells with kifunensine, we were able to prepare antigens mainly with N-linked high-mannose-type glycans. Analysis of epitopes of a monoclonal antibody S309 using antigens prepared with this method allowed us to identify an epitope that included the previously reported N-linked glycan attachment sites for this anti-body. We propose that using antigens with uniformed glycans should be effective for epitope analysis of glycoproteins, such as virus spike proteins covered by glycan shields. Moreover, we believe that this approach accelerates research on vaccines and neutralizing antibodies against viruses that escape host immunity through glycan shields or mutations.

biochemistry↗

bioRxiv2024

Association Between Relational Mobility and DNA Methylation in Oxytocin Receptor Gene: A Social Epigenetic Study

DNA methylation is a type of epigenetic modification known to exhibit fluctuations in response to environmental factors. The association of macrosocial factors, such as interpersonal mobility, on methylation has seldom been investigated. This study aimed to examine the association of relational mobility, defined as the extent to which individuals can form and replace social relationships, on the DNA methylation of oxytocin receptor genes. DNA was extracted from the buccal cells of 95 adult participants (50 men and 45 women) and subjected to microarray analysis of DNA methylation using Illumina EPIC v2.0. The findings indicate that the oxytocin receptor genes methylation level was higher in individuals residing in low relational mobility social environments. The CpG site associated with relational mobility is an enhancer region, indicating that social environments with low relational mobility exert a suppressive effect on the transcriptional efficiency of the oxytocin receptor gene. Significance StatementThe association between DNA methylation of the oxytocin receptor gene and relational mobility was examined in 95 adults in their 20s to 60s, and found that those living in social environments with lower levels of relationship mobility had higher rates of DNA methylation of the oxytocin receptor gene. This study is a novel approach to a problem discussed in the social sciences using new analytical techniques in epigenomics.

genetics↗

bioRxiv2024

ASO-enhancement of TARDBP exitron splicing mitigates TDP-43 proteinopathies

Amyotrophic lateral sclerosis and frontotemporal lobar degeneration are fatal neurodegenerative diseases characterized by pathological aggregation and nuclear functional loss of TDP-431,2. Current therapies inadequately address this core pathology3,4, necessitating innovative approaches that target aggregation while preserving TDP-43s essential functions. Here we demonstrate that enhancing the splicing of the TARDBP exitron--a cryptic intron encoding the aggregation-prone intrinsically disordered region (IDR) of TDP-435,6-- effectively mitigates TDP-43 pathology. This exitron splicing event, directly regulated by nuclear TDP-437-9, suppresses the expression of IDR-containing TDP-43 isoforms and generates IDR-spliced-out TDP-43 isoforms7,9,10 (which we term "IDRsTDP"). Our findings reveal that IDRsTDP, known to heterodimerize with full-length TDP-4310, inhibits TDP-43 aggregation by suppressing IDR-mediated clustering and enhances TDP-43 clearance via chaperone-mediated autophagy. In disease states, however, impaired nuclear TDP-43 function disrupts exitron splicing, leading to increased levels of IDR-containing TDP-439,11 and reduced levels of IDRsTDP, exacerbating aggregation and nuclear dysfunction6,12-17. By identifying HNRNPA1 and HNRNPC as key repressors of TARDBP exitron splicing, we designed antisense oligonucleotides (ASOs) to block their binding and restore splicing. These ASOs suppressed TDP-43 pathology and neurodegeneration in both neuronal cell models with impaired nuclear transport and a mouse model of proteasome dysfunction-induced TDP-43 proteinopathy. Our strategy, by rescuing the impaired autoregulatory pathway, inhibits the pathological cycle of TDP-43 aggregation and nuclear dysfunction, offering a promising avenue for treating these currently intractable neurodegenerative diseases.

neuroscience↗

bioRxiv2024

Discovery of anti-SARS-CoV-2 S2 protein antibody CV804 with broad-spectrum reactivity with various beta coronaviruses and analysis of its pharmacological properties in vitro and in vivo

SARS-CoV-2 pandemic alerts us that spillovers of various animal coronaviruses to human in the future may bring us enormous damages. Thus, there is a significant need of antibody-based drugs to treat patients infected with previously unseen coronaviruses.CV804 against the S2 domain of the spike protein, which is less prone to mutations. CV804 shows not only broad cross-reactivities with representative 20 animal-origin coronaviruses but also with diseases-associated human beta coronaviruses including SARS-CoV, MERS-CoV, HCoV-OC43, HCoV-HKU1 and mutant strains of SARS-CoV-2. Other than that, the main characteristics of CV804 are that it has strong antibody-dependent cellular cytotoxicity (ADCC) activity to SARS-CoV2 spike protein-expressed cells in vitro and completely lacks virus-neutralization activity. Comprehensively in animal models, CV804 suppressed disease progression by SARS-CoV-2 infection. Structural studies using HDX-MS and point mutations of recombinant spike proteins revealed that CV804 binds to a unique epitope within the highly conserved S2 domain of the spike proteins of various coronaviruses. Based on the overall data, we suggest that the non-neutralizing CV804 antibody recognizes the conformational structure of the spike protein expressed on the surface of the infected cells and weakens the viral virulence by supporting host immune cells attack through ADCC activity in vivo. CV804 epitope identified in this study is not only useful for the design of pan-corona antibody therapeutics but also to design next-generation coronavirus vaccines and antiviral drugs.

microbiology↗

bioRxiv2023

Uncovering the links between physical activity and prosocial behaviour: A functional near-infrared spectroscopy hyperscanning study on brain connectivity and synchrony

The prevalence of sedentary lifestyles in modern society raises concerns about their potential association with poor brain health, particularly in the lateral prefrontal cortex (LPFC), which is crucial for human prosocial behaviour. Here, we show the relationship between physical activity and prosocial behaviour, focusing on potential neural markers, including intra-brain functional connectivity and inter-brain synchrony in the LPFC. Forty participants, each paired with a stranger, underwent evaluation of neural activity in the LPFC using functional near-infrared spectroscopy hyperscanning during eye-to-eye contact and an economic game. Results showed that individuals with exercise habits and more leisure-time physical activity demonstrated greater reciprocity, less trust, longer decision-making time, and stronger intra-brain connectivity in the dorsal LPFC and inter-brain synchrony in the ventral LPFC. Our findings suggest that a sedentary lifestyle may alter human prosocial behaviour by impairing adaptable prosocial decision-making in response to social factors through altered intra-brain functional connectivity and inter-brain synchrony.

neuroscience↗

bioRxiv2023

Multimodal imaging for identifying brain markers of human prosocial behavior

How is the high degree of prosocial behavior that characterizes humans achieved? Here, we examined the structural and functional basis of the human brain with prosocial behavior using multimodal brain imaging data and 15 economic games. We identified that stronger interhemispheric connectivity, greater corpus callosum volume, higher functional segregation and integration, and fewer myelin maps combined with a thicker cortex were strongly associated with prosocial behavior. These associations were found especially in the social brain regions. This suggests that the strength of functional/structural connectivity between the left and right hemispheres, the strength of modular and efficient networks, and the high number of non-myelinated cells (i.e., dendrites, spines, synapses, and glia) are strongly associated with higher prosocial behavior in humans, particularly in the social brain regions.

neuroscience↗

bioRxiv2022

Deducing ensemble dynamics and information flow from the whole-brain imaging data

Recent development of large-scale activity imaging of neuronal ensembles provides opportunities for understanding how activity patterns are generated in the brain and how information is transmitted between neurons or neuronal ensembles. However, methodologies for extracting the component properties that generate overall dynamics are still limited. In this study, the results of time-lapse 3D imaging (4D imaging) of head neurons of the nematode C. elegans were analyzed by hitherto unemployed methodologies. By combining time-delay embedding with independent component analysis, the whole-brain activities were decomposed to a small number of component dynamics. Results from multiple samples, where different subsets of neurons were observed, were further combined by matrix factorization, revealing common dynamics from neuronal activities that are apparently divergent across sampled animals. By this analysis, we could identify components that show common relationships across different samples and those that show relationships distinct between individual samples. We also constructed a network model building on time-lagged prediction models of synaptic communications. This was achieved by dimension reduction of 4D imaging data using the general framework gKDR (gradient kernel dimension reduction). The model is able to decompose basal dynamics of the network. We further extended the model by incorporating probabilistic distribution, resulting in models that we call gKDR-GMM and gKDR-GP. The models capture the overall relationships of neural activities and reproduce the stochastic but coordinated dynamics in the neural network simulation. By virtual manipulation of individual neurons and synaptic contacts in this model, information flow could be estimated from whole-brain imaging results.

neuroscience↗

bioRxiv2022

Accuracy of a machine learning method based on structural and locational information from AlphaFold2 for predicting the pathogenicity of TARDBP and FUS gene variants in ALS

BackgroundIn the sporadic form of amyotrophic lateral sclerosis (ALS), the pathogenicity of rare variants in the causative genes characterizing the familial form remains largely unknown. To predict the pathogenicity of such variants, in silico analysis is commonly used. In some cases of ALS, the gene mutations are concentrated in specific regions, and the resulting alterations in protein structure are thought to significantly affect pathogenicity. However, existing methods have not taken this issue into account. To address this, we have developed a technique termed MOVA (method for evaluating the pathogenicity of missense variants using AlphaFold2), which applies positional information for structural variants predicted by AlphaFold2. Here we examined the utility of MOVA for analysis of several causative genes of ALS. MethodsWe analyzed variants of six ALS-related genes (TARDBP, FUS, SETX, TBK1, OPTN, and SOD1) and classified them as pathogenic or neutral. For each gene, the features of the variants, including their positions in the 3D structure predicted by AlphaFold2, were entered into a random forest algorithm and evaluated by leave-one-out cross-validation. We compared how accurately MOVA was able to classify the pathogenic and neutral mutation variants. ResultsMOVA yielded useful results (AUC [≥]0.70 for 3 (TARDBP 0.755, FUS 0.844, and SOD1 0.787) of the 6 genes) and was particularly useful for genes where pathogenic mutations were concentrated at specific sites (TARDBP, FUS). ConclusionsMOVA is useful for predicting the virulence of rare variants of ALS-causing genes in which mutations are concentrated at specific structural sites.

bioinformatics↗

bioRxiv2021

Age-related demethylation of the TDP-43 autoregulatory region in the human motor cortex

In amyotrophic lateral sclerosis (ALS), TAR DNA-binding protein 43 (TDP-43), which is encoded by TARDBP, forms aggregates in the motor cortex. This aggregate formation may be triggered by an increase in the TDP-43 level with aging. However, the amount of TDP-43 is autoregulated by alternative splicing of the TARDBP 3UTR, and how this autoregulation is affected by aging remains to be elucidated. We found that DNA demethylation in the autoregulatory region in the TARDBP 3'UTR reduced alternative splicing and increased TARDBP mRNA expression. Furthermore, in the human motor cortex, we found that this region was demethylated with aging, resulting in increased expression of TARDBP mRNA. The acceleration of DNA demethylation in the motor cortex was associated with the age of ALS onset. In summary, the dysregulation of TDP-43 autoregulation by age-related DNA demethylation in the motor cortex may explain the contribution of aging and motor system selectivity in ALS.

molecular biology↗

bioRxiv2019

An annotation dataset facilitates automatic annotation of whole-brain activity imaging of C. elegans

Annotation of cell identity is an essential process in neuroscience that allows for comparing neural activities across different animals. In C. elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal is limited in practice and comprehensive methods for cell annotation are required. Here we propose an efficient annotation method that can be integrated with the whole-brain imaging technique. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. The large positional variations illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters to tackle this problem. We also developed an automatic annotation method with human interaction functionality that facilitates annotation for whole-brain imaging.

neuroscience↗

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↗