Biology subjects

Takata, N.

Publications and source records attributed to Takata, N..

11 recordsLinked to original sources

bioRxiv2025

Effects of Combination Therapy of a CDK4/6 and MEK Inhibitor in Diffuse Midline Glioma Preclinical Models

BackgroundDiffuse midline glioma (DMG) is an incurable brain cancer without a single FDA-approved drug that prolongs survival. CDK4/6 inhibitors have been evaluated in children with DMG with limited efficacy. Since MAPK pathway activation is upstream of cell proliferation, we hypothesized that MEK inhibitors may increase the anti-tumor effects of CDK4/6 inhibitors. Here, we evaluated the efficacy of the CDK4/6 inhibitor ribociclib and the MEK inhibitor trametinib in human and murine DMG models to investigate combinational effects. MethodsWe conducted in vitro and in vivo assays using DMG cell lines from human patient-derived xenografts (PDX) and murine genetically engineered models (GEM). In vitro, we assessed synergy across human DMG lines. In vivo, we evaluated therapeutic effects with histological examinations, survival analysis, pharmacokinetic measurements, and RNA-sequencing analysis. ResultsIn vitro, ribociclib and trametinib had variable synergistic effects against human DMG cell lines. In vivo, a five-day treatment with combination therapy in the GEM DMG model significantly decreased cell proliferation and increased apoptosis compared with the vehicle, with trametinib having mostly cytotoxic effects and ribociclib having primarily cytostatic effects. In addition, a 21-day treatment with combination therapy significantly prolonged mice survival compared with the vehicle in the GEM DMG model (median survival: 112 days vs. 71.5 days, log rank test p=0.0195). In an orthotopic PDX model, combination therapy did not prolong mice survival compared with vehicle, ribociclib, and trametinib. LC/MS analysis showed adequate drug delivery across the blood-brain-barrier (BBB) into tumor tissue in both GEM and PDX models. Transcriptomic analysis in the GEM model suggests that combination therapy inhibited the MAPK pathway and inflammation. ConclusionsCombination therapy with ribociclib and trametinib significantly prolonged survival in the GEM model but not in the PDX model, highlighting the importance of testing novel therapies in diverse models. Key PointsO_LICombination therapy had cytotoxic and cytostatic effects in vivo in the GEM model. C_LIO_LICombination therapy had variable synergy in vitro in human DIPG models. C_LIO_LICombination therapy significantly prolonged mice survival compared with the vehicle in the GEM model. C_LIO_LICombination therapy did not prolong survival in the PDX model. C_LIO_LITranscriptional analysis suggests that the combination modulated inflammation in the GEM model. C_LIO_LIThis work highlights the importance of testing novel therapies in diverse models. C_LI Importance of the StudyDMG is an incurable brain cancer without a single FDA-approved drug that prolongs survival. CDK4/6 inhibitors have been evaluated in children with DMG with limited efficacy. As MAPK pathway activation is known to be upstream of cell proliferation, we hypothesize that combination therapy will have additive effects relative to monotherapy. In this study, we evaluated the efficacy of the CDK4/6 inhibitor ribociclib and the MEK inhibitor trametinib in GEM and PDX DMG models. In vitro, the inhibitor combination demonstrated variable synergy in DMG human cell-lines, but in vivo, it had limited efficacy in a PDX orthotopic model. In the GEM model, the combination prolonged survival compared with the vehicle and with single agents. PK studies showed similar drug levels in tumor tissue between the GEM and PDX models. Transcriptomic analysis in the GEM suggests that the drug combination significantly inhibited inflammation. These results highlight the importance of testing therapies in diverse models and suggest that this combination may be an effective therapy in patients with DMG.

cancer biology↗

bioRxiv2023

A Reinforcement Learning Model with Choice Traces for a Progressive Ratio Schedule

The progressive ratio (PR) lever-press task serves as a benchmark for assessing goal-oriented motivation. However, a well-recognized limitation of the PR task is that only a single data point, known as the breakpoint, is obtained from an entire session as a barometer of motivation. Because the breakpoint is defined as the final ratio of responses achieved in a PR session, variations in choice behavior during the PR task cannot be captured. We addressed this limitation by constructing four reinforcement learning models: a Simple Q- learning model, an Asymmetric model with two learning rates, a Perseverance model with choice traces, and a Perseverance model without learning. These models incorporated three behavioral choices: reinforced and non-reinforced lever presses and void magazine nosepokes (MNPs), because we noticed that mice performed frequent MNPs during PR tasks. The best model was the Perseverance model, which predicted a gradual reduction in amplitudes of reward prediction errors (RPEs) upon void MNPs. We confirmed the prediction experimentally with fiber photometry of extracellular dopamine (DA) dynamics in the ventral striatum of mice using a fluorescent protein (genetically encoded GPCR activation-based DA sensor: GRABDA2m). We verified application of the model by acute intraperitoneal injection of low-dose methamphetamine (METH) before a PR task, which increased the frequency of MNPs during the PR session without changing the breakpoint. The Perseverance model captured behavioral modulation as a result of increased initial action values, which are customarily set to zero and disregarded in reinforcement learning analysis. Our findings suggest that the Perseverance model reveals effects of psychoactive drugs on choice behaviors during PR tasks.

neuroscience↗

bioRxiv2023

Machine learning-based estimation of spatial gene expression pattern during ESC-derived retinal organoid development

Organoids, which can reproduce the complex tissue structures found in embryos, are revolutionizing basic research and regenerative medicine. In order to use organoids for research and medicine, it is necessary to assess the composition and arrangement of cell types within the organoid, i.e., spatial gene expression. However, current methods are invasive and require gene editing and immunostaining. In this study, we developed a non-invasive estimation method of spatial gene expression patterns using machine learning. A deep learning model was trained with an encoder-decoder architecture on a dataset of retinal organoids derived from mouse embryonic stem cells. This method successfully estimated spatially plausible fluorescent patterns with appropriate intensities, enabling the non-invasive, quantitative estimation of spatial gene expression patterns within each tissue. Thus, this method could lead to new avenues for evaluating spatial gene expression patterns across a wide range of biology and medicine fields. HighlightsO_LIA non-invasive estimation method of spatial gene expression pattern is proposed C_LIO_LIA CNN architecture is employed to convert a phase-contrast to fluorescence image C_LIO_LIThe method was trained on a dataset of mouse ESC-derived retinal organoids C_LIO_LISpatially plausible patterns of Rx gene expressions were successfully estimated C_LI

developmental biology↗

bioRxiv2022

Optogenetic activation of dorsal raphe serotonin neurons induces a brain-wide response in reward network

Serotonin is a neuromodulator that affects multiple behavioral and cognitive functions. Nonetheless, how serotonin causes such a variety of effects via brain-wide projections and various receptors remains unclear. Here we measured brain-wide responses to optogenetic stimulation of serotonin neurons in the dorsal raphe nucleus (DRN) of the male mouse brain using functional MRI with an 11.7T scanner and a cryoprobe. Transient activation of DRN serotonin neurons caused brain-wide activation, including the medial prefrontal cortex, the striatum, and the ventral tegmental area. The same stimulation under anesthesia with isoflurane decreased brain-wide activation, including the hippocampal complex. These brain-wide response patterns can be explained by DRN serotonergic projection topography and serotonin receptor expression profiles, with enhanced weights on 5-HT1 receptors. Together, these results provide insight into the DR serotonergic system, which is consistent with recent discoveries of its functions in adaptive behaviors.

neuroscience↗

bioRxiv2022

Pupil dynamics-derived sleep stage classification of a head-fixed mouse using a recurrent neural network

The standard method for sleep state classification is thresholding amplitudes of electroencephalography (EEG) and electromyography (EMG), followed by an experts manual correction. Although popular, the method entails some shortcomings: 1) the time-consuming manual correction by human experts is sometimes a bottleneck hindering sleep studies; 2) EEG electrodes on the skull interfere with wide-field imaging of the cortical activity of a head-fixed mouse under a microscope; 3) invasive surgery to fix the electrodes on the thin skull of a mouse risks brain tissue injury; and 4) metal electrodes for EEG and EMG are difficult to apply to some experiment apparatus such as that for functional magnetic resonance imaging. To overcome these shortcomings, we propose a pupil dynamics-based vigilance state classification for a head-fixed mouse using a long short-term memory (LSTM) model, a variant of recurrent neural networks, for multi-class labeling of NREM, REM, and WAKE states. For supervisory hypnography, EEG and EMG recording were performed for a head-fixed mouse, combined with left eye pupillometry using a USB camera and a markerless tracking toolbox, DeepLabCut. Our open-source LSTM model with feature inputs of pupil diameter, location, velocity, and eyelid opening for 10 s at a 10 Hz sampling rate achieved vigilance state estimation with a higher classification performance (macro F1 score, 0.77; accuracy, 86%) than a feed forward neural network. Findings from diverse pupillary dynamics implied subdivision of a vigilance state defined by EEG and EMG. Pupil dynamics-based hypnography can expand the scope of alternatives for sleep stage scoring of head fixed mice.

neuroscience↗

bioRxiv2021

Oscillatory population-level activity of dorsal raphe serotonergic neurons sculpts sleep structure

Dorsal raphe (DR) 5-HT neurons are involved in regulating sleep-wake transitions. Previous studies demonstrated that single-unit activity of DR 5-HT neurons is high during wakefulness, decreases during non-rapid eye movement (NREM) sleep, and ceases during rapid eye movement (REM) sleep. However, characteristics of the population-level activity of DR 5-HT neurons, which can influence the entire brain, are largely unknown. Here we measured population activities of 5-HT neurons in male and female mouse DR across the sleep-wake cycle by a ratiometric fiber photometry system. We found a slow oscillatory activity of compound intracellular Ca2+ signals during NREM sleep. The trough of concave 5-HT activity increased along with sleep progression, but the 5-HT activity level always returned to that seen in wake periods. When the trough reached the minimum level and remained there, REM sleep initiated. We also found a unique coupling of the oscillatory 5-HT activity and EEG power fluctuation, suggesting that EEG fluctuation is a proxy for 5-HT activity. Optogenetic activation of 5-HT neurons during NREM sleep triggered a high EMG power and induced wakefulness. Optogenetic inhibition induced REM sleep or sustained NREM with an EEG power increase and EEG fluctuation. These manipulations demonstrated a causal role of DR 5-HT neurons in sculpting sleep-wake structure. We also observed EEG fluctuations in human males during NREM sleep, implicating the existence of 5- HT oscillatory activity in humans. We propose that NREM sleep is not a monotonous state, but that it is dynamically regulated by the oscillatory population activity of DR 5- HT neurons. Significant statementPrevious studies have demonstrated single-cell 5-HT neuronal activity across sleep- wake conditions; however, population-level activities of these neurons are largely unknown. We monitored dorsal raphe (DR) 5-HT population activity using a fiber photometry system in mice and demonstrated that activity was highest during wakefulness, and lowest during rapid eye movement (REM) sleep. Surprisingly, during non-REM (NREM) sleep, the 5-HT population activity decreased with an oscillatory pattern, coinciding with EEG fluctuations. We examined the causal role of these 5-HT neuron activities by optogenetics and found that DR 5-HT neurons sculpted sleep-wake conditions by influencing EEG and EMG patterns. We found similar EEG fluctuations in a human sleep EEG study, suggesting the presence of oscillatory 5-HT neuron activity during NREM across species.

neuroscience↗

bioRxiv2021

The dopamine dip amplitude is a quantitative measure of disappointment

The greater the reward expectations are, the more different the brains physiological response will be. Although it is well-documented that better-than-expected outcomes are encoded quantitatively via midbrain dopaminergic (DA) activity, it has been less addressed experimentally whether worse-than-expected outcomes are expressed quantitatively as well. We show that larger reward expectations upon unexpected reward omissions are associated with the preceding slower rise and following larger decrease (DA dip) in the DA concentration at the ventral striatum of mice. We set up a lever press task on a fixed ratio (FR) schedule requiring five lever presses as an effort for a food reward (FR5). The mice occasionally checked the food magazine without a reward before completing the task. The percentage of this premature magazine entry (PME) increased as the number of lever presses approached five, showing rising expectations with increasing proximity to task completion, and hence greater reward expectations. Fiber photometry of extracellular DA dynamics in the ventral striatum using a fluorescent protein (genetically encoded GPCR-activation-based-DA sensor: GRABDA2m) revealed that the slow increase and fast decrease in DA levels around PMEs were correlated with the PME percentage, demonstrating a monotonic relationship between the DA dip amplitude and degree of expectations. Computational modeling of the lever press task implementing temporal difference errors and state transitions replicated the observed correlation between the PME frequency and DA dip amplitude in the FR5 task. Taken together, these findings indicate that the DA dip amplitude represents the degree of reward expectations monotonically, which may guide behavioral adjustment.

neuroscience↗

bioRxiv2021

Optogenetic control of apical constriction induces synthetic morphogenesis in mammalian tissues

During embryonic development, cellular forces synchronize in space and time to generate functional tissue shapes. Apical constriction is one of these force-generating processes, and it is necessary to modulate epithelial curvature in fundamental morphogenetic events, such as neural tube folding. The emerging field of synthetic developmental biology proposes bottom-up approaches to examine the contribution of each cellular process to complex morphogenesis. However, the shortage of tools to manipulate three-dimensional (3D) shapes of mammalian tissues currently hinders the progress of the field. Here we report the development of "OptoShroom3", a new optogenetic tool that achieves fast spatiotemporal control of apical constriction in mammalian epithelia. Activation of OptoShroom3 through illumination of individual cells in an epithelial cell sheet reduced their apical surface while illumination of groups of cells caused deformation in the adjacent regions. By using OptoShroom3, we further manipulated 3D tissue shapes. Light-induced apical constriction provoked the folding of epithelial cell colonies on soft gels. Its application to murine and human neural organoids led to thickening of neuroepithelia, apical lumen reduction in optic vesicles, and flattening in neuroectodermal tissues. These results show that spatiotemporal control of apical constriction can trigger several types of 3D deformation depending on the initial tissue context.

developmental biology↗

bioRxiv2020

Flexible annotation atlas of the mouse brain: combining and dividing brain structures of the Allen Brain Atlas while maintaining anatomical hierarchy

A brain atlas is necessary for analyzing structure and function in neuroimaging research. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researchers necessity, leading to inconsistent ROIs among studies. One reason for such a situation is the fact that earlier AVs were fixed, i.e. combination and division of nodes were not implemented. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. Four FAAs with total node count of 4, 101, 866, and 1,381 were demonstrated. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility. Highlights- A flexible annotation atlas (FAA) for the mouse brain is proposed. - FAA is expected to improve whole brain ROI-definition consistency among laboratories. - The ROI can be combined or divided objectively while maintaining anatomical hierarchy. - FAA realizes functional connectivity analysis across the anatomical hierarchy. - Codes for FAA reconstruction is available at https://github.com/ntakata/flexible-annotation-atlas - Datasets for resting-state fMRI in awake mice are available at https://openneuro.org/datasets/ds002551

neuroscience↗

bioRxiv2019

A Human Accelerated Region participates in early human forebrain patterning and expansion

The expansion of the mammalian brain is associated with specific developmental processes; however, not much is known about how evolutionary changes participated in the acquisition of human brain traits during early developmental stages. Here we investigated whether enhancers active during the phylotypic stage show human-specific genomic divergence which could contribute to the evolutionary expansion of the forebrain. Notably, we identified an active enhancer containing a human accelerated region (HAR) located in the Chromosome 14q12, a region enriched with neurodevelopmental genes, such as Foxg1, Nkx2.1 and Nova1. Reporter analysis revealed that the human variant is active in the forebrain in transgenic mice and that it has stronger enhancer activity than the mouse or chimpanzee versions. Humanization of the mouse enhancer variant in transgenic mice and in mouse organoids resulted in an expansion of Foxg1 expressing domains in the forebrain early neural progenitors with a bias towards dorsal identities. Overall, our results suggest that human-specific mutations in critical regulatory elements controlling early brain development impact the expansion and patterning of the forebrain.

developmental biology↗

bioRxiv2019

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

neuroscience↗