Biology subjects

Ishii, S.

Publications and source records attributed to Ishii, S..

6 recordsLinked to original sources

bioRxiv2018

Logical design of oral glucose ingestion pattern minimizing blood glucose in humans

Excessive increase in blood glucose level after eating increases the risk of macroangiopathy, and a method for not increasing the postprandial blood glucose level is desired. However, a logical design method of the dietary ingestion pattern controlling the postprandial blood glucose 2 level has not yet been established. We constructed a mathematical model of blood glucose control by oral glucose ingestion in 3 healthy human subjects, used the model to predict an optimal glucose ingestion pattern, and showed that the optimal ingestion pattern minimized the peak value of blood glucose level. Subjects orally ingested 3 doses of glucose by bolus or over 2 hours, and blood glucose, insulin, C-peptide and incretins were measured for 4 hours. We constructed an ordinary differential equation model that reproduced the time course data of the blood glucose and blood hormone levels. Using the model, we predicted that intermittent ingestion 30 minutes apart was the optimal glucose ingestion patterns that minimized the peak value of blood glucose level. We confirmed with subjects that this intermittent pattern decreased the peak value of blood glucose level. This approach could be applied to design optimal dietary ingestion patterns.\n\nIn BriefAs a forward problem, we measured blood glucose and hormones in three human subjects after oral glucose ingestion and constructed a mathematical model of blood glucose control. As an inverse problem, we used the model to predict the optimal oral glucose ingestion pattern that minimized the peak value of blood glucose level, and validated the pattern with the subjects.\n\nHighlightsO_LIModeling blood glucose concentrations predicts an intermittent ingestion pattern is optimal\nC_LIO_LIHuman validation shows ingestion at 30-minute intervals limits peak blood glucose\nC_LIO_LIWe provide a strategy to design optimal dietary ingestion patterns\nC_LI

systems biology↗

bioRxiv2018

System level analyses of motor-related neural activities in larval Drosophila

The way in which the central nervous system (CNS) governs animal movement is complex and difficult to solve solely by the analyses of muscle movement patterns. We tackle this problem by observing the activity of a large population of neurons in the CNS of larval Drosophila. We focused on two major behaviors of the larvae, forward and backward locomotion, and analyzed the neuronal activity related to these behaviors during fictive locomotion that spontaneously occurs in the isolated CNS. We expressed genetically-encoded calcium indicator, GCaMP, and a nuclear marker in all neurons and used digital scanned light-sheet microscopy to record neural activities in the entire ventral nerve cord at a fast frame rate. We developed image processing tools that automatically detect the cell position based on the nuclear staining and allocate the activity signals to each detected cell. We also applied a machine learning-based method that we developed recently to assign motor status in each time frame. Based on these methods, we find cells whose activity is biased to forward versus backward locomotion and vice versa. In particular, we identified a group of neurons near the boundary of subesophageal zone (SEZ) and thoracic neuromeres, which are strongly active during an early phase of backward but not forward fictive locomotion. Our experimental procedure and computational pipeline enable systematic identification of neurons to show characteristic motor activities in larval Drosophila.

neuroscience↗

bioRxiv2018

Noise-resistant developmental reproducibility in vertebrate somite formation

The reproducibility of embryonic development is remarkable, although molecular processes are intrinsically stochastic at the single-cell level. How the multi-cellular system resists the inevitable noise to acquire developmental reproducibility constitutes a fundamental question in developmental biology. Toward this end, we focused on vertebrate somitogenesis as a representative system, because somites are repeatedly reproduced within a single embryo whereas such reproducibility is lost in segmentation clock gene-deficient embryos. However, the effect of noise on developmental reproducibility has not been fully investigated, because of the technical difficulty in manipulating the noise intensity in experiments. In this study, we developed a computational model of ERK-mediated somitogenesis, in which bistable ERK activity is regulated by an FGF gradient, cell-cell communication, and the segmentation clock, subject to the intrinsic noise. The model simulation generated our previous in vivo observation that the ERK activity was distributed in a step-like gradient in the presomitic mesoderm, and its boundary was posteriorly shifted by the clock in a stepwise manner, leading to regular somite formation. Here we showed that this somite regularity was robustly maintained against the noise. Removing the clock from the model predicted that the stepwise shift of the ERK activity occurs at irregular timing with irregular distance owing to the noise, resulting in somite size variation. Through theoretical analysis, we presented a mechanism by which the clock reduces the inherent somite irregularity observed in clock-deficient embryos. Therefore, this study indicates a novel role of the segmentation clock in noise-resistant developmental reproducibility.

developmental biology↗

bioRxiv2017

Self-organization mechanism of distinct microtubule orientations in axons and dendrites

The identities of axons and dendrites are acquired through the self-organization of distinct microtubule (MT) orientations during neuronal polarization. The axon is generally characterized by a uniform MT orientation with all plus-ends pointing outward to the neurite terminal ( plus-end-out pattern). On the other hand, the MT orientation pattern in the dendrites depends on species: vertebrate dendrites have a mixed alignment with both plus and minus ends facing either the terminal or the cell body ( mixed pattern), whereas invertebrate dendrites have a minus-end-out pattern. However, how MT organizations are developed in the axon and the dendrites is largely unknown. To investigate the mechanism of MT organization, we developed a biophysical model of MT kinetics, consisting of polymerization/depolymerization and MT catastrophe coupled with neurite outgrowth. The model simulation showed that the MT orientation can be controlled mainly by the speed of neurite growth and the hydrolysis rate. With a low hydrolysis rate, vertebrate plus-end-out and mixed microtubule patterns emerged in fast- and slow-growing neurites, respectively. In contrast, with a high hydrolysis rate, invertebrate plus-end-out and minus-end-out microtubule patterns emerged in fast- and slow-growing neurites, respectively. Thus, our model can provide a unified understanding of distinct microtubule organizations by simply changing the parameters.

neuroscience↗

bioRxiv2017

Identification Of Animal Behavioral Strategy By Inverse Reinforcement Learning ~ Its Application To Thermotaxis In C. elegans ~

Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animals behavioral strategy from behavioral time-series data. As a particular target, we applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, the fed and starved worms prefer and avoid from the cultivation temperature on a thermal gradient, respectively. Our IRL approach revealed that the fed worms used both absolute and temporal derivative of temperature and that their strategy comprised mixture of two strategies: directed migration (DM) and isothermal migration (IM). The DM is a strategy that the worms efficiently reach to specific temperature, which explained thermotactic behaviors of the fed worms. The IM is a strategy that the worms track along a constant temperature, which reflects isothermal tracking well observed in previous studies. We also showed the neural basis underlying the strategies, by applying our method to thermosensory neuron-deficient worms. In contrast to fed animals, the strategy of starved animals indicated that they escaped the cultivation temperature using only absolute, but not temporal derivative of temperature. Thus, our IRL-based approach is capable of identifying animal strategies from behavioral time-series data and will be applicable to wide range of behavioral studies, including decision-making of other organisms.\n\nAuthor SummaryUnderstanding animal decision-making has been a fundamental problem in neuroscience and behavioral ecology. Many studies analyze actions that represent decision-making in behavioral tasks, in which rewards are artificially designed with specific objectives. However, it is impossible to extend this artificially designed experiment to a natural environment, because in a natural environment, the rewards for freely-behaving animals cannot be clearly defined. To this end, we must reverse the current paradigm so that rewards are identified from behavioral data. Here, we propose a new reverse-engineering approach (inverse reinforcement learning) that can estimate a behavioral strategy from time-series data of freely-behaving animals. By applying this technique with thermotaxis in C. elegans, we successfully identified the reward-based behavioral strategy.

neuroscience↗

bioRxiv2016

Lower brain pH as a shared endophenotype of psychotic disorders

Lower pH is a well-replicated finding in the postmortem brains of patients with schizophrenia and bipolar disorder. Interpretation of the data, however, is controversial as to whether this finding reflects a primary feature of the diseases or is a result of confounding factors such as medication, postmortem interval, and agonal state. To date, systematic investigation of brain pH has not been undertaken using animal models, which can be studied without confounds inherent in human studies. In the present study, we first confirmed that the brains of patients with schizophrenia and bipolar disorder exhibit lower pH values by conducting a meta-analysis of existing datasets. We then utilized neurodevelopmental mouse models of psychiatric disorders in order to test the hypothesis that lower brain pH exists in these brains compared to controls due to the underlying pathophysiology of the disorders. We measured pH, lactate levels, and related metabolite levels in brain homogenates from three mouse models of schizophrenia (Schnurri-2 KO, forebrain-specific calcineurin KO, and neurogranin KO mice) and one of bipolar disorder (Camk2a HKO mice), and one of autism spectrum disorders (Chd8 HKO mice). All mice were drug-naive with the same postmortem interval and agonal state at death. Upon postmortem examination, we observed significantly lower pH and higher lactate levels in the brains of model mice relative to controls. There was a significant negative correlation between pH and lactate levels. These results suggest that lower pH associated with increased lactate levels is a pathophysiology of such diseases rather than mere artifacts.

neuroscience↗