Biology subjects

Kitamura, K.

Publications and source records attributed to Kitamura, K..

12 recordsLinked to original sources

bioRxiv2026

Light Guiding in Scattering Media Using Focused Laser-Induced Acoustic Waves with an Open Elliptical Reflector

Light scattering in biological tissue limits deep optical imaging. Acoustic waves can modulate optical properties and enhance photon delivery, but source-positioning requirements can complicate integration with other imaging modalities. Here, we present an open elliptical reflector that focuses laser-induced acoustic waves at a spatially separated target while maintaining open optical access. We characterized the spatiotemporal optical modulation induced by the localized acoustic focus. The system increased the local transmitted-light intensity by a factor of 2.57-fold through a 2-mm-thick 1% intralipid hydrogel and enhanced fluorescence signal under two-photon excitation through a 1.5-mm-thick scattering sample. These results demonstrate spatially separated, reflector-based acoustically assisted light guiding for enhanced light delivery and fluorescence excitation through scattering media.

bioengineering↗

bioRxiv2025

Whole chloroplast genomes reveal a complex genetic legacy of lost lineages, past radiations and secondary contacts in the dominant temperate deciduous tree genus Fagus

Background--Major northern temperate tree genera emerged in the Eocene and now have vast ranges across the Northern Hemisphere. Here we undertake a multi-discipline study to provide novel insights into the formation and biogeographic history of a dominant, yet understudied temperate tree genus, Fagus L. Data and methodology--A whole chloroplast genome phylogeny (eighty-two chloroplast genomes) with multi-accessions of most species was determined and contrasted with the timing of lineage diversification inferred from three different nuclear and chloroplast gene time-calibrated phylogenies using 101 fossils as age priors. Main results--Five deeply diverged chloroplast lineages were revealed that, with the exception of a Eurasian lineage, underwent divergence decoupled from speciation predating modern species lineages by up to 28 million years (Ma). The geographic distribution of chloroplast lineages reflects a complex history of genetic admixture during past contact between extinct and modern species including between different subgenera in East Asia and long-term persistence particularly in Japan which is the hotspot of plastome diversity. Conclusion--Modern Fagus forests are the consequence of 62 million years of evolution, migration, genetic exchange and species extinction with most modern species harbouring a mosaic of genetic material, a legacy of multiple admixture events in deep time.

evolutionary biology↗

bioRxiv2024

Isotonic and minimally invasive optical clearing media for live cell imaging ex vivo and in vivo

Tissue clearing has been widely used for fluorescence imaging of fixed tissues, but not for live tissues due to its toxicity. Here we develop minimally invasive optical clearing media for fluorescence imaging of live mammalian tissues. Light scattering is minimized by adding spherical polymers with low osmolarity to the extracellular medium. A clearing medium containing bovine serum albumin (SeeDB-Live) is minimally invasive to live cells, allowing for structural and functional imaging of live tissues, such as spheroids, organoids, acute brain slices, and the mouse brain in vivo. SeeDB-Live minimally affects the electrophysiological properties and sensory responses of neurons. We demonstrate its utility for widefield imaging of subcellular voltage dynamics, such as backpropagating action potentials, in acute brain slices. We also utilize SeeDB-Live for widefield voltage imaging of dozens of dendrites in vivo, demonstrating population dynamics. Thus, SeeDB-Live expands the scale and modalities of fluorescence imaging of live mammalian tissues.

neuroscience↗

bioRxiv2024

Near-Infrared Afterglow Luminescence Amplification via Albumin Complexation of Semiconducting Polymer Nanoparticles for Surgical Navigation in Ex Vivo Porcine Models

Afterglow imaging, leveraging persistent luminescence following light cessation, has emerged as a promising modality for surgical interventions. However, the scarcity of efficient near-infrared (NIR) responsive afterglow materials, along with their inherently low brightness and lack of cyclic modulation in afterglow emission, has impeded their widespread adoption. Addressing these challenges requires a strategic repurposing of afterglow materials that improve on such limitations. Here, we have developed an afterglow probe, composed of bovine serum albumin (BSA) coated with an afterglow material, a semiconducting polymer dye (PFODBT/SP1), called BSA@SP1 demonstrating a substantial amplification of the afterglow luminescence ([~]3-fold) compared to polymer-lipid coated PFODBT (DSPE-PEG@SP1) under same experimental conditions. This enhancement is believed to be attributed to the electron-rich matrix provided by BSA that immobilizes SP1 and enhances the generation of 1O2 radicals, which improves the afterglow luminescence brightness. Through molecule docking, physicochemical characterization, and optical assessments, we highlight BSA@SP1s superior afterglow properties, cyclic afterglow behavior, long-term colloidal stability, and biocompatibility. Furthermore, we demonstrate superior tissue permeation profiling of afterglow signals of BSA@SP1s compared to fluorescence signals using ex vivo tumor-mimicking phantoms and various porcine tissue types (skin, muscle, and fat). Expanding on this, to showcase BSA@SP1s potential in image-guided surgeries, we implanted tumor-mimicking phantoms within porcine lungs and conducted direct comparisons between fluorescence and afterglow-guided interventions to illustrate the latters superiority. Overall, our study introduces a promising strategy for enhancing current afterglow materials through protein complexation, resulting in both ultrahigh signal-to-background ratios and cyclic afterglow signals.

bioengineering↗

bioRxiv2023

Evasion of APOBEC1-mediated Intrinsic Immunity by a Herpesvirus Uracil DNA Glycosylase Is a Determinant of Viral Encephalitis

Herpes simplex virus 1 (HSV-1) is the most common cause of viral encephalitis, which can be lethal or result in severe neurological defects, even when treated with antiviral therapy. We demonstrated that activation of HSV-1 uracil-DNA glycosylase (vUNG) by phosphorylation, essential for its enzymatic activity, counteracted APOBEC1 to promote viral replication and encephalitis in the central nervous system (CNS) of mice. The activation of vUNG protected HSV-1 genomes from APOBEC1-mediated DNA editing, allowing efficient viral replication to occur. The presence of APOBEC1 markedly improved lethal encephalitis in mice infected with an HSV-1 mutant carrying a mutation in the phosphorylation site and an UNG inhibitor protected wild-type HSV-1-infected mice from lethal encephalitis. These findings re-define vUNG as an important factor that allows evasion from intrinsic anti-viral immunity mediated by APOBEC1 in the CNS, and suggest a new therapeutic approach for the treatment of fetal and critical HSV-1 encephalitis.

microbiology↗

bioRxiv2023

Negative reward-prediction errors of climbing fiber inputs for cerebellar reinforcement learning algorithm

Although the cerebellum is typically linked to supervised learning algorithms, it also exhibits extensive involvement in reward processing. In this study, we investigated the cerebellums role in executing reinforcement learning algorithms, with a particular emphasis on essential reward-prediction errors. We employed the Q-learning model to accurately reproduce the licking responses of mice in a Go/No-go auditory-discrimination task. This method enabled the calculation of reinforcement learning variables, such as reward, predicted reward, and reward-prediction errors in each learning trial. By tensor component analysis of two-photon Ca2+ imaging data from more than 6,000 Purkinje cells, we found that climbing fiber inputs of the two distinct components, which were specifically activated during Go and No-go cues in the learning process, showed an inverse relationship with predictive reward-prediction errors. By assuming bidirectional parallel-fiber Purkinje-cell synaptic plasticity, we constructed a cerebellar neural-network model with 5,000 spiking neurons of granule cells, Purkinje cells, cerebellar nuclei neurons, and inferior olive neurons. The network model qualitatively reproduced distinct changes in licking behaviors, climbing-fiber firing rates and their synchronization during discrimination learning separately for Go/No-go conditions. We found that Purkinje cells in the two components could develop specific motor commands for their respective auditory cues, guided by the predictive reward-prediction errors from their climbing fiber inputs. These results indicate a possible role of context-specific actors in modular reinforcement learning, integrating with cerebellar supervised learning capabilities.

neuroscience↗

bioRxiv2023

A multicolor suite for deciphering population coding in calcium and cAMP in vivo

cAMP is a pivotal second messenger regulated by various upstream pathways including Ca2+ and G protein-coupled receptors (GPCRs). To decipher in vivo cAMP dynamics, we rationally designed cAMPinG1, an ultrasensitive genetically encoded green cAMP indicator that outperformed its predecessors in both dynamic range and cAMP affinity. Two-photon cAMPinG1 imaging detected cAMP transients in the somata and dendritic spines of neurons in the mouse visual cortex on the order of tens of seconds. In addition, multicolor imaging with a highly sensitive new red Ca2+ indicator RCaMP3 allowed simultaneous measurement of population patterns in Ca2+ and cAMP in hundreds of neurons. We identified Ca2+-induced cAMP responses that represented specific information, such as direction selectivity in vision and locomotion, as well as GPCR-induced cAMP responses. Overall, our multicolor suite revealed that information encoded in Ca2+ and GPCRs signaling is integrated and stored as cAMP transients for longer periods in vivo. HighlightsO_LIDeveloping an ultrasensitive cAMP indicator, cAMPinG1, for visualizing cAMP transients in somata and dendritic spines in vivo. C_LIO_LIDeveloping a highly sensitive red Ca2+ indicator, RCaMP3, for visualizing Ca2+ transients in large neuronal population. C_LIO_LIDual-color Ca2+ and cAMP imaging for dissecting Ca2+-induced and GPCR-induced cAMP responses. C_LIO_LISingle-cell, single-timepoint cAMP imaging for GRCR biology and drug screening. C_LI

neuroscience↗

bioRxiv2022

Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional modules reduces dimensions for reinforcement learning

Daynamic functional organization by synchronization is theorized to be essential for dimension reduction of the cerebellar learning space. We analyzed a large amount of coordinate-localized, two-photon imaging data from cerebellar Crus II in mice undergoing "Go/No-go" reinforcement learning. Tensor component analysis revealed that a majority of climbing fiber inputs to Purkinje cells were reduced to only four functional components, corresponding to accurate timing control of motor initiation related to a Go cue, cognitive error-based learning, reward processing, and inhibition of erroneous behaviors after a No-go cue. Spatial distribution of these components coincided well with the boundaries of Aldolase-C/zebrin II expression in Purkinje cells, whereas several components are mixed in single neurons. Synchronization within individual components was bidirectionally regulated according to specific task contexts and learning stages. These findings suggest that the cerebellum, based on anatomical compartments, reduces dimensions by self-organization of components, a feature that may inspire new-generation AI designs.

neuroscience↗

bioRxiv2022

Cerebellar climbing fibers convey behavioral information of multiplex modalities and form functional modules

Cerebellar climbing fibers (CFs) convey sensorimotor information and their errors, which are used for motor control and learning. Furthermore, they represent reward-related information. Despite such functional diversity of CF signals, it is still unclear whether each CF conveys the information of single or multiple modalities and how the CFs conveying different information are distributed over the cerebellar cortex. We performed two-photon calcium imaging from cerebellar Purkinje cells (PCs) in mice engaged in a voluntary forelimb lever-pull task and demonstrated that CF responses in 93% of PCs could be explained by the combination of multiple behavioral variables, such as lever movement, licking, and reward delivery. Neighboring PCs exhibited similar CF response properties, formed functional clusters, and shared noise fluctuations of responses. Taken together, individual CFs convey behavioral information on multiplex variables and are spatially organized into the functional modules of the cerebellar cortex.

neuroscience↗

bioRxiv2020

A deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging data

Calcium imaging is a key method to record patterns of neuronal activity across populations of identified neurons. Inference of temporal patterns of action potentials ( spikes) from calcium signals is, however, challenging and often limited by the scarcity of ground truth data containing simultaneous measurements of action potentials and calcium signals. To overcome this problem, we compiled a large and diverse ground truth database from publicly available and newly performed recordings. This database covers various types of calcium indicators, cell types, and signal-to-noise ratios and comprises a total of >35 hours from 298 neurons. We then developed a novel algorithm for spike inference (CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates, and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level. As a consequence, no parameters need to be adjusted by the user. To facilitate routine application of CASCADE we developed systematic performance assessments for unseen data, we openly release all resources, and we provide a user-friendly cloud-based implementation.

neuroscience↗

bioRxiv2019

Precise hyperacuity estimation of spike timing from calcium imaging

Two-photon imaging is a major recording technique in neuroscience, but it suffers from several limitations, including a low sampling rate, the nonlinearity of calcium responses, the slow dynamics of calcium dyes and a low signal-to-noise ratio, all of which impose a severe limitation on the application of two-photon imaging in elucidating neuronal dynamics with high temporal resolution. Here, we developed a hyperacuity algorithm (HA_time) based on an approach combining a generative model and machine learning to improve spike detection and the precision of spike time inference. First, Bayesian inference estimates the calcium spike model by assuming the constancy of the spike shape and size. A support vector machine employs this information and detects spikes with higher temporal precision than the sampling rate. Compared with conventional thresholding, HA_time improved the precision of spike time estimation up to 20-fold for simulated calcium data. Furthermore, the benchmark analysis of experimental data from different brain regions and simulation of a broader range of experimental conditions showed that our algorithm was among the best in a class of hyperacuity algorithms. We encourage experimenters to use the proposed algorithm to precisely estimate hyperacuity spike times from two-photon imaging.

neuroscience↗

bioRxiv2019

Predictive neural processing in adult zebrafish depends on shank3b

Intelligent behavior requires a comparison between the predicted and the actual consequences of behavioral actions. According to the theory of predictive processing, this comparison relies on a neuronal error signal that reflects the mismatch between an internal prediction and sensory input. Inappropriate error signals may generate pathological experiences in neuropsychiatric conditions. To examine the processing of sensorimotor prediction errors across different telencephalic brain areas we optically measured neuronal activity in head-fixed, adult zebrafish in a virtual reality. Brief perturbations of visuomotor feedback triggered distinct changes in swimming behavior and different neuronal responses. Neuronal activity reflecting sensorimotor mismatch, rather than sensory input or motor output alone, was prominent throughout multiple forebrain areas. This activity preceded and predicted the transition in motor behavior. Error signals were altered in specific forebrain regions by a mutation in the autism-related gene shank3b. Predictive processing is therefore a widespread phenomenon that may contribute to disease phenotypes.

neuroscience↗