Biology subjects

Yamagata, H.

Publications and source records attributed to Yamagata, H..

9 recordsLinked to original sources

bioRxiv2025

Automated and parallelized microfluidic generation of large and precisely-defined lipid nanoparticle libraries

Building on the success of lipid nanoparticles (LNPs) in vaccines, LNPs are being developed for a broad set of therapeutic applications by changing both the structures of the lipids used to formulate each LNP and their relative proportions. Because lipid synthesis and in vivo screening have been parallelized using combinatorial chemistry and LNP barcoding respectively, the manual and sequential microfluidic formulation of LNPs has become the rate-limiting step in the discovery process. In this work, we present a high-throughput, automated microfluidic platform capable of generating large, precisely-defined LNP libraries in parallel at a rate of one distinct formulation every three seconds. Each formulation is defined by varying the reagent flow ratios into one of eight microscale mixers using litho-graphically encoded fluidic resistors and dynamically controlled external pressure supplies. The microfluidic chip is integrated with custom frobotic plate handling for the rapid collection of each distinct formulation. Using this platform, we produce a library of 96 formulations, which we profile physicochemically and evaluate in terms of both in vitro and in vivo transfection.

bioengineering↗

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

Solution biophysics identifies lipid nanoparticle non-sphericity, polydispersity, and dependence on internal ordering for efficacious mRNA delivery

Designing lipid nanoparticle (LNP) delivery systems with specific targeting, potency and minimal side effects is crucial for their clinical use. However, traditional characterization methods, such as dynamic light scattering, cannot accurately quantify physicochemical properties of LNPs and how they are influenced by the lipid composition and mixing method. Here we structurally characterize polydisperse LNP formulations by applying emerging solution-based biophysical methods that have higher resolution and provide biophysical data beyond size and polydispersity. These techniques include sedimentation velocity analytical ultracentrifugation, field-flow fractionation followed by multi-angle light scattering, and size-exclusion chromatography in-line with synchrotron small-angle X-ray scattering. We show that LNPs have intrinsic polydispersity in size, RNA loading, and shape, which depends on both the formulation technique and lipid composition. Lastly, we predict LNP transfection in vitro and in vivo by examining the relationship between mRNA translation and physicochemical characteristics. Solution-based biophysical methods will be essential for determining LNP structure-function relationships, facilitating the creation of new design rules for LNPs.

bioengineering↗

bioRxiv2024

Induced systemic resistance by the root colonization of Trichoderma atroviride is independent from the chitin-mediated signaling pathway in Arabidopsis

Beneficial root endophytic fungi induce systemic responses, growth promotion, and induced systemic resistance (ISR) in the colonized host plants. Soil application of chitin, a main component of fungal cell walls, also systemically induces disease resistance. Thus, chitin recognition and its downstream signaling pathway are supposed to mediate ISR triggered by beneficial fungi colonizing the root. This study compared systemic disease resistance and transcriptional responses induced by Trichoderma, a representative beneficial root endophytic fungus, and chitin in Arabidopsis. A significant plant growth promotion was observed under root colonization by the three tested beneficial fungi, Trichoderma atroviride, Serendipita indica, and S. vermifera. Still, only T. atroviride and S. indica triggered ISR against the necrotrophic fungal pathogen Alternaria brassicicola. Induced systemic resistance triggered by T. atroviride was compromised in the chitin-receptor mutant, while systemic resistance caused by soil application of chitin was not. Transcriptome analysis demonstrated that the chitin-regulated genes are mostly shared with those regulated by T. atroviride, but many of the latter were specific. However, the commonly enriched gene ontologies for those regulated genes indicated that T. atroviride inoculation and chitin application systemically control similar transcriptional responses, mainly associated with cell wall functions. Taken together, Trichoderma could trigger ISR primarily independently from the chitin-mediated signaling pathway; however, chitin and Trichoderma would systemically induce similar cellular functions in ISR aboveground.

plant biology↗

bioRxiv2024

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets

The objective diagnostic and stratification biomarkers developed with resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for mental disorders. Unfortunately, there are currently no widely accepted biomarkers, partially due to the large variety of analysis pipelines for developing them. In this study we comprehensively evaluated analysis pipelines using a large-scale, multi-site fMRI dataset for major depressive disorder (MDD) (1162 participants from eight imaging sites). We explored the combinations of options in four subprocesses of analysis pipelines: six types of brain parcellation, four types of estimations of functional connectivity (FC), three types of site difference harmonization, and five types of machine learning methods. 360 different MDD diagnostic biomarkers were constructed using the SRPBS dataset acquired with unified protocols (713 participants from four imaging sites) as a discovery dataset and evaluated with datasets from other projects acquired with heterogeneous protocols (449 participants from four imaging sites) for independent validation. To identify the optimal options regardless of the discovery dataset, we repeated the same procedure after swapping the roles of the two datasets. We found pipelines that included Glassers parcellation, tangent-covariance, no harmonization, and non-sparse machine learning methods tended to result in high classification performance. The diagnosis results of the top 10 biomarkers showed high similarity, and weight similarity was also observed between eight of the biomarkers, except two that used both data-driven parcellation and FC computation. We applied the top 10 pipelines to the datasets of other mental disorders (autism spectral disorder: ASD and schizophrenia: SCZ) and eight of the ten biomarkers showed sufficient classification performances for both disorders, except two pipelines that included Pearson correlation, ComBat harmonization and random forest classifier combination. HighlightsO_LIWe evaluated the analysis pipelines of rsFC biomarker development. C_LIO_LIFour subprocesses in them were investigated with two multi-site datasets. C_LIO_LIGlassers parcellation, tangent covariance, and non-sparse methods were preferred. C_LIO_LIThe weight patterns of eight of the top 10 biomarkers showed high commonality. C_LIO_LIEight of the top 10 pipelines were successful for developing SCZ/ASD biomarkers. C_LI

neuroscience↗

bioRxiv2022

PNPO-PLP Axis Senses Prolonged Hypoxia by Regulating Lysosomal Activity

Oxygen is critical for all metazoan organisms on the earth and impacts various biological processes in physiological and pathological conditions. While oxygen sensing systems inducing acute hypoxic response, including HIF pathway, have been identified, those operating in prolonged hypoxia remain to be elucidated. Here, we show that pyridoxine 5-phosphate oxidase (PNPO) that catalyzes bioactivation of vitamin B6 serves as an oxygen sensor and regulates lysosomal activity in macrophages. Decline of PNPO activity under prolonged hypoxia reduced an active form of vitamin B6, pyridoxal 5-phosphate (PLP), and inhibited lysosomal activity, leading to the augmentation of inflammatory response of macrophages. The PNPO-PLP axis creates a distinct layer of oxygen sensing, which gradually turns down and up the PLP-dependent metabolism according to prolonged changes in oxygen availability.

biochemistry↗

bioRxiv2020

Common brain networks between major depressive disorder and symptoms of depression that are validated for independent cohorts

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable major depressive disorder (MDD) brain network markers which would distinguish patients from healthy controls (a classifier) or would predict symptom severity (a prediction model) based on resting state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD brain network markers. The classifier achieved 70% generalization accuracy, and the prediction model moderately well predicted symptom severity for an independent validation dataset with 449 participants from 4 different imaging sites. Finally, we found common 2 functional connections between those related to MDD diagnosis and those related to depression symptoms. The successful generalization to the perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

neuroscience↗

bioRxiv2018

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

When collecting large neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent the greatest barrier when acquiring multi-site neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multi-site, multi-disorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. Effects on resting-state functional MRI connectivity because of both bias types were greater than or equal to those because of psychiatric disorders. Furthermore, our findings indicated that each site can sample only from among a subpopulation of participants. This result suggests that it is essential to collect large neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using traveling-subject dataset and achieved the reduction of the measurement bias by 29% and the improvement of the signal to noise ratios by 40%.

neuroscience↗

bioRxiv2017

Repeated co-option of a conserved gene regulatory module underpins the evolution of the crustacean carapace, insect wings and other flat outgrowths

Summary statementThe genes vestigial, scalloped and wingless comprise a conserved regulatory module that was co-opted repeatedly for the evolution of flat structures, such as insect wings, and crustacean carapace, tergites and coxal plates.\n\nSummaryHow novelties arise is a key question in evolutionary developmental biology. The crustacean carapace is a novelty that evolved in the early Cambrian. In an extant crustacean, Daphnia magna, the carapace grows from the body wall as a double-layered sheet with a specialized margin. We show that the growing margin of this carapace expresses vestigial, scalloped and wingless, genes that are known to play key roles in regulating growth at the insect wing margin. RNAi-mediated knockdown of scalloped and wingless impair carapace development, indicating that carapace and wing might share a common mechanism for margin outgrowth. However, carapace and wings arise in different parts of the body and their margins have different orientations, arguing that these structures have independent evolutionary origins. We show that scalloped is also expressed at the margin of unrelated flat outgrowths (tergites and coxal plates) in the distantly related crustacean Parhyale hawaiensis. Based on these observations, we propose that the vestigial-scalloped-wingless gene module has a common role in the margin of diverse flat structures, originating before the divergence of major crustacean lineages and the emergence of insects. Repeated co-option of this module occurred independently in the carapace, wing and other flat outgrowths, underpinning the evolution of distinct novelties in different arthropod lineages.

developmental biology↗