Biology subjects

Yoshida, T.

Publications and source records attributed to Yoshida, T..

5 recordsLinked to original sources

bioRxiv2026

Ex vivo human tumor slices more accurately predict patient responses to an oncolytic virus than in vivo mouse models

Immunotherapies, including oncolytic viruses (OV), are promising therapies that can enhance anti-tumor immune responses. However, preclinical success of immunotherapies in mouse models has not always translated to clinical benefit in cancer patients. This study compared preclinical efficacy and mechanism of action for ASP9801, a vaccinia virus expressing IL-7 and IL-12, using mouse models of colorectal cancer (CRC) in vivo and in human organotypic tumor slice models ex vivo. The murine surrogate for ASP9801 significantly reduced tumor volumes in treated and abscopal tumors in two different CRC models in vivo (MC38 and RO100). Treatment efficacy was accentuated when combined with anti-PD1 treatment, and single-cell RNA sequencing analysis revealed depletion of tumor cells and increased T cell infiltration and activation in both treated and abscopal tumors. However, human tissue analysis ex vivo (E-slices) using PDX models and patient samples showed that ASP9801 is not effective in CRC, consistent with clinical trial results. On the other hand, ASP9801 was highly effective in GBM, indicating indication-specific efficacy of ASP9801, and how E-slice assays can be used to identify treatment-sensitive indications. This study demonstrates the superiority of E-slices over mouse models for predicting clinical response and its utility in planning clinical trials.

cancer biology↗

bioRxiv2018

Hypomorphic mutation of the mouse Huntingtons disease gene orthologue

Rare individuals with hypomorphic inactivating mutations in the Huntingtons Disease (HD) gene (HTT), identified by CAG repeat expansion in the eponymous neurodegenerative disorder, exhibit variable abnormalities that imply HTT essential roles during organ development. Here we report phenotypes produced when increasingly severe hypomorphic mutations in Htt, the murine HTT orthologue (in HdhneoQ20, HdhneoQ50, HdhneoQ111 mice), were placed over a null allele (Hdhex4/5). The most severe hypomorphic allele failed to rescue null lethality at gastrulation, while the intermediate alleles yielded perinatal lethality and a variety of fetal abnormalities affecting body size, skin, skeletal and ear formation, and transient defects in hematopoiesis. Comparative molecular analysis of wild-type and Htt-null retinoic acid-differentiated cells revealed gene network dysregulation associated with organ development and proposed polycomb repressive complexes and miRNAs as molecular mediators. Together these findings demonstrate that the HD gene acts both pre- and post-gastrulation and possibly suggest pleiotropic consequences of HTT-lowering therapeutic strategies.\n\nAuthor SummaryThe HTT gene product mutated in Huntingtons Disease (HD) has essential roles during normal organism development, however, still not fully predictable are the functional consequences of its partial inactivation. Our genetic study provides a comprehensive effects description of progressively stronger suppression of Htt gene, the murine HTT counterpart. The most severe Htt reduction leads to embryo lethality, while intermediate Htt dosages yield a variety of developmental abnormalities affecting body size, skin, skeletal and ear formation, and hematopoiesis. Complementing molecular analysis in differentiating cells depleted of a functional Htt gene further elucidates genes networks dysregulated during organ development and proposes chromatin regulators and short non-coding RNAs as key molecular mediators. Together these findings demonstrate that the HD gene acts both at early and later stages of development, thus possibly suggesting long-term consequences associated to the newest HD therapeutic strategies aimed at lowering the HTT gene product.

genetics↗

bioRxiv2018

Relationships of trainee dentists’ empathy and communication characteristics with simulated patients’ assessment in medical interviews

ObjectivesWe aimed to clarify the characteristics of communication between trainee dentists and simulated patients (SPs) and to examine how the level of trainee dentists self-reported empathy influences assessment by SPs in medical interviews.\n\nMaterials and methodsThe study involved 100 trainee dentists at Okayama University Hospital and eight SPs. The trainee dentists conducted initial interviews with the SPs after completing the Japanese version of the Jefferson Scale of Empathy. Their interviews were recorded and analyzed using the Roter Interaction Analysis System. The SPs assessed the trainees communication immediately after each interview. The trainee dentists were classified into two groups (more positive and less positive groups) according to SP assessment scores.\n\nResultsCompared with the less positive trainees, the more positive trainees scored higher on the [Emotional expression] and lower on the [Medical data gathering] Roter Interaction Analysis System categories. There was no difference in [Dental data gathering] between the two groups. The SPs of more positive trainees had higher rates of [Positive talk] and [Emotional expression] and lower rates of [Medical information giving] and [Dental information giving]. The trainees with more positive ratings from SPs had significantly higher Jefferson Scale of Empathy total scores.\n\nConclusionThe results of this study suggest that responding to the SPs emotions is a relevant characteristic of dentist-SP communication to SPs positive assessment in medical interviews. Further, trainees self-reported empathy was related with the SPs assessment of trainees communication, which indicated that patient satisfaction can be improved by increasing the dentists empathy. Thus, an empathic attitude among dentists is a significant determinant of patient satisfaction.

scientific communication and education↗

bioRxiv2018

Characterization of nonlinear receptive fields of visual neurons by convolutional neural network

A comprehensive understanding of the stimulus-response properties of individual neurons is necessary to crack the neural code of sensory cortices. However, a barrier to achieving this goal is the difficulty of analyzing the nonlinearity of neuronal responses. In computer vision, artificial neural networks, especially convolutional neural networks (CNNs), have demonstrated state-of-the-art performance in image recognition by capturing the higher-order statistics of natural images. Here, we incorporated CNN for encoding models of neurons in the visual cortex to develop a new method of nonlinear response characterization, especially nonlinear estimation of receptive fields (RFs), without assumptions regarding the type of nonlinearity. Briefly, after training CNN to predict the visual responses of neurons to natural images, we synthesized the RF image such that the image would predictively evoke a maximum response (\"maximization-of-activation\" method). We first demonstrated the proof-of-principle using a dataset of simulated cells with various types of nonlinearity, revealing that CNN could be used to estimate the nonlinear RF of simulated cells. In particular, we could visualize various types of nonlinearity underlying the responses, such as shift-invariant RFs or rotation-invariant RFs. These results suggest that the method may be applicable to neurons with complex nonlinearities, such as rotation-invariant neurons in higher visual areas. Next, we applied the method to a dataset of neurons in the mouse primary visual cortex (V1) whose responses to natural images were recorded via two-photon Ca2+ imaging. We could visualize shift-invariant RFs with Gabor-like shapes for some V1 neurons. By quantifying the degree of shift-invariance, each V1 neuron was classified as either a shift-variant (simple) cell or shift-invariant (complex-like) cell, and these two types of neurons were not clustered in cortical space. These results suggest that the novel CNN encoding model is useful in nonlinear response analyses of visual neurons and potentially of any sensory neurons.

neuroscience↗

bioRxiv2018

Representation of natural image contents by sparsely active neurons in visual cortex

Natural scenes sparsely activate neurons in the primary visual cortex (V1). However, how sparsely active neurons robustly represent natural images and how the information is optimally decoded from the representation have not been revealed. We reconstructed natural images from V1 activity in anaesthetized and awake mice. A single natural image was linearly decodable from a surprisingly small number of highly responsive neurons, and an additional use of remaining neurons even degraded the decoding. This representation was achieved by diverse receptive fields (RFs) of the small number of highly responsive neurons. Furthermore, these neurons reliably represented the image across trials, regardless of trial-to-trial response variability. The reliable representation was supported by multiple neurons with overlapping RFs. Based on our results, the diverse, partially overlapping RFs ensure sparse and reliable representation. We propose a new representation scheme in which information is reliably represented while the representing neuronal patterns change across trials and that collecting only the activity of highly responsive neurons is an optimal decoding strategy for the downstream neurons

neuroscience↗