Tohoku University · 생화학·유전·분자생물학
Yuta Takahashi 교수의 연구실은 신경정신의학적 질환의 분자 기반 메커니즘을 밝히는 데 초점을 맞추고 있으며, 특히 정신질환과 관련된 미세글리아 및 혈액 단핵구의 활성화 메커니즘, 대사체 기반 정서적 증상 예측 모델 개발, 유전적 소견을 활용한 정신질환 예측 알고리즘 개선 등 다학제적 접근을 통해 정신질환의 병태생리학을 탐구하고 있습니다. 또한, 단백질의 비정상적 접힘과 아밀로이드 섬유 형성 메커니즘을 기반으로 한 단백질 재료 설계 연구도 수행하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
This large, endoscopy-based study demonstrated that CE prevalence increased in non-HIV-infected patients but decreased in HIV-infected patients over 13 years. Risk analysis revealed that increasing age, HIV infection, and corticosteroids use, particularly at higher doses, were independently associated with CE, but alcohol, other infections, diabetes, anticancer drugs, and PPIs use were not.
The misfolding process of the amyloidogenic proteins such as prion proteins is mimicked by the α- to β-structural transition of a peptide obtained by introducing adamantanecarbonyl groups at the N-terminals of two linked α-helices. The α- to β-transition (left to right of graph) coincided with the formation of fibrils (inset, bottom right), which further assembled into larger amyloid deposits.
A wide variety of studies have identified microglial activation in psychiatric disorders, such as schizophrenia, bipolar disorder, and major depressive disorder. Relatively fewer, but robust, studies have detected activation of peripheral monocytic cells in psychiatric disorders. Considering the origin of microglia, as well as neuropsychoimmune interactions in the context of the pathophysiology of psychiatric disorders, it is reasonable to speculate that microglia interact with peripheral monocy
The amyloid fibril is a misfolded and undesirable state for proteins that has been proposed to be a causative agent for a variety of fatal diseases known as amyloid diseases, such as Alzheimer's and prion diseases. However, the fibril has a highly ordered tertiary structure in which numerous β-strand polypeptide chains align in a regular pattern. Thus, this kind of fibril has the potential to be engineered into proteinaceous materials. Amyloid fibrils of misfolded proteins primarily comprise a s
To solve major limitations in algorithms for the metabolite-based prediction of psychiatric phenotypes, a novel prediction model for depressive symptoms based on nonlinear feature selection machine learning, the Hilbert-Schmidt independence criterion least absolute shrinkage and selection operator (HSIC Lasso) algorithm, was developed and applied to a metabolomic dataset with the largest sample size to date. In total, 897 population-based subjects were recruited from the communities affected by
The accuracy of previous genetic studies in predicting polygenic psychiatric phenotypes has been limited mainly due to the limited power in distinguishing truly susceptible variants from null variants and the resulting overfitting. A novel prediction algorithm, Smooth-Threshold Multivariate Genetic Prediction (STMGP), was applied to improve the genome-based prediction of psychiatric phenotypes by decreasing overfitting through selecting variants and building a penalized regression model. Predict
The mechanism underlying the emergence of emotional categories from visual facial expression information during the developmental process is largely unknown. Therefore, this study proposes a system-level explanation for understanding the facial emotion recognition process and its alteration in autism spectrum disorder (ASD) from the perspective of predictive processing theory. Predictive processing for facial emotion recognition was implemented as a hierarchical recurrent neural network (RNN). T
Upper gastrointestinal (GI) symptoms are common in both HIV and non-HIV-infected patients, but the difference of GI symptom severity between 2 groups remains unknown. Candida esophagitis and erosive esophagitis, 2 major types of esophagitis, are seen in both HIV and non-HIV-infected patients, but differences in GI symptoms that are predictive of esophagitis between 2 groups remain unknown. We aimed to determine whether GI symptoms differ between HIV-infected and non-HIV-infected patients, and id
At the forefront of bridging computational brain modeling with personalized medicine, this study introduces a novel, real-time, electrocorticogram (ECoG) simulator, based on the digital twin brain concept. Utilizing advanced data assimilation techniques, specifically a Variational Bayesian Recurrent Neural Network model with hierarchical latent units, the simulator dynamically predicts ECoG signals reflecting real-time brain latent states. By assimilating broad ECoG signals from macaque monkeys
We produced spherical superconducting submicron particles by laser ablation of their base metal tips in superfluid helium, and trapped them using a quadrupole magnetic field owing to the diamagnetism caused by the Meissner effect. We also measured their critical temperatures of superconductivity, by observing the threshold temperatures for the confinement of superconducting submicron particles in the trap.
The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactorial. The Massive Parallel Limitless-Arity Multiple-testing Procedure (MP-LAMP), which was developed to detect significant combinational risk factors comprehensively, was utilized to reveal hidden combinational risk factors to explain the long-term trajectory of the PTSD symptoms. In 624 population-based subjects severely affected by the Great East Japan Earthquake, 61 potential risk factors encompas
Functional connectivity (FC) and neural excitability may interact to affect symptoms of autism spectrum disorder (ASD). We tested this hypothesis with neural network simulations, and applied it with functional magnetic resonance imaging (fMRI). A hierarchical recurrent neural network embodying predictive processing theory was subjected to a facial emotion recognition task. Neural network simulations examined the effects of FC and neural excitability on changes in neural representations by develo