Biology subjects

Ogihara, T.

Publications and source records attributed to Ogihara, T..

3 recordsLinked to original sources

bioRxiv2022

Predicting the Degree of Distracted Driving Based on fNIRS Functional Connectivity: A Pilot Study

Distracted driving is one of the main causes of traffic accidents. By predicting the attentional state of drivers, it is possible to prevent distractions and promote safe driving. In this study, we developed a model that could predict the degree of distracted driving based on brain activity. Changes in oxyhemoglobin concentrations were measured in drivers while driving a real car using functional near-infrared spectroscopy (fNIRS). A regression model was constructed for each participant using functional connectivity as an explanatory variable and break reaction time to random beeps while driving as an objective variable. As a result, we were able to construct a prediction model for 11 of the 12 participants. Furthermore, the regression model with the highest prediction accuracy for each participant was analyzed to gain a better understanding of the neural basis of distracted driving. The 11 models were classified into five clusters by hierarchical clustering based on their functional connectivity edges used in each cluster. The results showed that the combinations of the dorsal attention network (DAN)-sensory motor network (SMN) and DAN-ventral attention network (VAN) connections were common in all clusters and that these networks were essential to predict the degree of distraction in complex multitask driving. They also confirmed the existence of multiple types of prediction models with different within- and between-network connectivity patterns. These results indicate that it is possible to predict the degree of distracted driving based on the brain activity of the driver during actual driving. These results are expected to contribute to the development of safe driving systems and elucidation of the neural basis of distracted driving.

neuroscience↗

bioRxiv2021

A selective glucocorticoid receptor modulator attenuates lung inflammation and improves alveolarization in a neonatal rat model of bronchopulmonary dysplasia.

BackgroundBronchopulmonary dysplasia (BPD) is a major problem for extremely preterm infants. Glucocorticoids effectively treat BPD; however, they have many side effects. Compound A (Cpd A) is a nonsteroidal Selective Glucocorticoid Receptor Modulator (SEGRM) that acts as a glucocorticoid receptor ligand without inducing the expression of glucocorticoid-response element-driven genes. Cpd A reportedly has anti-inflammatory properties with fewer side effects than glucocorticoids. MethodsUsing a bleomycin (Bleo)-induced BPD model, we evaluated the therapeutic effects of Cpd A. 0-day-old Sprague-Dawley rats were administered Bleo for 10 days and treated with dexamethasone (Dex) or Cpd A from day 0 to 13. We evaluated lung pathology by histology and the mRNA levels of interleukin (IL)-1{beta}, transforming growth factor (TGF)-{beta}1 and chemokines, CXCL1 and CCL2. ResultsBleo-treated mice had lungs with impaired alveolarization. Dex and Cpd A treatments improved the alveolar structure, attenuating the lung injury. Bleo-exposed lungs had increased inflammatory cells recruitment and inflammatory mediator mRNA levels. Cpd A treatment reduced inflammatory cells infiltration and CXCL1, CCL2 and TGF-{beta}1 expression. ConclusionCpd A improved lung inflammation and alveolar maturation arrest, and restored histological and biochemical changes in a model of BPD. SEGRMs, including Cpd A, are promising candidates for the therapy of BPD. Impact Statement{circ} What is the key message of your article? Compound A decreased lung inflammation and improved lung morphometric changes in Bleomycin-exposed lungs. {circ}What does it add to the existing literature? Compound A has anti-inflammatory effects in an experimental model of BPD. {circ}What is the impact? SEGRMs, including Cpd A, may be promising candidates for the therapy of BPD.

pathology↗

bioRxiv2020

Gastrointestinal absorption of pimozide is enhanced by inhibition of P-glycoprotein

Following the death due to cardiac arrest of a patient taking pimozide, sertraline and aripiprazole antipsychotic/antidepressant combination therapy, a role of drug-drug interaction was suggested. Here, we investigated P-glycoprotein (P-gp)-mediated interaction among the three drugs using in vitro methods. Sertraline or aripiprazole significantly increased the permeability of pimozide in Caco-2 cell monolayers. ATPase assay indicated that pimozide is a P-gp substrate, and might act as a P-gp inhibitor at higher concentrations. The values of the kinetic parameters of carrier-mediated efflux, calculated from the concentration dependence of pimozide efflux from LLC-GA5-COL150 cells expressing human P-gp, were as follows: maximum transport rate (Jmax) = 84.9 {+/-} 8.9 pmol/min/mg protein, half-saturation concentration (Kt) = 10.6 {+/-} 4.7 M, first-order rate constant (kd) = 0.67 {+/-} 0.14 pmol/min/mg protein. Further, the efflux ratio of pimozide in LLC-GA5-COL150 cells was significantly decreased in the presence of sertraline or aripiprazole. These results indicate that pimozide is a substrate of P-gp, and its efflux is inhibited by sertraline and aripiprazole. Thus, P-gp inhibition by sertraline and/or aripiprazole may alter the gastrointestinal permeability of co-administered pimozide, resulting in an increased blood concentration of pimozide, which may increase the likelihood of pimozides known life-threatening side effect of QT prolongation.

pharmacology and toxicology↗