Factors Influencing Users’ Attitudes Towards Using Brain Computer Interface (BCI) for Non Medical Uses: An Application of the Technology Acceptance Model (TAM)

While brain-computer interfaces (BCI) are gaining popularity in assisting people with illnesses, there is also increased technical research on incorporating BCI into healthy people’s lives. So far, not much research has focused on user attitudes, although some research has pointed out privacy and trust issues. Understanding potential users’ attitudes, expectations, and concerns early in the technology development stage is crucial for the novelty\u27s success. For this reason, this study aims to understand the general publics’ attitude towards BCI for nonmedical uses using the technology acceptance model (TAM). The study will offer insights into how external factors including technology optimism, familiarity, and perceived enjoyment influence perceived usefulness (PU), perceived ease of use (PEOU), and perceived trust affect BCI uses. It is hypothesized that each independent variable is positively correlated with the dependent variable in the proposed TAM. Two hundred participants between the ages of 20 and 50 were recruited to participate in the survey. The data were analyzed using structural equation modeling (SEM), including a series of goodness-of-fit (GOF) tests and path analysis. The path coefficient for each path is analyzed with a t-test and tested at a 95% confidence level. Suppose the p-value is determined to be lower than 0.05. In that case, the null hypotheses can be confidently rejected, suggesting the model accurately represents 95% of the variances of the positive correlation observed in the population

Aminoisoxazoles as Potent Inhibitors of Tryptophan 2,3-Dioxygenase 2 (TDO2)

Tryptophan 2,3-dioxygenase 2 (TDO2) catalyzes the conversion of tryptophan to the immunosuppressive metabolite kynurenine. TDO2 overexpression has been observed in a number of cancers; therefore, TDO inhibition may be a useful therapeutic intervention for cancers. We identified an aminoisoxazole series as potent TDO2 inhibitors from a high-throughput screen (HTS). An extensive medicinal chemistry effort revealed that both the amino group and the isoxazole moiety are important for TDO2 inhibitory activity. Computational modeling yielded a binding hypothesis and provided insight into the observed structure–activity relationships. The optimized compound <b>21</b> is a potent TDO2 inhibitor with modest selectivity over indolamine 2,3-dioxygenase 1 (IDO1) and with improved human whole blood stability

Discovery of GluN2A-Selective NMDA Receptor Positive Allosteric Modulators (PAMs): Tuning Deactivation Kinetics via Structure-Based Design

The <i>N</i>-methyl-d-aspartate receptor (NMDAR) is a Na⁺ and Ca²⁺ permeable ionotropic glutamate receptor that is activated by the coagonists glycine and glutamate. NMDARs are critical to synaptic signaling and plasticity, and their dysfunction has been implicated in a number of neurological disorders, including schizophrenia, depression, and Alzheimer’s disease. Herein we describe the discovery of potent GluN2A-selective NMDAR positive allosteric modulators (PAMs) starting from a high-throughput screening hit. Using structure-based design, we sought to increase potency at the GluN2A subtype, while improving selectivity against related α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). The structure–activity relationship of channel deactivation kinetics was studied using a combination of electrophysiology and protein crystallography. Effective incorporation of these strategies resulted in the discovery of GNE-0723 (<b>46</b>), a highly potent and brain penetrant GluN2A-selective NMDAR PAM suitable for <i>in vivo</i> characterization