No abstract

Retinoic acid receptor alpha (RARα) antagonist ER‐50891 and 15 analogs were prepared and tested in vitro for potency and selectivity at RARα, RARβ, and RARγ using transactivation assays. Minor modifications to the parent molecule such as the introduction of a C4 tolyl group in place of the C4 phenyl group on the quinoline moiety slightly increased the RARα selectivity but larger substituents significantly decreased the potency. Replacement of the pyrrole moiety of ER‐50891 with triazole, amides, or a double bond produced inactive compounds. ER‐50891 was found to be stable in male mouse liver microsomes and was tested in male mice to assess its effects on spermatogenesis. Characteristic, albeit modest and transient, effects on spermatogenesis were observed.

Businesses must be aware of customer sentiment in order to provide the best customer service. Instead of using cash or a credit card, a user can use a payment app on a mobile device to pay for a variety of services and digital or physical goods, which is becoming increasingly popular around the world. The goal of this study is to evaluate and predict user sentiment for payment apps using supervised and unsupervised machine learning (ML) approaches. For the study's data, Google Play Store reviews of the PayPal and Google Pay apps were gathered. Following cleaning, the filtered summary sentences were assessed for positive, neutral, or negative feelings using two unsupervised and five supervised machine learning approaches. According to the findings of the current study, the majority of customer reviews for payment apps were positive, with the average number of words with negative sentiment being higher. Furthermore, recent research found that, while all ML approaches can correctly classify review text into sentiment classes, logistic regression outperforms them in terms of accuracy.