The advancement in the processing speeds of computing machines has facilitated the development of complex physiologically based pharmacokinetic (PBPK) models. These PBPK models can incorporate disease-specific data and could be used to predict pharmacokinetics (PK) of administered drugs in different chronic conditions. The present study aimed to develop and evaluate PBPK drug-disease models for captopril after incorporating relevant pathophysiological changes occurring in adult chronic kidney disease (CKD) and chronic heart failure (CHF) populations. The population-based PBPK simulator Simcyp was used as a modeling and simulation platform. The visual predictive checks and mean observed/predicted ratios (ratio(Obs/pred)) of the PK parameters were used for model evaluation. The developed disease models were successful in predicting captopril PK in all three stages of CKD (mild, moderate, and severe) and CHF, as the observed and predicted PK profiles and the ratio(obs/pred) for the PK parameters were in close agreement. The developed captopril PBPK models can assist in tailoring captopril dosages in patients with different disease severity (CKD and CHF).

Prosthetic rehabilitation of a partial or total maxillectomy with an obturator is the most acceptable treatment option. The hollowing of the obturator prosthesis is beneficial as it reduces the stresses over the underlying and surrounding tissues. A simple technique of fabricating a hollow bulb obturator has been discussed in this article. At the step of the packing of a denture, the hollow wax pattern of the defect area is formed with modeling wax. This hollow wax pattern is filled with water and is allowed to freeze to form an ice block. This ice block is removed from the wax pattern and is interposed between two layers for heat-cured acrylic resin and is then cured. After processing the denture, the water is retrieved by making a small hole in denture base, which is packed after hollowing with a cold cure acrylic resin. A lightweight prosthesis with a uniform thickness was achieved with a readily available and easily retrievable material, i.e., ice.

No abstract

Using technology in teaching may help to meet the expectations that traditional education is unable to fulfill (Gunuç & Babacan, 2018). Therefore, in designing computer-assisted language learning (CALL), teachers may consider how technology might support standards and learning outcomes. This review focuses on educational technology standards for English language learners to evaluate the Explain Everything application. The criteria for review have been curated and adopted from the TESOL Technology Standards Framework (Healey et al., 2008). These criteria focus on performing basic functions, working collaboratively and individually, and providing opportunities to create content. Here is a list of the curated criteria: The app provides opportunities to perform basic functions on digital devices; The app provides opportunities to use technology-based productivity tools collaboratively and individually in order to enhance their language learning competence; and The app provides opportunities to create content to share online or offline. This review will be divided into three sections: first, a general description of Explain Everything is presented. In the second section, I will evaluate the program based on the criteria. In the last section, the review will provide some general recommendations for language teachers to consider if they decide to use Explain Everything.

No abstract