Chemical profiling and cytotoxicity screening of agarwood essential oil (Aquilaria sinensis) in brine shrimp nauplii and cancer cell lines.

Agarwood essential oil (AEO) has gained attention from healthcare industries due to its numerous pharmacological properties. However, a comprehensive understanding of the chemical composition and its cytotoxic property is lacking. The objective of this study was to investigate the chemical profile as well as the cytotoxic concentration range of AEO derived from Aquilaria sinensis agarwood.

Deep Learning Models for Automatic Upper Airway Segmentation and Minimum Cross-Sectional Area Localisation in Two-Dimensional Images.

Objective: To develop and validate convolutional neural network algorithms for automatic upper airway segmentation and minimum cross-sectional area (CSAmin) localisation in two-dimensional (2D) radiographic airway images.

Materials And Methods: Two hundred and one 2D airway images acquired using cone-beam computed tomography (CBCT) scanning were randomly assigned to a test group ( = 161) to train artificial intelligence (AI) models and a validation group ( = 40) to evaluate the accuracy of AI processing. Four AI models, UNet18, UNet36, DeepLab50 and DeepLab101, were trained to automatically segment the upper airway 2D images in the test group.

Miniaturisation and simplification of solid-state proton activity sensors for non-aqueous media and ionic liquids.

This work is the further development of the previous pH (effective) sensor work where a biologically derived proton-active redox centre - riboflavin (RFN) - was entrapped into a vapour phase polymerised poly(3,4-ethylenedioxythiophene) film and ferrocene (Fc) dissolved in the sample solution was used as an internal reference redox couple. Here, we report a disposable solid state pH (effective) sensor where we successfully incorporated both RFN and Fc into a single solid state electrode. The electrodes were then used for pH (effective) sensing where water is not required.