Evaluation of smartphone-based cough data in amyotrophic lateral sclerosis as a potential predictor of functional disability.

Objectives: Cough dysfunction is a feature of patients with amyotrophic lateral sclerosis (ALS). The cough sounds carry information about the respiratory system and bulbar involvement. Our goal was to explore the association between cough sound characteristics and the respiratory and bulbar functions in ALS.

Voice Assessment in Patients with Amyotrophic Lateral Sclerosis: An Exploratory Study on Associations with Bulbar and Respiratory Function.

Background: Speech production is a possible way to monitor bulbar and respiratory functions in patients with amyotrophic lateral sclerosis (ALS). Moreover, the emergence of smartphone-based data collection offers a promising approach to reduce frequent hospital visits and enhance patient outcomes. Here, we studied the relationship between bulbar and respiratory functions with voice characteristics of ALS patients, alongside a speech therapist's evaluation, at the convenience of using a simple smartphone.

Digested galactoglucomannan mitigates oxidative stress in human cells, restores gut bacterial diversity, and provides chemopreventive protection against colon cancer in rats.

Galactoglucomannan (GGM) is the predominant hemicellulose in coniferous trees, such as Norway spruce, and has been used as a multipurpose emulsifier in the food industry. In vitro digestion with a cellular antioxidant activity assay was performed to determine the bioaccessibility and antioxidant activity of phenolic compounds, and the behaviour of GGM on in vivo experimental assay against induced colon cancer. The results showed that digestion decreased the bioaccessibility and antioxidant capacity of phenolic compounds.

Leverage demand-side policies for energy security.

Conventional supply-side approaches overlook potential benefits.

Classifiers based on artificial intelligence in the prediction of recently planted coffee cultivars using a Remotely Piloted Aircraft System.

The classification and prediction methods through artificial intelligence algorithms are applied in different sectors to assist and promote intelligent decision-making. In this sense, due to the great importance in the cultivation, consumption and export of coffee in Brazil and the technological application of the Remotely Piloted Aircraft System (RPAS) this study aimed to compare and select models based on different data classification techniques by different classification algorithms for the prediction of different coffee cultivars (Coffea arabica L.) recently planted.