"Wait, Do I Need More Fiber?" Exploring UK Consumers' Dietary Fiber-Related Awareness and White Bread as a Viable Solution to Promote Subsequent Intake.

Background: Sufficient dietary fiber consumption is associated with well-established health benefits, yet such intake is currently suboptimal globally. Thus, there is interest in developing strategies to improve dietary fiber intake. One such approach is to increase the dietary fiber content of staple foods, but this needs relevant investigation.

Patients', physiotherapists' and other stakeholders' experiences and perceptions about supported home physiotherapy for people with musculoskeletal conditions: a qualitative study.

Objectives: Exercise, support and advice are the key treatment strategies of musculoskeletal problems. The aims of this study were to determine patients', physiotherapists', and other stakeholders' perspectives about supported home physiotherapy for the management of musculoskeletal problems and to identify the barriers and facilitators to rolling out this model of physiotherapy service delivery.

Methods: This study was conducted as part of a process evaluation run alongside a large trial designed to determine whether supported home physiotherapy is as good or better than a course of in-person physiotherapy.

Fibre4life: Investigating older adults dietary fibre preferences and the role of targeted educational materials on modulating future dietary fibre intake.

The UK has an ever-increasing ageing population; hence, promoting balanced nutrition can have fundamental health and cost benefits. In addition, the majority of older adults' dietary fibre intake is below recommendations and this is despite its well-cited benefits; therefore, more emphasis should be placed on identifying viable age-suitable strategies to overcome the associated dietary fibre-related knowledge gap. Accordingly, one hundred and seventy older adults (65-87 years) were recruited to partake in two survey related studies: (1) initial insights (e.

Quantitative Systems Pharmacology and Machine Learning: A Match Made in Heaven or Hell?

As pharmaceutical development moves from early-stage in vitro experimentation to later in vivo and subsequent clinical trials, data and knowledge are acquired across multiple time and length scales, from the subcellular to whole patient cohort scale. Realizing the potential of this data for informing decision making in pharmaceutical development requires the individual and combined application of machine learning (ML) and mechanistic multiscale mathematical modeling approaches. Here we outline how these two approaches, both individually and in tandem, can be applied at different stages of the drug discovery and development pipeline to inform decision making compound development.

A multiscale mathematical model describing the growth and development of bambara groundnut.

A principal objective in agriculture is to maximise food production; this is particularly relevant with the added demands of an ever increasing population, coupled with the unpredictability that climate change brings. Further improvements in productivity can only be achieved with an increased understanding of plant and crop processes. In this respect, mathematical modelling of plants and crops plays an important role.