Prediction of disease progression indicators in prostate cancer patients receiving HDR-brachytherapy using Raman spectroscopy and semi-supervised learning: a pilot study.

This work combines Raman spectroscopy (RS) with supervised learning methods-group and basis restricted non-negative matrix factorisation (GBR-NMF) and linear discriminant analysis (LDA)-to aid in the prediction of clinical indicators of disease progression in a cohort of 9 patients receiving high dose rate brachytherapy (HDR-BT) as the primary treatment for intermediate risk (D'Amico) prostate adenocarcinoma. The combination of Raman spectroscopy and GBR-NMF-sparseLDA modelling allowed for the prediction of the following clinical information; Gleason score, cancer of the prostate risk assessment (CAPRA) score of pre-treatment biopsies and a Ki67 score of < 3.5% or > 3.5% in post treatment biopsies. The three clinical indicators of disease progression investigated in this study were predicted using a single set of Raman spectral data acquired from each individual biopsy, obtained pre HDR-BT treatment. This work highlights the potential of RS, combined with supervised learning, as a tool for the prediction of multiple types of clinically relevant information to be acquired simultaneously using pre-treatment biopsies, therefore opening up the potential for avoiding the need for multiple immunohistochemistry (IHC) staining procedures (H&E, Ki67) and blood sample analysis (PSA) to aid in CAPRA scoring.

Raman spectroscopy and supervised learning as a potential tool to identify high-dose-rate-brachytherapy induced biochemical profiles of prostate cancer.

High-dose-rate-brachytherapy (HDR-BT) is an increasingly attractive alternative to external beam radiation-therapy for patients with intermediate risk prostate cancer. Despite this, no bio-marker based method currently exists to monitor treatment response, and the changes which take place at the biochemical level in hypo-fractionated HDR-BT remain poorly understood. The aim of this pilot study is to assess the capability of Raman spectroscopy (RS) combined with principal component analysis (PCA) and random-forest classification (RF) to identify radiation response profiles after a single dose of 13.5 Gy in a cohort of nine patients. We here demonstrate, as a proof-of-concept, how RS-PCA-RF could be utilised as an effective tool in radiation response monitoring, specifically assessing the importance of low variance PCs in complex sample sets. As RS provides information on the biochemical composition of tissue samples, this technique could provide insight into the changes which take place on the biochemical level, as result of HDR-BT treatment.

"It's not as easy as saying, 'just get them to eat more veggies'": Exploring healthy eating in residential care in Australia.

Young people living in residential out-of-home care (henceforth OoHC) are at increased risk of becoming overweight or obese. Currently, recognition of the everyday mechanisms that might be contributing to excess weight for children and young people in this setting is limited. The aim of this study was to better understand the barriers and complexities involved in the provision of a 'healthy' food environment in residential OoHC. Heightening awareness of these factors and how they might compromise a young person's physical health, will inform the development, refinement and evaluation of more sensitive and tailored weight-related interventions for this population. The paper presents a nuanced picture of the complexity of everyday food routines in residential care, and illustrates the ways in which food is 'done' in care; how food can be both symbolic of care but also used to exercise control; the way in which food can be used to create a 'family-like' environment; and the impact of traumatic experiences in childhood on subsequent behaviours and overall functioning in relation to food. It is argued that a health agenda designed for a mainstream population ignores the very complex relationship that children in residential OoHC may have with food. It is recommended that future intervention approaches account for personal food biographies, trauma and children's social backgrounds and how these are implicated in everyday practices and interactions around food.