The message on the bottle:Rethinking plastic labelling to better encourage sustainable use

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordPlastic pollution continues to worsen globally in volume and complexity. The complexity in plastic production, use and disposal is significant, highlighting the importance of clear communication to consumers. Yet despite this, poor plastic labelling is clear, evident from poor waste management metrics even in the most equipped countries. Plastic labelling must change to contribute to a holistic intervention on global plastic mismanagement. Discussion on this topic leads to three key recommendations: 1. An accurate and clear “sustainability scale” to empower consumers to make decisions informed by environmental and human health implications; 2. Directions for appropriate disposal action in the region of purchase; 3. A comprehensive list of plastic composition, including additives.Natural Environment Research Council (NERC)QUEX InstituteQueensland Health, AustraliaMinderoo Foundation, Australi

Neural networks for genetic epidemiology: past, present, and future

During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN) are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes

Bladder Sparing Approaches for Muscle-Invasive Bladder Cancers.

OPINION STATEMENT: Organ preservation has been increasingly utilised in the management of muscle-invasive bladder cancer. Multiple bladder preservation options exist, although the approach of maximal TURBT performed along with chemoradiation is the most favoured. Phase III trials have shown superiority of chemoradiotherapy compared to radiotherapy alone. Concurrent chemoradiotherapy gives local control outcomes comparable to those of radical surgery, but seemingly more superior when considering quality of life. Bladder-preserving techniques represent an alternative for patients who are unfit for cystectomy or decline major surgical intervention; however, these patients will need lifelong rigorous surveillance. It is important to emphasise to the patients opting for organ preservation the need for lifelong bladder surveillance as risk of recurrence remains even years after radical chemoradiotherapy treatment. No randomised control trials have yet directly compared radical cystectomy with bladder-preserving chemoradiation, leaving the age-old question of superiority of one modality over another unanswered. Radical cystectomy and chemoradiation, however, must be seen as complimentary treatments rather than competing treatments. Meticulous patient selection is vital in treatment modality selection with the success of recent trials within the field of bladder preservation only being possible through this application of meticulous selection criteria compared to previous decades. A multidisciplinary approach with radiation oncologists, medical oncologists, and urologists is needed to closely monitor patients who undergo bladder preservation in order to optimise outcomes

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease