University of South Australia

About: University of South Australia is a education organization based out in Adelaide, South Australia, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 10086 authors who have published 32587 publications receiving 913683 citations. The organization is also known as: The University of South Australia & UniSA.

General practice vs surgical-based follow-up for patients with colon cancer: randomised controlled trial

Abstract: This trial examined the optimal setting for follow-up of patients after treatment for colon cancer by either general practitioners or surgeons. In all, 203 consenting patients who had undergone potentially curative treatment for colon cancer were randomised to follow-up by general practitioners or surgeons. Follow-up guidance recommended three monthly clinical review and annual faecal occult blood tests (FOBT) and were identical in both study arms. Primary outcome measures (measured at baseline, 12 and 24 months were (1) quality of life, SF-12; physical and mental component scores, (2) anxiety and depression: Hospital Anxiety and Depression Scale and (3) patient satisfaction: Patient Visit-Specific Questionnaire. Secondary outcomes (at 24 months) were: investigations, number and timing of recurrences and deaths. In all, 170 patients were available for follow-up at 12 months and 157 at 24 months. At 12 and 24 months there were no differences in scores for quality of life (physical component score, P=0.88 at 12 months; P=0.28 at 24 months: mental component score, P=0.51, P=0.47; adjusted), anxiety (P=0.72; P=0.11) depression (P=0.28; P=0.80) or patient satisfaction (P=0.06, 24 months). General practitioners ordered more FOBTs than surgeons (rate ratio 2.4, 95% CI 1.4–4.4), whereas more colonoscopies (rate ratio 0.7, 95% CI 0.5–1.0), and ultrasounds (rate ratio 0.5, 95% CI 0.3–1.0) were undertaken in the surgeon-led group. Results suggest similar recurrence, time to detection and death rates in each group. Colon cancer patients with follow-up led by surgeons or general practitioners experience similar outcomes, although patterns of investigation vary.

Review on shell materials used in the encapsulation of phase change materials for high temperature thermal energy storage

Abstract: This paper presents a detailed review of shell materials that have the potential to be used for high temperature thermal energy storage (TES) applications, particularly in conjunction with concentrated solar power (CSP) plants. This paper considers shell materials that are thermally stable at more than 300 °C and have successfully been used to encapsulate a phase change material (PCM). The current review does not consider the thermal performance of the shell material and PCM combinations that have been studied. Using these constraints several feasible materials were identified including: steel (carbon and stainless), nickel (and nickel alloy), sodium silicate, silicon dioxide, calcium carbonate and titanium dioxide. These materials have the potential to encapsulate high temperature PCMs and thus provide a suitable method of high temperature TES.

Lysosomal Storage Disease: Revealing Lysosomal Function and Physiology

Abstract: The discovery over five decades ago of the lysosome, as a degradative organelle and its dysfunction in lysosomal storage disorder patients, was both insightful and simple in concept. Here, we review some of the history and pathophysiology of lysosomal storage disorders to show how they have impacted on our knowledge of lysosomal biology. Although a significant amount of information has been accrued on the molecular genetics and biochemistry of lysosomal storage disorders, we still do not fully understand the mechanistic link between the storage material and disease pathogenesis. However, the accumulation of undegraded substrate(s) can disrupt other lysosomal degradation processes, vesicular traffic, and lysosomal biogenesis to evoke the diverse pathophysiology that is evident in this complex set of disorders.

GraphDTA: predicting drug-target binding affinity with graph neural networks.

Abstract: The development of new drugs is costly, time consuming, and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to repurpose drugs effectively, it is useful to know which proteins are targeted by which drugs. Computational models that estimate the interaction strength of new drug–target pairs have the potential to expedite drug repurposing. Several models have been proposed for this task. However, these models represent the drugs as strings, which is not a natural way to represent molecules. We propose a new model called GraphDTA that represents drugs as graphs and uses graph neural networks to predict drug–target affinity. We show that graph neural networks not only predict drug–target affinity better than non-deep learning models, but also outperform competing deep learning methods. Our results confirm that deep learning models are appropriate for drug–target binding affinity prediction, and that representing drugs as graphs can lead to further improvements. Availability of data and materials The proposed models are implemented in Python. Related data, pre-trained models, and source code are publicly available at https://github.com/thinng/GraphDTA. All scripts and data needed to reproduce the post-hoc statistical analysis are available from https://doi.org/10.5281/zenodo.3603523.