University of Adelaide

About: University of Adelaide is a education organization based out in Adelaide, South Australia, Australia. It is known for research contribution in the topics: Population & Pregnancy. The organization has 27251 authors who have published 79167 publications receiving 2671128 citations. The organization is also known as: The University of Adelaide & Adelaide University.

Information from Pharmaceutical Companies and the Quality, Quantity, and Cost of Physicians' Prescribing: A Systematic Review

Abstract: Background Pharmaceutical companies spent $57.5 billion on pharmaceutical promotion in the United States in 2004. The industry claims that promotion provides scientific and educational information to physicians. While some evidence indicates that promotion may adversely influence prescribing, physicians hold a wide range of views about pharmaceutical promotion. The objective of this review is to examine the relationship between exposure to information from pharmaceutical companies and the quality, quantity, and cost of physicians' prescribing.

Contextual extracellular cues promote tumor cell EMT and metastasis by regulating miR-200 family expression

Abstract: Metastatic disease is a primary cause of cancer-related death, and factors governing tumor cell metastasis have not been fully elucidated. Here, we address this question by using tumor cell lines derived from mice that develop metastatic lung adenocarcinoma owing to expression of mutant K-ras and p53. Despite having widespread somatic genetic alterations, the metastasis-prone tumor cells retained a marked plasticity. They transited reversibly between epithelial and mesenchymal states, forming highly polarized epithelial spheres in three-dimensional culture that underwent epithelial-to-mesenchymal transition (EMT) following treatment with transforming growth factor-beta or injection into syngeneic mice. This transition was entirely dependent on the microRNA (miR)-200 family, which decreased during EMT. Forced expression of miR-200 abrogated the capacity of these tumor cells to undergo EMT, invade, and metastasize, and conferred transcriptional features of metastasis-incompetent tumor cells. We conclude that tumor cell metastasis is regulated by miR-200 expression, which changes in response to contextual extracellular cues.

Observation of active sites for oxygen reduction reaction on nitrogen-doped multilayer graphene

Abstract: Active sites and the catalytic mechanism of nitrogen-doped graphene in an oxygen reduction reaction (ORR) have been extensively studied but are still inconclusive, partly due to the lack of an experimental method that can detect the active sites. It is proposed in this report that the active sites on nitrogen-doped graphene can be determined via the examination of its chemical composition change before and after ORR. Synchrotron-based X-ray photoelectron spectroscopy analyses of three nitrogen-doped multilayer graphene samples reveal that oxygen reduction intermediate OH(ads), which should chemically attach to the active sites, remains on the carbon atoms neighboring pyridinic nitrogen after ORR. In addition, a high amount of the OH(ads) attachment after ORR corresponds to a high catalytic efficiency and vice versa. These pinpoint that the carbon atoms close to pyridinic nitrogen are the main active sites among the different nitrogen doping configurations.

Wider or Deeper: Revisiting the ResNet Model for Visual Recognition

Abstract: The trend towards increasingly deep neural networks has been driven by a general observation that increasing depth increases the performance of a network. Recently, however, evidence has been amassing that simply increasing depth may not be the best way to increase performance, particularly given other limitations. Investigations into deep residual networks have also suggested that they may not in fact be operating as a single deep network, but rather as an ensemble of many relatively shallow networks. We examine these issues, and in doing so arrive at a new interpretation of the unravelled view of deep residual networks which explains some of the behaviours that have been observed experimentally. As a result, we are able to derive a new, shallower, architecture of residual networks which significantly outperforms much deeper models such as ResNet-200 on the ImageNet classification dataset. We also show that this performance is transferable to other problem domains by developing a semantic segmentation approach which outperforms the state-of-the-art by a remarkable margin on datasets including PASCAL VOC, PASCAL Context, and Cityscapes. The architecture that we propose thus outperforms its comparators, including very deep ResNets, and yet is more efficient in memory use and sometimes also in training time. The code and models are available at this https URL

Thirty-seven candidate genes for polycystic ovary syndrome : strongest evidence for linkage is with follistatin

Abstract: Polycystic ovary syndrome (PCOS) is a common endocrine disorder of women, characterized by hyperandrogenism and chronic anovulation. It is a leading cause of female infertility and is associated with polycystic ovaries, hirsutism, obesity, and insulin resistance. We tested a carefully chosen collection of 37 candidate genes for linkage and association with PCOS or hyperandrogenemia in data from 150 families. The strongest evidence for linkage was with the follistatin gene, for which affected sisters showed increased identity by descent (72%; chi(2) = 12.97; nominal P = 3.2 x 10(-4)). After correction for multiple testing (33 tests), the follistatin findings were still highly significant (P(c) = 0.01). Although the linkage results for CYP11A were also nominally significant (P = 0.02), they were no longer significant after correction. In 11 candidate gene regions, at least one allele showed nominally significant evidence for population association with PCOS in the transmission/disequilibrium test (chi(2) >/= 3.84; nominal P < 0.05). The strongest effect in the transmission/disequilibrium test was observed in the INSR region (D19S884; allele 5; chi(2) = 8.53) but was not significant after correction. Our study shows how a systematic screen of candidate genes can provide strong evidence for genetic linkage in complex diseases and can identify those genes that should have high (or low) priority for further study.