La Trobe University

About: La Trobe University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Health care. The organization has 13370 authors who have published 41291 publications receiving 1138269 citations. The organization is also known as: LaTrobe University & LTU.

Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome

Abstract: Introgression is a potential source of beneficial genetic diversity. The contribution of introgression to adaptive evolution and improvement of wheat as it was disseminated worldwide remains unknown. We used targeted re-sequencing of 890 diverse accessions of hexaploid and tetraploid wheat to identify wild-relative introgression. Introgression, and selection for improvement and environmental adaptation, each reduced deleterious allele burden. Introgression increased diversity genome wide and in regions harboring major agronomic genes, and contributed alleles explaining a substantial proportion of phenotypic variation. These results suggest that historic gene flow from wild relatives made a substantial contribution to the adaptive diversity of modern bread wheat.

Pulmonary nodule classification with deep residual networks

Abstract: Lung cancer has the highest death rate among all cancers in the USA. In this work we focus on improving the ability of computer-aided diagnosis (CAD) systems to predict the malignancy of nodules from cropped CT images of lung nodules. We evaluate the effectiveness of very deep convolutional neural networks at the task of expert-level lung nodule malignancy classification. Using the state-of-the-art ResNet architecture as our basis, we explore the effect of curriculum learning, transfer learning, and varying network depth on the accuracy of malignancy classification. Due to a lack of public datasets with standardized problem definitions and train/test splits, studies in this area tend to not compare directly against other existing work. This makes it hard to know the relative improvement in the new solution. In contrast, we directly compare our system against two state-of-the-art deep learning systems for nodule classification on the LIDC/IDRI dataset using the same experimental setup and data set. The results show that our system achieves the highest performance in terms of all metrics measured including sensitivity, specificity, precision, AUROC, and accuracy. The proposed method of combining deep residual learning, curriculum learning, and transfer learning translates to high nodule classification accuracy. This reveals a promising new direction for effective pulmonary nodule CAD systems that mirrors the success of recent deep learning advances in other image-based application domains.

Fire and biodiversity in the Anthropocene

Abstract: Fire has been a source of global biodiversity for millions of years. However, interactions with anthropogenic drivers such as climate change, land use, and invasive species are changing the nature of fire activity and its impacts. We review how such changes are threatening species with extinction and transforming terrestrial ecosystems. Conservation of Earth's biological diversity will be achieved only by recognizing and responding to the critical role of fire. In the Anthropocene, this requires that conservation planning explicitly includes the combined effects of human activities and fire regimes. Improved forecasts for biodiversity must also integrate the connections among people, fire, and ecosystems. Such integration provides an opportunity for new actions that could revolutionize how society sustains biodiversity in a time of changing fire activity.

Aggregation-Induced Electrochemiluminescence of Platinum(II) Complexes

Abstract: We report the electrochemiluminescence properties of square-planar Pt(II) complexes that result from the formation of supramolecular nanostructures. We define this new phenomenon as aggregation-induced electrochemiluminescence (AIECL). In this system, self-assembly changes the HOMO and LUMO energies, making their population accessible via ECL pathways and leading to the generation of the luminescent excited state. Significantly, the emission from the self-assembled system is the first example of electrochemiluminescence (ECL) of Pt(II) complexes in aqueous solution having higher efficiency than the standard, Ru(bpy)32+.The finding can lead to a new generation of bright emitters that can be used as ECL labels.

Intelligence and Duchenne muscular dystrophy: full-scale, verbal, and performance intelligence quotients.

Abstract: Duchenne muscular dystrophy (DMD) is a disease which has as its hallmarks progressive muscle weakness and degeneration of skeletal muscle. Also observed among those with DMD is a higher rate of mental retardation than in the normally developing population.