Showing papers by "Macquarie University published in 2018"

Nivolumab plus Ipilimumab versus Sunitinib in Advanced Renal-Cell Carcinoma

Abstract: Background Nivolumab plus ipilimumab produced objective responses in patients with advanced renal-cell carcinoma in a pilot study. This phase 3 trial compared nivolumab plus ipilimumab with sunitinib for previously untreated clear-cell advanced renal-cell carcinoma. Methods We randomly assigned adults in a 1:1 ratio to receive either nivolumab (3 mg per kilogram of body weight) plus ipilimumab (1 mg per kilogram) intravenously every 3 weeks for four doses, followed by nivolumab (3 mg per kilogram) every 2 weeks, or sunitinib (50 mg) orally once daily for 4 weeks (6-week cycle). The coprimary end points were overall survival (alpha level, 0.04), objective response rate (alpha level, 0.001), and progression-free survival (alpha level, 0.009) among patients with intermediate or poor prognostic risk. Results A total of 1096 patients were assigned to receive nivolumab plus ipilimumab (550 patients) or sunitinib (546 patients); 425 and 422, respectively, had intermediate or poor risk. At a median follo...

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

Abstract: The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V.

Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments

Abstract: A robot that can carry out a natural-language instruction has been a dream since before the Jetsons cartoon series imagined a life of leisure mediated by a fleet of attentive robot helpers. It is a dream that remains stubbornly distant. However, recent advances in vision and language methods have made incredible progress in closely related areas. This is significant because a robot interpreting a natural-language navigation instruction on the basis of what it sees is carrying out a vision and language process that is similar to Visual Question Answering. Both tasks can be interpreted as visually grounded sequence-to-sequence translation problems, and many of the same methods are applicable. To enable and encourage the application of vision and language methods to the problem of interpreting visually-grounded navigation instructions, we present the Matter-port3D Simulator - a large-scale reinforcement learning environment based on real imagery [11]. Using this simulator, which can in future support a range of embodied vision and language tasks, we provide the first benchmark dataset for visually-grounded natural language navigation in real buildings - the Room-to-Room (R2R) dataset1.

Inflammasome inhibition prevents α-synuclein pathology and dopaminergic neurodegeneration in mice

Abstract: Parkinson's disease (PD) is characterized by a profound loss of dopaminergic neurons in the substantia nigra, accompanied by chronic neuroinflammation, mitochondrial dysfunction, and widespread accumulation of α-synuclein-rich protein aggregates in the form of Lewy bodies. However, the mechanisms linking α-synuclein pathology and dopaminergic neuronal death to chronic microglial neuroinflammation have not been completely elucidated. We show that activation of the microglial NLR family pyrin domain containing 3 (NLRP3) inflammasome is a common pathway triggered by both fibrillar α-synuclein and dopaminergic degeneration in the absence of α-synuclein aggregates. Cleaved caspase-1 and the inflammasome adaptor protein apoptosis-associated speck-like protein containing a C-terminal caspase recruitment domain (ASC) were elevated in the substantia nigra of the brains of patients with PD and in multiple preclinical PD models. NLRP3 activation by fibrillar α-synuclein in mouse microglia resulted in a delayed but robust activation of the NLRP3 inflammasome leading to extracellular interleukin-1β and ASC release in the absence of pyroptosis. Nanomolar doses of a small-molecule NLRP3 inhibitor, MCC950, abolished fibrillar α-synuclein-mediated inflammasome activation in mouse microglial cells and extracellular ASC release. Furthermore, oral administration of MCC950 in multiple rodent PD models inhibited inflammasome activation and effectively mitigated motor deficits, nigrostriatal dopaminergic degeneration, and accumulation of α-synuclein aggregates. These findings suggest that microglial NLRP3 may be a sustained source of neuroinflammation that could drive progressive dopaminergic neuropathology and highlight NLRP3 as a potential target for disease-modifying treatments for PD.

Lifetime-engineered NIR-II nanoparticles unlock multiplexed in vivo imaging.

Abstract: Deep tissue imaging in the second near-infrared (NIR-II) window holds great promise for physiological studies and biomedical applications1–6. However, inhomogeneous signal attenuation in biological matter7,8 hampers the application of multiple-wavelength NIR-II probes to multiplexed imaging. Here, we present lanthanide-doped NIR-II nanoparticles with engineered luminescence lifetimes for in vivo quantitative imaging using time-domain multiplexing. To achieve this, we have devised a systematic approach based on controlled energy relay that creates a tunable lifetime range spanning three orders of magnitude with a single emission band. We consistently resolve selected lifetimes from the NIR-II nanoparticle probes at depths of up to 8 mm in biological tissues, where the signal-to-noise ratio derived from intensity measurements drops below 1.5. We demonstrate that robust lifetime coding is independent of tissue penetration depth, and we apply in vivo multiplexing to identify tumour subtypes in living mice. Our results correlate well with standard ex vivo immunohistochemistry assays, suggesting that luminescence lifetime imaging could be used as a minimally invasive approach for disease diagnosis. Using lifetime-resolved imaging techniques, engineered nanoparticles can be used to perform multiplexed imaging in the NIR-II region with limited interference from biological tissues, thus by-passing the challenges of conventional deep imaging.

How many human proteoforms are there

Abstract: Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function O

A comprehensive review of state-of-the-art concentrating solar power (CSP) technologies: current status and research trends

Abstract: Concentrating solar power (CSP) has received significant attention among researchers, power-producing companies and state policymakers for its bulk electricity generation capability, overcoming the intermittency of solar resources. The parabolic trough collector (PTC) and solar power tower (SPT) are the two dominant CSP systems that are either operational or in the construction stage. The USA and Spain are global leaders in CSP electricity generation, whereas developing countries such as China and India are emerging by aggressive investment. Each year, hundreds of articles have been published on CSP. However, there is a need to observe the overall research development of this field which is missing in the current body of literature. To bridge this gap, this study 1) provides a most up-to-date overview of the CSP technologies implemented across the globe, 2) reviews previously published review articles on this issue to highlight major findings and 3) analyzes future research trends in the CSP research. Text mining approach is utilized to analyze and visualize the scientific landscape of the research. Thermal energy storage, solar collector and policy-level analysis are found as core topics of discussion in the previous studies. With a holistic analysis, it is found that direct steam generation (DSG) is a promising innovation which is reviewed in this study. This paper provides a comprehensive outlook on the CSP technologies and its research which offers practical help to the future researchers who start to research on this topic.

Ending the reading wars: reading acquisition from novice to expert

Abstract: There is intense public interest in questions surrounding how children learn to read and how they can best be taught. Research in psychological science has provided answers to many of these questio...

Recent Advances in Nanogenerator-Driven Self-Powered Implantable Biomedical Devices

Abstract: Implantable medical devices (IMDs) have experienced a rapid progress in recent years to the advancement of state-of-the-art medical practices. However, the majority of this equipment requires external power sources like batteries to operate, which may restrict their application for in vivo situations. Furthermore, these external batteries of the IMDs need to be changed at times by surgical processes once expired, causing bodily and psychological annoyance to patients and rising healthcare financial burdens. Currently, harvesting biomechanical energy in vivo is considered as one of the most crucial energy-based technologies to ensure sustainable operation of implanted medical devices. This review aims to highlight recent improvements in implantable triboelectric nanogenerators (iTENG) and implantable piezoelectric nanogenerators (iPENG) to drive self-powered, wireless healthcare systems. Furthermore, their potential applications in cardiac monitoring, pacemaker energizing, nerve-cell stimulating, orthodontic treatment and real-time biomedical monitoring by scavenging the biomechanical power within the human body, such as heart beating, blood flowing, breathing, muscle stretching and continuous vibration of the lung are summarized and presented. Finally, a few crucial problems which significantly affect the output performance of iTENGs and iPENGs under in vivo environments are addressed.

Graphene and its sensor-based applications: A review

Abstract: This paper presents an overview of the work done on graphene in recent years. It explains the preparation techniques, the properties of graphene related to its physio-chemical structure and some key applications. Graphene, due to its outstanding electrical, mechanical and thermal properties, has been one of the most popular choices to develop the electrodes of a sensor. It has been used in different forms including nanoparticle and oxide forms. Along with the preparation and properties of graphene, the categorization of the applications has been done based on the type of sensors. Comparisons between different research studies for each type have been made to highlight their performances. The challenges faced by the current graphene-based sensors along with some of the probable solutions and their future opportunities are also briefly explained in this paper.

Plant functional trait change across a warming tundra biome

Abstract: The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

When complexity science meets implementation science: a theoretical and empirical analysis of systems change

Abstract: Implementation science has a core aim – to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naive at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

The GALAH Survey: Second Data Release

Abstract: The Galactic Archaeology with HERMES (GALAH) survey is a large-scale stellar spectroscopic survey of theMilkyWay, designed to deliver complementary chemical information to a large number of stars covered by the Gaia mission. We present the GALAH second public data release (GALAH DR2) containing 342 682 stars. For these stars, the GALAH collaboration provides stellar parameters and abundances for up to 23 elements to the community. Here we present the target selection, observation, data reduction, and detailed explanation of how the spectra were analysed to estimate stellar parameters and element abundances. For the stellar analysis, we have used a multistep approach. We use the physics-driven spectrum synthesis of Spectroscopy Made Easy (SME) to derive stellar labels (T eff , logg, [Fe/H], [X/Fe], v mic , vsin i, AK S ) for a representative training set of stars. This information is then propagated to the whole sample with the data-driven method of The Cannon. Special care has been exercised in the spectral synthesis to only consider spectral lines that have reliable atomic input data and are little affected by blending lines. Departures from local thermodynamic equilibrium (LTE) are considered for several key elements, including Li, O, Na, Mg, Al, Si, and Fe, using 1D MARCS stellar atmosphere models. Validation tests including repeat observations, Gaia benchmark stars, open and globular clusters, and K2 asteroseismic targets lend confidence to our methods and results. Combining the GALAH DR2 catalogue with the kinematic information from Gaia will enable a wide range of Galactic Archaeology studies, with unprecedented detail, dimensionality, and scope.

Continental-scale animal tracking reveals functional movement classes across marine taxa.

Abstract: Acoustic telemetry is a principle tool for observing aquatic animals, but coverage over large spatial scales remains a challenge. To resolve this, Australia has implemented the Integrated Marine Observing System’s Animal Tracking Facility which comprises a continental-scale hydrophone array and coordinated data repository. This national acoustic network connects localized projects, enabling simultaneous monitoring of multiple species over scales ranging from 100 s of meters to 1000 s of kilometers. There is a need to evaluate the utility of this national network in monitoring animal movement ecology, and to identify the spatial scales that the network effectively operates over. Cluster analyses assessed movements and residency of 2181 individuals from 92 species, and identified four functional movement classes apparent only through aggregating data across the entire national network. These functional movement classes described movement metrics of individuals rather than species, and highlighted the plasticity of movement patterns across and within populations and species. Network analyses assessed the utility and redundancy of each component of the national network, revealing multiple spatial scales of connectivity influenced by the geographic positioning of acoustic receivers. We demonstrate the significance of this nationally coordinated network of receivers to better reveal intra-specific differences in movement profiles and discuss implications for effective management.

Biological responses to the press and pulse of climate trends and extreme events

Abstract: The interaction of gradual climate trends and extreme weather events since the turn of the century has triggered complex and, in some cases, catastrophic ecological responses around the world. We illustrate this using Australian examples within a press–pulse framework. Despite the Australian biota being adapted to high natural climate variability, recent combinations of climatic presses and pulses have led to population collapses, loss of relictual communities and shifts into novel ecosystems. These changes have been sudden and unpredictable, and may represent permanent transitions to new ecosystem states without adaptive management interventions. The press–pulse framework helps illuminate biological responses to climate change, grounds debate about suitable management interventions and highlights possible consequences of (non-) intervention.

Changing how we think about healthcare improvement

Abstract: Complexity science offers ways to change our collective mindset about healthcare systems, enabling us to improve performance that is otherwise stagnant, argues Jeffrey Braithwaite

Phantom: A smoothed particle hydrodynamics and magnetohydrodynamics code for astrophysics

Abstract: We present Phantom, a fast, parallel, modular, and low-memory smoothed particle hydrodynamics and magnetohydrodynamics code developed over the last decade for astrophysical applications in three dimensions. The code has been developed with a focus on stellar, galactic, planetary, and high energy astrophysics, and has already been used widely for studies of accretion discs and turbulence, from the birth of planets to how black holes accrete. Here we describe and test the core algorithms as well as modules for magnetohydrodynamics, self-gravity, sink particles, dust–gas mixtures, H2 chemistry, physical viscosity, external forces including numerous galactic potentials, Lense–Thirring precession, Poynting–Robertson drag, and stochastic turbulent driving. Phantom is hereby made publicly available.

Australia's continental-scale acoustic tracking database and its automated quality control process.

Abstract: Our ability to predict species responses to environmental changes relies on accurate records of animal movement patterns. Continental-scale acoustic telemetry networks are increasingly being established worldwide, producing large volumes of information-rich geospatial data. During the last decade, the Integrated Marine Observing System's Animal Tracking Facility (IMOS ATF) established a permanent array of acoustic receivers around Australia. Simultaneously, IMOS developed a centralised national database to foster collaborative research across the user community and quantify individual behaviour across a broad range of taxa. Here we present the database and quality control procedures developed to collate 49.6 million valid detections from 1891 receiving stations. This dataset consists of detections for 3,777 tags deployed on 117 marine species, with distances travelled ranging from a few to thousands of kilometres. Connectivity between regions was only made possible by the joint contribution of IMOS infrastructure and researcher-funded receivers. This dataset constitutes a valuable resource facilitating meta-analysis of animal movement, distributions, and habitat use, and is important for relating species distribution shifts with environmental covariates.

Call for a Paradigm Shift in the Genetic Management of Fragmented Populations

Abstract: Thousands of small populations are at increased risk of extinction because genetics and evolutionary biology are not well-integrated into conservation planning–a major lost opportunity for effective actions. We propose that if the risk of outbreeding depression is low, the default should be to evaluate restoration of gene flow to small inbred populations of diploid outbreeding organisms that were isolated by human activities within the last 500 years, rather than inaction. We outline the elements of a scientific-based genetic management policy for fragmented populations of plants and animals, and discuss the reasons why the current default policy is, inappropriately, inaction.

Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed Through Cryptocurrencies?

Abstract: Cryptocurrencies are among the largest unregulated markets in the world. We find that approximately one-quarter of bitcoin users are involved in illegal activity. We estimate that around $76 billion of illegal activity per year involves bitcoin (46% of bitcoin transactions), which is close to the scale of the US and European markets for illegal drugs. The illegal share of bitcoin activity declines with mainstream interest in bitcoin and with the emergence of more opaque cryptocurrencies. The techniques developed in this paper have applications in cryptocurrency surveillance. Our findings suggest that cryptocurrencies are transforming the black markets by enabling “black e-commerce.”

APOGEE Data Releases 13 and 14: Data and Analysis

Abstract: Alfred P. Sloan Foundation; U.S. Department of Energy Office of Science; Center for High-Performance Computing at the University of Utah; Brazilian Participation Group; Carnegie Institution for Science; Carnegie Mellon University; Chilean Participation Group; French Participation Group; Harvard-Smithsonian Center for Astrophysics; Instituto de Astrofisica de Canarias; Johns Hopkins University; Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo; Lawrence Berkeley National Laboratory; Leibniz Institut fur Astrophysik Potsdam (AIP); Max-Planck-Institut fur Astronomie (MPIA Heidelberg); Max-Planck-Institut fur Astrophysik (MPA Garching); Max-Planck-Institut fur Extra-terrestrische Physik (MPE); National Astronomical Observatories of China; New Mexico State University; New York University; University of Notre Dame; Observatorio Nacional/MCTI; Ohio State University; Pennsylvania State University; Shanghai Astronomical Observatory; United Kingdom Participation Group; Universidad Nacional Autonoma de Mexico; University of Arizona; University of Colorado Boulder; University of Oxford; University of Portsmouth; University of Utah; University of Virginia; University of Washington; University of Wisconsin; Vanderbilt University; Yale University; National Science Foundation [AST-1109178]; NSF [AST-1616636, AST-1211673]; Premium Postdoctoral Research Program of the Hungarian Academy of Sciences; Hungarian NKFI Grants of the Hungarian National Research, Development and Innovation Office [K-119517]; Birgit and Hellmuth Hertz Foundation (via the Royal Physiographic Society of Lund); Crafoord Foundation; Stiftelsen Olle Engkvist Byggmastare

Improving Topic Models with Latent Feature Word Representations

Abstract: Probabilistic topic models are widely used to discover latent topics in document collections, while latent feature vector representations of words have been used to obtain high performance in many NLP tasks. In this paper, we extend two different Dirichlet multinomial topic models by incorporating latent feature vector representations of words trained on very large corpora to improve the word-topic mapping learnt on a smaller corpus. Experimental results show that by using information from the external corpora, our new models produce significant improvements on topic coherence, document clustering and document classification tasks, especially on datasets with few or short documents.