Griffith, Australia
Griffith, Australia

Griffith University is a public research university in southeastern Queensland on the east coast of Australia. The university has five campuses located on the Gold Coast, Logan City and the Brisbane suburbs of Mount Gravatt, Nathan and South Bank. Current total enrolment is approximately 43,000 with 4,000 full-time equivalent staff. Griffith University offers undergraduate and postgraduate degrees across ten discipline areas including Arts, Education, Business, Health, Law, Engineering, Information Technology, Environment, Music and Visual Arts. Wikipedia.

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Patent
Griffith University | Date: 2017-07-12

The present invention relates to compounds which are found to exhibit an antiviral effect. The compounds are modulators of the activity of the viral haemagglutinin and/or neuraminidase enzymes.


Patent
Griffith University | Date: 2017-02-22

A method and composition for eliciting an immune response to group A streptococcal bacteria in a mammal is provided, which includes administering to the mammal an M protein fragment, variant or derivative thereof and a SpyCEP protein or peptide fragment, or an antibody to the SpyCEP protein or fragment to facilitate restoring or enhancing neutrophil activity. Also provided is an immunodominant peptide fragment of SpyCEP.


Patent
Griffith University | Date: 2015-07-03

Organosilane functionalised carbon nanoparticles comprising a carbon dot bonded to an organosilane functionalization agent in a first orientation having one or more functional groups capable of binding mercury located at or proximal to a free end thereof.


Patent
Griffith University | Date: 2017-05-10

Organosilane functionalised carbon nanoparticles comprising a carbon dot bonded to an organosilane functionalization agent in a first orientation having one or more functional groups capable of binding mercury located at or proximal to a free end thereof.


Patent
Griffith University | Date: 2015-04-15

A method and composition for eliciting an immune response to group A streptococcal bacteria in a mammal is provided, which includes administering to the mammal an M protein fragment, variant or derivative thereof and a SpyCEP protein or peptide fragment, or an antibody to the SpyCEP protein or fragment to facilitate restoring or enhancing neutrophil activity. Also provided is an immunodominant peptide fragment of SpyCEP.


News Article | May 10, 2017
Site: news.yahoo.com

Data-intensive research is changing the way African researchers can work and the impact they can have. It is also opening up new career paths in the field of data science. By increasing the volume of data that researchers can analyze and work with at any given time, data-intensive technology allows them to make bigger strides in less time in their chosen disciplines. Data scientists assist this process by providing the skills to help researchers and managers first analyze large volumes of data and then use that analysis to make effective decisions. Big data is already making a big difference in fields ranging from banking and social media to healthcare and astronomy. Data-intensive research, or big data technology, has come to Africa by way of the stars: the establishment of the Square Kilometre Array (SKA) pointed to the need for the continent to be able to analyze the extremely high volumes of data to be generated by the network of telescope dishes that will ultimately be placed across remote regions of southern Africa. The SKA project is an internationally renowned effort to build the world’s largest radio telescope with more than a square kilometer of collecting area. It is one of the largest scientific endeavors in history and drives one of the world’s most significant big data challenges of the coming decade. Three South Africa-based universities involved in the SKA project—North-West University, the University of Cape Town (UCT) and the University of the Western Cape (UWC)—established a partnership in 2015 to form the Inter-University Institute for Data Intensive Astronomy (IDiA). IDiA is mobilizing researchers in fields such as astronomy, computer science, statistics and eResearch technologies to create data science capacity for leadership in SKA precursor projects such as MeerKAT, which is scheduled to achieve full operation in early 2018. MeerKAT marks the beginning of a radio big data revolution in Africa. It will be operated as a South African national facility for about five years before it is incorporated into the SKA dish array. The IDiA is also establishing a data-intensive research and training program to develop capacity on the continent to use the data that MeerKAT will deliver. On its own, radio astronomy data is raw; it requires analysis to provide the kinds of answers astronomers and astrophysicists are seeking about the origins of the cosmos. The astronomy project will also involve developing data systems and tools for analysis with multi-wavelength astronomy data. The SKA is a multinational project involving researchers and data scientists around the world. Thus, one of IDiA’s projects is to create a data platform that will allow remote teams to access the data: the African Research Cloud (ARC). IDiA will also develop and apply processing algorithms that allow for analysis of the data so that we can turn high volumes of information into knowledge we can apply and use. The ARC involves collaborators from around the world. Much of this work is also part of a collaboration with SKA partners in the Netherlands to establish an Advanced European Network of E-infrastructure for astronomy. The ARC is the first stage of a three-phase plan to address specific uses of data-intensive research. One such application is the African Research Cloud Astronomy Demonstration project (ARCADE), which will specifically serve MeerKAT teams. The MeerKAT large surveys will produce a terrifying deluge of data. Observations are expected to produce almost 100-terabytes worth of data each day — orders of magnitude more than the conventional volume from a radio telescope. This data will have to be transported, calibrated, imaged, processed and analysed by dozens of astronomers around the world. ARCADE, thus, focuses on two important aspects of scientific utility: data processing of radio data and large-scale scientific collaboration. A proof-of-concept approach is used: compact and incisive interventions are developed for well-defined technological problem statements. One such successful intervention involved a large-scale collaborative project, which used a second-year astronomical techniques class at UCT as a test-subject. The project focused on practical learning outcomes for the class of 50. Students had to perform a simple, yet challenging set of analyses on radio and optical images, which included inspection, statistical analyses, plotting and documentation. A cloud-based hub was created for the project and a beefy virtual machine was populated with state-of-the-art software tools that are the contemporary standards in open source big data initiatives. Students could log onto the ARC via a web browser in a computer lab during a supervised session, but they could also have completed the exercise anywhere in UCT, on their own laptops and mobile devices. This successful case study demonstrated the power of big data solutions and the advantages of cloud-based technologies, and resulted in two very important findings. First, the ARC and IDiA provide an unprecedented opportunity for training and collaboration in scientific analyses. The test-subject students were exposed to critical skills in mathematics, statistics and programming in an immersive and collaborative environment. They were at liberty to discuss, share and work on their projects in a safe and robust programming environment. This sort of intervention can be deployed at a larger scale, and can provide a training environment for anyone with an internet connection. Additionally, the students experienced a first glimpse of tools and techniques that will provide them with an advantage in their future careers in academic institutions or industry. Second, this cloud-based intervention showcased a lean, information technology (IT)-on-a-diet approach, while retaining a high-degree of technical flexibility. The virtual machine was designed and deployed in a matter of hours, and required only the interaction between a single technical specialist and the scientific researcher. Indeed, one of the aims of ARCADE is to deliver a framework that does not require an IT technical specialist, but is deployable using standard recipes and a few mouse-clicks. In this respect, we are drawing alongside commercial solutions that are available at a financial premium. Our studies will provide easily accessible solutions for smaller projects that can benefit from large-scale designs for well-defined science projects. A similar project in bioinformatics will help researchers who are investigating, for instance, the relationship between genetics and disease. Their work involves not only dealing with data in large volumes, but detecting relationships that are highly specialized in certain molecules. Big data analysis can do this kind of sifting and identifying work in a relatively short time. One such strategic project, based at UWC, will implement a platform for tuberculosis surveillance in Africa, to glean insights into the dynamics of tuberculosis infection. Such an approach can ultimately assist in rolling out cost-effective diagnostic technologies and health interventions. The pilot project involves researchers as far afield as Ghana, South Africa, Uganda and Zimbabwe, but the plan is to involve more countries once the pilot project is completed. A potential breakthrough in malaria medicine demonstrates the kind of difference big data computing can offer to African science. In 2012, researchers at UCT’s Drug Discovery and Development Centre (H3D) identified a molecule that showed great promise of not only becoming part of a single-dose cure for malaria but also possibly blocking transmission of the malaria parasite from person to person through mosquito bites. The first part of their work on this project, however, took place at Griffith University in Australia, where scientists with big data capacity screened an initial group of about 36,000 small molecules. When those compounds had been narrowed down to several hundreds, a team of scientists from H3D took over the project and further explored the antimalarial potential of the various chemotypes (or chemical classes). The candidate molecule is now in the clinical trial process, with a second next-generation back-up candidate also identified and expected to enter the same process in due course. Globally many small molecules have been screened in a similar manner, paving way for exploring new, potential medicines against malaria. This type of multinational cooperation is part of the modern research landscape around the world. With the development of big data capacity and the ARC, African science will be able to bring a more substantial contribution to such partnerships and influence new breakthroughs based on the data gleaned from projects such as the SKA. It is opening a new door of opportunity. Russell Taylor is the director of IDiA and Joint UCT/UWC/SKA chair. Bradley Frank is a lecturer at UWC and a senior researcher at IDiA. This piece was produced by SciDev.Net’s Sub-Saharan Africa English desk. This article was originally published on SciDev.Net. Read the original article. Sign up for the Quartz Africa Weekly Brief — the most important and interesting news from across the continent, in your inbox. Sign up for the Quartz Daily Brief, our free daily newsletter with the world’s most important and interesting news. SpaceX is building the world’s most powerful rocket, and it is nearly ready to fly Good luck with finding American engineers for the drudgery at companies like Infosys and Cognizant


Mackay-Sim A.,Griffith University
Frontiers in Cellular Neuroscience | Year: 2013

The concept of drug discovery through stem cell biology is based on technological developments whose genesis is now coincident. The first is automated cell microscopy with concurrent advances in image acquisition and analysis, known as high content screening (HCS). The second is patient-derived stem cells for modeling the cell biology of brain diseases. HCS has developed from the requirements of the pharmaceutical industry for high throughput assays to screen thousands of chemical compounds in the search for new drugs. HCS combines new fluorescent probes with automated microscopy and computational power to quantify the effects of compounds on cell functions. Stem cell biology has advanced greatly since the discovery of genetic reprograming of somatic cells into induced pluripotent stem cells (iPSCs). There is now a rush of papers describing their generation from patients with various diseases of the nervous system. Although the majority of these have been genetic diseases, iPSCs have been generated from patients with complex diseases (schizophrenia and sporadic Parkinson's disease). Some genetic diseases are also modeled in embryonic stem cells (ESCs) generated from blastocysts rejected during in vitro fertilization. Neural stem cells have been isolated from post-mortem brain of Alzheimer's patients and neural stem cells generated from biopsies of the olfactory organ of patients is another approach. These "olfactory neurosphere-derived" cells demonstrate robust disease-specific phenotypes in patients with schizophrenia and Parkinson's disease. HCS is already in use to find small molecules for the generation and differentiation of ESCs and iPSCs. The challenges for using stem cells for drug discovery are to develop robust stem cell culture methods that meet the rigorous requirements for repeatable, consistent quantities of defined cell types at the industrial scale necessary for HCS. © 2013 Mackay-Sim.


Berners-Price S.J.,Griffith University
Angewandte Chemie - International Edition | Year: 2011

The next generation: Classical Pt II anticancer compounds contain cis diam(m)ine ligands and are activated by ligand-substitution reactions. Pt IV diam(m)ine diazido dihydroxo complexes are nontoxic to cells until activated by light. Replacement of the diam(m)ine ligands in a trans configuration by pyridine gives a complex that is potently cytotoxic when irradiated with visible light and which has potential as a photochemotherapeutic agent. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Good M.F.,Griffith University
Science | Year: 2013

A rationalized and reinvented approach to vaccinating against malaria shows impressive results.


Fry B.,Griffith University
Marine Ecology Progress Series | Year: 2013

Statistical mixing models have been developed to help ecologists deal with isotope tracer data and to estimate source contributions in complex systems such as food webs and sediments. However, there are often too few tracer measurements and too many sources, so that unique solutions are not possible in underdetermined mixing models. This review highlights 3 approaches for solving otherwise underdetermined mixing models. The approaches include frequency-based statistics, calculations based on sectors measured in mixing polygons, and linear mixing between central and sidewall points in the mixing polygons. All approaches have some assumptions that allow extrapolation of mean solutions from measured data, with the simplest assumption being that any uncertainty in source contributions is divided in an even-handed manner among sources. A new graphical approach is proposed that allows scientists to critically recognize and separate datasupported aspects of solutions from any assumed aspects of solutions. The data-supported aspects of solutions can be tracked conservatively as the sum of the minimum source contributions, SMIN, and for the many cases where SMIN is low, additional ways to approach mixing problems are summarized from the published literature. Many underdetermined mixing problems do not have robust mean solutions with tracers employed thus far, so that there is a longerterm need for additional tracers and methodologies to really solve these complex ecological problems. This review concludes with several practical steps one can take to interpret isotope tracer information from underdetermined systems. © Inter-Research 2013.

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