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Institution

University of Queensland

EducationBrisbane, Queensland, Australia
About: University of Queensland is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 51138 authors who have published 155721 publications receiving 5717659 citations. The organization is also known as: UQ & The University of Queensland.


Papers
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Journal ArticleDOI
TL;DR: The state-of-the-art progress of this dynamically developed material family of 2D-GAs with a particular focus on biomedical applications is summarized and some critical unresolved issues, possible challenges/obstacles are summarized.
Abstract: The increasing demand of clinical biomedicine and fast development of nanobiotechnology has substantially promoted the generation of a variety of organic/inorganic nanosystems for biomedical applications. Biocompatible two-dimensional (2D) graphene analogues (e.g., nanosheets of transition metal dichalcogenides, transition metal oxides, g-C3N4, Bi2Se3, BN, etc.), which are referred to as 2D-GAs, have emerged as a new unique family of nanomaterials that show unprecedented advantages and superior performances in biomedicine due to their unique compositional, structural and physicochemical features. In this review, we summarize the state-of-the-art progress of this dynamically developed material family with a particular focus on biomedical applications. After the introduction, the second section of the article summarizes a range of synthetic methods for new types of 2D-GAs as well as their surface functionalization. The subsequent section provides a snapshot on the use of these biocompatible 2D-GAs for a broad spectrum of biomedical applications, including therapeutic (photothermal/photodynamic therapy, chemotherapy and synergistic therapy), diagnostic (fluorescent/magnetic resonance/computed tomography/photoacoustic imaging) and theranostic (concurrent diagnostic imaging and therapy) applications, especially on oncology. In addition, we briefly present the biosensing applications of these 2D-GAs for the detection of biomacromolecules and their in vitro/in vivo biosafety evaluations. The last section summarizes some critical unresolved issues, possible challenges/obstacles and also proposes future perspectives related to the rational design and construction of 2D-GAs for biomedical engineering, which are believed to promote their clinical translations for benefiting the personalized medicine and human health.

750 citations

Journal ArticleDOI
TL;DR: It is reported that Cu(II) markedly potentiates the neurotoxicity exhibited by Abeta in cell culture, suggesting that certain redox active metal ions may be important in exacerbating and perhaps facilitating Abeta-mediated oxidative damage in Alzheimer's disease.

750 citations

Journal ArticleDOI
TL;DR: It is demonstrated using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation, and evidence that height- and BMI-associated variants have been under natural selection is found.
Abstract: We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.

748 citations

Journal ArticleDOI
TL;DR: It is found that an inner-plasma membrane lipid raft marker displays cholesterol-dependent clustering in microdomains with a mean diameter of 44 nm that occupy 35% of the cell surface, illustrating that the inner plasma membrane comprises a complex mosaic of discrete micro domains.
Abstract: Localization of signaling complexes to specific microdomains coordinates signal transduction at the plasma membrane Using immunogold electron microscopy of plasma membrane sheets coupled with spatial point pattern analysis, we have visualized morphologically featureless microdomains, including lipid rafts, in situ and at high resolution We find that an inner-plasma membrane lipid raft marker displays cholesterol-dependent clustering in microdomains with a mean diameter of 44 nm that occupy 35% of the cell surface Cross-linking an outer-leaflet raft protein results in the redistribution of inner leaflet rafts, but they retain their modular structure Analysis of Ras microlocalization shows that inactive H-ras is distributed between lipid rafts and a cholesterol-independent microdomain Conversely, activated H-ras and K-ras reside predominantly in nonoverlapping, cholesterol-independent microdomains Galectin-1 stabilizes the association of activated H-ras with these nonraft microdomains, whereas K-ras clustering is supported by farnesylation, but not geranylgeranylation These results illustrate that the inner plasma membrane comprises a complex mosaic of discrete microdomains Differential spatial localization within this framework can likely account for the distinct signal outputs from the highly homologous Ras proteins

747 citations

Journal ArticleDOI
TL;DR: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list as mentioned in this paper.
Abstract: Background: To comprehend the results of diagnostic accuracy studies, readers must understand the design, conduct, analysis, and results of such studies. That goal can be achieved only through complete transparency from authors. Objective: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy to allow readers to assess the potential for bias in the study and to evaluate its generalisability. Methods: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a two-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. Results: The search for published guidelines on diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. The consensus meeting shortened the list to 25 items, using evidence on bias whenever available. A prototypical flow diagram provides information about the method of patient recruitment, the order of test execution and the numbers of patients undergoing the test under evaluation, the reference standard or both. Conclusions: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.

746 citations


Authors

Showing all 52145 results

NameH-indexPapersCitations
Graham A. Colditz2611542256034
George Davey Smith2242540248373
David J. Hunter2131836207050
Daniel Levy212933194778
Christopher J L Murray209754310329
Matthew Meyerson194553243726
Luigi Ferrucci1931601181199
Nicholas G. Martin1921770161952
Paul M. Thompson1832271146736
Jie Zhang1784857221720
Alan D. Lopez172863259291
Ian J. Deary1661795114161
Steven N. Blair165879132929
Carlos Bustamante161770106053
David W. Johnson1602714140778
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023507
20221,728
202111,678
202010,832
20199,671
20189,015