ORCID Profile
0000-0002-2826-6367
Current Organisations
University of South Australia
,
University of Sydney
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Publisher: Institution of Engineering and Technology (IET)
Date: 08-2014
DOI: 10.1049/EL.2014.2294
Publisher: MDPI AG
Date: 04-04-2019
DOI: 10.3390/C5020017
Abstract: Advances in wearable, highly sensitive and multifunctional strain sensors open up new opportunities for the development of wearable human interface devices for various applications such as health monitoring, smart robotics and wearable therapy. Herein, we present a simple and cost-effective method to fabricate a multifunctional strain sensor consisting of a skin-mountable dry adhesive substrate, a robust sensing component and a transdermal drug delivery system. The sensor has high piezoresisitivity to monitor real-time signals from finger bending to ulnar pulse. A transdermal drug delivery system consisting of polylactic-co-glycolic acid nanoparticles and a chitosan matrix is integrated into the sensor and is able to release the nanoparticles into the stratum corneum at a depth of ~60 µm. Our approach to the design of multifunctional strain sensors will lead to the development of cost-effective and well-integrated multifunctional wearable devices.
Publisher: Cold Spring Harbor Laboratory
Date: 07-06-2023
DOI: 10.1101/2023.06.07.544051
Abstract: The Parkinson’s VPS35[D620N] mutation causes lysosome dysfunction enhancing LRRK2 kinase activity. We find the VPS35[D620N] mutation alters expression of ∼350 lysosomal proteins and stimulates LRRK2 phosphorylation of Rab proteins at the lysosome. This recruits the phosphoRab effector protein RILPL1 to the lysosome where it binds to the lysosomal integral membrane protein TMEM55B. We identify highly conserved regions of RILPL1 and TMEM55B that interact and design mutations that block binding. In mouse fibroblasts, brain, and lung, we demonstrate that the VPS35 [D620N] mutation reduces RILPL1 levels, in a manner reversed by LRRK2 inhibition. Knock-out of RILPL1 enhances phosphorylation of Rab substrates and knock-out of TMEM55B increases RILPL1 levels. The lysosomotropic agent LLOMe, also induced LRRK2 kinase mediated association of RILPL1 to the lysosome, but to a lower extent than the D620N mutation. Our study uncovers a pathway through which dysfunctional lysosomes resulting from the VPS35[D620N] mutation recruit and activate LRRK2 on the lysosomal surface, driving assembly of the RILPL1-TMEM55B complex. Our analysis identified a pathway involving LRRK2, pRabs, RILPL1 and TMEM55B implicated in Parkinson’s Lysosomal dysfunction.
Publisher: IEEE
Date: 12-2015
Publisher: Elsevier BV
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
Publisher: IEEE
Date: 06-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 17-01-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: MDPI AG
Date: 24-08-2020
DOI: 10.3390/JOF6030145
Abstract: Plant defensins are best known for their antifungal activity and contribution to the plant immune system. The defining feature of plant defensins is their three-dimensional structure known as the cysteine stabilized alpha-beta motif. This protein fold is remarkably tolerant to sequence variation with only the eight cysteines that contribute to the stabilizing disulfide bonds absolutely conserved across the family. Mature defensins are typically 46–50 amino acids in length and are enriched in lysine and/or arginine residues. Examination of a database of approximately 1200 defensin sequences revealed a subset of defensin sequences that were extended in length and were enriched in histidine residues leading to their classification as histidine-rich defensins (HRDs). Using these initial HRD sequences as a query, a search of the available sequence databases identified over 750 HRDs in solanaceous plants and 20 in brassicas. Histidine residues are known to contribute to metal binding functions in proteins leading to the hypothesis that HRDs would have metal binding properties. A selection of the HRD sequences were recombinantly expressed and purified and their antifungal and metal binding activity was characterized. Of the four HRDs that were successfully expressed all displayed some level of metal binding and two of four had antifungal activity. Structural characterization of the other HRDs identified a novel pattern of disulfide linkages in one of the HRDs that is predicted to also occur in HRDs with similar cysteine spacing. Metal binding by HRDs represents a specialization of the plant defensin fold outside of antifungal activity.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2016
Publisher: Elsevier BV
Date: 05-2013
DOI: 10.1016/J.BIOTECHADV.2011.12.001
Abstract: Complete profiling would substantially facilitate the fundamental understanding of tumor angiogenesis and of possible anti-angiogenesis cancer treatments. We developed an integrated synchrotron-based methodology with excellent performances: detection of very small vessels by high spatial resolution (~1 μm) and nanoparticle contrast enhancement, in vivo dynamics investigations with high temporal resolution (~1 ms), and three-dimensional quantitative morphology parametrization by computer tracing. The smallest (3-10 μm) microvessels were found to constitute >80% of the tumor vasculature and exhibit many structural anomalies. Practical applications are presented, including vessel microanalysis in xenografted tumors, monitoring the effects of anti-angiogenetic agents and in vivo detection of tumor vascular rheological properties.
Publisher: Springer Science and Business Media LLC
Date: 20-07-2011
Publisher: ACM
Date: 11-12-2011
Publisher: IEEE
Date: 11-2018
Publisher: ACM
Date: 21-08-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2017
Publisher: IEEE
Date: 09-2015
Publisher: Elsevier BV
Date: 07-2022
Publisher: Springer Science and Business Media LLC
Date: 2008
DOI: 10.1155/2008/380867
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 07-2016
Publisher: Public Library of Science (PLoS)
Date: 29-03-2018
Publisher: IEEE
Date: 07-2015
Publisher: Elsevier BV
Date: 10-2023
Publisher: Springer Science and Business Media LLC
Date: 08-11-2022
DOI: 10.1038/S41421-022-00479-Y
Abstract: Medullary thyroid carcinoma (MTC) is a rare neuroendocrine malignancy derived from parafollicular cells (C cells) of the thyroid. Here we presented a comprehensive multi-omics landscape of 102 MTCs through whole-exome sequencing, RNA sequencing, DNA methylation array, proteomic and phosphoproteomic profiling. Integrated analyses identified BRAF and NF1 as novel driver genes in addition to the well-characterized RET and RAS proto-oncogenes. Proteome-based stratification of MTCs revealed three molecularly heterogeneous subtypes named as: (1) Metabolic, (2) Basal and (3) Mesenchymal, which are distinct in genetic drivers, epigenetic modification profiles, clinicopathologic factors and clinical outcomes. Furthermore, we explored putative therapeutic targets of each proteomic subtype, and found that two tenascin family members TNC/TNXB might serve as potential prognostic biomarkers for MTC. Collectively, our study expands the knowledge of MTC biology and therapeutic vulnerabilities, which may serve as an important resource for future investigation on this malignancy.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2012
Publisher: MDPI AG
Date: 25-06-2017
DOI: 10.3390/INFO8030073
Publisher: Springer London
Date: 2009
Publisher: BMJ
Date: 18-10-2019
DOI: 10.1136/BMJQS-2018-007988
Abstract: The Primary Care Patient Measure of Safety (PC PMOS) is designed to capture patient feedback about the contributing factors to patient safety incidents in primary care. It required further reliability and validity testing to produce a robust tool intended to improve safety in practice. 490 adult patients in nine primary care practices in Greater Manchester, UK, completed the PC PMOS. Practice staff (n = 81) completed a survey on patient safety culture to assess convergent validity. Confirmatory factor analysis (CFA) assessed the construct validity and internal reliability of the PC PMOS domains and items. A multivariate analysis of variance was conducted to assess discriminant validity, and Spearman correlation was conducted to establish test–retest reliability. Initial CFA results showed data did not fit the model well (a chi-square to df ratio (CMIN/DF) = 5.68 goodness-of-fit index (GFI) = 0.61, CFI = 0.57, SRMR = 0.13 and root mean square error of approximation (RMSEA) = 0.10). On the basis of large modification indices ( ), standardised residuals ± 2.58 and assessment of item content 22 items were removed. This revised nine-factor model (28 items) was found to fit the data satisfactorily (CMIN/DF = 2.51 GFI = 0.87, CFI = 0.91, SRMR = 0.04 and RMSEA = 0.05). New factors demonstrated good internal reliability with average inter-item correlations ranging from 0.20 to 0.70. The PC PMOS demonstrated good discriminant validity between primary care practices (F = 2.64, df = 72, p 0.001) and showed some association with practice staff safety score (convergent validity) but failed to reach statistical significance (r = −0.64, k = 9, p = 0.06). This study led to a reliable and valid 28-item PC PMOS. It could enhance or complement current data collection methods used in primary care to identify and prevent error.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2017
Publisher: Elsevier BV
Date: 11-2019
Publisher: Springer Science and Business Media LLC
Date: 06-09-2022
DOI: 10.1038/S41421-022-00442-X
Abstract: Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue s les from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.
Publisher: Elsevier BV
Date: 11-2019
Publisher: Cold Spring Harbor Laboratory
Date: 07-04-2020
DOI: 10.1101/2020.04.07.20054585
Abstract: Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control in iduals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: Oxford University Press (OUP)
Date: 11-2020
DOI: 10.1093/EURHEARTJ/SUAA166
Abstract: Atrial fibrillation (AF) and stroke are inextricably connected, with classical Virchow pathophysiology explaining thromboembolism through blood stasis in the fibrillating left atrium. This conceptualization has been reinforced by the remarkable efficacy of oral anticoagulant (OAC) for stroke prevention in AF. A number of observations showing that the presence of AF is neither necessary nor sufficient for stroke, cast doubt on the causal role of AF as a villain in vascular brain injury (VBI). The requirement for additional risk factors before AF increases stroke risk temporal disconnect of AF from a stroke in patients with no AF for months before stroke during continuous ECG monitoring but manifesting AF only after stroke and increasing recognition of the role of atrial cardiomyopathy and atrial substrate in AF-related stroke, and also stroke without AF, have led to rethinking the pathogenetic model of cardioembolic stroke. This is quite separate from recognition that in AF, shared cardiovascular risk factors can lead both to non-embolic stroke, or emboli from the aorta and carotid arteries. Meanwhile, VBI is now expanded to include dementia and cognitive decline: research is required to see if reduced by OAC. A changed conceptual model with less focus on the arrhythmia, and more on atrial substrate/cardiomyopathy causing VBI both in the presence or absence of AF, is required to allow us to better prevent AF-related VBI. It could direct focus towards prevention of the atrial cardiomyopathy though much work is required to better define this entity before the balance between AF as villain or bystander can be determined.
Publisher: Informa UK Limited
Date: 16-03-2018
Publisher: Akademiai Kiado Zrt.
Date: 05-10-2023
Publisher: MDPI AG
Date: 22-10-2018
DOI: 10.3390/MOLECULES23102715
Abstract: μ-Conotoxins are potent and highly specific peptide blockers of voltage-gated sodium channels. In this study, the solution structure of μ-conotoxin GIIIC was determined using 2D NMR spectroscopy and simulated annealing calculations. Despite high sequence similarity, GIIIC adopts a three-dimensional structure that differs from the previously observed conformation of μ-conotoxins GIIIA and GIIIB due to the presence of a bulky, non-polar leucine residue at position 18. The side chain of L18 is oriented towards the core of the molecule and consequently the N-terminus is re-modeled and located closer to L18. The functional characterization of GIIIC defines it as a canonical μ-conotoxin that displays substantial selectivity towards skeletal muscle sodium channels (NaV), albeit with ~2.5-fold lower potency than GIIIA. GIIIC exhibited a lower potency of inhibition of NaV1.4 channels, but the same NaV selectivity profile when compared to GIIIA. These observations suggest that single amino acid differences that significantly affect the structure of the peptide do in fact alter its functional properties. Our work highlights the importance of structural factors, beyond the disulfide pattern and electrostatic interactions, in the understanding of the functional properties of bioactive peptides. The latter thus needs to be considered when designing analogues for further applications.
Publisher: IEEE
Date: 12-2009
Publisher: IEEE
Date: 10-2005
Publisher: No publisher found
Date: 2009
Publisher: IEEE
Date: 10-2019
Publisher: Springer Berlin Heidelberg
Date: 2005
Publisher: IEEE
Date: 12-2009
Publisher: The Optical Society
Date: 27-09-2011
DOI: 10.1364/OE.19.019919
Publisher: ACM Press
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: IEEE
Date: 07-2006
Publisher: IEEE
Date: 2003
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Wiley
Date: 18-05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2009
Publisher: SAGE Publications
Date: 02-2014
DOI: 10.1155/2014/735674
Publisher: IEEE
Date: 08-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2017
Publisher: Public Library of Science (PLoS)
Date: 18-12-2018
Publisher: Springer Science and Business Media LLC
Date: 05-08-2009
Publisher: Elsevier BV
Date: 02-2019
Publisher: Institution of Engineering and Technology (IET)
Date: 11-2014
DOI: 10.1049/EL.2014.2651
Publisher: IEEE
Date: 10-2008
DOI: 10.1109/UMC.2008.30
Publisher: Institute of Electronics, Information and Communications Engineers (IEICE)
Date: 2015
Publisher: Elsevier BV
Date: 02-2022
Publisher: Wiley
Date: 08-2021
Abstract: Cereal grains and nuts are represented as the economic backbone of many developed and developing countries. Kernels of cereal grains and nuts are prone to mold infection under high relative humidity and suitable temperature conditions in the field as well as storage conditions. Health risks caused by molds and their molecular metabolite mycotoxins are, therefore, important topics to investigate. Strict regulations have been developed by international trade regulatory bodies for the detection of mold growth and mycotoxin contamination across the food chain starting from the harvest to storage and consumption. Molds and aflatoxins are not evenly distributed over the bulk of grains, thus appropriate s ling for detection and quantification is crucial. Existing reference methods for mold and mycotoxin detection are destructive in nature as well as involve skilled labor and hazardous chemicals. Also, these methods cannot be used for inline sorting of the infected kernels. Thus, analytical methods have been extensively researched to develop the one that is more practical to be used in commercial detection and sorting processes. Among various analytical techniques, optical imaging and spectroscopic techniques are attracting growers’ attention for their potential of nondestructive and rapid inline identification and quantification of molds and mycotoxins in various food products. This review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X‐ray imaging, near‐infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging. Advance chemometric techniques to identify very low‐level mold growth and mycotoxin contamination are also discussed. Benefits, limitations, and challenges of deploying these techniques in practice are also presented in this paper.
Publisher: The Eurographics Association
Date: 2014
DOI: 10.2312/PGS.20141251
Publisher: Institute of Electronics, Information and Communications Engineers (IEICE)
Date: 2015
Publisher: American Chemical Society (ACS)
Date: 05-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Elsevier BV
Date: 11-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: Public Library of Science (PLoS)
Date: 12-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: IEEE
Date: 12-2010
Publisher: IEEE
Date: 11-2010
Publisher: ACM
Date: 03-07-2014
Publisher: Elsevier BV
Date: 05-2017
Publisher: IEEE
Date: 03-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2016
Publisher: Association for Computing Machinery (ACM)
Date: 16-02-2023
DOI: 10.1145/3570906
Abstract: Anomaly analytics is a popular and vital task in various research contexts that has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks, like node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories based on their model architectures, namely graph convolutional network, graph attention network, graph autoencoder, and other graph learning models. The differences between these methods are also compared in a systematic manner. Furthermore, we outline several graph-based anomaly analytics applications across various domains in the real world. Finally, we discuss five potential future research directions in this rapidly growing field.
Publisher: IEEE
Date: 10-2006
Publisher: Public Library of Science (PLoS)
Date: 08-09-2016
Publisher: Springer International Publishing
Date: 2014
Publisher: Springer New York
Date: 2011
Publisher: IEEE
Date: 07-2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 11-2013
Publisher: ACM
Date: 10-07-2016
Publisher: Springer Science and Business Media LLC
Date: 15-12-2018
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Wiley
Date: 27-03-2015
DOI: 10.1002/ASI.23319
Publisher: Springer Science and Business Media LLC
Date: 21-10-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: American Chemical Society (ACS)
Date: 02-11-2018
DOI: 10.1021/ACS.JNATPROD.8B00572
Abstract: Cyclotides are macrocyclic cystine-knotted peptides most commonly found in the Violaceae plant family. Although Rinorea is the second-largest genera within the Violaceae family, few studies have examined whether or not they contain cyclotides. To further our understanding of cyclotide ersity and evolution, we examined the cyclotide content of two Rinorea species found in Southeast Asia: R. virgata and R. bengalensis. Seven cyclotides were isolated from R. virgata (named Rivi1-7), and a known cyclotide (cT10) was found in R. bengalensis. Loops 2, 5, and 6 of Rivi1-4 contained sequences not previously seen in corresponding loops of known cyclotides, thereby expanding our understanding of the ersity of cyclotides. In addition, the sequence of loop 2 of Rivi3 and Rivi4 were identical to some related noncyclic "acyclotides" from the Poaceae plant family. As only acyclotides, but not cyclotides, have been reported in monocotyledons thus far, our findings support an evolutionary link between monocotyledon-derived ancestral cyclotide precursors and dicotyledon-derived cyclotides. Furthermore, Rivi2 and Rivi3 had comparable cytotoxic activities to the most cytotoxic cyclotide known to date: cycloviolacin O2 from Viola odorata yet, unlike cycloviolacin O2, they did not show hemolytic activity. Therefore, these cyclotides represent novel scaffolds for use in future anticancer drug design.
Publisher: Springer Science and Business Media LLC
Date: 20-10-2011
Publisher: Springer London
Date: 2009
Publisher: Inderscience Publishers
Date: 2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2009
Publisher: Hindawi Limited
Date: 2012
DOI: 10.1155/2012/238460
Publisher: IEEE
Date: 10-2010
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 08-2015
Publisher: American Chemical Society (ACS)
Date: 08-06-2010
DOI: 10.1021/LA101253G
Abstract: We demonstrate the application of time-of-flight secondary ion mass spectrometry (TOF-SIMS) in conjunction with multivariate statistics to differentiate trace levels of denatured proteins in adsorbed monolayers specifically, human serum albumin (HSA) on oxidized silicon substrates. Subtle differences in protein conformation due to thermal denaturation of HSA, unable to be determined by dynamic light scattering nor circular dichroism, were differentiated by TOF-SIMS. The fragmentation pattern is highly sensitive to protein conformation, allowing assessment of relative amounts of proteins in mixtures and quantifying amounts of denatured protein in a s le. Discussion is presented on ascribing orientation and conformational differences between s les based upon TOF-SIMS spectra. This has implications for detecting denatured protein in biotechnology and medical applications.
Publisher: The Optical Society
Date: 30-03-2011
DOI: 10.1364/OL.36.001269
Publisher: Wiley
Date: 18-02-2019
Publisher: IEEE
Date: 07-2009
Publisher: Wiley
Date: 14-09-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2021
Publisher: IEEE
Date: 10-2008
DOI: 10.1109/UMC.2008.19
Publisher: ACM
Date: 21-08-2012
Publisher: Elsevier BV
Date: 02-2019
Publisher: IEEE
Date: 2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Elsevier BV
Date: 09-2021
Publisher: Wiley
Date: 15-07-2018
DOI: 10.1111/JPC.14104
Abstract: Bronchiolitis is the most common lower respiratory tract disorder in infants aged less than 12 months, and research has demonstrated that there is substantial variation in practice patterns despite treatment being well defined. In order to align and improve the consistency of the management of bronchiolitis, an evidence-based guideline was developed for the Australasian population. The guideline development committee included representation from emergency and paediatric specialty medical and nursing personnel in addition to geographical representation across Australia and New Zealand - rural, remote and metropolitan. Formulation of the guideline included identification of population, intervention, comparator, outcomes and time questions and was associated with an extensive literature search from 2000 to 2015. Evidence was summarised and graded using the National Health and Medical Research Council and Grading of Recommendations Assessment, Development and Evaluation methodology, and consensus within the guideline group was sought using nominal group technique principles to formulate the clinical practice recommendations. The guideline was reviewed and endorsed by key paediatric health bodies. The guideline consists of a usable clinical interface for bedside functionality supported by evidence summary and tables. The Grading of Recommendations Assessment, Development and Evaluation and National Health and Medical Research Council processes provided a systematic and transparent process to review and assess the literature, resulting in a guideline that is relevant to the management of bronchiolitis in the Australasian setting. This is the first robust Australasian acute paediatric guideline and provides clear guidance for the management of the vast majority of patients seen in Australasian emergency departments and general paediatric wards with bronchiolitis.
Publisher: IEEE
Date: 11-2013
Publisher: IEEE
Date: 2005
Publisher: IEEE
Date: 09-2010
DOI: 10.1109/NSS.2010.48
Publisher: IEEE
Date: 10-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2009
Publisher: Cold Spring Harbor Laboratory
Date: 14-04-2020
DOI: 10.1101/2020.04.09.20059741
Abstract: Up to 30% of thyroid nodules cannot be accurately classified as benign or malignant by cytopathology. Diagnostic accuracy can be improved by nucleic acid-based testing, yet a sizeable number of diagnostic thyroidectomies remains unavoidable. In order to develop a protein classifier for thyroid nodules, we analyzed the quantitative proteomes of 1,725 retrospective thyroid tissue s les from 578 patients using pressure-cycling technology and data-independent acquisition mass spectrometry. With artificial neural networks, a classifier of 14 proteins achieved over 93% accuracy in classifying malignant thyroid nodules. This classifier was validated in retrospective s les of 271 patients (91% accuracy), and prospective s les of 62 patients (88% accuracy) from four independent centers. These rapidly acquired proteotypes and artificial neural networks supported the establishment of an effective protein classifier for classifying thyroid nodules.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: IEEE
Date: 10-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 30-11-2022
DOI: 10.1038/S41467-022-34824-2
Abstract: Spatially resolved proteomics is an emerging approach for mapping proteome heterogeneity of biological s les, however, it remains technically challenging due to the complexity of the tissue micros ling techniques and mass spectrometry analysis of nanoscale specimen volumes. Here, we describe a spatially resolved proteomics method based on the combination of tissue expansion with mass spectrometry-based proteomics, which we call Expansion Proteomics (ProteomEx). ProteomEx enables quantitative profiling of the spatial variability of the proteome in mammalian tissues at ~160 µm lateral resolution, equivalent to the tissue volume of 0.61 nL, using manual micros ling without the need for custom or special equipment. We validated and demonstrated the utility of ProteomEx for streamlined large-scale proteomics profiling of biological tissues including brain, liver, and breast cancer. We further applied ProteomEx for identifying proteins associated with Alzheimer’s disease in a mouse model by comparative proteomic analysis of brain subregions.
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Publisher: Springer Science and Business Media LLC
Date: 10-12-2018
Publisher: Springer International Publishing
Date: 2019
No related grants have been discovered for Ivan Lee.