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Institution

La Trobe University

EducationMelbourne, Victoria, Australia
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.


Papers
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Journal ArticleDOI
TL;DR: MSC-sEVs should be defined by quantifiable metrics to identify the cellular origin of the sEVs in a preparation, presence of lipid-membrane vesicles, and the degree of physical and biochemical integrity of the vesicle.
Abstract: Small extracellular vesicles (sEVs) from mesenchymal stromal/stem cells (MSCs) are transiting rapidly towards clinical applications. However, discrepancies and controversies about the biology, functions, and potency of MSC-sEVs have arisen due to several factors: the diversity of MSCs and their preparation; various methods of sEV production and separation; a lack of standardized quality assurance assays; and limited reproducibility of in vitro and in vivo functional assays. To address these issues, members of four societies (SOCRATES, ISEV, ISCT and ISBT) propose specific harmonization criteria for MSC-sEVs to facilitate data sharing and comparison, which should help to advance the field towards clinical applications. Specifically, MSC-sEVs should be defined by quantifiable metrics to identify the cellular origin of the sEVs in a preparation, presence of lipid-membrane vesicles, and the degree of physical and biochemical integrity of the vesicles. For practical purposes, new MSC-sEV preparations might also be measured against a well-characterized MSC-sEV biological reference. The ultimate goal of developing these metrics is to map aspects of MSC-sEV biology and therapeutic potency onto quantifiable features of each preparation.

342 citations

Journal ArticleDOI
TL;DR: The Doha agreement meeting on terminology and definitions in groin pain in athletes reached a consensus on a clinically based taxonomy using three major categories based on history and physical examination to categorise athletes, making it simple and suitable for both clinical practice and research.
Abstract: Background Heterogeneous taxonomy of groin injuries in athletes adds confusion to this complicated area. Aim The ‘Doha agreement meeting on terminology and definitions in groin pain in athletes’ was convened to attempt to resolve this problem. Our aim was to agree on a standard terminology, along with accompanying definitions. Methods A one-day agreement meeting was held on 4 November 2014. Twenty-four international experts from 14 different countries participated. Systematic reviews were performed to give an up-to-date synthesis of the current evidence on major topics concerning groin pain in athletes. All members participated in a Delphi questionnaire prior to the meeting. Results Unanimous agreement was reached on the following terminology. The classification system has three major subheadings of groin pain in athletes: 1. Defined clinical entities for groin pain: Adductor-related, iliopsoas-related, inguinal-related and pubic-related groin pain. 2. Hip-related groin pain. 3. Other causes of groin pain in athletes. The definitions are included in this paper. Conclusions The Doha agreement meeting on terminology and definitions in groin pain in athletes reached a consensus on a clinically based taxonomy using three major categories. These definitions and terminology are based on history and physical examination to categorise athletes, making it simple and suitable for both clinical practice and research.

342 citations

Journal ArticleDOI
TL;DR: There is a need for further investigation of the causes of vocal dysfunction in teachers and for the development of educational programs aimed at preventing voice problems in this group of professional voice users.

342 citations

Journal ArticleDOI
TL;DR: This survey evaluated the techniques of deep learning in developing SDN-based Network Intrusion Detection Systems (NIDS) and covered tools that can be used to develop NIDS models in SDN environment.
Abstract: Software Defined Networking Technology (SDN) provides a prospect to effectively detect and monitor network security problems ascribing to the emergence of the programmable features. Recently, Machine Learning (ML) approaches have been implemented in the SDN-based Network Intrusion Detection Systems (NIDS) to protect computer networks and to overcome network security issues. A stream of advanced machine learning approaches – the deep learning technology (DL) commences to emerge in the SDN context. In this survey, we reviewed various recent works on machine learning (ML) methods that leverage SDN to implement NIDS. More specifically, we evaluated the techniques of deep learning in developing SDN-based NIDS. In the meantime, in this survey, we covered tools that can be used to develop NIDS models in SDN environment. This survey is concluded with a discussion of ongoing challenges in implementing NIDS using ML/DL and future works.

341 citations

Journal ArticleDOI
10 Jan 2013-Nature
TL;DR: The first view, to the authors' knowledge, of the interaction of insulin with its primary binding site on the insulin receptor is presented, on the basis of four crystal structures of insulin bound to truncated insulin receptor constructs, providing an explanation for a wealth of biochemical data from the insulin receptors and IGF1R systems relevant to the design of therapeutic insulin analogues.
Abstract: Insulin receptor signalling has a central role in mammalian biology, regulating cellular metabolism, growth, division, differentiation and survival. Insulin resistance contributes to the pathogenesis of type 2 diabetes mellitus and the onset of Alzheimer's disease; aberrant signalling occurs in diverse cancers, exacerbated by cross-talk with the homologous type 1 insulin-like growth factor receptor (IGF1R). Despite more than three decades of investigation, the three-dimensional structure of the insulin-insulin receptor complex has proved elusive, confounded by the complexity of producing the receptor protein. Here we present the first view, to our knowledge, of the interaction of insulin with its primary binding site on the insulin receptor, on the basis of four crystal structures of insulin bound to truncated insulin receptor constructs. The direct interaction of insulin with the first leucine-rich-repeat domain (L1) of insulin receptor is seen to be sparse, the hormone instead engaging the insulin receptor carboxy-terminal α-chain (αCT) segment, which is itself remodelled on the face of L1 upon insulin binding. Contact between insulin and L1 is restricted to insulin B-chain residues. The αCT segment displaces the B-chain C-terminal β-strand away from the hormone core, revealing the mechanism of a long-proposed conformational switch in insulin upon receptor engagement. This mode of hormone-receptor recognition is novel within the broader family of receptor tyrosine kinases. We support these findings by photo-crosslinking data that place the suggested interactions into the context of the holoreceptor and by isothermal titration calorimetry data that dissect the hormone-insulin receptor interface. Together, our findings provide an explanation for a wealth of biochemical data from the insulin receptor and IGF1R systems relevant to the design of therapeutic insulin analogues.

340 citations


Authors

Showing all 13601 results

NameH-indexPapersCitations
Rasmus Nielsen13555684898
C. N. R. Rao133164686718
James Whelan12878689180
Jacqueline Batley119121268752
Eske Willerslev11536743039
Jonathan E. Shaw114629108114
Ary A. Hoffmann11390755354
Mike Clarke1131037164328
Richard J. Simpson11385059378
Alan F. Cowman11137938240
David C. Page11050944119
Richard Gray10980878580
David S. Wishart10852376652
Alan G. Marshall107106046904
David A. Williams10663342058
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023102
2022398
20213,407
20202,992
20192,661
20182,394