scispace - formally typeset
Search or ask a question
Institution

University of Exeter

EducationExeter, United Kingdom
About: University of Exeter is a education organization based out in Exeter, United Kingdom. It is known for research contribution in the topics: Population & Climate change. The organization has 15820 authors who have published 50650 publications receiving 1793046 citations. The organization is also known as: Exeter University & University of the South West of England.


Papers
More filters
Journal ArticleDOI
14 Aug 2003-Nature
TL;DR: By altering the structure of a metal's surface, the properties of surface plasmons—in particular their interaction with light—can be tailored, which could lead to miniaturized photonic circuits with length scales that are much smaller than those currently achieved.
Abstract: Surface plasmons are waves that propagate along the surface of a conductor. By altering the structure of a metal's surface, the properties of surface plasmons--in particular their interaction with light--can be tailored, which offers the potential for developing new types of photonic device. This could lead to miniaturized photonic circuits with length scales that are much smaller than those currently achieved. Surface plasmons are being explored for their potential in subwavelength optics, data storage, light generation, microscopy and bio-photonics.

10,689 citations

Journal ArticleDOI
Theo Vos1, Theo Vos2, Theo Vos3, Stephen S Lim  +2416 moreInstitutions (246)
TL;DR: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates, and there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries.

5,802 citations

Journal ArticleDOI
TL;DR: Three broad categories of naturalistic sampling are described: convenience, judgement and theoretical models, which are illustrated with practical examples from the author's own research.
Abstract: The probability sampling techniques used for quantitative studies are rarely appropriate when conducting qualitative research. This article considers and explains the differences between the two approaches and describes three broad categories of naturalistic sampling: convenience, judgement and theoretical models. The principles are illustrated with practical examples from the author's own research.

5,299 citations

Journal ArticleDOI
Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

5,187 citations

Journal ArticleDOI
TL;DR: “BCT taxonomy v1,” an extensive taxonomy of 93 consensually agreed, distinct BCTs, offers a step change as a method for specifying interventions, but the authors anticipate further development and evaluation based on international, interdisciplinary consensus.
Abstract: CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of interventions with precision and specificity. The objective of this study is to develop an extensive, consensually agreed hierarchically structured taxonomy of techniques [behavior change techniques (BCTs)] used in behavior change interventions. In a Delphi-type exercise, 14 experts rated labels and definitions of 124 BCTs from six published classification systems. Another 18 experts grouped BCTs according to similarity of active ingredients in an open-sort task. Inter-rater agreement amongst six researchers coding 85 intervention descriptions by BCTs was assessed. This resulted in 93 BCTs clustered into 16 groups. Of the 26 BCTs occurring at least five times, 23 had adjusted kappas of 0.60 or above. “BCT taxonomy v1,” an extensive taxonomy of 93 consensually agreed, distinct BCTs, offers a step change as a method for specifying interventions, but we anticipate further development and evaluation based on international, interdisciplinary consensus.

4,568 citations


Authors

Showing all 16338 results

NameH-indexPapersCitations
Clive Ballard11773661663
David Harvey11573894678
Kevin C. Jones11474450207
Inês Barroso11330176241
Robert West112106153904
Austin Smith11130163156
Adam J. Burgasser11061542833
Alan Campbell10968753463
Richard J. Hobbs10859268141
John Campbell107115056067
Paul W. Franks10550652068
Pierre Friedlingstein10528569536
Paul Dieppe10561853529
Rod S Taylor10452439332
Andrew M. Jones10376437253
Network Information
Related Institutions (5)
University of Birmingham
115.3K papers, 4.3M citations

96% related

University of Manchester
168K papers, 6.4M citations

96% related

University of Oxford
258.1K papers, 12.9M citations

95% related

University of Bristol
113.1K papers, 4.9M citations

95% related

University College London
210.6K papers, 9.8M citations

95% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023295
2022782
20214,412
20204,192
20193,721
20183,385