Disability and physical activity behaviours : an application of theoretical frameworks

Background: The prevalence of disability increases with age; therefore with an aging population, interventions to reduce disability are crucial. This thesis adopts a behavioural conceptualisation of disability. The theoretical frameworks of the International Classification of Functioning, Disability and Health (ICF), the Theory of Planned Behaviour (TPB) and the integrated ICF/TPB model are applied to investigate disability and physical activity (PA) behaviours. The thesis aims to: (1) identify the factors involved in the prioritisation of patients for total joint replacement; (2) classify patient pre-operative expectations of total hip replacement (THR) and investigate the relationship between expectations and recovery after surgery, and; (3) test whether the TPB and theory-based interventions can predict and explain PA within individuals. Method: Five studies were conducted. In the first study, health professionals judged whether the items from two prioritisation tools measured each of the ICF constructs. In the second study, surgeons ranked patient vignettes, which differed by constructs from the integrated model, in order of priority for THR. In the third study, a large cohort of THR patients reported expectations of surgery pre-operatively. Health and functioning were also reported pre-operatively and 1-year post-operatively. The fourth and fifth studies were a series of experimental n-of-1 studies using diary methods assessing TPB cognitions and PA behaviours. Results: There is a lack of agreement between judges in relation to the content of many of the items from prioritisation tools. Behavioural and psychological factors can influence prioritisation for THR. The majority of patient expectations of THR addressed activities and social participation; however, the evidence for a relationship between expectations and recovery was limited. The TPB can predict PA within some individuals but the evidence in support of interventions to increase PA was limited. Discussion: The findings provide important clinical and theoretical implications for understanding disability and physical activity behaviours.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

High-Throughput Single-Cell Transcriptome Profiling of Plant Cell Types

Summary: Single-cell transcriptome profiling of heterogeneous tissues can provide high-resolution windows into developmental dynamics and environmental responses, but its application to plants has been limited. Here, we used the high-throughput Drop-seq approach to profile >12,000 cells from Arabidopsis roots. This identified numerous distinct cell types, covering all major root tissues and developmental stages, and illuminated specific marker genes for these populations. In addition, we demonstrate the utility of this approach to study the impact of environmental conditions on developmental processes. Analysis of roots grown with or without sucrose supplementation uncovers changes in the relative frequencies of cell types in response to sucrose. Finally, we characterize the transcriptome changes that occur across endodermis development and identify nearly 800 genes with dynamic expression as this tissue differentiates. Collectively, we demonstrate that single-cell RNA-seq can be used to profile developmental processes in plants and show how they can be altered by external stimuli. : The application of single-cell transcriptome profiling to plants has been limited. Shulse et al. performed Drop-seq on Arabidopsis roots, generating a transcriptional resource for >12,000 cells across major populations. This revealed marker genes for distinct cell types, cell frequency changes resulting from sucrose addition, and genes dynamically regulated during development. Keywords: single-cell RNA-seq, plant, root, Arabidopsis, transcriptomics, endodermis, development, sucros

High-Throughput Single-Cell Transcriptome Profiling of Plant Cell Types.

Single-cell transcriptome profiling of heterogeneous tissues can provide high-resolution windows into developmental dynamics and environmental responses, but its application to plants has been limited. Here, we used the high-throughput Drop-seq approach to profile &gt;12,000 cells from Arabidopsis roots. This identified numerous distinct cell types, covering all major root tissues and developmental stages, and illuminated specific marker genes for these populations. In addition, we demonstrate the utility of this approach to study the impact of environmental conditions on developmental processes. Analysis of roots grown with or without sucrose supplementation uncovers changes in the relative frequencies of cell types in response to sucrose. Finally, we characterize the transcriptome changes that occur across endodermis development and identify nearly 800 genes with dynamic expression as this tissue differentiates. Collectively, we demonstrate that single-cell RNA-seq can be used to profile developmental processes in plants and show how they can be altered by external stimuli

Plant single-cell solutions for energy and the environment.

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species' cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward

Plant single-cell solutions for energy and the environment.

Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species' cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward