Screening for pre-clinical disability in different residential settings

<p>Abstract</p> <p>Background</p> <p>Preventing disability and offering effective interventions to older people during early decline in function is most likely to be effective if those most at risk of progressive disablement are able to be identified. Similarly the ability to easily identify a group with similar functional profile from disparate sectors of the community is of significant benefit to researchers. This study aimed to (1) describe the use of a pre-clinical disability screening tool to select a functionally comparable group of older men and women with early functional limitation from different settings, and (2) explore factors associated with function and disability.</p> <p>Methods</p> <p>Self-reported function and disability measured with the Late-Life Function and Disability Instrument along with a range of physical performance measurements were compared across residential settings and gender in a sample of 471 trial participants identified as pre-clinically disabled after being screened with the Fried pre-clinical disability tool. Factors that might lie on the pathway to progressive disablement were identified using multiple linear regression analysis.</p> <p>Results</p> <p>We found that a sample population, screened for pre-clinical disability, had a functional status and disability profile reflecting early functional limitation, regardless of residential setting or gender. Statistical models identified a range of factors associated with function and disability which explained a greater degree of the variation in function, than disability.</p> <p>Conclusions</p> <p>We selected a group of people with a comparable function and disability profile, consistent with the pre-clinical stage of disability, from a sample of older Australian men and women from different residential settings using the Fried pre-clinical disability screening tool. The results suggest that the screening tool can be used with greater confidence for research, clinical and population health purposes. Further research is required to examine the validity of the tool. These findings offer insight into the type of impairment factors characterising early functional loss that could be addressed through disability prevention initiatives.</p> <p>Trial Registration</p> <p>ACTRN01206000431527</p

Detecting Radio AGN Signatures in Red Geysers

A new class of quiescent galaxies harboring possible AGN-driven winds has been discovered using spatially resolved optical spectroscopy from the ongoing SDSS-IV MaNGA survey. These galaxies, termed "red geysers", constitute 5−10% of the local quiescent population and are characterized by narrow bisymmetric patterns in ionized gas emission features. Cheung et al. argued that these galaxies host large-scale AGN-driven winds that may play a role in suppressing star formation at late times. In this work, we test the hypothesis that AGN activity is ultimately responsible for the red geyser phenomenon. We compare the nuclear radio activity of the red geysers to a matched control sample with similar stellar mass, redshift, rest frame NUV−r color, axis ratio and presence of ionized gas. We have used the 1.4 GHz radio continuum data from VLA FIRST survey to stack the radio flux from the red geyser and control samples. In addition to a 3 times higher FIRST detection rate, we find that red geysers have a 5σ higher level of average radio flux than control galaxies. After restricting to rest-frame NUV−r color > 5 and checking mid-IR WISE photometry, we rule out star formation contamination and conclude that red geysers are associated with more active AGN. Red geysers and a possibly-related class with disturbed Hα emission account for 40\% of all radio-detected red galaxies with log (M⋆/M⊙)<11. Our results support a picture in which episodic AGN activity drives large-scale-relatively weak ionized winds that may provide a feedback mechanism for many early-type galaxies

Time-resolved angiography with stochastic trajectories for dynamic contrast-enhanced MRI in head and neck cancer: Are pharmacokinetic parameters affected?

Purpose To investigate the effects of different time-resolved angiography with stochastic trajectories (TWIST) k-space undersampling schemes on calculated pharmacokinetic dynamic contrast-enhanced (DCE) vascular parameters.Methods A digital perfusion phantom was employed to simulate effects of TWIST on characteristics of signal changes in DCE. Furthermore, DCE-MRI was acquired without undersampling in a group of patients with head and neck squamous cell carcinoma and used to simulate a range of TWIST schemes. Errors were calculated as differences between reference and TWIST-simulated DCE parameters. Parametrical error maps were used to display the averaged results from all tumors.Results For a relatively wide range of undersampling schemes, errors in pharmacokinetic parameters due to TWIST were under 10% for the volume transfer constant, Ktrans, and total extracellular extravascular space volume, Ve. TWIST induced errors in the total blood plasma volume, Vp, were the largest observed, and these were inversely dependent on the area of the fully sampled k-space. The magnitudes of errors were not correlated with Ktrans, Vp and weakly correlated with Ve.Conclusions The authors demonstrated methods to validate and optimize k-space view-sharing techniques for pharmacokinetic DCE studies using a range of clinically relevant spatial and temporal patient derived data. The authors found a range of undersampling patterns for which the TWIST sequence can be reliably used in pharmacokinetic DCE-MRI. The parameter maps created in the study can help to make a decision between temporal and spatial resolution demands and the quality of enhancement curve characterization

Interview guide: Motivation to participate in lung cancer screening.

(DOCX)</p

Coding framework with definitions.

(PDF)</p

Coding framework: Drivers of lung cancer screening participation in Australia using the COM-B (capability, opportunity, motivation-behaviour) model.

Coding framework: Drivers of lung cancer screening participation in Australia using the COM-B (capability, opportunity, motivation-behaviour) model.</p

Demographic characteristics of participants.

Demographic characteristics of participants.</p

COM-B model: Gates of capability and opportunity adapted from <i>West et al 2020</i> [32].

Note the crosses represent a barrier to the opening of the gates of capability and opportunity, reducing the chance motivation will lead to behaviour.</p