Stroke Induces Prolonged Changes in Lipid Metabolism, the Liver and Body Composition in Mice

Acknowledgements We would like to thank the Biological Services Facility at the University of Manchester for expert animal husbandry and Karen Davies who helped with the MRI. The Histology Facility equipment that was used in this study was purchased by the University of Manchester Strategic Fund. Special thanks goes to Peter Walker for their help with the histology. Funding information This work was supported by the Kohn Foundation, an Edward Bonham Carter Doctoral Scholarship, an EPSRC/MRC Centre for Doctoral Training in Regenerative Medicine studentship grant (EP/L014904/1), and the Medical Research Council (MR/K501311/1).Peer reviewedPublisher PD

Interacting Galaxies in the A901/902 Supercluster with STAGES

We present a study of galaxy mergers and the influence of environment in the Abell 901/902 supercluster at z~0.165. We use HST ACS F606W data from the STAGES survey, COMBO-17, Spitzer 24um, and XMM-Newton X-ray data. Our analysis utilizes both a visual classification system, and quantitative CAS parameters to identify systems which show evidence of a recent or ongoing merger of mass ratio >1/10. Our results are: (1) After visual classification and minimizing the contamination from false projection pairs, we find that the merger fraction f_merge is 0.023+/-0.007. The estimated fractions of likely major mergers, likely minor mergers, and ambiguous cases are 0.01+/-0.004, 0.006+/-0.003, and 0.007+/-0.003, respectively. (2) The mergers lie outside the cluster core of radius R < 0.25 Mpc: the lack of mergers in the core is likely due to the large galaxy velocity dispersion in the core. Mergers populate the region (0.25 Mpc < R <= 2 Mpc) between the core and outskirt. In this region, the estimated frequency of mergers is similar to those seen at typical group overdensities. This suggests ongoing growth of the clusters via accretion of group and field galaxies. (3) We compare our observed merger fraction with those reported in other clusters and groups out to z~0.4. Existing data points on the merger fraction for L<= L* galaxies in clusters allow for a range of evolutionary scenarios. (4) The fraction of mergers, which lie on the blue cloud is 80%+/-18% versus 34%+/-7% for non-interacting galaxies, implying that interacting galaxies are preferentially blue. (5) The average SFR, based on UV or UV+IR data, is enhanced by a factor of ~1.5 to 2 in mergers compared to non-interacting galaxies. However, mergers in the clusters contribute only a small fraction (between 10% and 15%) of the total SFR density.(Abridged)Comment: Accepted for publication in ApJ. 34 pages, 16 figures. Version with full resolution figures available at: http://www.as.utexas.edu/~alh/apj/int/ ; updated abridged abstrac

Less than 10 percent of star formation in z=0.6 massive galaxies is triggered by major interactions

Both observations and simulations show that major tidal interactions or mergers between gas-rich galaxies can lead to intense bursts of starformation. Yet, the average enhancement in star formation rate (SFR) in major mergers and the contribution of such events to the cosmic SFR are not well estimated. Here we use photometric redshifts, stellar masses and UV SFRs from COMBO-17, 24 micron SFRs from Spitzer and morphologies from two deep HST cosmological survey fields (ECDFS/GEMS and A901/STAGES) to study the enhancement in SFR as a function of projected galaxy separation. We apply two-point projected correlation function techniques, which we augment with morphologically-selected very close pairs (separation <2 arcsec) and merger remnants from the HST imaging. Our analysis confirms that the most intensely star-forming systems are indeed interacting or merging. Yet, for massive (M* > 10^10 Msun) star-forming galaxies at 0.4<z<0.8, we find that the SFRs of galaxies undergoing a major interaction (mass ratios <1:4 and separations < 40 kpc) are only 1.80 +/- 0.30 times higher than the SFRs of non-interacting galaxies when averaged over all interactions and all stages of the interaction, in good agreement with other observational works. We demonstrate that these results imply that <10% of star formation at 0.4 < z < 0.8 is triggered directly by major mergers and interactions; these events are not important factors in the build-up of stellar mass since z=1.Comment: Submitted to ApJ. 41 pages, 11 figure

Mobile health applications for managing atrial fibrillation for healthcare professionals and patients: a systematic review

Aims A plethora of mobile health applications (m-health apps) to support healthcare are available for both patients and healthcare professionals (HCPs) but content and quality vary considerably and few have undergone formal assessment. The aim is to systematically review the literature on m-health apps for managing atrial fibrillation (AF) that examine the impact on knowledge of AF, patient and HCP behaviour, patients’ quality-of-life, and user engagement. Methods and results MEDLINE, EMBASE, CINAHL, and PsychInfo were searched from 1 January 2005 to 5 September 2019, with hand-searching of clinical trial registers and grey literature. Studies were eligible for inclusion if they reported changes in any of the following: (i) knowledge of AF; (ii) provider behaviour (e.g. guideline adherence); (iii) patient behaviour (e.g. medication adherence); (iv) patient quality-of-life; and (v) user engagement. Two reviewers independently assessed articles for eligibility. A narrative review was undertaken as included studies varied widely in their design, interventions, comparators, and outcomes. Seven studies were included; six m-health apps aimed at patients and one at HCPs. Mobile health apps ranged widely in design, features, and method of delivery. Four studies reported patient knowledge of AF; three demonstrated significant knowledge improvement post-intervention or compared to usual care. One study reported greater HCP adherence to oral anticoagulation guidelines after m-health app implementation. Two studies reported on patient medication adherence and quality-of-life; both showed improved quality-of-life post-intervention but only one observed increased adherence. Regarding user engagement, five studies reported patient perspectives on usability, three on acceptability, and one on feasibility; overall all m-health apps were rated positively. Conclusion Mobile health apps demonstrate improvements in patient knowledge, behaviour, and quality of life. Studies formally evaluating the impact of m-health on HCP behaviour are scarce and larger-scale studies with representative patient cohorts, appropriate comparators, and longer-term assessment of the impact of m-health apps are warranted

Interventions to increase engagement with rehabilitation in adults with acquired brain injury: A systematic review

Rehabilitation in adults with acquired brain injury is often hampered by a lack of client engagement with the rehabilitation process, leading to frustration, withdrawal of services and poorer recovery. Motivation, apathy and awareness are potential mechanisms underlying engagement, but few studies have suggested potential intervention techniques. A systematic review of the literature was carried out to identify and evaluate interventions designed to increase rehabilitation engagement in adults with acquired brain injury. Database searches used the following terms: rehabilitation, brain injury, and compliance/engagement/adherence in PsychInfo, Medline, Cinahl, Embase, AMED, Web of Knowledge, PsycBite, Cochrane clinical trials, and clinicaltrials.org. Hand searches were conducted of reference lists and relevant journals. Fifteen studies were included in the review. Intervention techniques fell into two broad categories: behavioural modification techniques and cognitive/meta-cognitive skills. Contingent reward techniques were most effective at increasing adherence and compliance, while interventions enabling clients' active participation in rehabilitation appeared to increase engagement and motivation. The review highlighted methodological and measurement inconsistencies in the field and suggested that interventions should be tailored to clients' abilities and circumstances

Automated mitral inflow Doppler peak velocity measurement using deep learning

Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce variability, prompting the need for automated solutions. This study introduces an innovative deep learning model for automated detection of peak velocity measurements from mitral inflow Doppler images, independent from Electrocardiogram information. A dataset of Doppler images annotated by multiple expert cardiologists was established, serving as a robust benchmark. The model leverages heatmap regression networks, achieving 96% detection accuracy. The model discrepancy with the expert consensus falls comfortably within the range of inter- and intra-observer variability in measuring Doppler peak velocities. The dataset and models are open-source, fostering further research and clinical application

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Dynamics of Inflammatory Responses After SARS-CoV-2 Infection by Vaccination Status in the USA: A Prospective Cohort Study

BACKGROUND: Cytokines and chemokines play a critical role in the response to infection and vaccination. We aimed to assess the longitudinal association of COVID-19 vaccination with cytokine and chemokine concentrations and trajectories among people with SARS-CoV-2 infection. METHODS: In this longitudinal, prospective cohort study, blood samples were used from participants enrolled in a multi-centre randomised trial assessing the efficacy of convalescent plasma therapy for ambulatory COVID-19. The trial was conducted in 23 outpatient sites in the USA. In this study, participants (aged ≥18 years) were restricted to those with COVID-19 before vaccination or with breakthrough infections who had blood samples and symptom data collected at screening (pre-transfusion), day 14, and day 90 visits. Associations between COVID-19 vaccination status and concentrations of 21 cytokines and chemokines (measured using multiplexed sandwich immunoassays) were examined using multivariate linear mixed-effects regression models, adjusted for age, sex, BMI, hypertension, diabetes, trial group, and COVID-19 waves (pre-alpha or alpha and delta). FINDINGS: Between June 29, 2020, and Sept 30, 2021, 882 participants recently infected with SARS-CoV-2 were enrolled, of whom 506 (57%) were female and 376 (43%) were male. 688 (78%) of 882 participants were unvaccinated, 55 (6%) were partly vaccinated, and 139 (16%) were fully vaccinated at baseline. After adjusting for confounders, geometric mean concentrations of interleukin (IL)-2RA, IL-7, IL-8, IL-15, IL-29 (interferon-λ), inducible protein-10, monocyte chemoattractant protein-1, and tumour necrosis factor-α were significantly lower among the fully vaccinated group than in the unvaccinated group at screening. On day 90, fully vaccinated participants had approximately 20% lower geometric mean concentrations of IL-7, IL-8, and vascular endothelial growth factor-A than unvaccinated participants. Cytokine and chemokine concentrations decreased over time in the fully and partly vaccinated groups and unvaccinated group. Log INTERPRETATION: Initially and during recovery from symptomatic COVID-19, fully vaccinated participants had lower concentrations of inflammatory markers than unvaccinated participants suggesting vaccination is associated with short-term and long-term reduction in inflammation, which could in part explain the reduced disease severity and mortality in vaccinated individuals. FUNDING: US Department of Defense, National Institutes of Health, Bloomberg Philanthropies, State of Maryland, Mental Wellness Foundation, Moriah Fund, Octapharma, HealthNetwork Foundation, and the Shear Family Foundation