The link between the nature of the human–companion animal relationship and well-being outcomes in companion animal owners

Research into the impact of companion animals on well-being has been both extensive and inconclusive, with studies finding both positive and negative relationships. The present research explored three previously unexamined relationship science concepts that may help clarify whether companion animals provide well-being benefits: self-expansion (the process of adding positive content to the self through incorporating new resources and perspectives into one’s identity or engaging in novel, exciting activities), perceived pet responsiveness, and perceived pet insensitivity; as well as attachment. We focused on dog and cat owners’ depression, anxiety, positive and negative affect, and loneliness through an online survey with a large sample population (N = 1359). We found that perceived pet insensitivity is a significant positive predictor of depression, anxiety, negative affect, and loneliness; that attachment is a significant positive predictor of depression, anxiety, and loneliness, and a significant negative predictor of positive affect; and that self-expansion is a significant positive predictor of positive affect, and a significant negative predictor of loneliness. Loneliness emerged as a mediator in the relationship between perceived pet insensitivity, attachment, self-expansion, and all mental well-being outcome variables. These findings indicate that perceived pet insensitivity, attachment, and self-expansion may play an important yet neglected role in well-being outcomes

Heavy Drinking in College Students Is Associated with Accelerated Gray Matter Volumetric Decline over a 2 Year Period

Background: Heavy and/or harmful alcohol use while in college is a perennial and significant public health issue. Despite the plethora of cross-sectional research suggesting deleterious effects of alcohol on the brain, there is a lack of literature investigating the longitudinal effects of alcohol consumption on the adolescent brain. We aim to probe the longitudinal effects of college drinking on gray matter change in students during this crucial neurodevelopmental period. Methods: Data were derived from the longitudinal Brain and Alcohol Research in College Students (BARCS) study of whom a subset underwent brain MRI scans at two time points 24 months apart. Students were young adults with a mean age at baseline of about 18.5 years. Based on drinking metrics assessed at both baseline and followup, subjects were classified as sustained abstainers/light drinkers (N = 45) or sustained heavy drinkers (N = 84) based on criteria established in prior literature. Gray matter volumetric change (GMV-c) maps were derived using the longitudinal DARTEL pipeline as implemented in SPM12. GMV-c maps were then subjected to a 1-sample and 2-sample t-test in SPM12 to determine within- and between-group GMV-c differences in drinking groups. Supplementary between-group differences were also computed at baseline only. Results: Within-group analysis revealed significant decline in GMV in both groups across the 2 year followup period. However, tissue loss in the sustained heavy drinking group was more significant, larger per region, and more widespread across regions compared to abstainers/light drinkers. Between-group analysis confirmed the above and showed a greater rate of GMV-c in the heavy drinking group in several brain regions encompassing inferior/medial frontal gyrus, parahippocampus, and anterior cingulate. Supplementary analyses suggest that some of the frontal differences existed at baseline and progressively worsened. Conclusion: Sustained heavy drinking while in college was associated with accelerated GMV decline in brain regions involved with executive functioning, emotional regulation, and memory, which are critical to everyday life functioning. Areas of significant GMV decreases also overlapped largely with brain reward and stress systems implicated in addictive behavior

21-cm synthesis observations of VIRGOHI 21 - a possible dark galaxy in the Virgo Cluster

Many observations indicate that dark matter dominates the extra-galactic Universe, yet no totally dark structure of galactic proportions has ever been convincingly identified. Previously we have suggested that VIRGOHI 21, a 21-cm source we found in the Virgo Cluster using Jodrell Bank, was a possible dark galaxy because of its broad line-width (~200 km/s) unaccompanied by any visible gravitational source to account for it. We have now imaged VIRGOHI 21 in the neutral-hydrogen line and find what could be a dark, edge-on, spinning disk with the mass and diameter of a typical spiral galaxy. Moreover, VIRGOHI 21 has unquestionably been involved in an interaction with NGC 4254, a luminous spiral with an odd one-armed morphology, but lacking the massive interactor normally linked with such a feature. Numerical models of NGC 4254 call for a close interaction ~10^8 years ago with a perturber of ~10^11 solar masses. This we take as additional evidence for the massive nature of VIRGOHI 21 as there does not appear to be any other viable candidate. We have also used the Hubble Space Telescope to search for stars associated with the HI and find none down to an I band surface brightness limit of 31.1 +/- 0.2 mag/sq. arcsec.Comment: 8 pages, accepted to ApJ, uses emulateapj.cls. Mpeg animation (Fig. 2) available at ftp://ftp.naic.edu/pub/publications/minchin/video2.mp

Dynamically constraining the length of the Milky Way bar

We present a novel method for constraining the length of the Galactic bar using 6D phase space information to directly integrate orbits. We define a pseudo-length for the Galactic bar, named $R_{Freq}$, based on the maximal extent of trapped bar orbits. We find the $R_{Freq}$ measured from orbits is consistent with the $R_{Freq}$ of the assumed potential only when the length of the bar and pattern speed of said potential is similar to the model from which the initial phase-space coordinates of the orbits are derived. Therefore, one can measure the model's or the Milky Way's bar length from 6D phase-space coordinates by determining which assumed potential leads to a self-consistent measured $R_{Freq}$. When we apply this method to $\approx$210,000 stars in APOGEE DR17 and $Gaia$ eDR3 data, we find a consistent result only for potential models with a dynamical bar length of $\approx$3.5 kpc. We find the Milky Way's trapped bar orbits extend out to only $\approx$3.5 kpc, but there is also an overdensity of stars at the end of the bar out to 4.8 kpc which could be related to an attached spiral arm. We also find that the measured orbital structure of the bar is strongly dependent on the properties of the assumed potential.Comment: 15 pages, 8 figures, 2 tables, accepted to MNRAS, comments welcom

Regulation of PTEN Inhibition by the Pleckstrin Homology Domain of P-REX2 During Insulin Signaling and Glucose Homeostasis

Insulin activation of phosphoinositide 3-kinase (PI3K) signaling regulates glucose homeostasis through the production of phosphatidylinositol 3,4,5-trisphosphate (PIP3). The dual-specificity phosphatase and tensin homolog deleted on chromosome 10 (PTEN) blocks PI3K signaling by dephosphorylating PIP3, and is inhibited through its interaction with phosphatidylinositol 3,4,5-trisphosphate-dependent Rac exchanger 2 (P-REX2). The mechanism of inhibition and its physiological significance are not known. Here, we report that P-REX2 interacts with PTEN via two interfaces. The pleckstrin homology (PH) domain of P-REX2 inhibits PTEN by interacting with the catalytic region of PTEN, and the inositol polyphosphate 4-phosphatase domain of P-REX2 provides high-affinity binding to the postsynaptic density-95/Discs large/zona occludens-1-binding domain of PTEN. P-REX2 inhibition of PTEN requires C-terminal phosphorylation of PTEN to release the P-REX2 PH domain from its neighboring diffuse B-cell lymphoma homology domain. Consistent with its function as a PTEN inhibitor, deletion of Prex2 in fibroblasts and mice results in increased Pten activity and decreased insulin signaling in liver and adipose tissue. Prex2 deletion also leads to reduced glucose uptake and insulin resistance. In human adipose tissue, P-REX2 protein expression is decreased and PTEN activity is increased in insulin-resistant human subjects. Taken together, these results indicate a functional role for P-REX2 PH-domain-mediated inhibition of PTEN in regulating insulin sensitivity and glucose homeostasis and suggest that loss of P-REX2 expression may cause insulin resistance

Quantitative Analysis of Radiation-Associated Parenchymal Lung Change

We present a novel classification system of the parenchymal features of radiation-induced lung damage (RILD). We developed a deep learning network to automate the delineation of five classes of parenchymal textures. We quantify the volumetric change in classes after radiotherapy in order to allow detailed, quantitative descriptions of the evolution of lung parenchyma up to 24 months after RT, and correlate these with radiotherapy dose and respiratory outcomes. Diagnostic CTs were available pre-RT, and at 3, 6, 12 and 24 months post-RT, for 46 subjects enrolled in a clinical trial of chemoradiotherapy for non-small cell lung cancer. All 230 CT scans were segmented using our network. The five parenchymal classes showed distinct temporal patterns. Moderate correlation was seen between change in tissue class volume and clinical and dosimetric parameters, e.g., the Pearson correlation coefficient was ≤0.49 between V30 and change in Class 2, and was 0.39 between change in Class 1 and decline in FVC. The effect of the local dose on tissue class revealed a strong dose-dependent relationship. Respiratory function measured by spirometry and MRC dyspnoea scores after radiotherapy correlated with the measured radiological RILD. We demonstrate the potential of using our approach to analyse and understand the morphological and functional evolution of RILD in greater detail than previously possible

The timing of anthropogenic emergence in simulated climate extremes

Determining the time of emergence of climates altered from their natural state by anthropogenic influences can help inform the development of adaptation and mitigation strategies to climate change. Previous studies have examined the time of emergence of climate averages. However, at the global scale, the emergence of changes in extreme events, which have the greatest societal impacts, has not been investigated before. Based on state-of-the-art climate models, we show that temperature extremes generally emerge slightly later from their quasi-natural climate state than seasonal means, due to greater variability in extremes. Nevertheless, according to model evidence, both hot and cold extremes have already emerged across many areas. Remarkably, even precipitation extremes that have very large variability are projected to emerge in the coming decades in Northern Hemisphere winters associated with a wettening trend. Based on our findings we expect local temperature and precipitation extremes to already differ significantly from their previous quasi-natural state at many locations or to do so in the near future. Our findings have implications for climate impacts and detection and attribution studies assessing observed changes in regional climate extremes by showing whether they will likely find a fingerprint of anthropogenic climate change

Local CpG density affects the trajectory and variance of age-associated DNA methylation changes

Acknowledgements We thank Riccardo Marioni, Chris Haley, Ailith Ewing, David Porteous, Chris Ponting, Rob Illingworth, Tamir Chandra, Sara Hagg, Yunzhang Wang, Chantriolnt-Andreas Kapourani, Nick Gilbert, Hannes Becher and members of the Sproul lab for helpful discussions about the study and the manuscript. This work has made use of the resources provided by the University of Edinburgh digital research services and the MRC IGC compute cluster. We are grateful to all the families who took part in the Generation Scotland study along with the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the entire Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants, and nurses. Peer review information Anahita Bishop and Kevin Pang were the primary editors of this article and managed its editorial process and peer review in collaboration with the rest of the editorial team. Review history The review history is available as Additional file 3. Funding DS is a Cancer Research UK Career Development fellow (reference C47648/A20837), and work in his laboratory is also supported by an MRC university grant to the MRC Human Genetics Unit. LK is a cross-disciplinary postdoctoral fellow supported by funding from the University of Edinburgh and Medical Research Council (MC_UU_00009/2). S.R.C. and I.J.D. were supported by a National Institutes of Health (NIH) research grant R01AG054628, and S.R.C is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (221890/Z/20/Z). AMM is supported by the Wellcome Trust (104036/Z/14/Z, 216767/Z/19/Z, 220857/Z/20/Z) and UKRI MRC (MC_PC_17209, MR/S035818/1). PMV acknowledges support from the Australian National Health and Medical Research Council (1113400) and the Australian Research Council (FL180100072). DMH is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). We thank the LBC1936 participants and team members who contributed to the study. Further study information can be found at https://www.ed.ac.uk/lothian-birth-cohorts. The LBC1936 is supported by a jointly funded grant from the BBSRC and ESRC (BB/W008793/1), and also by Age UK (Disconnected Mind project), the Medical Research Council (G0701120, G1001245, MR/M013111/1, MR/R024065/1), and the University of Edinburgh. Genotyping of LBC1936 was funded by the BBSRC (BB/F019394/1), and methylation typing of LBC1936 was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. Work on Generation Scotland was supported by a Wellcome Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL; 104036/Z/14/Z) to AMM, KLE, and others, and an MRC Mental Health Data Pathfinder Grant (MC_PC_17209) to AMM. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). DNA methylation profiling and analysis of the GS:SFHS samples was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI: AM McIntosh) and through funding from NARSAD (Ref: 27404; awardee: Dr DM Howard) and the Royal College of Physicians of Edinburgh (Sim Fellowship; Awardee: Dr HC Whalley).Peer reviewedPublisher PD