Attitudes Regarding the Use of Ventilator Support Given a Supposed Terminal Condition among Community-Dwelling Mexican American and Non-Hispanic White Older Adults: A Pilot Study

Purpose. To determine the factors that are associated with Mexican Americans' preference for ventilator support, given a supposed terminal diagnosis. Methods. 100 Mexican Americans, aged 60–89, were recruited and screened for MMSE scores above 18. Eligible subjects answered a questionnaire in their preferred language (English/Spanish) concerning ventilator use during terminal illness. Mediator variables examined included demographics, generation, religiosity, occupation, self-reported depression, self-reported health, and activities of daily living. Results. Being first or second generation American (OR = 0.18, CI = 0.05–0.66) with no IADL disability (OR = 0.11, CI = 0.02–0.59) and having depressive symptoms (OR = 1.43, CI = 1.08–1.89) were associated with preference for ventilator support. Implications. First and second generation older Mexican Americans and those functionally independent are more likely to prefer end-of-life ventilation support. Although depressive symptoms were inversely associated with ventilator use at the end of life, scores may more accurately reflect psychological stress associated with enduring the scenario. Further studies are needed to determine these factors' generalizability to the larger Mexican American community

Impact of Systematic Errors in Sunyaev-Zel'dovich Surveys of Galaxy Clusters

Future high-resolution microwave background measurements hold the promise of detecting galaxy clusters throughout our Hubble volume through their Sunyaev-Zel'dovich (SZ) signature, down to a given limiting flux. The number density of galaxy clusters is highly sensitive to cluster mass through fluctuations in the matter power spectrum, as well as redshift through the comoving volume and the growth factor. This sensitivity in principle allows tight constraints on such quantities as the equation of state of dark energy and the neutrino mass. We evaluate the ability of future cluster surveys to measure these quantities simultaneously when combined with PLANCK-like CMB data. Using a simple effective model for uncertainties in the cluster mass-SZ flux relation, we evaluate systematic shifts in cosmological constraints from cluster SZ surveys. We find that a systematic bias of 10% in cluster mass measurements can give rise to shifts in cosmological parameter estimates at levels larger than the $1\sigma$ statistical errors. Systematic errors are unlikely to be detected from the mass and redshift dependence of cluster number counts alone; increasing survey size has only a marginal effect. Implications for upcoming experiments are discussed.Comment: 12 pages, 6 figures; accepted to JCAP; revised to match submitted versio

The Impact of Antiretroviral Therapy in a Cohort of HIV Infected Patients Going in and out of the San Francisco County Jail

BackgroundJails are an important venue of HIV care and a place for identification, treatment and referral for care. HIV infected inmates in the San Francisco County jail are offered antiretroviral treatment (ART), which many take only while in jail. We evaluated the effect of ART administration in a cohort of jail inmates going in and out of jail over a nine year period.Methodology/Principal FindingsIn this retrospective study, we examined inmates with HIV going in and out of jail. Inmates were categorized by patterns of ART use: continuous ART - ART both in and out of jail, [...] more likely to have higher VL than inmates on continuous ART. Furthermore, Inmates on intermittent ART and never-on ART lost 1.60; 95%CI (1.06, 2.13) and 1.97; 95%CI (0.96, 3.00) more CD4 cells per month, respectively, compared to continuously treated inmates. The continuous ART inmates gained 0.67CD4 cells/month.Conclusions/SignificanceContinuous ART therapy in jail inmate's benefits CD4 cell counts and control of VL especially compared to those who never took ART. Although jail inmates on intermittent ART were more likely to lose CD4 cells and experience higher VL over time than those on continuous ART, CD4 cell loss was slower in these inmates as compared to inmates never on ART. Further studies are needed to evaluate whether or not intermittent ART provides some benefit in outcome if continuous ART is not possible or likely

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

Cost-effectiveness of exercise therapy versus general practitioner care for osteoarthritis of the hip: design of a randomised clinical trial

<p>Abstract</p> <p>Background</p> <p>Osteoarthritis (OA) is the most common joint disease, causing pain and functional impairments. According to international guidelines, exercise therapy has a short-term effect in reducing pain/functional impairments in knee OA and is therefore also generally recommended for hip OA. Because of its high prevalence and clinical implications, OA is associated with considerable (healthcare) costs. However, studies evaluating cost-effectiveness of common exercise therapy in hip OA are lacking. Therefore, this randomised controlled trial is designed to investigate the cost-effectiveness of exercise therapy in conjunction with the general practitioner's (GP) care, compared to GP care alone, for patients with hip OA.</p> <p>Methods/Design</p> <p>Patients aged ≥ 45 years with OA of the hip, who consulted the GP during the past year for hip complaints and who comply with the American College of Rheumatology criteria, are included. Patients are randomly assigned to either exercise therapy in addition to GP care, or to GP care alone. Exercise therapy consists of (maximally) 12 treatment sessions with a physiotherapist, and home exercises. These are followed by three additional treatment sessions in the 5th, 7th and 9th month after the first treatment session. GP care consists of usual care for hip OA, such as general advice or prescribing pain medication. Primary outcomes are hip pain and hip-related activity limitations (measured with the Hip disability Osteoarthritis Outcome Score [HOOS]), direct costs, and productivity costs (measured with the PROductivity and DISease Questionnaire). These parameters are measured at baseline, at 6 weeks, and at 3, 6, 9 and 12 months follow-up. To detect a 25% clinical difference in the HOOS pain score, with a power of 80% and an alpha 5%, 210 patients are required. Data are analysed according to the intention-to-treat principle. Effectiveness is evaluated using linear regression models with repeated measurements. An incremental cost-effectiveness analysis and an incremental cost-utility analysis will also be performed.</p> <p>Discussion</p> <p>The results of this trial will provide insight into the cost-effectiveness of adding exercise therapy to GPs' care in the treatment of OA of the hip. This trial is registered in the Dutch trial registry <url>http://www.trialregister.nl</url>: trial number <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1462">NTR1462</a>.</p

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity

Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2*-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2*-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as task-switching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills