Physical exercise recommendations for patients with chronic myeloid leukemia based on individual preferences identified in a large international patient survey study of the East German Study Group for Hematology and Oncology (OSHO #97)

BackgroundTyrosine kinase inhibitors (TKIs) have significantly lowered mortality of chronic myeloid leukemia (CML) patients adjusting life expectancy to that of the standard population. However, CML and its treatment with TKIs causes a high disease burden. Physical exercise (PE) could be a non-pharmacological approach to reducing these and improving quality of life.PurposeThe aim of this study was to determine the individual disease burden as well as PE preferences of CML patients and to deduce thereof specific PE recommendations.MethodsThis multicenter survey was conducted in cooperation with the LeukaNET/Leukemia-patient network including CML patients aged ≥18 years (German Registry of Clinical Trials, DRKS00023698). The severity of selected symptoms was assessed using the adapted Myeloproliferative Neoplasms Symptom Assessment Form: 0 (absent), 1–30 (mild), 31–70 (moderate), or 71–100 (severe). Information about patients’ PE needs and preferences depending on their motivation was recorded.ResultsA total of 212 questionnaires were analyzed (52% female, median age 54 years). The prevalence of moderate-to-severe symptoms was 49% for fatigue, 40% for musculoskeletal pain, and 37% for concentration problems. Other commonly reported symptoms included skin reactions (42%) and weight gain (24%). The proportion of overweight/obese patients was 52%. Half of all respondents requested more information regarding PE. Patients with CML preferred individual training (82%), located outdoors (71%), at home (47%), or in an indoor swimming pool (31%). Regarding the training frequency, sports-inactive patients preferred a frequency of 1–2 training sessions per week, whereas sports-active patients preferred 3–4 sessions per week (p <0.001). Sports-inactive patients preferred a training time of 15–45 minutes, while sports-active patients preferred 30–60 minutes (p = 0.002). Subsequently, PE recommendations were developed for patients with CML. Combined resistance and endurance training (moderate intensity twice per week for 30 minutes) was recommended for beginners. Obese patients should prioritize joint-relieving sports. To reduce the risk of skin reactions, direct sunlight and possibly water sports should be avoided, and UV protection should be used.ConclusionCounseling and motivation of CML patients to be physically active should be part of the standard of care as well as support for implementation

Pain and Problem Behavior in Cats and Dogs

We argue that there is currently an under-reporting of the ways in which pain can be associated with problem behavior, which is seriously limiting the recognition of this welfare problem. A review of the caseloads of 100 recent dog cases of several authors indicates that a conservative estimate of around a third of referred cases involve some form of painful condition, and in some instances, the figure may be nearly 80%. The relationship is often complex but always logical. Musculoskeletal but also painful gastro-intestinal and dermatological conditions are commonly recognized as significant to the animal’s problem behavior. The potential importance of clinical abnormalities such as an unusual gait or unexplained behavioral signs should not be dismissed by clinicians in general practice, even when they are common within a given breed. In general, it is argued that clinicians should err on the side of caution when there is a suspicion that a patient could be in pain by carefully evaluating the patient’s response to trial analgesia, even if a specific physical lesion has not been identified

Dust Reverberation Mapping in Distant Quasars from Optical and Mid-Infrared Imaging Surveys

The size of the dust torus in Active Galactic Nuclei (AGN) and their high-luminosity counterparts, quasars, can be inferred from the time delay between UV/optical accretion disk continuum variability and the response in the mid-infrared (MIR) torus emission. This dust reverberation mapping (RM) technique has been successfully applied to $\sim 70$ $z\lesssim 0.3$ AGN and quasars. Here we present first results of our dust RM program for distant quasars covered in the SDSS Stripe 82 region combining $\sim 20$-yr ground-based optical light curves with 10-yr MIR light curves from the WISE satellite. We measure a high-fidelity lag between W1-band (3.4 $\mu$m) and $g$ band for 587 quasars over $0.3\lesssim z\lesssim 2$ (\left\sim 0.8) and two orders of magnitude in quasar luminosity. They tightly follow (intrinsic scatter $\sim 0.17$ dex in lag) the IR lag-luminosity relation observed for $z<0.3$ AGN, revealing a remarkable size-luminosity relation for the dust torus over more than four decades in AGN luminosity, with little dependence on additional quasar properties such as Eddington ratio and variability amplitude. This study motivates further investigations in the utility of dust RM for cosmology, and strongly endorses a compelling science case for the combined 10-yr Vera C. Rubin Observatory Legacy Survey of Space and Time (optical) and 5-yr Nancy Grace Roman Space Telescope 2$\mu$m light curves in a deep survey for low-redshift AGN dust RM with much lower luminosities and shorter, measurable IR lags. The compiled optical and MIR light curves for 7,384 quasars in our parent sample are made public with this work.Comment: Accepted for publication in Ap

Minimum Technical Data Elements for Liquid Biopsy Data Submitted to Public Databases

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/1/cpt1747.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/2/cpt1747-sup-0001-FigS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154656/3/cpt1747_am.pd

An r -process enhanced star in the dwarf galaxy Tucana III

Chemically peculiar stars in dwarf galaxies provide a window for exploring the birth environment of stars with varying chemical enrichment. We present a chemical abundance analysis of the brightest star in the newly discovered ultra-faint dwarf galaxy candidate Tucana III. Because it is particularly bright for a star in an ultra-faint Milky Way (MW) satellite, we are able to measure the abundance of 28 elements, including 13 neutron-capture species. This star, DES J235532.66−593114.9 (DES J235532), shows a mild enhancement in neutron-capture elements associated with the r-process and can be classified as an r-I star. DES J235532 is the first r-I star to be discovered in an ultra-faint satellite, and Tuc III is the second extremely low-luminosity system found to contain rprocess enriched material, after Reticulum II. Comparison of the abundance pattern of DES J235532 with r-I and r-II stars found in other dwarf galaxies and in the MW halo suggests a common astrophysical origin for the neutron-capture elements seen in all r-process enhanced stars. We explore both internal and external scenarios for the r-process enrichment of Tuc III and show that with abundance patterns for additional stars, it should be possible to distinguish between them

The glaciers climate change initiative: Methods for creating glacier area, elevation change and velocity products

Glaciers and their changes through time are increasingly obtained from a wide range of satellite sensors. Due to the often remote location of glaciers in inaccessible and high-mountain terrain, satellite observations frequently provide the only available measurements. Furthermore, satellite data provide observations of glacier character- istics that are difficult to monitor using ground-based measurements, thus complementing the latter. In the Glaciers_cci project of the European Space Agency (ESA), three of these characteristics are investigated in detail: glacier area, elevation change and surface velocity. We use (a) data from optical sensors to derive glacier outlines, (b) digital elevation models from at least two points in time, (c) repeat altimetry for determining elevation changes, and (d) data from repeat optical and microwave sensors for calculating surface velocity. For the latter, the two sensor types provide complementary information in terms of spatio-temporal coverage. While (c) and (d) can be generated mostly automatically, (a) and (b) require the intervention of an analyst. Largely based on the results of various round robin experiments (multi-analyst benchmark studies) for each of the products, we suggest and describe the most suitable algorithms for product creation and provide recommendations concerning their practical implementation and the required post-processing. For some of the products (area, velocity) post-processing can influence product quality more than the main-processing algorithm

Constraints on dark matter to dark radiation conversion in the late universe with DES-Y1 and external data

84siWe study a class of decaying dark matter models as a possible resolution to the observed discrepancies between early- and late-time probes of the universe. This class of models, dubbed DDM, characterizes the evolution of comoving dark matter density with two extra parameters. We investigate how DDM affects key cosmological observables such as the CMB temperature and matter power spectra. Combining 3x2pt data from Year 1 of the Dark Energy Survey,Planck-2018 CMB temperature and polarization data, Supernova (SN) Type Ia data from Pantheon, and BAO data from BOSS DR12, MGS and 6dFGS, we place new constraints on the amount of dark matter that has decayed and the rate with which it converts to dark radiation. The fraction of the decayed dark matter in units of the current amount of dark matter, $zeta$, is constrained at 68% confidence level to be <0.32 for DES-Y1 3x2pt data, <0.030 for CMB+SN+BAO data, and <0.037 for the combined dataset. The probability that the DES and CMB+SN+BAO datasets are concordant increases from 4% for the $Lambda$CDM model to 8% (less tension) for DDM. Moreover, tension in $S_8=sigma_8sqrt{Omega_m/0.3}$ between DES-Y1 3x2pt and CMB+SN+BAO is reduced from 2.3$sigma$ to 1.9$sigma$. We find no reduction in the Hubble tension when the combined data is compared to distance-ladder measurements in the DDM model. The maximum-posterior goodness-of-fit statistics of DDM and $Lambda$CDM are comparable, indicating no preference for the DDM cosmology over $Lambda$CDM....partially_openopenChen, Angela; Huterer, Dragan; Lee, Sujeong; Ferté, Agnès; Weaverdyck, Noah; Alonso Alves, Otavio; Leonard, C. Danielle; MacCrann, Niall; Raveri, Marco; Porredon, Anna; Di Valentino, Eleonora; Muir, Jessica; Lemos, Pablo; Liddle, Andrew; Blazek, Jonathan; Campos, Andresa; Cawthon, Ross; Choi, Ami; Dodelson, Scott; Elvin-Poole, Jack; Gruen, Daniel; Ross, Ashley; Secco, Lucas F.; Sevilla, Ignacio; Sheldon, Erin; Troxel, Michael A.; Zuntz, Joe; Abbott, Tim; Aguena, Michel; Allam, Sahar; Annis, James; Avila, Santiago; Bertin, Emmanuel; Bhargava, Sunayana; Bridle, Sarah; Brooks, David; Carnero Rosell, Aurelio; Carrasco Kind, Matias; Carretero, Jorge; Costanzi, Matteo; Crocce, Martin; da Costa, Luiz; Elidaiana da Silva Pereira, Maria; Davis, Tamara; Doel, Peter; Eifler, Tim; Ferrero, Ismael; Fosalba, Pablo; Frieman, Josh; Garcia-Bellido, Juan; Gaztanaga, Enrique; Gerdes, David; Gruendl, Robert; Gschwend, Julia; Gutierrez, Gaston; Hinton, Samuel; Hollowood, Devon L.; Honscheid, Klaus; Hoyle, Ben; James, David; Jarvis, Mike; Kuehn, Kyler; Lahav, Ofer; Maia, Marcio; Marshall, Jennifer; Menanteau, Felipe; Miquel, Ramon; Morgan, Robert; Palmese, Antonella; Paz-Chinchon, Francisco; Plazas Malagón, Andrés; Roodman, Aaron; Sanchez, Eusebio; Scarpine, Vic; Schubnell, Michael; Serrano, Santiago; Smith, Mathew; Suchyta, Eric; Tarle, Gregory; Thomas, Daniel; To, Chun-Hao; Varga, Tamas Norbert; Weller, Jochen; Wilkinson, ReeseChen, Angela; Huterer, Dragan; Lee, Sujeong; Ferté, Agnès; Weaverdyck, Noah; Alonso Alves, Otavio; Leonard, C. Danielle; Maccrann, Niall; Raveri, Marco; Porredon, Anna; Di Valentino, Eleonora; Muir, Jessica; Lemos, Pablo; Liddle, Andrew; Blazek, Jonathan; Campos, Andresa; Cawthon, Ross; Choi, Ami; Dodelson, Scott; Elvin-Poole, Jack; Gruen, Daniel; Ross, Ashley; Secco, Lucas F.; Sevilla, Ignacio; Sheldon, Erin; Troxel, Michael A.; Zuntz, Joe; Abbott, Tim; Aguena, Michel; Allam, Sahar; Annis, James; Avila, Santiago; Bertin, Emmanuel; Bhargava, Sunayana; Bridle, Sarah; Brooks, David; Carnero Rosell, Aurelio; Carrasco Kind, Matias; Carretero, Jorge; Costanzi, Matteo; Crocce, Martin; da Costa, Luiz; Elidaiana da Silva Pereira, Maria; Davis, Tamara; Doel, Peter; Eifler, Tim; Ferrero, Ismael; Fosalba, Pablo; Frieman, Josh; Garcia-Bellido, Juan; Gaztanaga, Enrique; Gerdes, David; Gruendl, Robert; Gschwend, Julia; Gutierrez, Gaston; Hinton, Samuel; Hollowood, Devon L.; Honscheid, Klaus; Hoyle, Ben; James, David; Jarvis, Mike; Kuehn, Kyler; Lahav, Ofer; Maia, Marcio; Marshall, Jennifer; Menanteau, Felipe; Miquel, Ramon; Morgan, Robert; Palmese, Antonella; Paz-Chinchon, Francisco; Plazas Malagón, Andrés; Roodman, Aaron; Sanchez, Eusebio; Scarpine, Vic; Schubnell, Michael; Serrano, Santiago; Smith, Mathew; Suchyta, Eric; Tarle, Gregory; Thomas, Daniel; Chun-Hao, To; Varga, Tamas Norbert; Weller, Jochen; Wilkinson, Rees

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches