Endogenous Gonadal Hormone Exposure and Bone Sarcoma Risk

Although experimental and clinical evidence suggest that endogenous sex hormones influence bone sarcoma genesis, the hypothesis has not been adequately tested in an appropriate animal model. We conducted a historical cohort study of Rottweiler dogs because they frequently undergo elective gonadectomy and spontaneously develop appendicular bone sarcomas, which mimic the biological behavior of the osteosarcomas that affect children and adolescents. Data were collected by questionnaire from owners of 683 Rottweiler dogs living in North America. To determine whether there was an association between endogenous sex hormones and risk of bone sarcoma, relative risk (RR) of incidence rates and hazard ratios for bone sarcoma were calculated for dogs subdivided on the basis of lifetime gonadal hormone exposure. Bone sarcoma was diagnosed in 12.6% of dogs in this cohort during 71,004 dog-months follow-up. Risk for bone sarcoma was significantly influenced by age at gonadectomy. Male and female dogs that underwent gonadectomy before 1 year of age had an approximate one in four lifetime risk for bone sarcoma and were significantly more likely to develop bone sarcoma than dogs that were sexually intact [RR ±95% CI = 3.8 (1.5–9.2) for males; RR ±95% CI = 3.1 (1.1–8.3) for females]. χ2 test for trend showed a highly significant inverse dose-response relationship between duration of lifetime gonadal exposure and incidence rate of bone sarcoma (P = 0.008 for males, P = 0.006 for females). This association was independent of adult height or body weight. We conclude that the subset of Rottweiler dogs that undergo early gonadectomy represent a unique, highly accessible target population to further study the gene:environment interactions that determine bone sarcoma risk and to test whether interventions can inhibit the spontaneous development of bone sarcoma

Variation in the Use of 12-Lead Electrocardiography for Patients With Chest Pain by Emergency Medical Services in North Carolina

BackgroundPrehospital 12‐lead electrocardiography (ECG) is critical to timely STEMI care although its use remains inconsistent. Previous studies to identify reasons for failure to obtain a prehospital ECG have generally only focused on individual emergency medical service (EMS) systems in urban areas. Our study objective was to identify patient, geographic, and EMS agency‐related factors associated with failure to perform a prehospital ECG across a statewide geography.Methods and ResultsWe analyzed data from the Prehospital Medical Information System (PreMIS) in North Carolina from January 2008 to November 2010 for patients >30 years of age who used EMS and had a prehospital chief complaint of chest pain. Among 3.1 million EMS encounters, 134 350 patients met study criteria. From 2008–2010, 82 311 (61%) persons with chest pain received a prehospital ECG; utilization increased from 55% in 2008 to 65% in 2010 (trend P<0.001). Utilization by health referral region ranged from 22.9% to 74.2% and was lowest in rural areas. Men were more likely than women to have an ECG performed (63.0% vs 61.3%, adjusted RR 1.02, 95% CI 1.01 to 1.04). The certification‐level of the EMS provider (paramedic vsbasic/intermediate) and system‐level ECG equipment availability were the strongest predictors of ECG utilization. Persons in an ambulance with a certified paramedic were significantly more likely to receive a prehospital ECG than nonparamedics (RR 2.15, 95% CI 1.55, 2.99).ConclusionsAcross a large geographic area prehospital ECG use increased significantly, although important quality improvement opportunities remain. Increasing ECG availability and improving EMS certification and training levels are needed to improve overall care and reduce rural‐urban treatment differences

Proteasome Lid Bridges Mitochondrial Stress with Cdc53/Cullin1 NEDDylation Status

Cycles of Cdc53/Cullin1 rubylation (a.k.a NEDDylation) protect ubiquitin-E3 SCF (Skp1-Cullin1-F-box protein) complexes from self-destruction and play an important role in mediating the ubiquitination of key protein substrates involved in cell cycle progression, development, and survival. Cul1 rubylation is balanced by the COP9 signalosome (CSN), a multi-subunit derubylase that shows 1:1 paralogy to the 26 S proteasome lid. The turnover of SCF substrates and their relevance to various diseases is well studied, yet, the extent by which environmental perturbations influence Cul1 rubylation/derubylation cycles per se is still unclear. In this study, we show that the level of cellular oxidation serves as a molecular switch, determining Cullin1 rubylation/derubylation ratio. We describe a mutant of the proteasome lid subunit, Rpn11 that exhibits accumulated levels of Cullin1-Rub1 conjugates, a characteristic phenotype of csn mutants. By dissecting between distinct phenotypes of rpn11 mutants, proteasome and mitochondria dysfunction, we were able to recognize the high reactive oxygen species (ROS) production during the transition of cells into mitochondrial respiration, as a checkpoint of Cullin1 rubylation in a reversible manner. Thus, the study adds the rubylation cascade to the list of cellular pathways regulated by redox homeostasis

A network-based dynamical ranking system for competitive sports

From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.Comment: 6 figure

How to Choose a Champion

League competition is investigated using random processes and scaling techniques. In our model, a weak team can upset a strong team with a fixed probability. Teams play an equal number of head-to-head matches and the team with the largest number of wins is declared to be the champion. The total number of games needed for the best team to win the championship with high certainty, T, grows as the cube of the number of teams, N, i.e., T ~ N^3. This number can be substantially reduced using preliminary rounds where teams play a small number of games and subsequently, only the top teams advance to the next round. When there are k rounds, the total number of games needed for the best team to emerge as champion, T_k, scales as follows, T_k ~N^(\gamma_k) with gamma_k=1/[1-(2/3)^(k+1)]. For example, gamma_k=9/5,27/19,81/65 for k=1,2,3. These results suggest an algorithm for how to infer the best team using a schedule that is linear in N. We conclude that league format is an ineffective method of determining the best team, and that sequential elimination from the bottom up is fair and efficient.Comment: 6 pages, 3 figure

Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients

Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9$1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1$1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8$50,000 per life-year saved. Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development

Evaluation of mechanisms of hot and cold days in climate models over Central Europe

Changes in intensity, frequency, and location of temperature extreme events are a focus for many studies that often rely on simulations from climate models to assess changes in temperature extremes. Given the use of climate models for attributing such events to human and natural influences and for projecting future changes, an assessment of the capability of climate models to properly simulate the mechanisms associated with temperature extreme events is necessary. In this study, known mechanisms and relevant meteorological variables are explored in a composite analysis to identify and quantify a climatology of synoptic weather patterns related to hot and cold seasonal temperature extreme events over Central Europe. The analysis is based on extremes that recur once or several times per season for better sampling. Weather patterns from a selection of CMIP5 models are compared with patterns derived from the ERA interim reanalysis. The results indicate that climate models simulate mechanisms associated with temperature extreme events reasonably well, in particular circulation-based mechanisms. The amplitude and average length of events is assessed, where in some cases significant deviations from ERA interim are found. In three cases, the models have on average significantly more days per season with extreme events than ERA interim. Quantitative analyses of physical links between extreme temperature and circulation, relative humidity, and radiation reveal that the strength of the link between the temperature and the variables does not vary greatly from model to model and ERA interim

Quasielastic 12C(e,e'p) Reaction at High Momentum Transfer

We measured the 12C(e,e'p) cross section as a function of missing energy in parallel kinematics for (q,w) = (970 MeV/c, 330 MeV) and (990 MeV/c, 475 MeV). At w=475 MeV, at the maximum of the quasielastic peak, there is a large continuum (E_m > 50 MeV) cross section extending out to the deepest missing energy measured, amounting to almost 50% of the measured cross section. The ratio of data to DWIA calculation is 0.4 for both the p- and s-shells. At w=330 MeV, well below the maximum of the quasielastic peak, the continuum cross section is much smaller and the ratio of data to DWIA calculation is 0.85 for the p-shell and 1.0 for the s-shell. We infer that one or more mechanisms that increase with $\omega$ transform some of the single-nucleon-knockout into multinucleon knockout, decreasing the valence knockout cross section and increasing the continuum cross section.Comment: 14 pages, 7 figures, Revtex (multicol, prc and aps styles), to appear in Phys Rev

A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent