Supernova / Acceleration Probe: A Satellite Experiment to Study the Nature of the Dark Energy

The Supernova / Acceleration Probe (SNAP) is a proposed space-based experiment designed to study the dark energy and alternative explanations of the acceleration of the Universe's expansion by performing a series of complementary systematics-controlled measurements. We describe a self-consistent reference mission design for building a Type Ia supernova Hubble diagram and for performing a wide-area weak gravitational lensing study. A 2-m wide-field telescope feeds a focal plane consisting of a 0.7 square-degree imager tiled with equal areas of optical CCDs and near infrared sensors, and a high-efficiency low-resolution integral field spectrograph. The SNAP mission will obtain high-signal-to-noise calibrated light-curves and spectra for several thousand supernovae at redshifts between z=0.1 and 1.7. A wide-field survey covering one thousand square degrees resolves ~100 galaxies per square arcminute. If we assume we live in a cosmological-constant-dominated Universe, the matter density, dark energy density, and flatness of space can all be measured with SNAP supernova and weak-lensing measurements to a systematics-limited accuracy of 1%. For a flat universe, the density-to-pressure ratio of dark energy can be similarly measured to 5% for the present value w0 and ~0.1 for the time variation w'. The large survey area, depth, spatial resolution, time-sampling, and nine-band optical to NIR photometry will support additional independent and/or complementary dark-energy measurement approaches as well as a broad range of auxiliary science programs. (Abridged)Comment: 40 pages, 18 figures, submitted to PASP, http://snap.lbl.go

Orbital effects of a monochromatic plane gravitational wave with ultra-low frequency incident on a gravitationally bound two-body system

We analytically compute the long-term orbital variations of a test particle orbiting a central body acted upon by an incident monochromatic plane gravitational wave. We assume that the characteristic size of the perturbed two-body system is much smaller than the wavelength of the wave. Moreover, we also suppose that the wave's frequency is much smaller than the particle's orbital one. We make neither a priori assumptions about the direction of the wavevector nor on the orbital geometry of the planet. We find that, while the semi-major axis is left unaffected, the eccentricity, the inclination, the longitude of the ascending node, the longitude of pericenter and the mean anomaly undergo non-vanishing long-term changes. They are not secular trends because of the slow modulation introduced by the tidal matrix coefficients and by the orbital elements themselves. They could be useful to indepenedently constrain the ultra-low frequency waves which may have been indirectly detected in the BICEP2 experiment. Our calculation holds, in general, for any gravitationally bound two-body system whose characteristic frequency is much larger than the frequency of the external wave. It is also valid for a generic perturbation of tidal type with constant coefficients over timescales of the order of the orbital period of the perturbed particle.Comment: LaTex2e, 24 pages, no figures, no tables. Changes suggested by the referees include

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

Clinical and Genetic Risk Factors for Adverse Metabolic Outcomes in North American Testicular Cancer Survivors

Background: Testicular cancer survivors (TCS) are at significantly increased risk for cardiovascular disease (CVD), with metabolic syndrome (MetS) an established risk factor. No study has addressed clinical and genetic MetS risk factors in North American TCS. Patients and Methods: TCS were aged <55 years at diagnosis and received first-line chemotherapy. Patients underwent physical examination, and had lipid panels, testosterone, and soluble cell adhesion molecule-1 (sICAM-1) evaluated. A single nucleotide polymorphism in rs523349 (5-α-reductase gene, SRD5A2), recently implicated in MetS risk, was genotyped. Using standard criteria, MetS was defined as ≥3 of the following: hypertension, abdominal obesity, hypertriglyceridemia, decreased high-density lipoprotein (HDL) cholesterol level, and diabetes. Matched controls were derived from the National Health and Nutrition Examination Survey. Results: We evaluated 486 TCS (median age, 38.1 years). TCS had a higher prevalence of hypertension versus controls (43.2% vs 30.7%; P<.001) but were less likely to have decreased HDL levels (23.7% vs 34.8%; P<.001) or abdominal obesity (28.2% vs 40.1%; P<.001). Overall MetS frequency was similar in TCS and controls (21.0% vs 22.4%; P=.59), did not differ by treatment (P=.20), and was not related to rs523349 (P=.61). For other CVD risk factors, TCS were significantly more likely to have elevated low-density lipoprotein (LDL) cholesterol levels (17.7% vs 9.3%; P<.001), total cholesterol levels (26.3% vs 11.1%; P<.001), and body mass index ≥25 kg/m2 (75.1% vs 69.1%; P=.04). On multivariate analysis, age at evaluation (P<.001), testosterone level ≤3.0 ng/mL (odds ratio [OR], 2.06; P=.005), and elevated sICAM-1 level (ORhighest vs lowest quartile, 3.58; P=.001) were significantly associated with MetS. Conclusions and Recommendations: Metabolic abnormalities in TCS are characterized by hypertension and increased LDL and total cholesterol levels but lower rates of decreased HDL levels and abdominal obesity, signifying possible shifts in fat distribution and fat metabolism. These changes are accompanied by hypogonadism and inflammation. TCS have a high prevalence of CVD risk factors that may not be entirely captured by standard MetS criteria. Cancer treatment–associated MetS requires further characterization

Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries

Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

A phase II study of medroxyprogesterone acetate in patients with hormone receptor negative metastatic breast cancer: translational breast cancer research consortium trial 007

Preclinical data suggest that medroxyprogesterone acetate (MPA) has both anti-metastatic and anti-angiogenic activity in the absence of hormone receptors (HR). This phase II trial assessed the activity of MPA alone or in combination with low-dose chemotherapy in patients with metastatic HR-negative breast cancer. Postmenopausal women with HR-negative disease were eligible if they had not received more than 3 chemotherapy regimens for metastatic disease. All patients were treated with MPA 1,000–1,500 mg/day orally; patients in cohort two also received low-dose oral cyclophosphamide and methotrexate (ldCM, 50 mg/day and 2.5 mg twice daily on Days 1 and 2 each week). Tissue and circulating biomarkers were assessed serially. The primary endpoint was clinical benefit response defined as objective response or stable disease >6 months. Thirty patients were enrolled (14 MPA monotherapy; 16 MPA + ldCM); median age was 55 (35–80); nearly all had visceral involvement. Despite dose escalation in 90 % of patients, only 17 (57 %) patients ever achieved MPA trough concentrations >50 ng/ml. One patient developed grade 4 renal failure in the setting of rapid disease progression and dehydration. There were no objective responses. One patient in each cohort (~7 %) had stable disease for > 6 months. Skin Nm23 expression increased after 4 weeks of MPA + ldCM, but there were no significant changes in TSP-1, PAI-1 antigen, or PAI-1 activity. MPA had limited activity and does not warrant further development in patients with HR-negative advanced breast cancer. Poor bioavailability limited exposure despite dose escalation

Spatial scales of COVID-19 transmission in Mexico

During outbreaks of emerging infectious diseases, internationally connected cities often experience large and early outbreaks, while rural regions follow after some delay. This hierarchical structure of disease spread is influenced primarily by the multiscale structure of human mobility. However, during the COVID-19 epidemic, public health responses typically did not take into consideration the explicit spatial structure of human mobility when designing nonpharmaceutical interventions (NPIs). NPIs were applied primarily at national or regional scales. Here, we use weekly anonymized and aggregated human mobility data and spatially highly resolved data on COVID-19 cases at the municipality level in Mexico to investigate how behavioral changes in response to the pandemic have altered the spatial scales of transmission and interventions during its first wave (March–June 2020). We find that the epidemic dynamics in Mexico were initially driven by exports of COVID-19 cases from Mexico State and Mexico City, where early outbreaks occurred. The mobility network shifted after the implementation of interventions in late March 2020, and the mobility network communities became more disjointed while epidemics in these communities became increasingly synchronized. Our results provide dynamic insights into how to use network science and epidemiological modeling to inform the spatial scale at which interventions are most impactful in mitigating the spread of COVID-19 and infectious diseases in general