Off-Diagonal Hyperfine Interaction and Parity Non-conservation in Cesium

We have performed relativistic many-body calculations of the hyperfine interaction in the $6s$ and $7s$ states of Cs, including the off-diagonal matrix element. The calculations were used to determine the accuracy of the semi-empirical formula for the electromagnetic transition amplitude $$ induced by the hyperfine interaction. We have found that even though the contribution of the many-body effects into the matrix elements is very large, the square root formula $= \sqrt{ }$ remains valid to the accuracy of a fraction of $10^{-3}$. The result for the M1-amplitude is used in the interpretation of the parity-violation measurement in the $6s-7s$ transition in Cs which claims a possible deviation from the Standard model.Comment: 13 pages, 4 figures, LaTeX, Submitted to Phys. Rev.

Calculations of parity nonconserving s-d transitions in Cs, Fr, Ba II, and Ra II

We have performed ab initio mixed-states and sum-over-states calculations of parity nonconserving (PNC) electric dipole (E1) transition amplitudes between s-d electron states of Cs, Fr, Ba II, and Ra II. For the lower states of these atoms we have also calculated energies, E1 transition amplitudes, and lifetimes. We have shown that PNC E1 transition amplitudes between s-d states can be calculated to high accuracy. Contrary to the Cs 6s-7s transition, in these transitions there are no strong cancelations between different terms in the sum-over-states approach. In fact, there is one dominating term which deviates from the sum by less than 20%. This term corresponds to an s-p_{1/2} weak matrix element, which can be calculated to better than 1%, and a p_{1/2}-d_{3/2} E1 transition amplitude, which can be measured. Also, the s-d amplitudes are about four times larger than the corresponding s-s transitions. We have shown that by using a hybrid mixed-states/sum-over-states approach the accuracy of the calculations of PNC s-d amplitudes could compete with that of Cs 6s-7s if p_{1/2}-d_{3/2} E1 amplitudes are measured to high accuracy.Comment: 15 pages, 8 figures, submitted to Phys. Rev.

High accuracy calculation of 6s -> 7s parity nonconserving amplitude in Cs

We calculated the parity nonconserving (PNC) 6s -> 7s amplitude in Cs. In the Dirac-Coulomb approximation our result is in a good agreement with other calculations. Breit corrections to the PNC amplitude and to the Stark-induced amplitude $\beta$ are found to be -0.4% and -1% respectively. The weak charge of $^{133}$Cs is $Q_W=-72.5 \pm 0.7$ in agreement with the standard model.Comment: 4 pages, LaTeX2e, uses revtex4.cls, submitted to PR

Emerging uses of patient generated health data in clinical research

Recent advancements in consumer directed personal computing technology have led to the generation of biomedically-relevant data streams with potential health applications. This has catalyzed international interest in Patient Generated Health Data (PGHD), defined as "health-related data - including health history, symptoms, biometric data, treatment history, lifestyle choices, and other information-created, recorded, gathered, or inferred by or from patients or their designees (i.e. care partners or those who assist them) to help address a health concern."(Shapiro et al., 2012) PGHD offers several opportunities to improve the efficiency and output of clinical trials, particularly within oncology. These range from using PGHD to understand mechanisms of action of therapeutic strategies, to understanding and predicting treatment-related toxicity, to designing interventions to improve adherence and clinical outcomes. To facilitate the optimal use of PGHD, methodological research around considerations related to feasibility, validation, measure selection, and modeling of PGHD streams is needed. With successful integration, PGHD can catalyze the application of "big data" to cancer clinical research, creating both "n of 1" and population-level observations, and generating new insights into the nature of health and disease

Measurement of the 6S-7S transition polarizablility in atomic cesium and an improved test of the standard model

The ratio of the off-diagonal hyperfine amplitude to the tensor transition polarizability (Mhf/beta) for the 6S-7S transition in cesium has been measured. The value of beta=27.024(43)(expt)(67)(theory)a_0^3 is then obtained using an accurate semi-empirical value of Mhf. This is combined with a previous measurement of parity nonconservation in atomic cesium and previous atomic structure calculations to determine the value of the weak charge. The uncertainties in the atomic structure calculations are updated (and reduced) in light of new experimental tests. The result Q_W=-72.06(28)(expt) (34)(theory) differs from the prediction of the standard model of elementary particle physics by 2.5 sigma.Comment: 12 pages, 1 figur

Evolutionary adaptation of an AraC-like regulatory protein in Citrobacter rodentium and Escherichia species

© 2015, American Society for Microbiology. The evolution of pathogenic bacteria is a multifaceted and complex process, which is strongly influenced by the horizontal acquisition of genetic elements and their subsequent expression in their new hosts. A well-studied example is the RegA regulon of the enteric pathogen Citrobacter rodentium. The RegA regulatory protein is a member of the AraC/XylS superfamily, which coordinates the expression of a gene repertoire that is necessary for full pathogenicity of this murine pathogen. Upon stimulation by an exogenous, gut-associated signal, namely, bicarbonate ions, RegA activates the expression of a series of genes, including virulence factors, such as autotransporters, fimbriae, a dispersin-like protein, and the grlRA operon on the locus of enterocyte effacement pathogenicity island. Interestingly, the genes encoding RegA homologues are distributed across the genus Escherichia, encompassing pathogenic and nonpathogenic subtypes. In this study, we carried out a series of bioinformatic, transcriptional, and functional analyses of the RegA regulons of these bacteria. Our results demonstrated that regA has been horizontally transferred to Escherichia spp. and C. rodentium. Comparative studies of two RegA homologues, namely, those from C. rodentium and E. coli SMS-3-5, a multiresistant environmental strain of E. coli, showed that the two regulators acted similarly in vitro but differed in terms of their abilities to activate the virulence of C. rodentium in vivo, which evidently was due to their differential activation of grlRA. Our data indicate that RegA from C. rodentium has strain-specific adaptations that facilitate infection of its murine host. These findings shed new light on the development of virulence by C. rodentium and on the evolution of virulence- regulatory genes of bacterial pathogens in general

Precise calculation of parity nonconservation in cesium and test of the standard model

We have calculated the 6s-7s parity nonconserving (PNC) E1 transition amplitude, E_{PNC}, in cesium. We have used an improved all-order technique in the calculation of the correlations and have included all significant contributions to E_{PNC}. Our final value E_{PNC} = 0.904 (1 +/- 0.5 %) \times 10^{-11}iea_{B}(-Q_{W}/N) has half the uncertainty claimed in old calculations used for the interpretation of Cs PNC experiments. The resulting nuclear weak charge Q_{W} for Cs deviates by about 2 standard deviations from the value predicted by the standard model.Comment: 24 pages, 8 figure

The project data sphere initiative: accelerating cancer research by sharing data

Background. In this paper, we provide background and context regarding the potential for a new data-sharing platform, the Project Data Sphere (PDS) initiative, funded by financial and in-kind contributions from the CEO Roundtable on Cancer, to transform cancer research and improve patient outcomes. Given the relatively modest decline in cancer death rates over the past several years, a new research paradigm is needed to accelerate therapeutic approaches for oncologic diseases. Phase III clinical trials generate large volumes of potentially usable information, often on hundreds of patients, including patients treated with standard of care therapies (i.e., controls). Both nationally and internationally, a variety of stakeholders have pursued data-sharing efforts to make individual patient-level clinical trial data available to the scientific research community. Potential Benefits and Risks of Data Sharing. For researchers, shared data have the potential to foster a more collaborative environment, to answer research questions in a shorter time frame than traditional randomized control trials, to reduce duplication of effort, and to improve efficiency. For industry participants, use of trial data to answer additional clinical questions could increase research and development efficiency and guide future projects through validation of surrogate end points, development of prognostic or predictive models, selection of patients for phase II trials, stratification in phase III studies, and identification of patient subgroups for development of novel therapies. Data transparency also helps promote a public image of collaboration and altruism among industry participants. For patient participants, data sharing maximizes their contribution to public health and increases access to information that may be used to develop better treatments. Concerns about data-sharing efforts include protection of patient privacy and confidentiality. To alleviate these concerns, data sets are deidentified to maintain anonymity. To address industry concerns about protection of intellectual property and competitiveness, we illustrate several models for data sharing with varying levels of access to the data and varying relationships between trial sponsors and data access sponsors. The Project Data Sphere Initiative. PDS is an independent initiative of the CEO Roundtable on Cancer Life Sciences Consortium, built to voluntarily share, integrate, and analyze comparator arms of historical cancer clinical trial data sets to advance future cancer research. The aim is to provide a neutral, broad-access platform for industry and academia to share raw, deidentified data from late-phase oncology clinical trials using comparator-arm data sets. These data are likely to be hypothesis generating or hypothesis confirming but, notably, do not take the place of performing a well-designed trial to address a specific hypothesis. Prospective providers of data to PDS complete and sign a data sharing agreement that includes a description of the data they propose to upload, and then they follow easy instructions on the website for uploading their deidentified data. The SAS Institute has also collaborated with the initiative to provide intrinsic analytic tools accessible within the website itself. As of October 2014, the PDS website has available data from 14 cancer clinical trials covering 9,000 subjects, with hopes to further expand the database to include more than 25,000 subject accruals within the next year. PDS differentiates itself from other data-sharing initiatives by its degree of openness, requiring submission of only a brief application with background information of the individual requesting access and agreement to terms of use. Data from several different sponsors may be pooled to develop a comprehensive cohort for analysis. In order to protect patient privacy, data providers in the U.S. are responsible for deidentifying data according to standards set forth by the Privacy Rule of the U.S. Health Insurance Portability and Accountability Act of 1996. Using Data Sharing to Improve Outcomes in Cancer: The “Prostate Cancer Challenge.” Control-arm data of several studies among patients with metastatic castration-resistant prostate cancer (mCRPC) are currently available through PDS. These data sets have multiple potential uses. The “Prostate Cancer Challenge” will ask the cancer research community to use clinical trial data deposited in the PDS website to address key research questions regarding mCRPC. General themes that could be explored by the cancer community are described in this article: prognostic models evaluating the influence of pretreatment factors on survival and patient-reported outcomes; comparative effectiveness research evaluating the efficacy of standard of care therapies, as illustrated in our companion article comparing mitoxantrone plus prednisone with prednisone alone; effects of practice variation in dose, frequency, and duration of therapy; level of patient adherence to elements of trial protocols to inform the design of future clinical trials; and age of subjects, regional differences in health care, and other confounding factors that might affect outcomes. Potential Limitations and Methodological Challenges. The number of data sets available and the lack of experimental arm data limit the potential scope of research using the current PDS. The number of trials is expected to grow exponentially over the next year and may include multiple cancer settings, such as breast, colorectal, lung, hematologic malignancy, and bone marrow transplantation. Other potential limitations include the retrospective nature of the data analyses performed using PDS and its generalizability, given that clinical trials are often conducted among younger, healthier, and less racially diverse patient populations. Methodological challenges exist when combining individual patient data from multiple clinical trials; however, advancements in statistical methods for secondary database analysis offer many tools for reanalyzing data arising from disparate trials, such as propensity score matching. Despite these concerns, few if any comparable data sets include this level of detail across multiple clinical trials and populations. Conclusion. Access to large, late-phase, cancer-trial data sets has the potential to transform cancer research by optimizing research efficiency and accelerating progress toward meaningful improvements in cancer care. This type of platform provides opportunities for unique research projects that can examine relatively neglected areas and that can construct models necessitating large amounts of detailed data.The full potential of PDS will be realized only when multiple tumor types and larger numbers of data sets are available through the website

Osculating and neighbour-avoiding polygons on the square lattice

We study two simple modifications of self-avoiding polygons. Osculating polygons are a super-set in which we allow the perimeter of the polygon to touch at a vertex. Neighbour-avoiding polygons are only allowed to have nearest neighbour vertices provided these are joined by the associated edge and thus form a sub-set of self-avoiding polygons. We use the finite lattice method to count the number of osculating polygons and neighbour-avoiding polygons on the square lattice. We also calculate their radius of gyration and the first area-weighted moment. Analysis of the series confirms exact predictions for the critical exponents and the universality of various amplitude combinations. For both cases we have found exact solutions for the number of convex and almost-convex polygons.Comment: 14 pages, 5 figure

Evaluation of pedometry as a patient-centered outcome in patients undergoing hematopoietic cell transplant (HCT): A comparison of pedometry and patient-reports of symptoms, health, and quality of life.

Aims We evaluated pedometry as a novel patient-centered outcome because it enables passive continuous assessment of activity and may provide information about the consequences of symptomatic toxicity complementary to self-report. Methods Adult patients undergoing hematopoietic cell transplant (HCT) wore pedometers and completed PRO assessments during transplant hospitalization (4 weeks) and 4 weeks post-discharge. Patient reports of symptomatic treatment toxicities (single items from PROCTCAE, http://healthcaredelivery.cancer.gov/pro-ctcae) and symptoms, physical health, mental health, and quality of life (PROMIS Global-10, http://nih.promis.org), assessed weekly with 7-day recall on Likert scales, were compared individually with pedometry data, summarized as average daily steps per week, using linear mixed models. Results Thirty-two patients [mean age 55 (SD = 14), 63 % male, 84 % white, 56 % autologous, 43 % allogeneic] completed a mean 4.6 (SD = 1.5, range 1–8) evaluable assessments. Regression model coefficients (β) indicated within-person decrements in average daily steps were associated with increases in pain (β = -852; 852 fewer steps per unit increase in pain score, p<0.001), fatigue (β = -886, p<0.001), vomiting (β = -518, p<0.01), shaking/chills (β = -587, p<0.01), diarrhea (β = -719, p<0.001), shortness of breath (β = -1018, p<0.05), reduction in carrying out social activities (β = 705, p<0.01) or physical activities (β = 618, p<0.01), and global physical health (β = 101, p<0.001), but not global mental health or quality of life. Conclusions In this small sample of HCT recipients, more severe symptoms, impaired physical health, and restrictions in the performance of usual daily activities were associated with statistically significant decrements in objectively measured daily steps. Pedometry may be a valuable outcome measure and validation anchor in clinical research