The Mediational Role of Coping Strategies in the Relationship Between Self-Esteem and Risk of Internet Addiction

The aim of the present study is to explore, through a mediation model, the relationship among self-esteem, coping strategies, and the risk of Internet addiction in a sample of 300 Italian university students. We submitted the data to a descriptive, mediational comparison between variables (t-test), and correlational statistical analyses. The results confirmed the effect of self-esteem on the risk of Internet addiction. However, we found that the introduction of coping strategies as a mediator gives rise to partial mediation. A low level of self-esteem is a predictor of avoidance-oriented coping that, in turn, affects the risk of Internet addiction

Cooling to the Ground State of Axial Motion for One Atom Strongly Coupled to an Optical Cavity

Localization to the ground state of axial motion is demonstrated for a single, trapped atom strongly coupled to the field of a high finesse optical resonator. The axial atomic motion is cooled by way of coherent Raman transitions on the red vibrational sideband. An efficient state detection scheme enabled by strong coupling in cavity QED is used to record the Raman spectrum, from which the state of atomic motion is inferred. We find that the lowest vibrational level of the axial potential with zero-point energy 13uK is occupied with probability P0~0.95.Comment: 5 pages, 4 figure

Optical pumping via incoherent Raman transitions

A new optical pumping scheme is presented that uses incoherent Raman transitions to prepare a trapped Cesium atom in a specific Zeeman state within the 6S_{1/2}, F=3 hyperfine manifold. An important advantage of this scheme over existing optical pumping schemes is that the atom can be prepared in any of the F=3 Zeeman states. We demonstrate the scheme in the context of cavity quantum electrodynamics, but the technique is equally applicable to a wide variety of atomic systems with hyperfine ground-state structure.Comment: 8 pages, 4 figure

Quantification and expert evaluation of evidence for chemopredictive biomarkers to personalize cancer treatment.

Predictive biomarkers have the potential to facilitate cancer precision medicine by guiding the optimal choice of therapies for patients. However, clinicians are faced with an enormous volume of often-contradictory evidence regarding the therapeutic context of chemopredictive biomarkers.We extensively surveyed public literature to systematically review the predictive effect of 7 biomarkers claimed to predict response to various chemotherapy drugs: ERCC1-platinums, RRM1-gemcitabine, TYMS-5-fluorouracil/Capecitabine, TUBB3-taxanes, MGMT-temozolomide, TOP1-irinotecan/topotecan, and TOP2A-anthracyclines. We focused on studies that investigated changes in gene or protein expression as predictors of drug sensitivity or resistance. We considered an evidence framework that ranked studies from high level I evidence for randomized controlled trials to low level IV evidence for pre-clinical studies and patient case studies.We found that further in-depth analysis will be required to explore methodological issues, inconsistencies between studies, and tumor specific effects present even within high evidence level studies. Some of these nuances will lend themselves to automation, others will require manual curation. However, the comprehensive cataloging and analysis of dispersed public data utilizing an evidence framework provides a high level perspective on clinical actionability of these protein biomarkers. This framework and perspective will ultimately facilitate clinical trial design as well as therapeutic decision-making for individual patients