Stochastic Norton-Simon-Massagu\ue9 Tumor Growth Modeling: Controlled and Mixed-Effects Uncontrolled Analysis

Tumorigenesis is a complex process that is heterogeneous and affected by numerous sources of variability. This study presents a stochastic extension of a biologically grounded tumor growth model, referred to as the Norton-Simon-Massagu\ue9 (NSM) tumor growth model. We first study the uncontrolled version of the model where the effect of chemotherapeutic drug agent is absent. Conditions on the model\u2019s parameters are derived to guarantee the positivity of the tumor volume and hence the validity of the proposed stochastic NSM model. To calibrate the proposed model we utilize a maximum likelihood- based estimation algorithm and population mixed-effect modeling formulation. The algorithm is tested by fitting previously published tumor volume mice data. Then, we study the controlled version of the model which includes the effect of chemotherapy treatment. Analysis of the influence of adding the control drug agent into the model and how sensitive it is to the stochastic parameters is performed both in open-loop and closed-loop viewpoints through different numerical simulations

Search for lepton flavor violating decays of a heavy neutral particle in p-pbar collisions at root(s)=1.8 TeV

We report on a search for a high mass, narrow width particle that decays directly to e+mu, e+tau, or mu+tau. We use approximately 110 pb^-1 of data collected with the Collider Detector at Fermilab from 1992 to 1995. No evidence of lepton flavor violating decays is found. Limits are set on the production and decay of sneutrinos with R-parity violating interactions.Comment: Figure 2 fixed. Reference 4 fixed. Minor changes to tex

Evaluation of patients with a recent clinical fracture and osteoporosis, a multidisciplinary approach

The aetiology of osteoporotic fractures is multifactorial, but little is known about the way to evaluate patients with a recent clinical fracture for the presence of secondary osteoporosis

Psychosocial factors and health as determinants of quality of life in community-dwelling older adults.

PURPOSE: It is important to understand the determinants of differences in quality of life in old age and to include a wide range of possible predictors. The present study investigated the determinants of quality of life in two groups of older adults for whom there was an unusually informative set of possible predictor variables. METHOD: Participants were members of the Lothian Birth Cohorts of 1921 (n = 550) or 1936 (n = 1,091). Four facets of quality of life (QoL) and general QoL were measured using the WHOQOL-BREF. Possible determinants included personality traits, measured with the International Personality Item Pool (IPIP) scales; childhood and old age general cognitive ability, measured with the Moray House Test; minor psychological symptoms, measured with the Hospital Anxiety and Depression Scale (HADS); physical health, assessed by grip strength and cardiovascular disease history; and sociodemographic factors, assessed by interview. RESULTS: Linear regression analyses revealed that HADS depression had the greatest influence on quality of life. Personality traits, most notably Emotional Stability, also predicted quality of life to varying degrees, along with factors reflecting current life circumstances. There were differences between the two cohorts in the variables which predicted quality of life. There were different, conceptually relevant, contributions to the different QoL facets. CONCLUSIONS: Personality traits and minor depressive symptoms have an important influence on self-reported quality of life in old age. Quality of life may be influenced more by current than past circumstances, and this relationship may change with age

Risk and resilience in gifted young people from low socio-economic backgrounds

Gifted and talented young people from low socio-economic backgrounds are consistently under-represented in gifted programmes in New Zealand schools. This chapter reports on a qualitative study that explored the lived experiences of 101 gifted New Zealand young people from low socio-economic back-grounds. An overarching question for this study was ‘What is it about gifted young people from low socio-economic backgrounds who have achieved to exceptional levels, that has enabled them to do so?’ The risk and resilience construct was used as a lens through which to explore their experiences across a range of contexts. These young people reflected on their perceptions of their giftedness and socio-economic circumstances, their childhoods and school ex-periences, and their home lives. The stories of the participants in this study in-dicated that there are particular risks associated with both giftedness and low socio-economic status, and contribute to ideas about how these young people might be more effectively supported to develop their potential

Momentum distribution of charged particles in jets in dijet events in p(p)over-bar collisions at root s=1.8 TeV and comparisons to perturbative QCD predictions

Inclusive momentum distributions of charged particles in restricted cones around jet axes were measured in dijet events with invariant dijet masses in the range 80 to 600 GeV/c(2). Events were produced at the Fermilab Tevatron in p (p) over bar collisions with a center of mass energy of 1.8 TeV and recorded by the Collider Detector at Fermilab. The results were compared to perturbative QCD calculations carried out in the framework of the modified leading log approximation (MLLA) and assuming local parton-hadron duality. It was shown that the data follow theoretical predictions quite well over the whole range of the jet energies included in this analysis. We extracted the MLLA cutoff scale Q(eff) and found a value of 230+/-40 MeV. The theoretical prediction of E(jet)sin theta(c) scaling, where theta(c) is the cone opening angle, was experimentally observed for the first time. From the MLLA fits to the data, two more parameters were extracted: the ratio of parton multiplicities in gluon and quark jets, r=N-partons(g-jet)/N-partons(q-jet)=1.9+/-0.5, and the ratio of the number of charged hadrons to the number of predicted partons in a jet, K-LPHD(charged)=N-hadrons(charged)/N-partons=0.56+/-0.10