129 research outputs found

    Analytic Description of Critical Point Actinides in a Transition from Octupole Deformation to Octupole Vibrations

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    An analytic collective model in which the relative presence of the quadrupole and octupole deformations is determined by a parameter (phi_0), while axial symmetry is obeyed, is developed. The model [to be called the analytic quadrupole octupole axially symmetric model (AQOA)] involves an infinite well potential, provides predictions for energy and B(EL) ratios which depend only on phi_0, draws the border between the regions of octupole deformation and octupole vibrations in an essentially parameter-independent way, and describes well 226-Th and 226-Ra, for which experimental energy data are shown to suggest that they lie close to this border. The similarity of the AQOA results with phi_0=45 degrees for ground state band spectra and B(E2) transition rates to the predictions of the X(5) model is pointed out. Analytic solutions are also obtained for Davidson potentials, leading to the AQOA spectrum through a variational procedure.Comment: LaTeX, 27 pages, including 14 postscript figure

    Data-driven approach for creating synthetic electronic medical records

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    <p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p

    Moderators of Exercise Effects on Cancer-related Fatigue:A Meta-analysis of Individual Patient Data

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    PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCT) to investigate moderators of exercise intervention effects on cancer-related fatigue. METHODS: We used individual patient data from 31 exercise RCT worldwide, representing 4366 patients, of whom 3846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test. RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (β = -0.17; 95% confidence interval [CI], -0.22 to -0.12). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (βdifference = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration ≤12 wk showed larger effects on fatigue (β = -0.29; 95% CI, -0.39 to -0.20) than supervised interventions with a longer duration. CONCLUSIONS: In this individual patient data meta-analysis, we found statistically significant beneficial effects of exercise interventions on fatigue, irrespective of demographic and clinical characteristics. These findings support a role for exercise, preferably supervised exercise interventions, in clinical practice. Reasons for differential effects in duration require further exploration

    Dropout from exercise trials among cancer survivors—An individual patient data meta-analysis from the POLARIS study

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    Introduction: The number of randomized controlled trials (RCTs) investigating the effects of exercise among cancer survivors has increased in recent years; however, participants dropping out of the trials are rarely described. The objective of the present study was to assess which combinations of participant and exercise program characteristics were associated with dropout from the exercise arms of RCTs among cancer survivors. Methods: This study used data collected in the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) study, an international database of RCTs investigating the effects of exercise among cancer survivors. Thirty-four exercise trials, with a total of 2467 patients without metastatic disease randomized to an exercise arm were included. Harmonized studies included a pre and a posttest, and participants were classified as dropouts when missing all assessments at the post-intervention test. Subgroups were identified with a conditional inference tree. Results: Overall, 9.6% of the participants dropped out. Five subgroups were identified in the conditional inference tree based on four significant associations with dropout. Most dropout was observed for participants with BMI &gt;28.4 kg/m2, performing supervised resistance or unsupervised mixed exercise (19.8% dropout) or had low-medium education and performed aerobic or supervised mixed exercise (13.5%). The lowest dropout was found for participants with BMI &gt;28.4 kg/m2 and high education performing aerobic or supervised mixed exercise (5.1%), and participants with BMI ≤28.4 kg/m2 exercising during (5.2%) or post (9.5%) treatment. Conclusions: There are several systematic differences between cancer survivors completing and dropping out from exercise trials, possibly affecting the external validity of exercise effects.</p

    Targeting exercise interventions to patients with cancer in need:An individual patient data meta-analysis

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    Background: Exercise effects in cancer patients often appear modest, possibly because interventions rarely target patients most in need. This study investigated the moderator effects of baseline values on the exercise outcomes of fatigue, aerobic fitness, muscle strength, quality of life (QoL), and self-reported physical function (PF) in cancer patients during and post-treatment. Methods: Individual patient data from 34 randomized exercise trials (n = 4519) were pooled. Linear mixed-effect models were used to study moderator effects of baseline values on exercise intervention outcomes and to determine whether these moderator effects differed by intervention timing (during vs post-treatment). All statistical tests were two-sided. Results: Moderator effects of baseline fatigue and PF were consistent across intervention timing, with greater effects in patients with worse fatigue (Pinteraction = .05) and worse PF (Pinteraction = .003). Moderator effects of baseline aerobic fitness, muscle strength, and QoL differed by intervention timing. During treatment, effects on aerobic fitness were greater for patients with better baseline aerobic fitness (Pinteraction = .002). Post-treatment, effects on upper (Pinteraction &lt; .001) and lower (Pinteraction = .01) body muscle strength and QoL (Pinteraction &lt; .001) were greater in patients with worse baseline values. Conclusion: Although exercise should be encouraged for most cancer patients during and post-treatments, targeting specific subgroups may be especially beneficial and cost effective. For fatigue and PF, interventions during and post-treatment should target patients with high fatigue and low PF. During treatment, patients experience benefit for muscle strength and QoL regardless of baseline values; however, only patients with low baseline values benefit post-treatment. For aerobic fitness, patients with low baseline values do not appear to benefit from exercise during treatment

    Activating mutation in MET oncogene in familial colorectal cancer

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    <p>Abstract</p> <p>Background</p> <p>In developed countries, the lifetime risk of developing colorectal cancer (CRC) is 5%, and it is the second leading cause of death from cancer. The presence of family history is a well established risk factor with 25-35% of CRCs attributable to inherited and/or familial factors. The highly penetrant inherited colon cancer syndromes account for approximately 5%, leaving greater than 20% without clear genetic definition. Familial colorectal cancer has been linked to chromosome 7q31 by multiple affected relative pair studies. The <it>MET </it>proto-oncogene which resides in this chromosomal region is considered a candidate for genetic susceptibility.</p> <p>Methods</p> <p><it>MET </it>exons were amplified by PCR from germline DNA of 148 affected sibling pairs with colorectal cancer. Amplicons with altered sequence were detected with high-resolution melt-curve analysis using a LightScanner (Idaho Technologies). Samples demonstrating alternative melt curves were sequenced. A TaqMan assay for the specific c.2975C <b>></b>T change was used to confirm this mutation in a cohort of 299 colorectal cancer cases and to look for allelic amplification in tumors.</p> <p>Results</p> <p>Here we report a germline non-synonymous change in the <it>MET </it>proto-oncogene at amino acid position T992I (also reported as <it>MET </it>p.T1010I) in 5.2% of a cohort of sibling pairs affected with CRC. This genetic variant was then confirmed in a second cohort of individuals diagnosed with CRC and having a first degree relative with CRC at prevalence of 4.1%. This mutation has been reported in cancer cells of multiple origins, including 2.5% of colon cancers, and in <1% in the general population. The threonine at amino acid position 992 lies in the tyrosine kinase domain of MET and a change to isoleucine at this position has been shown to promote metastatic behavior in cell-based models. The average age of CRC diagnosis in patients in this study is 63 years in mutation carriers, which is 8 years earlier than the general population average for CRC.</p> <p>Conclusions</p> <p>Although the <it>MET </it>p.T992I genetic mutation is commonly found in somatic colorectal cancer tissues, this is the first report also implicating this <it>MET </it>genetic mutation as a germline inherited risk factor for familial colorectal cancer. Future studies on the cancer risks associated with this mutation and the prevalence in different at-risk populations will be an important extension of this work to define the clinical significance.</p

    Expression analysis of asthma candidate genes during human and murine lung development

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    <p>Abstract</p> <p>Background</p> <p>Little is known about the role of most asthma susceptibility genes during human lung development. Genetic determinants for normal lung development are not only important early in life, but also for later lung function.</p> <p>Objective</p> <p>To investigate the role of expression patterns of well-defined asthma susceptibility genes during human and murine lung development. We hypothesized that genes influencing normal airways development would be over-represented by genes associated with asthma.</p> <p>Methods</p> <p>Asthma genes were first identified via comprehensive search of the current literature. Next, we analyzed their expression patterns in the developing human lung during the pseudoglandular (gestational age, 7-16 weeks) and canalicular (17-26 weeks) stages of development, and in the complete developing lung time series of 3 mouse strains: A/J, SW, C57BL6.</p> <p>Results</p> <p>In total, 96 genes with association to asthma in at least two human populations were identified in the literature. Overall, there was no significant over-representation of the asthma genes among genes differentially expressed during lung development, although trends were seen in the human (Odds ratio, OR 1.22, confidence interval, CI 0.90-1.62) and C57BL6 mouse (OR 1.41, CI 0.92-2.11) data. However, differential expression of some asthma genes was consistent in both developing human and murine lung, e.g. <it>NOD1, EDN1, CCL5, RORA </it>and <it>HLA-G</it>. Among the asthma genes identified in genome wide association studies, <it>ROBO1</it>, <it>RORA, HLA-DQB1, IL2RB </it>and <it>PDE10A </it>were differentially expressed during human lung development.</p> <p>Conclusions</p> <p>Our data provide insight about the role of asthma susceptibility genes during lung development and suggest common mechanisms underlying lung morphogenesis and pathogenesis of respiratory diseases.</p

    Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study

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    Introduction: The use of anti-retroviral therapy (ART) has dramatically reduced HIV-1 associated morbidity and mortality. However, HIV-1 infected individuals have increased rates of morbidity and mortality compared to the non-HIV-1 infected population and this appears to be related to end-organ diseases collectively referred to as Serious Non-AIDS Events (SNAEs). Circulating miRNAs are reported as promising biomarkers for a number of human disease conditions including those that constitute SNAEs. Our study sought to investigate the potential of selected miRNAs in predicting mortality in HIV-1 infected ART treated individuals. Materials and Methods: A set of miRNAs was chosen based on published associations with human disease conditions that constitute SNAEs. This case: control study compared 126 cases (individuals who died whilst on therapy), and 247 matched controls (individuals who remained alive). Cases and controls were ART treated participants of two pivotal HIV-1 trials. The relative abundance of each miRNA in serum was measured, by RTqPCR. Associations with mortality (all-cause, cardiovascular and malignancy) were assessed by logistic regression analysis. Correlations between miRNAs and CD4+ T cell count, hs-CRP, IL-6 and D-dimer were also assessed. Results: None of the selected miRNAs was associated with all-cause, cardiovascular or malignancy mortality. The levels of three miRNAs (miRs -21, -122 and -200a) correlated with IL-6 while miR-21 also correlated with D-dimer. Additionally, the abundance of miRs -31, -150 and -223, correlated with baseline CD4+ T cell count while the same three miRNAs plus miR- 145 correlated with nadir CD4+ T cell count. Discussion: No associations with mortality were found with any circulating miRNA studied. These results cast doubt onto the effectiveness of circulating miRNA as early predictors of mortality or the major underlying diseases that contribute to mortality in participants treated for HIV-1 infection
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