A molecular map of mesenchymal tumors

Background Bone and soft tissue tumors represent a diverse group of neoplasms thought to derive from cells of the mesenchyme or neural crest. Histological diagnosis is challenging due to the poor or heterogenous differentiation of many tumors, resulting in uncertainty over prognosis and appropriate therapy. Results We have undertaken a broad and comprehensive study of the gene expression profile of 96 tumors with representatives of all mesenchymal tissues, including several problem diagnostic groups. Using machine learning methods adapted to this problem we identify molecular fingerprints for most tumors, which are pathognomonic (decisive) and biologically revealing. Conclusion We demonstrate the utility of gene expression profiles and machine learning for a complex clinical problem, and identify putative origins for certain mesenchymal tumor

Molecular dynamics simulations of vibrated granular gases

We present molecular dynamics simulations of mono- or bidisperse inelastic granular gases driven by vibrating walls, in two dimensions (without gravity). Because of the energy injection at the boundaries, a situation often met experimentally, density and temperature fields display heterogeneous profiles in the direction perpendicular to the walls. A general equation of state for an arbitrary mixture of fluidized inelastic hard spheres is derived and successfully tested against numerical data. Single-particle velocity distribution functions with non-Gaussian features are also obtained, and the influence of various parameters (inelasticity coefficients, density...) analyzed. The validity of a recently proposed Random Restitution Coefficient model is assessed through the study of projected collisions onto the direction perpendicular to that of energy injection. For the binary mixture, the non-equipartition of translational kinetic energy is studied and compared both to experimental data and to the case of homogeneous energy injection (``stochastic thermostat''). The rescaled velocity distribution functions are found to be very similar for both species

Robust Henderson III estimators of variance components in the nested error model

Common methods for estimating variance components in Linear Mixed Models include Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML). These methods are based on the strong assumption of multivariate normal distribution and it is well know that they are very sensitive to outlying observations with respect to any of the random components. Several robust altematives of these methods have been proposed (e.g. Fellner 1986, Richardson and Welsh 1995). In this work we present several robust alternatives based on the Henderson method III which do not rely on the normality assumption and provide explicit solutions for the variance components estimators. These estimators can later be used to derive robust estimators of regression coefficients. Finally, we describe an application of this procedure to small area estimation, in which the main target is the estimation of the means of areas or domains when the within-area sample sizes are small

Renormalized Path Integral for the Two-Dimensional Delta-Function Interaction

A path-integral approach for delta-function potentials is presented. Particular attention is paid to the two-dimensional case, which illustrates the realization of a quantum anomaly for a scale invariant problem in quantum mechanics. Our treatment is based on an infinite summation of perturbation theory that captures the nonperturbative nature of the delta-function bound state. The well-known singular character of the two-dimensional delta-function potential is dealt with by considering the renormalized path integral resulting from a variety of schemes: dimensional, momentum-cutoff, and real-space regularization. Moreover, compatibility of the bound-state and scattering sectors is shown.Comment: 26 pages. The paper was significantly expanded and numerous equations were added for the sake of clarity; the main results and conclusions are unchange

Specific heat and high-temperature series of lattice models: interpolation scheme and examples on quantum spin systems in one and two dimensions

We have developed a new method for evaluating the specific heat of lattice spin systems. It is based on the knowledge of high-temperature series expansions, the total entropy of the system and the low-temperature expected behavior of the specific heat as well as the ground-state energy. By the choice of an appropriate variable (entropy as a function of energy), a stable interpolation scheme between low and high temperature is performed. Contrary to previous methods, the constraint that the total entropy is log(2S+1) for a spin S on each site is automatically satisfied. We present some applications to quantum spin models on one- and two- dimensional lattices. Remarkably, in most cases, a good accuracy is obtained down to zero temperature.Comment: 10 pages (RevTeX 4) including 11 eps figures. To appear in Phys. Rev.

Association of Visual Impairment with Risk of Incident Dementia in a Women's Health Initiative Population

Importance: Dementia affects a large and growing population of older adults. Although past studies suggest an association between vision and cognitive impairment, there are limited data regarding longitudinal associations of vision with dementia. Objective: To evaluate associations between visual impairment and risk of cognitive impairment. Design, Setting, and Participants: A secondary analysis of a prospective longitudinal cohort study compared the likelihood of incident dementia or mild cognitive impairment (MCI) among women with and without baseline visual impairment using multivariable Cox proportional hazards regression models adjusting for characteristics of participants enrolled in Women's Health Initiative (WHI) ancillary studies. The participants comprised community-dwelling older women (age, 66-84 years) concurrently enrolled in WHI Sight Examination (enrollment 2000-2002) and WHI Memory Study (enrollment 1996-1998, ongoing). The study was conducted from 2000 to the present. Exposures: Objectively measured visual impairment at 3 thresholds (visual acuity worse than 20/40, 20/80, or 20/100) and self-reported visual impairment (determined using composite survey responses). Main Outcomes and Measures: Hazard ratios (HRs) and 95% CIs for incident cognitive impairment after baseline eye examination were determined. Cognitive impairment (probable dementia or MCI) was based on cognitive testing, clinical assessment, and centralized review and adjudication. Models for (1) probable dementia, (2) MCI, and (3) probable dementia or MCI were evaluated. Results: A total of 1061 women (mean [SD] age, 73.8 [3.7] years) were identified; 206 of these women (19.4%) had self-reported visual impairment and 183 women (17.2%) had objective visual impairment. Forty-two women (4.0%) were ultimately classified with probable dementia and 28 women (2.6%) with MCI that did not progress to dementia. Mean post-eye examination follow-up was 3.8 (1.8) years (range, 0-7 years). Women with vs without baseline objective visual impairment were more likely to develop dementia. Greatest risk for dementia was among women with visual acuity of 20/100 or worse at baseline (HR, 5.66; 95% CI, 1.75-18.37), followed by 20/80 or worse (HR, 5.20; 95% CI, 1.94-13.95), and 20/40 or worse (HR, 2.14; 95% CI, 1.08-4.21). Findings were similar for risk of MCI, with the greatest risk among women with baseline visual acuity of 20/100 or worse (HR, 6.43; 95% CI, 1.66-24.85). Conclusions and Relevance: In secondary analysis of a prospective longitudinal cohort study of older women with formal vision and cognitive function testing, objective visual impairment appears to be associated with an increased risk of incident dementia. However, incident cases of dementia and the proportion of those with visual impairment were low. Research is needed to evaluate the effect of specific ophthalmic interventions on dementia.

Investigating Predictors of Preserved Cognitive Function in Older Women Using Machine Learning: Women's Health Initiative Memory Study

Background: Identification of factors that may help to preserve cognitive function in late life could elucidate mechanisms and facilitate interventions to improve the lives of millions of people. However, the large number of potential factors associated with cognitive function poses an analytical challenge. Objective: We used data from the longitudinal Women's Health Initiative Memory Study (WHIMS) and machine learning to investigate 50 demographic, biomedical, behavioral, social, and psychological predictors of preserved cognitive function in later life. Methods: Participants in WHIMS and two consecutive follow up studies who were at least 80 years old and had at least one cognitive assessment following their 80th birthday were classified as cognitively preserved. Preserved cognitive function was defined as having a score ≥39 on the most recent administration of the modified Telephone Interview for Cognitive Status (TICSm) and a mean score across all assessments ≥39. Cognitively impaired participants were those adjudicated by experts to have probable dementia or at least two adjudications of mild cognitive impairment within the 14 years of follow-up and a last TICSm score < 31. Random Forests was used to rank the predictors of preserved cognitive function. Results: Discrimination between groups based on area under the curve was 0.80 (95%-CI-0.76-0.85). Women with preserved cognitive function were younger, better educated, and less forgetful, less depressed, and more optimistic at study enrollment. They also reported better physical function and less sleep disturbance, and had lower systolic blood pressure, hemoglobin, and blood glucose levels. Conclusion: The predictors of preserved cognitive function include demographic, psychological, physical, metabolic, and vascular factors suggesting a complex mix of potential contributors

Tight-binding parameters for charge transfer along DNA

We systematically examine all the tight-binding parameters pertinent to charge transfer along DNA. The $\pi$ molecular structure of the four DNA bases (adenine, thymine, cytosine, and guanine) is investigated by using the linear combination of atomic orbitals method with a recently introduced parametrization. The HOMO and LUMO wavefunctions and energies of DNA bases are discussed and then used for calculating the corresponding wavefunctions of the two B-DNA base-pairs (adenine-thymine and guanine-cytosine). The obtained HOMO and LUMO energies of the bases are in good agreement with available experimental values. Our results are then used for estimating the complete set of charge transfer parameters between neighboring bases and also between successive base-pairs, considering all possible combinations between them, for both electrons and holes. The calculated microscopic quantities can be used in mesoscopic theoretical models of electron or hole transfer along the DNA double helix, as they provide the necessary parameters for a tight-binding phenomenological description based on the $\pi$ molecular overlap. We find that usually the hopping parameters for holes are higher in magnitude compared to the ones for electrons, which probably indicates that hole transport along DNA is more favorable than electron transport. Our findings are also compared with existing calculations from first principles.Comment: 15 pages, 3 figures, 7 table