On central tendency and dispersion measures for intervals and hypercubes

The uncertainty or the variability of the data may be treated by considering, rather than a single value for each data, the interval of values in which it may fall. This paper studies the derivation of basic description statistics for interval-valued datasets. We propose a geometrical approach in the determination of summary statistics (central tendency and dispersion measures) for interval-valued variables

Simulations of grafted polymers in a good solvent

We present improved simulations of three-dimensional self avoiding walks with one end attached to an impenetrable surface on the simple cubic lattice. This surface can either be a-thermal, having thus only an entropic effect, or attractive. In the latter case we concentrate on the adsorption transition, We find clear evidence for the cross-over exponent to be smaller than 1/2, in contrast to all previous simulations but in agreement with a re-summed field theoretic $\epsilon$-expansion. Since we use the pruned-enriched Rosenbluth method (PERM) which allows very precise estimates of the partition sum itself, we also obtain improved estimates for all entropic critical exponents.Comment: 5 pages with 9 figures included; minor change

Finite size scaling in neural networks

We demonstrate that the fraction of pattern sets that can be stored in single- and hidden-layer perceptrons exhibits finite size scaling. This feature allows to estimate the critical storage capacity \alpha_c from simulations of relatively small systems. We illustrate this approach by determining \alpha_c, together with the finite size scaling exponent \nu, for storing Gaussian patterns in committee and parity machines with binary couplings and up to K=5 hidden units.Comment: 4 pages, RevTex, 5 figures, uses multicol.sty and psfig.st

Plagiorchis sp. in small mammals of Senegal and the potential emergence of a zoonotic trematodiasis

Trematodes of the genus Plagiorchis have a wide geographical distribution and can exploit a variety of hosts. The occurrence and zoonotic potential of Plagiorchis spp. have been characterised across several countries in Asia; in contrast, information on Plagiorchis parasites in Africa remains anecdotal. We isolated a previously undescribed Plagiorchis species from the biliary tract and small intestine of 201 out of 427 small mammals collected in the region of Lake Guiers, Senegal, with local prevalence ranging from 38.6% to 77.0%. Conversely, Plagiorchis isolates were not observed in the 244 small mammals sampled in and around the town of Richard Toll, Senegal. Molecular phylogenetics of the internal transcribed spacer region, nuclear ribosomal DNA, and of the cytochrome c oxidase subunit 1 gene, mitochondrial DNA, supported the monophyly and multi-host spectrum of this newly discovered West African Plagiorchis species. Sequencing of individual cercariae shed by Radix natalensis (Gastropoda: Lymnaeidae) suggested that these freshwater snails may act as suitable first intermediate hosts. Phylogenetic analysis yielded a highly resolved topology indicating two different clades, one composed by Plagiorchis spp. infecting rodents, insectivores, and birds, while the other included parasites of bats. Our findings showed the low host specificity and high prevalence of the isolated Plagiorchis sp. in the Lake Guiers region, with Hubert's multimammate mice (Mastomys huberti) appearing to play a primary role in the epidemiology of this parasite. The results raise concern about the zoonotic potential of Plagiorchis sp. in local communities of the Lake Guiers region, and highlight food-borne trematodiases and their link to land-use change as a neglected public health issue in regions of West Africa

Reconstruction of a first-order phase transition from computer simulations of individual phases and subphases

We present a new method for investigating first-order phase transitions using Monte Carlo simulations. It relies on the multiple-histogram method and uses solely histograms of individual phases. In addition, we extend the method to include histograms of subphases. The free energy difference between phases, necessary for attributing the correct statistical weights to the histograms, is determined by a detour in control parameter space via auxiliary systems with short relaxation times. We apply this method to a recently introduced model for structure formation in polypeptides for which other methods fail.Comment: 13 pages in preprint mode, REVTeX, 2 Figures available from the authors ([email protected], [email protected]

Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models

Introduction: Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction. Methods: We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures. Results: A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model. Conclusions: Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.This work was supported by a grant from the Susan G Komen Foundation (to YK)

Inhibition of 12/15-Lipoxygenase Protects Against β-Cell Oxidative Stress and Glycemic Deterioration in Mouse Models of Type 1 Diabetes

Islet β-cell dysfunction and aggressive macrophage activity are early features in the pathogenesis of type 1 diabetes (T1D). 12/15-Lipoxygenase (12/15-LOX) is induced in β-cells and macrophages during T1D and produces proinflammatory lipids and lipid peroxides that exacerbate β-cell dysfunction and macrophage activity. Inhibition of 12/15-LOX provides a potential therapeutic approach to prevent glycemic deterioration in T1D. Two inhibitors recently identified by our groups through screening efforts, ML127 and ML351, have been shown to selectively target 12/15-LOX with high potency. Only ML351 exhibited no apparent toxicity across a range of concentrations in mouse islets, and molecular modeling has suggested reduced promiscuity of ML351 compared with ML127. In mouse islets, incubation with ML351 improved glucose-stimulated insulin secretion in the presence of proinflammatory cytokines and triggered gene expression pathways responsive to oxidative stress and cell death. Consistent with a role for 12/15-LOX in promoting oxidative stress, its chemical inhibition reduced production of reactive oxygen species in both mouse and human islets in vitro. In a streptozotocin-induced model of T1D in mice, ML351 prevented the development of diabetes, with coincident enhancement of nuclear Nrf2 in islet cells, reduced β-cell oxidative stress, and preservation of β-cell mass. In the nonobese diabetic mouse model of T1D, administration of ML351 during the prediabetic phase prevented dysglycemia, reduced β-cell oxidative stress, and increased the proportion of anti-inflammatory macrophages in insulitis. The data provide the first evidence to date that small molecules that target 12/15-LOX can prevent progression of β-cell dysfunction and glycemic deterioration in models of T1D

Social approach in genetically engineered mouse lines relevant to autism

Profound impairment in social interaction is a core symptom of autism, a severe neurodevelopmental disorder. Deficits can include a lack of interest in social contact and low levels of approach and proximity to other children. In this study, a three-chambered choice task was used to evaluate sociability and social novelty preference in five lines of mice with mutations in genes implicated in autism spectrum disorders. Fmr1tm1Cgr/Y (Fmr1−/y) mice represent a model for fragile X, a mental retardation syndrome that is partially co-morbid with autism. We tested Fmr1−/y mice on two genetic backgrounds, C57BL/6J and FVB/N-129/OlaHsd (FVB/129). Targeted disruption of Fmr1 resulted in low sociability on one measure, but only when the mutation was expressed on FVB/129. Autism has been associated with altered serotonin levels and polymorphisms in SLC6A4 (SERT), the serotonin-transporter gene. Male mice with targeted disruption of Slc6a4 displayed significantly less sociability than wildtype controls. Mice with conditional overexpression of Igf-1 (Insulin-like growth factor-1) offered a model for brain overgrowth associated with autism. Igf-1 transgenic mice engaged in levels of social approach similar to wildtype controls. Targeted disruption in other genes of interest, En2 (Engrailed 2) and Dhcr7, was carried on genetic backgrounds that demonstrated low levels of exploration in the choice task, precluding meaningful interpretations of social behavior scores. Overall, results show that loss of Fmr1 or Slc6a4 gene function can lead to deficits in sociability. Findings from the fragile X-model suggest that the FVB/129 background confers enhanced susceptibility to consequences of Fmr1 mutation on social approach

Social approach and repetitive behavior in eleven inbred mouse strains

Core symptoms of autism include deficits in social interaction, impaired communication, and restricted, repetitive behaviors. The repetitive behavior domain encompasses abnormal motoric stereotypy, an inflexible insistence on sameness, and resistance to change. In recent years, many genetic mouse models of autism and related disorders have been developed, based on candidate genes for disease susceptibility. The present studies are part of an ongoing initiative to develop appropriate behavioral tasks for the evaluation of mouse models relevant to autism. We have previously reported profiles for sociability, preference for social novelty, and resistance to changes in a learned pattern of behavior, as well as other functional domains, for 10 inbred mouse strains of divergent genetic backgrounds. The present studies extend this multi-component behavioral characterization to several additional strains: C58/J, NOD/LtJ, NZB/B1NJ, PL/J, SJL/J, SWR/J, and the wild-derived PERA/EiJ. C58/J, NOD/LtJ, NZB/B1NJ, SJL/J, and PERA/EiJ demonstrated low sociability, measured by time spent in proximity to an unfamiliar conspecific, with 30% to 60% of mice from these strains showing social avoidance. In the Morris water maze, NZB/B1NJ had a persistent bias for the quadrant where the hidden platform was located during acquisition, even after nine days of reversal training. A particularly interesting profile was found for C58/J, which had low social preference, poor performance in the T-maze, and overt motoric stereotypy. Overall, this set of tasks and observational methods provides a strategy for evaluating novel mouse models in behavioral domains relevant to the autism phenotype