Breast cancer in young women: prevalence of LOH at p53, BRCA1 and BRCA2

Breast cancer in young women: prevalance of LOH at p53, BRCA1 and BRCA

Nutritional, pasting and sensory properties of a weaning food from rice (Oryza sativa), soybeans (Glycine Max) and kent Mango (Mangifera indica) flour blends

The effective use of readily available and inexpensive sources of protein and micronutrients has become a major focus of research in recent years. This study sought to provide a nutritionally adequate and culturally acceptable weaning food for infants, as well as tap the potential of broken rice fraction as an alternative use for weaning formulation in Ghana. Flour from broken rice fractions in combination with soybeans and dried mangoes were used to develop four weaning formulations. Rice-Soy Mango (RSM) was prepared with 75% rice flour, 25% soybeans flours and 0% mango flour (RSM-0), and used as control; RSM-5 was prepared with 70% rice flour, 25% soybeans flours and 5% mango flour; RSM-10 was prepared with 65% rice flour, 25% soybeans flours and 10% mango flour while RSM-15 was prepared with 60% rice flour, 25% soybeans flours and 15% mango flour. The products were evaluated for their nutritional composition, sensory characteristics and pasting properties. All the three newly formulated rice-mango weaning food met the Estimated Average Requirement (EAR) for energy (393.71-403.25 KCal/100 g), protein (10.7-15.24 g/100 g), carbohydrates (68.44-73.87g/100 g), zinc (8.67-10.84 mg/d and vitamin C (13.96-17.79 mg/100 g) levels but not for iron (3.99-7.61 mg/100 g), fat (6.22-7.61 g/100 g) and calcium (87.2-111.7 mg/100 g). The beta-carotene levels ranged from 74.8 to 346.6 μg/100 g and showed significant differences. The pasting profile for the blends with low amounts of mango (RSM-5 and RSM-10) had a similar profile as the control (RSM-0), while RSM-15 had a lower profile. Among the three newly formulated blends, RSM-10 had the highest peak viscosity (74.0 BU) and highest final viscosity of 107 BU. The RSM-5, RSM-10 and RSM-15 were all lighter than RSM-0, albeit not significant. Increasing the content of mango resulted in the flour blend becoming more yellow. Even though the sensory quality of RSM-5 was the most preferred, there was no significant difference (p>0.05) observed between the sensory quality of all the three newly formulated products (RSM-5, RSM-10, RSM-15). The RSM-10 showed great potential and may be recommended and adopted for promotion within Ghanaian households based on its high nutritional and good sensory qualities.Key words: Weaning, Broken Rice, Mangoes, Pasting, Sensory, Vitamin A, Iron, Childre

Plasma electrons above Saturn's main rings: CAPS observations

We present observations of thermal ( similar to 0.6 - 100eV) electrons observed near Saturn's main rings during Cassini's Saturn Orbit Insertion (SOI) on 1 July 2004. We find that the intensity of electrons is broadly anticorrelated with the ring optical depth at the magnetic footprint of the field line joining the spacecraft to the rings. We see enhancements corresponding to the Cassini division and Encke gap. We suggest that some of the electrons are generated by photoemission from ring particle surfaces on the illuminated side of the rings, the far side from the spacecraft. Structure in the energy spectrum over the Cassini division and A-ring may be related to photoelectron emission followed by acceleration, or, more likely, due to photoelectron production in the ring atmosphere or ionosphere

Cassini observations of the thermal plasma in the vicinity of Saturn's main rings and the F and G rings

The ion mass spectrometer on Cassini detected enhanced ion flux near Saturn's main rings that is consistent with the presence of atomic and molecular oxygen ions in the thermal plasma. The ring "atmosphere'' and "ionosphere'' are likely produced by UV photosputtering of the icy rings and subsequent photoionization of O-2. The identification of the O+ and O-2(+) ions is made using time-of-flight analysis and densities and temperatures are derived from the ion counting data. The ion temperatures over the main rings are a minimum near synchronous orbit and increase with radial distance from Saturn as expected from ion pick up in Saturn's magnetic field. The O-2(+) temperatures provide an estimate of the neutral O-2 temperature over the main rings. The ion mass spectrometer also detected significant O-2(+) outside of the main rings, near the F ring. It is concluded that between the F and G rings, the heavy ion population most likely consists of an admixture of O-2(+) and water group ions O+, OH+, and H2O+

Statistically Motivated Second Order Pooling

Second-order pooling, a.k.a.~bilinear pooling, has proven effective for deep learning based visual recognition. However, the resulting second-order networks yield a final representation that is orders of magnitude larger than that of standard, first-order ones, making them memory-intensive and cumbersome to deploy. Here, we introduce a general, parametric compression strategy that can produce more compact representations than existing compression techniques, yet outperform both compressed and uncompressed second-order models. Our approach is motivated by a statistical analysis of the network's activations, relying on operations that lead to a Gaussian-distributed final representation, as inherently used by first-order deep networks. As evidenced by our experiments, this lets us outperform the state-of-the-art first-order and second-order models on several benchmark recognition datasets.Comment: Accepted to ECCV 2018. Camera ready version. 14 page, 5 figures, 3 table

Clustering of tau-immunoreactive pathology in chronic traumatic encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder which may result from repetitive brain injury. A variety of tau-immunoreactive pathologies are present, including neurofibrillary tangles (NFT), neuropil threads (NT), dot-like grains (DLG), astrocytic tangles (AT), and occasional neuritic plaques (NP). In tauopathies, cellular inclusions in the cortex are clustered within specific laminae, the clusters being regularly distributed parallel to the pia mater. To determine whether a similar spatial pattern is present in CTE, clustering of the tau-immunoreactive pathology was studied in the cortex, hippocampus, and dentate gyrus in 11 cases of CTE and 7 cases of Alzheimer’s disease neuropathologic change (ADNC) without CTE. In CTE: (1) all aspects of tau-immunoreactive pathology were clustered and the clusters were frequently regularly distributed parallel to the tissue boundary, (2) clustering was similar in two CTE cases with minimal co-pathology compared with cases with associated ADNC or TDP-43 proteinopathy, (3) in a proportion of cortical gyri, estimated cluster size was similar to that of cell columns of the cortico-cortical pathways, and (4) clusters of the tau-immunoreactive pathology were infrequently spatially correlated with blood vessels. The NFT and NP in ADNC without CTE were less frequently randomly or uniformly distributed and more frequently in defined clusters than in CTE. Hence, the spatial pattern of the tau-immunoreactive pathology observed in CTE is typical of the tauopathies but with some distinct differences compared to ADNC alone. The spread of pathogenic tau along anatomical pathways could be a factor in the pathogenesis of the disease

Alcohol Schema Acquisition in Preschoolers: Differences Between Children of Alcoholics and Children of Nonalcoholics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65209/1/j.1530-0277.1995.tb00982.x.pd

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

Objective Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD. Method A multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. Results Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. Interpretation We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials