Bounds on the Complexity of Halfspace Intersections when the Bounded Faces have Small Dimension

We study the combinatorial complexity of D-dimensional polyhedra defined as the intersection of n halfspaces, with the property that the highest dimension of any bounded face is much smaller than D. We show that, if d is the maximum dimension of a bounded face, then the number of vertices of the polyhedron is O(n^d) and the total number of bounded faces of the polyhedron is O(n^d^2). For inputs in general position the number of bounded faces is O(n^d). For any fixed d, we show how to compute the set of all vertices, how to determine the maximum dimension of a bounded face of the polyhedron, and how to compute the set of bounded faces in polynomial time, by solving a polynomial number of linear programs

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

c-Abl downregulates the slow phase of double-strand break repair

c-Abl tyrosine kinase is activated by agents that induce double-strand DNA breaks (DSBs) and interacts with key components of the DNA damage response and of the DSB repair machinery. However, the functional significance of c-Abl in these processes, remained unclear. In this study, we demonstrate, using comet assay and pulsed-field gel electrophoresis, that c-Abl inhibited the repair of DSBs induced by ionizing radiation, particularly during the second and slow phase of DSB repair. Pharmacological inhibition of c-Abl and c-Abl depletion by siRNA-mediated knockdown resulted in higher DSB rejoining. c-Abl null MEFs exhibited higher DSB rejoining compared with cells reconstituted for c-Abl expression. Abrogation of c-Abl kinase activation resulted in higher H2AX phosphorylation levels and higher numbers of post-irradiation γH2AX foci, consistent with a role of c-Abl in DSB repair regulation. In conjunction with these findings, transient abrogation of c-Abl activity resulted in increased cellular radioresistance. Our findings suggest a novel function for c-Abl in inhibition of the slow phase of DSB repair

Proteome-Wide Search Reveals Unexpected RNA-Binding Proteins in Saccharomyces cerevisiae

The vast landscape of RNA-protein interactions at the heart of post-transcriptional regulation remains largely unexplored. Indeed it is likely that, even in yeast, a substantial fraction of the regulatory RNA-binding proteins (RBPs) remain to be discovered. Systematic experimental methods can play a key role in discovering these RBPs - most of the known yeast RBPs lack RNA-binding domains that might enable this activity to be predicted. We describe here a proteome-wide approach to identify RNA-protein interactions based on in vitro binding of RNA samples to yeast protein microarrays that represent over 80% of the yeast proteome. We used this procedure to screen for novel RBPs and RNA-protein interactions. A complementary mass spectrometry technique also identified proteins that associate with yeast mRNAs. Both the protein microarray and mass spectrometry methods successfully identify previously annotated RBPs, suggesting that other proteins identified in these assays might be novel RBPs. Of 35 putative novel RBPs identified by either or both of these methods, 12, including 75% of the eight most highly-ranked candidates, reproducibly associated with specific cellular RNAs. Surprisingly, most of the 12 newly discovered RBPs were enzymes. Functional characteristics of the RNA targets of some of the novel RBPs suggest coordinated post-transcriptional regulation of subunits of protein complexes and a possible link between mRNA trafficking and vesicle transport. Our results suggest that many more RBPs still remain to be identified and provide a set of candidates for further investigation

Alterations of the extracellular matrix in ovarian cancer studied by Second Harmonic Generation imaging microscopy

<p>Abstract</p> <p>Background</p> <p>Remodeling of the extracellular matrix (ECM) has been implicated in ovarian cancer, and we hypothesize that these alterations may provide a better optical marker of early disease than currently available imaging/screening methods and that understanding their physical manifestations will provide insight into invasion.</p> <p>Methods</p> <p>For this investigation we use Second Harmonic Generation (SHG) imaging microcopy to study changes in the structure of the ovarian ECM in human normal and malignant ex vivo biopsies. This method directly visualizes the type I collagen in the ECM and provides quantitative metrics of the fibrillar assembly. To quantify these changes in collagen morphology we utilized an integrated approach combining 3D SHG imaging measurements and bulk optical parameter measurements in conjunction with Monte Carlo simulations of the experimental data to extract tissue structural properties.</p> <p>Results</p> <p>We find the SHG emission attributes (directionality and relative intensity) and bulk optical parameters, both of which are related to the tissue structure, are significantly different in the tumors in a manner that is consistent with the change in collagen assembly. The normal and malignant tissues have highly different collagen fiber assemblies, where collectively, our findings show that the malignant ovaries are characterized by lower cell density, denser collagen, as well as higher regularity at both the fibril and fiber levels. This further suggests that the assembly in cancer may be comprised of newly synthesized collagen as opposed to modification of existing collagen.</p> <p>Conclusions</p> <p>Due to the large structural changes in tissue assembly and the SHG sensitivity to these collagen alterations, quantitative discrimination is achieved using small patient data sets. Ultimately these measurements may be developed as intrinsic biomarkers for use in clinical applications.</p

Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors

Monitoring and describing the physical movements and body postures of animals is one of the most fundamental tasks of ethology. The more precise the observations are the more sophisticated the interpretations can be about the biology of a certain individual or species. Animal-borne data loggers have recently contributed much to the collection of motion-data from individuals, however, the problem of translating these measurements to distinct behavioural categories to create an ethogram is not overcome yet. The objective of the present study was to develop a “behaviour tracker”: a system composed of a multiple sensor data-logger device (with a tri-axial accelerometer and a tri-axial gyroscope) and a supervised learning algorithm as means of automated identification of the behaviour of freely moving dogs. We collected parallel sensor measurements and video recordings of each of our subjects (Belgian Malinois, N=12; Labrador Retrievers, N=12) that were guided through a predetermined series of standard activities. Seven behavioural categories (lay, sit, stand, walk, trot, gallop, canter) were pre-defined and each video recording was tagged accordingly. Evaluation of the measurements was performed by support vector machine (SVM) classification. During the analysis we used different combinations of independent measurements for training and validation (belonging to the same or different individuals or using different training data size) to determine the robustness of the application. We reached an overall accuracy of above 90% perfect identification of all the defined seven categories of behaviour when both training and validation data belonged to the same individual, and over 80% perfect recognition rate using a generalized training data set of multiple subjects. Our results indicate that the present method provides a good model for an easily applicable, fast, automatic behaviour classification system that can be trained with arbitrary motion patterns and potentially be applied to a wide range of species and situations

Depauperate Avifauna in Plantations Compared to Forests and Exurban Areas

Native forests are shrinking worldwide, causing a loss of biological diversity. Our ability to prioritize forest conservation actions is hampered by a lack of information about the relative impacts of different types of forest loss on biodiversity. In particular, we lack rigorous comparisons of the effects of clearing forests for tree plantations and for human settlements, two leading causes of deforestation worldwide. We compared avian diversity in forests, plantations and exurban areas on the Cumberland Plateau, USA, an area of global importance for biodiversity. By combining field surveys with digital habitat databases, and then analyzing diversity at multiple scales, we found that plantations had lower diversity and fewer conservation priority species than did other habitats. Exurban areas had higher diversity than did native forests, but native forests outscored exurban areas for some measures of conservation priority. Overall therefore, pine plantations had impoverished avian communities relative to both native forests and to exurban areas. Thus, reports on the status of forests give misleading signals about biological diversity when they include plantations in their estimates of forest cover but exclude forested areas in which humans live. Likewise, forest conservation programs should downgrade incentives for plantations and should include settled areas within their purview

Association of CETP TaqI and APOE polymorphisms with type II diabetes mellitus in North Indians: a case control study

BACKGROUND: Genetic variants of proteins involved in lipid metabolism may play an important role in determining the susceptibility for complications associated with type II diabetes mellitus (T2DM). Goal of the present study was to determine the association of cholesteryl ester transfer protein TaqI B, D442G, and APOE Hha I polymorphisms with T2DM and its complications. METHODS: Study subjects were 136 patients and 264 healthy controls. All polymorphisms were detected using PCR-RFLP and statistical analysis done with χ(2 )test and ANOVA. RESULTS: Although CETP TaqI B polymorphism was not associated with the T2DM, yet B1B2 genotype was significantly (p = 0.028) associated with high risk of hypertension in diabetic patients (OR = 3.068, 95% CI 1.183–7.958). In North Indians D442G variation in CETP gene was found to be absent. Frequency of APOE HhaI polymorphism was also not different between patients and controls. In diabetic patients having neuropathy and retinopathy significantly different levels of total-cholesterol [(p = 0.001) and (p = 0.029) respectively] and LDL-cholesterol [(p = 0.001) and (p = 0.001) respectively] were observed when compared to patients with T2DM only. However, lipid levels did not show any correlation with the CETP TaqI B and APOE Hha I genetic polymorphisms. CONCLUSION: CETP TaqI B and APOE HhaI polymorphism may not be associated with type II diabetes mellitus in North Indian population, however CETP TaqI B polymorphism may be associated with hypertension along with T2DM

Linking early-life NMDAR hypofunction and oxidative stress in schizophrenia pathogenesis.

Molecular, genetic and pathological evidence suggests that deficits in GABAergic parvalbumin-positive interneurons contribute to schizophrenia pathophysiology through alterations in the brain's excitation-inhibition balance that result in impaired behaviour and cognition. Although the factors that trigger these deficits are diverse, there is increasing evidence that they converge on a common pathological hub that involves NMDA receptor hypofunction and oxidative stress. These factors have been separately linked to schizophrenia pathogenesis, but evidence now suggests that they are mechanistically interdependent and contribute to a common schizophrenia-associated pathology

Oxidative stress-driven parvalbumin interneuron impairment as a common mechanism in models of schizophrenia.

Parvalbumin inhibitory interneurons (PVIs) are crucial for maintaining proper excitatory/inhibitory balance and high-frequency neuronal synchronization. Their activity supports critical developmental trajectories, sensory and cognitive processing, and social behavior. Despite heterogeneity in the etiology across schizophrenia and autism spectrum disorder, PVI circuits are altered in these psychiatric disorders. Identifying mechanism(s) underlying PVI deficits is essential to establish treatments targeting in particular cognition. On the basis of published and new data, we propose oxidative stress as a common pathological mechanism leading to PVI impairment in schizophrenia and some forms of autism. A series of animal models carrying genetic and/or environmental risks relevant to diverse etiological aspects of these disorders show PVI deficits to be all accompanied by oxidative stress in the anterior cingulate cortex. Specifically, oxidative stress is negatively correlated with the integrity of PVIs and the extracellular perineuronal net enwrapping these interneurons. Oxidative stress may result from dysregulation of systems typically affected in schizophrenia, including glutamatergic, dopaminergic, immune and antioxidant signaling. As convergent end point, redox dysregulation has successfully been targeted to protect PVIs with antioxidants/redox regulators across several animal models. This opens up new perspectives for the use of antioxidant treatments to be applied to at-risk individuals, in close temporal proximity to environmental impacts known to induce oxidative stress