The rockefeller university

As nucleators of the mitotic spindle and primary cilium, centrosomes play crucial roles in equal segregation of DNA content to daughter cells, coordination of growth and differentiation, and transduction of homeostatic cues. Whereas the majority of mammalian cells carry no more than two centrosomes per cell, exceptions to this rule apply in certain specialized tissues and in select disease states, including cancer. Centrosome amplification, or the condition of having more than two centrosomes per cell, has been suggested to contribute to instability of chromosomes, imbalance in asymmetric divisions, and reorganization of tissue architecture; however, the degree to which these conditions are a direct cause of or simply a consequence of human disease is poorly understood. Here we addressed this issue by generating a mouse model inducing centrosome amplification in a naturally proliferative epithelial tissue by elevating Polo-like kinase 4 (Plk4) expression in the skin epidermis. By altering centrosome numbers, we observed multiciliated cells, spindle orientation errors, and chromosome segregation defects within developing epidermis. None of these defects was sufficient to impart a proliferative advantage within the tissue, however. Rather, impaired mitoses led to p53-mediated cell death and contributed to defective growth and stratification. Despite these abnormalities, mice remained viable and healthy, although epidermal cells with centrosome amplification were still appreciable. Moreover, these abnormalities were insufficient to disrupt homeostasis and initiate or enhance tumorigenesis, underscoring the powerful surveillance mechanisms in the skin.

Measurements of the five most significant angular coefficients, A(0) through A(4), for Z bosons produced in pp collisions at root S = 8 TeV and decaying to mu(+)mu(-) are presented as a function of the transverse momentum and rapidity of the Z boson. The integrated luminosity of the dataset collected with the CMS detector at the LHC corresponds to 19.7 fb(-1). These measurements provide comprehensive information about the Z boson production mechanisms, and are compared to the QCD predictions at leading order, next-to-leading order, and next-to-next-to-leading order in perturbation theory. (C) 2015 CERN for the benefit of the CMS Collaboration. Published by Elsevier B.V.

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1's intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.

Cow's milk protein allergy in exclusively breastfed infants, the main cause of food intolerance during the first 6 months of life, is triggered by the mother's diet. beta-Lactoglobulin (BLG) present in cow's milk is one of the most potent allergens for newborns. Since no prophylactic treatment is available, finding ligands capable of binding BLG and reducing its allergenicity is currently the focus of research. In this work, an innovative methodology encompassing microfluidics based on fully automated chip-nanoelectrospray ionization (nanoESI), coupled with high-resolution mass spectrometry (MS) on a quadrupole time-of-flight (QTOF MS) instrument was developed. This platform was employed for the assessment of the noncovalent interactions between maltohexaose (Glc(6)) and beta-lactoglobulin extracted from human milk upon deliberate intake of cow's milk. The experiments were carried out in (+) ESI mode, using ammonium acetate (pH 6.0) as the buffer and also in pure water. In both cases, the MS analysis revealed the formation of BLG-Glc(6) complex, which was characterized by top-down fragmentation in tandem MS (MS/MS) using collision-induced dissociation (CID). Our findings have a significant biomedical impact, indicating that Glc(6) binds BLG under conditions mimicking the in vivo environment and therefore might represent a ligand, able to reduce its allergenicity.

Taylor's power law (TPL) describes the empirical relationship sigma(2)=a mu(b) where sigma(2) are sample variances and mu are sample means in subsets of data in a data set. Equivalently, TPL states that the logarithm of the sample variance is a linear function of the logarithm of the sample mean across different subsets of data. Here we show that crop yields follow this relationship in several published data sets from varied situations. We show that TPL is frequently, but not always, valid for various factors structuring the data including varieties, crop species, trial environments or countries. We propose that the residuals from the linear regression of log(sigma(2)) against log(mu) can be used as a measure of stability, called POLAR (Power Law Residuals). We compare POLAR stability with other commonly used measures of stability, and show that POLAR stability offers an advantage over some frequently used stability measures. (C) 2015 Elsevier B.V. All rights reserved.

Eukaryotic ribosome biogenesis involves a plethora of ribosome-assembly factors, and their temporal order of association with preribosomal RNA is largely unknown. By using Saccharomyces cerevisiae as a model organism, we developed a system that recapitulates and arrests ribosome assembly at early stages, thus providing in vivo snapshots of nascent preribosomal particles. Here we report the stage-specific order in which 70 ribosome-assembly factors associate with preribosomal RNA domains, thereby forming the 6-MDa small-subunit processome.

Centrosomes are microtubule-organizing centers that facilitate bipolar mitotic spindle assembly and chromosome segregation. Recognizing that centrosome amplification is a common feature of aneuploid cancer cells, we tested whether supernumerary centrosomes are sufficient to drive tumor development. To do this, we constructed and analyzed mice in which centrosome amplification can be induced by a Cre-recombinase-mediated increase in expression of Polo-like kinase 4 (Plk4). Elevated Plk4 in mouse fibroblasts produced supernumerary centrosomes and enhanced the expected mitotic errors, but proliferation continued only after inactivation of the p53 tumor suppressor. Increasing Plk4 levels in mice with functional p53 produced centrosome amplification in liver and skin, but this did not promote spontaneous tumor development in these tissues or enhance the growth of chemically induced skin tumors. In the absence of p53, Plk4 overexpression generated widespread centrosome amplification, but did not drive additional tumors or affect development of the fatal thymic lymphomas that arise in animals lacking p53. We conclude that, independent of p53 status, supernumerary centrosomes are not sufficient to drive tumor formation.

Psoriasis vulgaris is a common, chronic inflammatory skin disease with a complex etiology involving genetic risk factors and environmental triggers. Here we describe the many known genetic predispositions of psoriasis with respect to immune genes and their encoded pathways in psoriasis susceptibility. These genes span an array of functions that involve antigen presentation (HLA-Cw6, ERAP1, ERAP2, MICA), the IL-23 axis (IL12Bp40, IL23Ap19, IL23R, JAK2, TYK2), T-cell development and T-cells polarization (RUNX1, RUNX3, STAT3, TAGAP, IL4, IL13), innate immunity (CARD14, c-REL, TRAF3IP2, DDX58, IFIH1), and negative regulators of immune responses (TNIP1, TNFAIP3, NFKBIA, ZC3H12C, IL36RN, SOCS1). The contribution of some of these gene products to psoriatic disease has also been revealed in recent years through targeting of key immune components, such as the Th17/IL-23 axis which has been highly successful in disease treatment. However, many of the genetic findings involve immune genes with less clear roles in psoriasis pathogenesis. This is particularly the case for those genes involved in innate immunity and negative regulation of immune specific pathways. It is possible that risk alleles of these genes decrease the threshold for the initial activation of the innate immune response. This could then lead to the onslaught of the pathogenic adaptive immune response known to be active in psoriatic skin. However, precisely how these various genes affect immunobiology need to be determined and some are speculated upon in this review. These novel genetic findings also open opportunities to explore novel therapeutic targets and potentially the development of personalized medicine, as well as discover new biology of human skin disease. (C) 2015 Elsevier Ltd. All rights reserved.

People learn modality-independent, conceptual representations from modality-specific sensory signals. Here, we hypothesize that any system that accomplishes this feat will include three components: a representational language for characterizing modality-independent representations, a set of sensory-specific forward models for mapping from modality-independent representations to sensory signals, and an inference algorithm for inverting forward models-that is, an algorithm for using sensory signals to infer modality-independent representations. To evaluate this hypothesis, we instantiate it in the form of a computational model that learns object shape representations from visual and/or haptic signals. The model uses a probabilistic grammar to characterize modality-independent representations of object shape, uses a computer graphics toolkit and a human hand simulator to map from object representations to visual and haptic features, respectively, and uses a Bayesian inference algorithm to infer modality-independent object representations from visual and/or haptic signals. Simulation results show that the model infers identical object representations when an object is viewed, grasped, or both. That is, the model's percepts are modality invariant. We also report the results of an experiment in which different subjects rated the similarity of pairs of objects in different sensory conditions, and show that the model provides a very accurate account of subjects' ratings. Conceptually, this research significantly contributes to our understanding of modality invariance, an important type of perceptual constancy, by demonstrating how modality-independent representations can be acquired and used. Methodologically, it provides an important contribution to cognitive modeling, particularly an emerging probabilistic language-of-thought approach, by showing how symbolic and statistical approaches can be combined in order to understand aspects of human perception.

Ghrelin receptor (GhrR) is a promising drug target because of its central role in energy homeostasis. GhrR, known for high constitutive activity, is thought to display multi-state conformations during activation and signaling. We used genetically encoded unnatural amino acids and bioorthogonal labeling reactions to engineer multiple fluorescent donor-acceptor pairs to probe ligand-directed structural changes in GhrR. We demonstrate how conformational dynamics of a G-protein-coupled receptor can be measured in reconstituted systems.