Cell-Type Specific Changes in Glial Morphology and Glucocorticoid Expression During Stress and Aging in the Medial Prefrontal Cortex.

Repeated exposure to stressors is known to produce large-scale remodeling of neurons within the prefrontal cortex (PFC). Recent work suggests stress-related forms of structural plasticity can interact with aging to drive distinct patterns of pyramidal cell morphological changes. However, little is known about how other cellular components within PFC might be affected by these challenges. Here, we examined the effects of stress exposure and aging on medial prefrontal cortical glial subpopulations. Interestingly, we found no changes in glial morphology with stress exposure but a profound morphological change with aging. Furthermore, we found an upregulation of non-nuclear glucocorticoid receptors (GR) with aging, while nuclear levels remained largely unaffected. Both changes are selective for microglia, with no stress or aging effect found in astrocytes. Lastly, we show that the changes found within microglia inversely correlated with the density of dendritic spines on layer III pyramidal cells. These findings suggest microglia play a selective role in synaptic health within the aging brain

Integration and publication of heterogeneous text-mined relationships on the Semantic Web

International audienceBackground - Advances in Natural Language Processing (NLP) techniques enable the extraction of fine-grained relationships mentioned in biomedical text. The variability and the complexity of natural language in expressing similar relationships causes the extracted relationships to be highly heterogeneous, which makes the construction of knowledge bases difficult and poses a challenge in using these for data mining or question answering. Results - We report on the semi-automatic construction of the PHARE relationship ontology (the PHArmacogenomic RElationships Ontology) consisting of 200 curated relations from over 40,000 heterogeneous relationships extracted via text-mining. These heterogeneous relations are then mapped to the PHARE ontology using synonyms, entity descriptions and hierarchies of entities and roles. Once mapped, relationships can be normalized and compared using the structure of the ontology to identify relationships that have similar semantics but different syntax. We compare and contrast the manual procedure with a fully automated approach using WordNet to quantify the degree of integration enabled by iterative curation and refinement of the PHARE ontology. The result of such integration is a repository of normalized biomedical relationships, named PHARE-KB, which can be queried using Semantic Web technologies such as SPARQL and can be visualized in the form of a biological network. Conclusions - The PHARE ontology serves as a common semantic framework to integrate more than 40,000 relationships pertinent to pharmacogenomics. The PHARE ontology forms the foundation of a knowledge base named PHARE-KB. Once populated with relationships, PHARE-KB (i) can be visualized in the form of a biological network to guide human tasks such as database curation and (ii) can be queried programmatically to guide bioinformatics applications such as the prediction of molecular interactions. PHARE is available at http://purl.bioontology.org/ontology/PHARE

Fermionic Modular Categories and the 16-fold Way

We study spin and super-modular categories systematically as inspired by fermionic topological phases of matter, which are always fermion parity enriched and modelled by spin TQFTs at low energy. We formulate a $16$-fold way conjecture for the minimal modular extensions of super-modular categories to spin modular categories, which is a categorical formulation of gauging the fermion parity. We investigate general properties of super-modular categories such as fermions in twisted Drinfeld doubles, Verlinde formulas for naive quotients, and explicit extensions of $PSU(2)_{4m+2}$ with an eye towards a classification of the low-rank cases.Comment: Latest post-referee version. Many typos fixed, many explanations expanded, several inconsistencies corrected. 8 figure

Light GUT Triplets and Yukawa Splitting

Triplet-mediated proton decay in Grand Unified Theories (GUTs) is usually suppressed by arranging a large triplet mass. Here we explore instead a mechanism for suppressing the couplings of the triplets to the first and second generations compared to the Yukawa couplings, so that the triplets' mass can be below the GUT scale. This mechanism is based on a ``triplet symmetry'' in the context of product-group GUTs. We study two possibilities. One, which requires the top Yukawa to arise from a non-renormalizable operator at the GUT scale, is that all triplet couplings to matter are negligible, so that the triplets can be at the weak scale. The second is that some triplet couplings, and in particular $T t b$ and $T \bar{t} \bar{l}$, are equal to the corresponding Yukawa couplings. This would give a distinct signature of grand unification if the triplets were sufficiently light. However, we derive a model-independent bound on the triplet mass in this case, which is at least 10$^6$GeV. Finally, we construct a GUT model based on Yukawa splitting, with the triplets at 10$^{14}$GeV, as required for coupling unification to work.Comment: 5 pages, Revtex4, 1 EPS figure. To appear in PRD: Minor changes. Appendix droppe

Product Groups, Discrete Symmetries, and Grand Unification

We study grand unified theories based on an SU(5)xSU(5) gauge group in which the GUT scale, M_{GUT}, is the VEV of an exact or approximate modulus, and in which fast proton decay is avoided through a combination of a large triplet mass and small triplet couplings. These features are achieved by discrete symmetries. In many of our models, M_{GUT} is generated naturally by the balance of higher dimension terms that lift the GUT modulus potential, and soft supersymmetry breaking masses. The theories often lead to interesting patterns of quark and lepton masses. We also discuss some distinctions between grand unified theories and string unification.Comment: 23 pages; no figures; revtex

The GUT Scale and Superpartner Masses from Anomaly Mediated Supersymmetry Breaking

We consider models of anomaly-mediated supersymmetry breaking (AMSB) in which the grand unification (GUT) scale is determined by the vacuum expectation value of a chiral superfield. If the anomaly-mediated contributions to the potential are balanced by gravitational-strength interactions, we find a model-independent prediction for the GUT scale of order $M_{\rm Planck} / (16\pi^2)$. The GUT threshold also affects superpartner masses, and can easily give rise to realistic predictions if the GUT gauge group is asymptotically free. We give an explicit example of a model with these features, in which the doublet-triplet splitting problem is solved. The resulting superpartner spectrum is very different from that of previously considered AMSB models, with gaugino masses typically unifying at the GUT scale.Comment: 17 page

Integration and publication of heterogeneous text-mined relationships on the Semantic Web

International audienceBackground - Advances in Natural Language Processing (NLP) techniques enable the extraction of fine-grained relationships mentioned in biomedical text. The variability and the complexity of natural language in expressing similar relationships causes the extracted relationships to be highly heterogeneous, which makes the construction of knowledge bases difficult and poses a challenge in using these for data mining or question answering. Results - We report on the semi-automatic construction of the PHARE relationship ontology (the PHArmacogenomic RElationships Ontology) consisting of 200 curated relations from over 40,000 heterogeneous relationships extracted via text-mining. These heterogeneous relations are then mapped to the PHARE ontology using synonyms, entity descriptions and hierarchies of entities and roles. Once mapped, relationships can be normalized and compared using the structure of the ontology to identify relationships that have similar semantics but different syntax. We compare and contrast the manual procedure with a fully automated approach using WordNet to quantify the degree of integration enabled by iterative curation and refinement of the PHARE ontology. The result of such integration is a repository of normalized biomedical relationships, named PHARE-KB, which can be queried using Semantic Web technologies such as SPARQL and can be visualized in the form of a biological network. Conclusions - The PHARE ontology serves as a common semantic framework to integrate more than 40,000 relationships pertinent to pharmacogenomics. The PHARE ontology forms the foundation of a knowledge base named PHARE-KB. Once populated with relationships, PHARE-KB (i) can be visualized in the form of a biological network to guide human tasks such as database curation and (ii) can be queried programmatically to guide bioinformatics applications such as the prediction of molecular interactions. PHARE is available at http://purl.bioontology.org/ontology/PHARE