An emerging role for adenosine and its receptors in bone homeostasis

Bone is continually being remodeled and defects in the processes involved lead to bone diseases. Many regulatory factors are known to influence remodeling but other mechanisms, hitherto unknown, may also be involved. Importantly, our understanding of these currently unknown mechanisms may lead to important new therapies for bone disease. It is accepted that purinergic signaling is involved in bone, and our knowledge of this area has increased significantly over the last 15 years, although most of the published work has studied the role of ATP and other signaling molecules via the P2 family of purinergic receptors. During the last few years, however, there has been increased interest within the bone field in the role of P1 receptors where adenosine is the primary signaling molecule. This review will bring together the current information available in relation to this expanding area of research

Adenosine receptor subtype expression and activation influence the differentiation of mesenchymal stem cells to osteoblasts and adipocytes

Osteoblasts and adipocytes differentiate from a common precursor cell, the mesenchymal stem cell (MSC). Adenosine is known to signal via four adenosine receptor subtypes, and significantly, recent findings indicate that these may play a role in MSC differentiation. We therefore investigated adenosine receptor expression and activation during the differentiation of MSCs to osteoblasts and adipocytes. The A2BR was dominant in MSCs, and its expression and activity were transiently upregulated at early stages of osteoblastic differentiation. Both activation and overexpression of A2BR induced the expression of osteoblast-related genes [Runx2 and alkaline phosphatase (ALP)], as well as ALP activity, and stimulation increased osteoblast mineralization. The expression of A2AR was upregulated during later stages of osteoblastic differentiation, when its activation stimulated ALP activity. Differentiation of MSCs to adipocytes was accompanied by significant increases in A1R and A2AR expression, and their activation was associated with increased adipogenesis. Enhanced A2AR expression was sufficient to promote expression of adipocyte-related genes (PPAR and C/EBP), and its activation resulted in increased adipocytic differentiation and lipid accumulation. In contrast, the A1R was involved mainly in lipogenic activity of adipocytes rather than in their differentiation. These results show that adenosine receptors are differentially expressed and involved in lineage-specific differentiation of MSCs. We conclude, therefore, that fruitful strategies for treating diseases associated with an imbalance in the differentiation and function of these lineages should include targeting adenosine receptor signal pathways. Specifically, these research avenues will be useful in preventing or treating conditions with insufficient bone or excessive adipocyte formation

Variable Baseline Papio cynocephalus Endogenous Retrovirus (PcEV) Expression Is Upregulated in Acutely SIV-Infected Macaques and Correlated to STAT1 Expression in the Spleen

Retroviral replication leaves a DNA copy in the host cell chromosome, which over millions of years of infection of germline cells has led to 5% of the human genome sequence being comprised of endogenous retroviruses (ERVs), distributed throughout an estimated 100,000 loci. Over time these loci have accrued mutations such as premature stop codons that prevent continued replication. However, many loci remain both transcriptionally and translationally active and ERVs have been implicated in interacting with the host immune system. Using archived plasma and tissue samples from past macaque studies, experimentally infected with simian immunodeficiency virus (SIV), the expression of one macaque ERV in response to acute viral infection was explored together with a measure of the innate immune response. Specifically, RNA levels were determined for (a) Papio cynocephalus Endogenous Retrovirus (PcEV), an ERV (b) STAT1, a key gene in the interferon signaling pathway, and (c) SIV, an exogenous pathogen. Bioinformatic analysis of DNA sequences of the PcEV loci within the macaque reference genome revealed the presence of open reading frames (ORFs) consistent with potential protein expression but not ERV replication. Quantitative RT-PCR analysis of DNase-treated RNA extracts from plasma derived from acute SIV-infection detected PcEV RNA at low levels in 7 of 22 macaques. PcEV RNA levels were significantly elevated in PBMC and spleen samples recovered during acute SIV infection, but not in the thymus and lymph nodes. A strong positive correlation was identified between PcEV and STAT1 RNA levels in spleen samples recovered from SIV-positive macaques. One possibility is that SIV infection induces PcEV expression in infected lymphoid tissue that contributes to induction of an antiviral response

De novo sequencing, assembly and analysis of the genome of the laboratory strain Saccharomyces cerevisiae CEN.PK113-7D, a model for modern industrial biotechnology

Saccharomyces cerevisiae CEN.PK 113-7D is widely used for metabolic engineering and systems biology research in industry and academia. We sequenced, assembled, annotated and analyzed its genome. Single-nucleotide variations (SNV), insertions/deletions (indels) and differences in genome organization compared to the reference strain S. cerevisiae S288C were analyzed. In addition to a few large deletions and duplications, nearly 3000 indels were identified in the CEN.PK113-7D genome relative to S288C. These differences were overrepresented in genes whose functions are related to transcriptional regulation and chromatin remodelling. Some of these variations were caused by unstable tandem repeats, suggesting an innate evolvability of the corresponding genes. Besides a previously characterized mutation in adenylate cyclase, the CEN.PK113-7D genome sequence revealed a significant enrichment of non-synonymous mutations in genes encoding for components of the cAMP signalling pathway. Some phenotypic characteristics of the CEN.PK113-7D strains were explained by the presence of additional specific metabolic genes relative to S288C. In particular, the presence of the BIO1 and BIO6 genes correlated with a biotin prototrophy of CEN.PK113-7D. Furthermore, the copy number, chromosomal location and sequences of the MAL loci were resolved. The assembled sequence reveals that CEN.PK113-7D has a mosaic genome that combines characteristics of laboratory strains and wild-industrial strains

Higgs Boson Theory and Phenomenology

Precision electroweak data presently favors a weakly-coupled Higgs sector as the mechanism responsible for electroweak symmetry breaking. Low-energy supersymmetry provides a natural framework for weakly-coupled elementary scalars. In this review, we summarize the theoretical properties of the Standard Model (SM) Higgs boson and the Higgs sector of the minimal supersymmetric extension of the Standard Model (MSSM). We then survey the phenomenology of the SM and MSSM Higgs bosons at the Tevatron, LHC and a future e+e- linear collider. We focus on the Higgs discovery potential of present and future colliders and stress the importance of precision measurements of Higgs boson properties.Comment: 90 pages, 31 figures. Revised version. To be published in Progress in Particle and Nuclear Physics. This paper with higher resolution figures can be found at http://scipp.ucsc.edu/~haber/higgsreview/higgsrev.p

Physics searches at the LHC

With the LHC up and running, the focus of experimental and theoretical high energy physics will soon turn to an interpretation of LHC data in terms of the physics of electroweak symmetry breaking and the TeV scale. We present here a broad review of models for new TeV-scale physics and their LHC signatures. In addition, we discuss possible new physics signatures and describe how they can be linked to specific models of physics beyond the Standard Model. Finally, we illustrate how the LHC era could culminate in a detailed understanding of the underlying principles of TeV-scale physics.Comment: 184 pages, 55 figures, 14 tables, hundreds of references; scientific feedback is welcome and encouraged. v2: text, references and Overview Table added; feedback still welcom

Continuous-time modeling of cell fate determination in Arabidopsis flowers

<p>Abstract</p> <p>Background</p> <p>The genetic control of floral organ specification is currently being investigated by various approaches, both experimentally and through modeling. Models and simulations have mostly involved boolean or related methods, and so far a quantitative, continuous-time approach has not been explored.</p> <p>Results</p> <p>We propose an ordinary differential equation (ODE) model that describes the gene expression dynamics of a gene regulatory network that controls floral organ formation in the model plant <it>Arabidopsis thaliana</it>. In this model, the dimerization of MADS-box transcription factors is incorporated explicitly. The unknown parameters are estimated from (known) experimental expression data. The model is validated by simulation studies of known mutant plants.</p> <p>Conclusions</p> <p>The proposed model gives realistic predictions with respect to independent mutation data. A simulation study is carried out to predict the effects of a new type of mutation that has so far not been made in <it>Arabidopsis</it>, but that could be used as a severe test of the validity of the model. According to our predictions, the role of dimers is surprisingly important. Moreover, the functional loss of any dimer leads to one or more phenotypic alterations.</p

The appended curve technique for deconvolutional analysis —method and validation

Deconvolutional analysis (DCA) is useful in correction of organ time activity curves (response function) for variations in blood activity (input function). Despite enthusiastic reports of applications of DCA in renal and cardiac scintigraphy, routine use has awaited an easily implemented algorithm which is insensitive to statistical noise. The matrix method suffers from the propagation of errors in early data points through the entire curve. Curve fitting or constraint methods require prior knowledge of the expected form of the results. DCA by Fourier transforms (FT) is less influenced by single data points but often suffers from high frequency artifacts which result from the abrupt termination of data acquisition at a nonzero value.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46829/1/259_2004_Article_BF00254393.pd