Genome-wide analyses of gene expression during mouse endochondral ossification

Background: Endochondral ossification is a complex process involving a series of events that are initiated by the establishment of a chondrogenic template and culminate in its replacement through the coordinated activity of osteoblasts, osteoclasts and endothelial cells. Comprehensive analyses of in vivo gene expression profiles during these processes are essential to obtain a complete understanding of the regulatory mechanisms involved. Methodology/Principal Findings: To address these issues, we completed a microarray screen of three zones derived from manually segmented embryonic mouse tibiae. Classification of genes differentially expressed between each respective zone, functional categorization as well as characterization of gene expression patterns, cytogenetic loci, signaling pathways and functional motifs both confirmed reported data and provided novel insights into endochondral ossification. Parallel comparisons of the microdissected tibiae data set with our previously completed micromass culture screen further corroborated the suitability of micromass cultures for modeling gene expression in chondrocyte development. The micromass culture system demonstrated striking similarities to the in vivo microdissected tibiae screen; however, the micromass system was unable to accurately distinguish gene expression differences in the hypertrophic and mineralized zones of the tibia. Conclusions/Significance: These studies allow us to better understand gene expression patterns in the growth plate and endochondral bones and provide an important technical resource for comparison of gene expression in diseased or experimentally-manipulated cartilages. Ultimately, this work will help to define the genomic context in which genes are expressed in long bones and to understand physiological and pathological ossification. © 2010 James et al

Genome-Wide Analyses of Gene Expression during Mouse Endochondral Ossification

Endochondral ossification is a complex process involving a series of events that are initiated by the establishment of a chondrogenic template and culminate in its replacement through the coordinated activity of osteoblasts, osteoclasts and endothelial cells. Comprehensive analyses of in vivo gene expression profiles during these processes are essential to obtain a complete understanding of the regulatory mechanisms involved.To address these issues, we completed a microarray screen of three zones derived from manually segmented embryonic mouse tibiae. Classification of genes differentially expressed between each respective zone, functional categorization as well as characterization of gene expression patterns, cytogenetic loci, signaling pathways and functional motifs both confirmed reported data and provided novel insights into endochondral ossification. Parallel comparisons of the microdissected tibiae data set with our previously completed micromass culture screen further corroborated the suitability of micromass cultures for modeling gene expression in chondrocyte development. The micromass culture system demonstrated striking similarities to the in vivo microdissected tibiae screen; however, the micromass system was unable to accurately distinguish gene expression differences in the hypertrophic and mineralized zones of the tibia.These studies allow us to better understand gene expression patterns in the growth plate and endochondral bones and provide an important technical resource for comparison of gene expression in diseased or experimentally-manipulated cartilages. Ultimately, this work will help to define the genomic context in which genes are expressed in long bones and to understand physiological and pathological ossification

Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours

Currently available human tumour cell line panels consist of a small number of lines in each lineage that generally fail to retain the phenotype of the original patient tumour. Here we develop a cell culture medium that enables us to routinely establish cell lines from diverse subtypes of human ovarian cancers with >95% efficiency. Importantly, the 25 new ovarian tumour cell lines described here retain the genomic landscape, histopathology and molecular features of the original tumours. Furthermore, the molecular profile and drug response of these cell lines correlate with distinct groups of primary tumours with different outcomes. Thus, tumour cell lines derived using this methodology represent a significantly improved platform to study human tumour pathophysiology and response to therapy

Reparametrizing Swung Surfaces over the Reals

Let K⊆R be a computable subfield of the real numbers (for instance, Q). We present an algorithm to decide whether a given parametrization of a rational swung surface, with coefficients in K(i), can be reparametrized over a real (i.e., embedded in R) finite field extension of K. Swung surfaces include, in particular, surfaces of revolution

TVL₁ Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

Multiple Holdouts With Stability: Improving the Generalizability of Machine Learning Analyses of Brain-Behavior Relationships.

BACKGROUND:In 2009, the National Institute of Mental Health launched the Research Domain Criteria, an attempt to move beyond diagnostic categories and ground psychiatry within neurobiological constructs that combine different levels of measures (e.g., brain imaging and behavior). Statistical methods that can integrate such multimodal data, however, are often vulnerable to overfitting, poor generalization, and difficulties in interpreting the results. METHODS:We propose an innovative machine learning framework combining multiple holdouts and a stability criterion with regularized multivariate techniques, such as sparse partial least squares and kernel canonical correlation analysis, for identifying hidden dimensions of cross-modality relationships. To illustrate the approach, we investigated structural brain-behavior associations in an extensively phenotyped developmental sample of 345 participants (312 healthy and 33 with clinical depression). The brain data consisted of whole-brain voxel-based gray matter volumes, and the behavioral data included item-level self-report questionnaires and IQ and demographic measures. RESULTS:Both sparse partial least squares and kernel canonical correlation analysis captured two hidden dimensions of brain-behavior relationships: one related to age and drinking and the other one related to depression. The applied machine learning framework indicates that these results are stable and generalize well to new data. Indeed, the identified brain-behavior associations are in agreement with previous findings in the literature concerning age, alcohol use, and depression-related changes in brain volume. CONCLUSIONS:Multivariate techniques (such as sparse partial least squares and kernel canonical correlation analysis) embedded in our novel framework are promising tools to link behavior and/or symptoms to neurobiology and thus have great potential to contribute to a biologically grounded definition of psychiatric disorders

Physiological properties of enkephalin-containing neurons in the spinal dorsal horn visualized by expression of green fluorescent protein in BAC transgenic mice

<p>Abstract</p> <p>Background</p> <p>Enkephalins are endogenous opiates that are assumed to modulate nociceptive information by mediating synaptic transmission in the central nervous system, including the spinal dorsal horn.</p> <p>Results</p> <p>To develop a new tool for the identification of <it>in vitro </it>enkephalinergic neurons and to analyze enkephalin promoter activity, we generated transgenic mice for a bacterial artificial chromosome (BAC). Enkephalinergic neurons from these mice expressed enhanced green fluorescent protein (eGFP) under the control of the preproenkephalin (PPE) gene (<it>penk1</it>) promoter. eGFP-positive neurons were distributed throughout the gray matter of the spinal cord, and were primarily observed in laminae I-II and V-VII, in a pattern similar to the distribution pattern of enkephalin-containing neurons. Double immunostaining analysis using anti-enkephalin and anti-eGFP antibodies showed that all eGFP-expressing neurons contained enkephalin. Incubation in the presence of forskolin, an activator of adenylate cyclase, increased the number of eGFP-positive neurons. These results indicate that eGFP expression is controlled by the <it>penk1 </it>promoter, which contains cyclic AMP-responsive elements. Sections obtained from sciatic nerve-ligated mice exhibited increased eGFP-positive neurons on the ipsilateral (nerve-ligated side) compared with the contralateral (non-ligated side). These data indicate that PPE expression is affected by peripheral nerve injury. Additionally, single-neuron RT-PCR analysis showed that several eGFP positive-neurons in laminae I-II expressed glutamate decarboxylase 67 mRNA and that some expressed serotonin type 3 receptors.</p> <p>Conclusions</p> <p>These results suggest that eGFP-positive neurons in laminae I-II coexpress enkephalin and γ-aminobutyric acid (GABA), and are activated by forskolin and in conditions of nerve injury. The <it>penk1</it>-eGFP BAC transgenic mouse contributes to the further characterization of enkephalinergic neurons in the transmission and modulation of nociceptive information.</p

Dexamethasone stimulates expression of C-type Natriuretic Peptide in chondrocytes

BACKGROUND: Growth of endochondral bones is regulated through the activity of cartilaginous growth plates. Disruption of the physiological patterns of chondrocyte proliferation and differentiation – such as in endocrine disorders or in many different genetic diseases (e.g. chondrodysplasias) – generally results in dwarfism and skeletal defects. For example, glucocorticoid administration in children inhibits endochondral bone growth, but the molecular targets of these hormones in chondrocytes remain largely unknown. In contrast, recent studies have shown that C-type Natriuretic Peptide (CNP) is an important anabolic regulator of cartilage growth, and loss-of-function mutations in the human CNP receptor gene cause dwarfism. We asked whether glucocorticoids could exert their activities by interfering with the expression of CNP or its downstream signaling components. METHODS: Primary mouse chondrocytes in monolayer where incubated with the synthetic glucocorticoid Dexamethasone (DEX) for 12 to 72 hours. Cell numbers were determined by counting, and real-time PCR was performed to examine regulation of genes in the CNP signaling pathway by DEX. RESULTS: We show that DEX does influence expression of key genes in the CNP pathway. Most importantly, DEX significantly increases RNA expression of the gene encoding CNP itself (Nppc). In addition, DEX stimulates expression of Prkg2 (encoding cGMP-dependent protein kinase II) and Npr3 (natriuretic peptide decoy receptor) genes. Conversely, DEX was found to down-regulate the expression of the gene encoding its receptor, Nr3c1 (glucocorticoid receptor), as well as the Npr2 gene (encoding the CNP receptor). CONCLUSION: Our data suggest that the growth-suppressive activities of DEX are not due to blockade of CNP signaling. This study reveals a novel, unanticipated relationship between glucocorticoid and CNP signaling and provides the first evidence that CNP expression in chondrocytes is regulated by endocrine factors