60 research outputs found

    An ovary transcriptome for all maturational stages of the striped bass (Morone saxatilis), a highly advanced perciform fish

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    <p>Abstract</p> <p>Background</p> <p>The striped bass and its relatives (genus <it>Morone</it>) are important fisheries and aquaculture species native to estuaries and rivers of the Atlantic coast and Gulf of Mexico in North America. To open avenues of gene expression research on reproduction and breeding of striped bass, we generated a collection of expressed sequence tags (ESTs) from a complementary DNA (cDNA) library representative of their ovarian transcriptome.</p> <p>Results</p> <p>Sequences of a total of 230,151 ESTs (51,259,448 bp) were acquired by Roche 454 pyrosequencing of cDNA pooled from ovarian tissues obtained at all stages of oocyte growth, at ovulation (eggs), and during preovulatory atresia. Quality filtering of ESTs allowed assembly of 11,208 high-quality contigs ≄ 100 bp, including 2,984 contigs 500 bp or longer (average length 895 bp). Blastx comparisons revealed 5,482 gene orthologues (E-value < 10<sup>-3</sup>), of which 4,120 (36.7% of total contigs) were annotated with Gene Ontology terms (E-value < 10<sup>-6</sup>). There were 5,726 remaining unknown unique sequences (51.1% of total contigs). All of the high-quality EST sequences are available in the National Center for Biotechnology Information (NCBI) Short Read Archive (GenBank: <ext-link ext-link-id="SRX007394" ext-link-type="gen">SRX007394</ext-link>). Informative contigs were considered to be abundant if they were assembled from groups of ESTs comprising ≄ 0.15% of the total short read sequences (≄ 345 reads/contig). Approximately 52.5% of these abundant contigs were predicted to have predominant ovary expression through digital differential display <it>in silico </it>comparisons to zebrafish (<it>Danio rerio</it>) UniGene orthologues. Over 1,300 Gene Ontology terms from Biological Process classes of Reproduction, Reproductive process, and Developmental process were assigned to this collection of annotated contigs.</p> <p>Conclusions</p> <p>This first large reference sequence database available for the ecologically and economically important temperate basses (genus <it>Morone</it>) provides a foundation for gene expression studies in these species. The predicted predominance of ovary gene expression and assignment of directly relevant Gene Ontology classes suggests a powerful utility of this dataset for analysis of ovarian gene expression related to fundamental questions of oogenesis. Additionally, a high definition Agilent 60-mer oligo ovary 'UniClone' microarray with 8 × 15,000 probe format has been designed based on this striped bass transcriptome (eArray Group: Striper Group, Design ID: 029004).</p

    NACCHO Exchange: Health Equity

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    Essential Elements of Health Equity Practice: Partnering to Support Power-Building; Revitalizing Communities: Partnerships to Create Active, Safe Places in Merced County, California; Advancing Health Equity through Regional Collaboration; and Governing for Racial Equity: A Local Health Department's Journe

    Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

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    Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95)

    Dogs demonstrate the existence of an epileptic seizure odour in humans

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    International audienceAlthough different studies have shown that diseases such as breast or lung cancer are associated with specific bodily odours, no study has yet tested the possibility that epileptic seizures may be reflected in an olfactory profile, probably because there is a large variety of seizure types. The question is whether a “seizure-odour”, that would be transversal to individuals and types of seizures, exists. This would be a pre requisite for potential anticipation, either by electronic systems (e.g., e-noses) or trained dogs. The aim of the present study therefore was to test whether trained dogs, as demonstrated for cancer or diabetes, may discriminate a general epileptic seizure odor (different from body odours of the same person in other contexts and common to different persons). The results were very clear: all dogs discriminated the seizure odour. The sensitivity and specificity obtained were amongst the highest shown up to now for discrimination of diseases. This constitutes a first proof that, despite the variety of seizures and individual odours, seizures are associated with olfactory characteristics. These results open a large field of research on the odour signature of seizures. Further studies will aim to look at potential applications in terms of anticipation of seizures

    Compartment Proteomics Analysis of White Perch (<i>Morone americana</i>) Ovary Using Support Vector Machines

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    Compartment proteomics enable broad characterization of target tissues. We employed a simple fractionation method and filter-aided sample preparation (FASP) to characterize the cytosolic and membrane fractions of white perch ovary tissues by semiquantitative tandem mass spectrometry using label-free quantitation based on normalized spectral counts. FASP depletes both low-molecular-weight and high-molecular-weight substances that could interfere with protein digestion and subsequent peptide separation and detection. Membrane proteins are notoriously difficult to characterize due to their amphipathic nature and association with lipids. The simple fractionation we employed effectively revealed an abundance of proteins from mitochondria and other membrane-bounded organelles. We further demonstrate that support vector machines (SVMs) offer categorical classification of proteomics data superior to that of parametric statistical methods such as analysis of variance (ANOVA). Specifically, SVMs were able to perfectly (100% correct) classify samples as either membrane or cytosolic fraction during cross-validation based on the expression of 242 proteins with the highest ANOVA <i>p</i>-values (i.e., those that were not significant for enrichment in either fraction). The white perch ovary cytosolic and membrane proteomes and transcriptome presented in this study can support future investigations into oogenesis and early embryogenesis of white perch and other members of the genus <i>Morone</i>

    Compartment Proteomics Analysis of White Perch (<i>Morone americana</i>) Ovary Using Support Vector Machines

    No full text
    Compartment proteomics enable broad characterization of target tissues. We employed a simple fractionation method and filter-aided sample preparation (FASP) to characterize the cytosolic and membrane fractions of white perch ovary tissues by semiquantitative tandem mass spectrometry using label-free quantitation based on normalized spectral counts. FASP depletes both low-molecular-weight and high-molecular-weight substances that could interfere with protein digestion and subsequent peptide separation and detection. Membrane proteins are notoriously difficult to characterize due to their amphipathic nature and association with lipids. The simple fractionation we employed effectively revealed an abundance of proteins from mitochondria and other membrane-bounded organelles. We further demonstrate that support vector machines (SVMs) offer categorical classification of proteomics data superior to that of parametric statistical methods such as analysis of variance (ANOVA). Specifically, SVMs were able to perfectly (100% correct) classify samples as either membrane or cytosolic fraction during cross-validation based on the expression of 242 proteins with the highest ANOVA <i>p</i>-values (i.e., those that were not significant for enrichment in either fraction). The white perch ovary cytosolic and membrane proteomes and transcriptome presented in this study can support future investigations into oogenesis and early embryogenesis of white perch and other members of the genus <i>Morone</i>
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