Understanding the Bare Breech Phenotype

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A phenotype of resiliency? cross-sectional psychobiological differences between caregivers who are vulnerable vs. resilient to depression, and controls

Introduction: Being a caregiver of chronically ill children is a source of chronic-psychological stress affecting general physical and mental health. However, there is tremendous variance among caregivers: some may develop stress-related depression, whereas others are more “resilient”. The objective of the study was to phenotypically differentiate on psychobiology caregivers who developed depressive symptoms (“vulnerable”) vs. those who did not (“resilient”) from each other and from age-matched controls. Methods: Forty-five mothers of chronically-ill children and 18 controls have been examined. Caregivers were divided via a median split of Center for Epidemiological Studies Depression Scale scores in “resilient” (RCs) and “vulnerable” (VCs). We assessed cognitive, affective, metabolic, neuroendocrine and oxidative markers at rest and in response to a laboratory social stressor. ANCOVAs and Bonferroni post-hoc tests were used to examine between-group differences. Results: Although RCs compared to VCs had similar levels of objective parenting-related burden (P = 0.51), they had lower subjective distress (P < 0.01) and higher levels of positive affect (P = 0.04). Although RCs compared to controls had higher levels of objective parenting-related burden (P = 0.04), they had greater cortisol suppression post-dexamethasone (P = 0.05), lower F2-isoprostanes/vitamin E ratio (P < 0.01) and lower fasting insulin levels (P = 0.06). Discussion: Our results suggest that caregivers with higher resiliency demonstrate more salutary stress-related functioning in comparison with less resilient caregivers and, more surprisingly, non-caregiver controls. These findings might be interpreted in the spirit of Nietzsche's quote “What does not kill me, makes me stronger” and of the idea that successfully overcoming adversity may be more psychobiologically beneficial than not having been exposed to any adversity

Virus-induced gene silencing database for phenomics and functional genomics in Nicotiana benthamiana

Virus-induced gene silencing (VIGS) is an important forward and reverse genetics method for the study of gene function in many plant species, especially Nicotiana benthamiana. However, despite the widespread use of VIGS, a searchable database compiling the phenotypes observed with this method is lacking. Such a database would allow researchers to know the phenotype associated with the silencing of a large number of individual genes without experimentation. We have developed a VIGS phenomics and functional genomics database (VPGD) that has DNA sequence information derived from over 4,000 N. benthamiana VIGS clones along with the associated silencing phenotype for approximately 1,300 genes. The VPGD has a built-in BLAST search feature that provides silencing phenotype information of specific genes. In addition, a keyword-based search function could be used to find a specific phenotype of interest with the corresponding gene, including its Gene Ontology descriptions. Query gene sequences from other plant species that have not been used for VIGS can also be searched for their homologs and silencing phenotype in N. benthamiana. VPGD is useful for identifying gene function not only in N. benthamiana but also in related Solanaceae plants such as tomato and potato. The database is accessible at http://vigs.noble.org.Noble Research Institute and NSF IOS-102564

PhenDisco: phenotype discovery system for the database of genotypes and phenotypes.

The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI's dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaP's search engine Entrez. The system can be accessed at http://pfindr.net

Notes on the Genetics of \u3ci\u3ePhymatodes Testaceus\u3c/i\u3e (Coleoptera: Cerambycidae)

Phenotype ratio for elytral coloration among reared offspring of Phymatodes testaceus suggests that this trait is controlled by a single gene with a dominant allele producing brown elytra and a reeessive allele for blue elytra. The brown-elytra phenotype previously has been reported as recessive in this species

Peroxisome biogenesis in Hansenula polymorpha: different mutations in genes, essential for peroxisome biogenesis, cause different peroxisomal mutant phenotypes

In Hansenula polymorpha, different monogenic recessive mutations mapped in either of two previously identified genes, PER1 and PER3, produced different peroxisomal mutant phenotypes. Among five per1 mutants, four showed a Pim- phenotype: the cells contained few small peroxisomes while the bulk of the matrix enzymes resided in the cytosol. One of these mutants, per1-124 had an enhanced rate of peroxisome proliferation. The fifth mutant completely lacked peroxisomes (Per- phenotype). Of seven per3 mutants, four displayed a Pim- phenotype, two others a Per- phenotype, while one mutant showed pH-dependent growth on methanol and was affected in oligomerization of peroxisomal matrix protein. Thus, the protein products of both PER1 and PER3 genes appear to be essential in different aspects of peroxisome assembly/proliferation.

Treating Macrophages with Anti-inflammatory Nanoparticles as a Strategy to Improve Muscle Repair

The macrophage is an immune cell that is involved in host defense. More recent research, however, has revealed that they also play a central role in mediating the skeletal muscle regenerative process. Upon muscle injury, macrophages are recruited to the damaged site and begin differentiating into a pro-inflammatory phenotype, known as the M1 phenotype. M1 macrophages secrete inflammatory cytokines to facilitate the acute response to muscle injury, and are characterized by phagocytosis of cellular debris and exhibiting strong microbicidal activity. However, another hallmark of inflammatory macrophages is the metabolism of arginine into nitric oxide (NO), which is further metabolized into other reactive oxygen species such as superoxide and peroxynitrite. If left unchecked, prolonged macrophage inflammation leads to muscle cell lysis due to the persistence of reactive oxygen radicals. The capacity of macrophages to stimulate myogenic cells to proliferate is also reduced if inflammation persists. To improve muscle regeneration, we have developed and synthesized a nanoparticle formulation that allows controlled reduction of macrophage inflammatory phenotype. Previous published studies have shown lactic acid and magnesium as chemical agents that attenuate M1 phenotype in macrophages. We developed a poly-lactic-co-glycolic acid (PLGA) nanoparticle emulsified with magnesium sulfate to attenuate the inflammatory phenotype in a murine macrophage cell line. This Magnesium-PLGA nanoparticle has been optimized to be uptaken by macrophages without affecting cell viability. We hope that these contributions make the first steps towards developing an injectable therapy to modulate macrophage phenotype, and can be used in conjunction with existing treatments to improve skeletal muscle repair following injury.Biomedical Engineerin

Multiple Ontologies for Integrating Complex Phenotype Datasets

There has been an emergence of multiple large scale phenotyping projects in the rat model organism community as well as renewed interest in the ongoing phenotype data generated by thousands of researchers using hundreds of rat strains worldwide. Unfortunately, this data is scattered and is neither described nor formatted in a standardized manner. A system to integrate complex phenotype data from multiple sources and facilitate data mining and analysis is being developed using multiple ontologies.&#xd;&#xa;&#xd;&#xa;*Introduction*&#xd;&#xa;The potential value of integrating phenotype data from multiple sources (different laboratories, varying techniques to measure similar phenotypes, multiple strains) is enormous. Presented here is a data integration system for complex phenotype data from both large-scale and individual experiments and the taxonomy and ontologies that provide the backbone of this format. RGD along with Mouse Genome Informatics (MGI) (Blake et al, 2009) and the Animal QTL Database (Hu and Reecy, 2007) is developing a Vertebrate Trait Ontology to represent morphological states and physiological processes to be used to annotate quantitative trait loci (QTL) and other data. RGD has also used the Mammalian Phenotype Ontology (Smith et al, 2005) for several years to indicate the relationship of genomic elements to abnormal phenotypes. The Vertebrate Trait Ontology represents what is being assessed, and the Mammalian Phenotype Ontology represents the conclusion that was made. The system presented here represents what was done to measure the trait in order to reach the conclusion. Because of the close relationship among these ontologies, care is being taken to ensure compatibility and similarity in structure using the phenotype properties in the Phenotypic Quality Ontology (PATO) for guidance. (&#x22;http://www.bioontology.org/wiki/index.php/PATO:Main_Page&#x22;:http://www.bioontology.org/wiki/index.php/PATO:Main_Page) &#xd;&#xa;&#xd;&#xa;*Data Format and Ontologies*&#xd;&#xa;Standardization of data types and relationships used to define the phenotype experiment and resulting data, and the ontologies to be used to standardize descriptive fields are being developed. For phenotype data, the major informational components include Researcher, Study, Experiment, Sample, Experimental Conditions and Clinical Measurement. A Rat Strain Taxonomy has been developed to standardize this information and provide the relationships among strains to allow investigators to retrieve and analyze phenotype data for strains that are related genetically. Two important aspects of a phenotype measurement include 1) what was measured and 2) how it was measured. The Clinical Measurement Ontology and the Measurement Method Ontology are being developed to standardize this information. In addition an Experimental Conditions ontology is under construction to allow integration of data measured under various conditions.&#xd;&#xa;&#xd;&#xa;*Pilot Study Results*&#xd;&#xa;Cardiovascular and biochemistry phenotype data from two major datasets have been integrated using the Rat Strain Taxonomy and the three phenotype related ontologies. A prototype data mining tool (&#x22;http://rgd.mcw.edu/rgdweb/&#x22;:http://rgd.mcw.edu/rgdweb/) has also been developed that provides the user with options to begin a search with strains or any of the ontologies and make subsequent filter choices from the other ontologies. Choices presented to the user are restricted to those for which data is available and query tracking functions are provided to alert the user to the number of results being returned and the query choices made.&#xd;&#xa;&#xd;&#xa;*References*&#xd;&#xa;Blake JA, Bult CJ, Eppig JT, Kadin JA, Richardson JE; Mouse Genome Database Group, 2009 _Nucleic Acids Res_. Jan;37:D712-9.&#xd;&#xa;&#xd;&#xa;HuZL, Reecy JM, Animal QTLdb: beyond a repository. A public platform for QTL comparisons and integration with diverse types of structural genomic information, 2007, _Mamm Genome_, Jan;18(1):1-4.&#xd;&#xa;&#xd;&#xa;Smith CL, Goldsmith CA, Eppig JT. The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information, _Genome Biol_. 2005 6(1):R7.&#xd;&#xa

Divergences in insulin resistance between the different phenotypes of the polycystic ovary syndrome

Context/Objective: Current diagnostic criteria for polycystic ovary syndrome (PCOS) have generated distinct PCOS phenotypes, based on the different combinations of diagnostic features found in each patient. Our aim was to assess whether either each single diagnostic feature or their combinations into the PCOS phenotypes may predict insulin resistance in these women. Patients/Design: A total of 137 consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of diagnostic and metabolic features. Insulin sensitivity was measured by the glucose clamp technique. Results: Among women with PCOS, 84.7% had hyperandrogenism, 84.7% had chronic oligoanovulation, and 89% had polycystic ovaries. According to the individual combinations of these features, 69.4% of women had the classic phenotype, 15.3% had the ovulatory phenotype, and 15.3% had the normoandrogenic phenotype. Most subjects (71.4%) were insulin resistant. However, insulin resistance frequency differed among phenotypes, being 80.4%, 65.0%, and 38.1%, respectively, in the 3 subgroups (P < .001). Although none of the PCOS diagnostic features per se was associated with the impairment in insulin action, after adjustment for covariates, the classic phenotype and, to a lesser extent, the ovulatory phenotype were independently associated with insulin resistance, whereas the normoandrogenic phenotype was not. Metabolic syndrome frequency was also different among phenotypes (P = .030). Conclusions: There is a scale of metabolic risk among women with PCOS. Although no single diagnostic features of PCOS are independently associated with insulin resistance, their combinations, which define PCOS phenotypes, may allow physicians to establish which women should undergo metabolic screening. In metabolic terms, women belonging to the normoandrogenic phenotype behave as a separate group