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Tyler, TX, United States

College Station is a city in Brazos County, Texas, situated in East Central Texas in the heart of the Brazos Valley. It is north from both Houston and Austin. As of the 2010 census, College Station had a population of 93,857, which had increased to an estimated population of 100,050 as of July 2013. College Station and Bryan together make up the Bryan-College Station metropolitan area, the 15th largest metropolitan area in Texas with 228,660 people as of the 2010 census.College Station is home to the main campus of Texas A&M University, the flagship institution of the Texas A&M University System. The city owes both its name and existence to the university's location along a railroad. Texas A&M's triple designation as a Land-, Sea-, and Space-Grant institution reflects the broad scope of the research endeavors it brings to the city, with ongoing projects funded by agencies such as NASA, the National Institutes of Health, the National Science Foundation and the Office of Naval Research.Due largely to the presence of Texas A&M University, College Station was named by Money magazine in 2006 as the most educated city in Texas, and the 11th most educated city in the United States. Wikipedia.


Sridharan S.,Texas College
BMC genomics | Year: 2012

Oxidative stress is a consequence of normal and abnormal cellular metabolism and is linked to the development of human diseases. The effective functioning of the pathway responding to oxidative stress protects the cellular DNA against oxidative damage; conversely the failure of the oxidative stress response mechanism can induce aberrant cellular behavior leading to diseases such as neurodegenerative disorders and cancer. Thus, understanding the normal signaling present in oxidative stress response pathways and determining possible signaling alterations leading to disease could provide us with useful pointers for therapeutic purposes. Using knowledge of oxidative stress response pathways from the literature, we developed a Boolean network model whose simulated behavior is consistent with earlier experimental observations from the literature. Concatenating the oxidative stress response pathways with the PI3-Kinase-Akt pathway, the oxidative stress is linked to the phenotype of apoptosis, once again through a Boolean network model. Furthermore, we present an approach for pinpointing possible fault locations by using temporal variations in the oxidative stress input and observing the resulting deviations in the apoptotic signature from the normally predicted pathway. Such an approach could potentially form the basis for designing more effective combination therapies against complex diseases such as cancer. In this paper, we have developed a Boolean network model for the oxidative stress response. This model was developed based on pathway information from the current literature pertaining to oxidative stress. Where applicable, the behaviour predicted by the model is in agreement with experimental observations from the published literature. We have also linked the oxidative stress response to the phenomenon of apoptosis via the PI3k/Akt pathway. It is our hope that some of the additional predictions here, such as those pertaining to the oscillatory behaviour of certain genes in the presence of oxidative stress, will be experimentally validated in the near future. Of course, it should be pointed out that the theoretical procedure presented here for pinpointing fault locations in a biological network with feedback will need to be further simplified before it can be even considered for practical biological validation. Source


In cattle, base color is assumed to depend on the enzymatic activity specified by the MC1R locus, i.e. the extension locus, with alleles coding for black (E(D)), red (e), and wild-type (E+). In most mammals, these alleles are presumed to follow the dominance model of E(D) > E+ > e, although exceptions are found. In Bos indicus x Bos taurus F2 cattle, some E(D)E+ heterozygotes are discordant with the dominance series for MC1R and display various degrees of red pigmentation on an otherwise predicted black background. The objective of this study was to identify loci that modify black coat color in these individuals. Reddening was classified with a subjective scoring system. Interval analyses identified chromosome-wide suggestive (P < 0.05) and significant (P < 0.01) QTL on bovine chromosomes (BTA) 4 and 5, although these were not confirmed using single-marker association or Bayesian methods. Evidence of a major locus (F = 114.61) that affects reddening was detected between 60 and 73 Mb on BTA 6 (Btau4.0 build), and at 72 Mb by single-marker association and Bayesian methods. The posterior mean of the genetic variance for this region accounted for 43.75% of the genetic variation in reddening. This region coincided with a cluster of tyrosine kinase receptor genes (PDGFRA, KIT and KDR). Fitting SNP haplotypes for a 1 Mb interval that contained all three genes and centered on KIT accounted for the majority of the variation attributed to this major locus, which suggests that one of these genes or associated regulatory elements, is responsible for the majority of variation in degree of reddening. Recombinants in a 5 Mb region surrounding the cluster of tyrosine kinase receptor genes implicated PDGFRA as the strongest positional candidate gene. A higher density marker panel and functional analyses will be required to validate the role of PDGFRA or other regulatory variants and their interaction with MC1R for the modification of black coat color in Bos indicus influenced cattle. Source


Domain microstructure evolution during magnetic field-induced twin boundary motion in magnetic shape memory alloys was investigated using phase field micromagnetic microelastic modeling. The computer simulations show bending and splitting of magnetic domain walls, magnetization rotation due to external and internal magnetic fields and pinning of magnetic domain wall motion at twin boundaries. The study reveals the important roles of magnetostatic interaction in the domain processes, providing insights into the complex domain phenomena in magnetic shape memory alloys and explaining experimentally observed domain microstructures. Source


BACKGROUND: Karenia brevis is a harmful algal species that blooms in the Gulf of Mexico and produces brevetoxins that cause neurotoxic shellfish poisoning. Elevated brevetoxin levels in K. brevis cells have been measured during laboratory hypo-osmotic stress treatments. To investigate mechanisms underlying K. brevis osmoacclimation and osmoregulation and establish a valuable resource for gene discovery, we assembled reference transcriptomes for three clones: Wilson-CCFWC268, SP3, and SP1 (a low-toxin producing variant). K. brevis transcriptomes were annotated with gene ontology terms and searched for putative transmembrane proteins that may elucidate cellular responses to hypo-osmotic stress. An analysis of single nucleotide polymorphisms among clones was used to characterize genetic divergence.RESULTS: K. brevis reference transcriptomes were assembled with 58.5 (Wilson), 78.0 (SP1), and 51.4 million (SP3) paired reads. Transcriptomes contained 86,580 (Wilson), 93,668 (SP1), and 84,309 (SP3) predicted transcripts. Approximately 40% of the transcripts were homologous to proteins in the BLAST nr database with an E value ≤ 1.00E-6. Greater than 80% of the highly conserved CEGMA core eukaryotic genes were identified in each transcriptome, which supports assembly completeness. Seven putative voltage-gated Na+ or Ca2+ channels, two aquaporin-like proteins, and twelve putative VATPase subunits were discovered in all clones using multiple bioinformatics approaches. Furthermore, 45% (Wilson) and 43% (SP1 and SP3) of the K. brevis putative peptides > 100 amino acids long produced significant hits to a sequence in the NCBI nr protein database. Of these, 77% (Wilson and SP1) and 73% (SP3) were successfully assigned gene ontology functional terms. The predicted single nucleotide polymorphism (SNP) frequencies between clones were 0.0028 (Wilson to SP1), 0.0030 (Wilson to SP3), and 0.0028 (SP1 to SP3).CONCLUSIONS: The K. brevis transcriptomes assembled here provide a foundational resource for gene discovery and future RNA-seq experiments. The identification of ion channels, VATPases, and aquaporins in all three transcriptomes indicates that K. brevis regulates cellular ion and water concentrations via transmembrane proteins. Additionally, > 40,000 unannotated loci may include potentially novel K. brevis genes. Ultimately, the SNPs identified among the three ecologically diverse clones with different toxin profiles may help to elucidate variations in K. brevis brevetoxin production. Source


Recent data demonstrated that MSCs can be activated by proinflammatory signals to introduce two negative feedback loops into the generic pathway of inflammation. In one loop, the activated MSCs secrete PGE2 that drives resident macrophages with an M1 proinflammatory phe-notype toward an M2 anti-inflammatory phenotype. In the second loop, the activated MSCs secrete TSG-6 that interacts with CD44 on resident macrophages to decrease TLR2/NFκ-B signaling and thereby decrease the secretion of proinflammatory mediators of inflammation. The PGE2 and TSG-6 negative feedback loops allow MSCs to serve as regulators of the very early phases of inflammation. These and many related observations suggest that the MSC-like cells found in most tissues may be part of the pantheon of cells that protect us from foreign invaders, tissue injury, and aging. © AlphaMed Press. Source

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