991 resultados para Reverse order
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Assigns responsibility to coordinate disparate information technology and to provide enterprise-wide information technology services to the exectutive branch agencies to the Information Technology Services (ITS) director appointed by the Governor.
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Rescinds Executive Order #54 and replaces it with a new team called the Primary Iowa Harzard Mitigation Team to coordinate state response to natural and technological disaters.
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Establishes a nine-number committee for the Automated Fingerprint Identification System.
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Amends Executive Order #48 only by changing the name from the Iowa Commission for National and Community Service to the Iowa Commission on Volunteer Service.
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Establish the Iowa Geographic Information Council.
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Establish the Iowa Geographic Information Council.
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Establishs the Council for continuous improvment in Education to facilitation statewide effort to prepare, recruit, induct, retrain effective educational infrastrucational
Higher-order expansions for compound distributions and ruin probabilities with subexponential claims
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Report written by Iowa DOT to Auditor Office about revolving fund purchase order.
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Executive order signed by Governor Thomas Vilsck
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Executive order signed by Governor Thomas Vilsck
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Executive order signed by Governor Thomas Vilsack
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Orders that the United States Flag be flown at half-staff to honor any member of Iowa National Guard, Iowa Air National Guard or an Iowa resident serving as a member of the United States Armed Forces who is killed in the line of duty.
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BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.
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Subtype-dependent selection of HIV-1 reverse transcriptase resistance mutation K65R was previously observed in cell culture and small clinical investigations. We compared K65R prevalence across subtypes A, B, C, F, G, and CRF02_AG separately in a cohort of 3,076 patients on combination therapy including tenofovir. K65R selection was significantly higher in HIV-1 subtype C. This could not be explained by clinical and demographic factors in multivariate analysis, suggesting subtype sequence-specific K65R pathways.