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Interacting Factors (interacting + factor)
Selected AbstractsAll-trans retinoic acid affects subcellular localization of a novel BmNIF3l protein: functional deduce and tissue distribution of NIF3l gene from silkworm (Bombyx mori),ARCHIVES OF INSECT BIOCHEMISTRY AND PHYSIOLOGY (ELECTRONIC), Issue 4 2010Jianqing Chen Abstract A novel cDNA sequence encoding a predicted protein of 271 amino acids containing a conserved NIF3 domain was found from a pupal cDNA library of silkworm. The corresponding gene was named BmNIF3l (Bombyx mori NGG1p interacting factor 3-like). It was found by bioinformatics that BmNIF3l gene consisted of five exons and four introns and BmNIF3l had a high degree of homology to other NIF3-like proteins, especially in the N-terminal and C-terminal regions. A His-tagged BmNIF3l fusion protein with a molecular weight of approximately 33.6,kDa was expressed and purified to homogeneity. We have used the purified fusion protein to produce polyclonal antibodies against BmNIF3l for histochemical analysis. Subcellular localization revealed that BmNIF3l is a cytoplasmic protein that responds to all-trans retinoic acid (ATRA). Western blotting and real-time reverse transcription polymerase chain reaction showed that the expression level of BmNIF3l is higher in tissues undergoing differentiation. Taken together, the results suggest that BmNIF3l functions in transcription. © 2010 Wiley Periodicals, Inc. [source] Pelagic and benthic net production of dissolved inorganic carbon in an unproductive subarctic lakeFRESHWATER BIOLOGY, Issue 3 2007JAN ÅBERG Summary 1. Both the pelagic and benthic net dissolved inorganic carbon (DIC) productions were measured in situ on four occasions from June to September 2004, in the unproductive Lake Diktar-Erik in subarctic Sweden. The stable isotopic signal (,13C) of respired organic material was estimated from hypolimnion water data and data from a laboratory incubation using epilimnion water. 2. Both pelagic and benthic habitats were net heterotrophic during the study period, with a total net DIC production of 416 mg C m,2 day,1, of which the pelagic habitat contributed approximately 85%. The net DIC production decreased with depth both in the pelagic water and in the sediments, and most of the net DIC production occurred in the upper water column. 3. Temporal variations in both pelagic and benthic DIC production were small, although we observed a significant decrease in pelagic net DIC production after the autumn turnover. Water temperature was the single most important factor explaining temporal and vertical variations in pelagic DIC production. No single factor explained more than 10% of the benthic net DIC production, which probably was regulated by several interacting factors. 4. Pelagic DIC production, and thus most of the whole-lake net production of DIC, was mainly due to the respiration of allochthonous organic carbon. Stable isotope data inferred that nearly 100% of accumulated DIC in the hypolimnion water had an allochthonous carbon source. Similarly, in the laboratory incubation using epilimnion water, c. 85% of accumulated DIC was indicated to have an allochthonous organic carbon source. [source] Transcription termination and anti-termination in E. coliGENES TO CELLS, Issue 8 2002Evgeny Nudler Transcription termination in Escherichia coli is controlled by many factors. The sequence of the DNA template, the structure of the transcript, and the actions of auxiliary proteins all play a role in determining the efficiency of the process. Termination is regulated and can be enhanced or suppressed by host and phage proteins. This complex reaction is rapidly yielding to biochemical and structural analysis of the interacting factors. Below we review and attempt to unify into basic principles the remarkable recent progress in understanding transcription termination and anti-termination. [source] Detecting interacting genetic loci with effects on quantitative traits where the nature and order of the interaction are unknownGENETIC EPIDEMIOLOGY, Issue 4 2010Joanna L. Davies Abstract Standard techniques for single marker quantitative trait mapping perform poorly in detecting complex interacting genetic influences. When a genetic marker interacts with other genetic markers and/or environmental factors to influence a quantitative trait, a sample of individuals will show different effects according to their exposure to other interacting factors. This paper presents a Bayesian mixture model, which effectively models heterogeneous genetic effects apparent at a single marker. We compute approximate Bayes factors which provide an efficient strategy for screening genetic markers (genome-wide) for evidence of a heterogeneous effect on a quantitative trait. We present a simulation study which demonstrates that the approximation is good and provide a real data example which identifies a population-specific genetic effect on gene expression in the HapMap CEU and YRI populations. We advocate the use of the model as a strategy for identifying candidate interacting markers without any knowledge of the nature or order of the interaction. The source of heterogeneity can be modeled as an extension. Genet. Epidemiol. 34: 299,308, 2010. © 2009 Wiley-Liss, Inc. [source] Case-only genome-wide interaction study of disease risk, prognosis and treatmentGENETIC EPIDEMIOLOGY, Issue 1 2010Brandon L. Pierce Abstract Case-control genome-wide association (GWA) studies have facilitated the identification of susceptibility loci for many complex diseases; however, these studies are often not adequately powered to detect gene-environment (G×E) and gene-gene (G×G) interactions. Case-only studies are more efficient than case-control studies for detecting interactions and require no data on control subjects. In this article, we discuss the concept and utility of the case-only genome-wide interaction (COGWI) study, in which common genetic variants, measured genome-wide, are screened for association with environmental exposures or genetic variants of interest. An observed G-E (or G-G) association, as measured by the case-only odds ratio (OR), suggests interaction, but only if the interacting factors are unassociated in the population from which the cases were drawn. The case-only OR is equivalent to the interaction risk ratio. In addition to risk-related interactions, we discuss how the COGWI design can be used to efficiently detect G×G, G×E and pharmacogenetic interactions related to disease outcomes in the context of observational clinical studies or randomized clinical trials. Such studies can be conducted using only data on individuals experiencing an outcome of interest or individuals not experiencing the outcome of interest. Sharing data among GWA and COGWI studies of disease risk and outcome can further enhance efficiency. Sample size requirements for COGWI studies, as compared to case-control GWA studies, are provided. In the current era of genome-wide analyses, the COGWI design is an efficient and straightforward method for detecting G×G, G×E and pharmacogenetic interactions related to disease risk, prognosis and treatment response. Genet. Epidemiol. 34:7,15, 2010. © 2009 Wiley-Liss, Inc. [source] Protocol-based care: the standardisation of decision-making?JOURNAL OF CLINICAL NURSING, Issue 10 2009Jo Rycroft-Malone Aim., To explore how protocol-based care affects clinical decision-making. Background., In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Design., Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Methods., Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Results., Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. Conclusions., While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. Relevance to clinical practice., The successful implementation and judicious use of tools such as protocols and guidelines will likely be dependant on approaches that facilitate the development of nurses' decision-making processes in parallel to paying attention to the influence of context. [source] Non-parametric habitat models with automatic interactionsJOURNAL OF VEGETATION SCIENCE, Issue 6 2006Bruce McCune Abstract Questions: Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods? Methods: Non-parametric multiplicative regression (NPMR) was developed from the premises that: the response variable has a minimum of zero and a physiologically-determined maximum, species respond simultaneously to multiple ecological factors, the response to any one factor is conditioned by the values of other factors, and that if any of the factors is intolerable then the response is zero. Key features of NPMR are interactive effects of predictors, no need to specify an overall model form in advance, and built-in controls on overfitting. The effectiveness of the method is demonstrated with simulated and real data sets. Results: Empirical and theoretical relationships of species response to multiple interacting predictors can be represented effectively by multiplicative kernel smoothers. NPMR allows us to abandon simplistic assumptions about overall model form, while embracing the ecological truism that habitat factors interact. [source] Models of influence in chronic liver diseaseLIVER INTERNATIONAL, Issue 5 2010Amnon Sonnenberg Abstract Background & Aims: Liver disease is often characterized by an intricate network of multiple, simultaneously interacting factors with organ-specific, as well as systemic effects. The aim of the present study is to introduce a new mathematical model on how to weigh a variety of factors contributing to chronic liver disease by the relevance of their influence on the overall disease processes. Methods: Liver disease is modelled as the interaction of multiple internal and external factors. Each factor can potentially interact with any of the other factors in the model. The strength of interactions is expressed as per cent. The sum of all interactions contributing to each individual factor adds up to 100%. This model corresponds mathematically to a transposed Markov matrix. The analysis uses the two examples of hepatitis C virus (HCV) and autoimmune hepatitis (AIH). Results: Impaired liver function is the most influential factor and increases in relevance as the degree of hepatic fibrosis increases. The relative importance of treating the primary disease process (HCV or AIH) diminishes as fibrosis develops. Similarly, psychosocial factors become less important with disease progression. Liver transplant is most important for Child's C cirrhosis. It is relatively influential for the early phase of AIH but not HCV, reflecting the fact that some cases of non-cirrhotic AIH can progress rapidly to acute liver failure. Conclusion: In a disease process characterized by a large array of multiple interacting factors, the decision tool of a transposed Markov chain helps to sort the contributing factors by the magnitude of their influence. [source] Overexpression of Upf1p compensates for mitochondrial splicing deficiency independently of its role in mRNA surveillanceMOLECULAR MICROBIOLOGY, Issue 4 2004B. De Pinto Summary In yeast the UPF1, UPF2 and UPF3 genes encode three interacting factors involved in translation termination and nonsense-mediated mRNA decay (NMD). UPF1 plays a central role in both processes. In addition, UPF1 was originally isolated as a multicopy suppressor of mitochondrial splicing deficiency, and its deletion leads to an impairment in respiratory growth. Here, we provide evidence that inactivation of UPF2 or ,UPF3, ,like ,that ,of ,UPF1, ,leads ,to ,an ,impairment in respiratory competence, suggesting that their products, Upf1p, Upf2p and Upf3p, are equivalently involved in mitochondrial biogenesis. In addition, however, we show that only Upf1p acts as a multicopy suppressor of mitochondrial splicing deficiency, and its activity does not require either Upf2p or Upf3p. Mutations in the conserved cysteine- and histidine-rich regions and ATPase and helicase motifs of Upf1p separate the ability of Upf1p to complement the respiratory impairment of a ,upf1 strain from its ability to act as a multicopy suppressor of mitochondrial splicing deficiency, indicating that distinct pathways express these phenotypes. In addition, we show that, when overexpressed, Upf1p is not detected within mitochondria, suggesting that its role as multicopy suppressor of mitochondrial splicing deficiency is indirect. Furthermore, we provide evidence that cells overexpressing certain upf1 alleles accumulate a phosphorylated isoform of Upf1p. Altogether, these results indicate that overexpression of Upf1p compensates for mitochondrial splicing deficiency independently of its role in mRNA surveillance, which relies on Upf1p,Upf2p,Upf3p functional interplay. [source] A physiological overview of the genetics of flowering time controlPLANT BIOTECHNOLOGY JOURNAL, Issue 1 2005Georges Bernier Summary Physiological studies on flowering time control have shown that plants integrate several environmental signals. Predictable factors, such as day length and vernalization, are regarded as ,primary', but clearly interfere with, or can even be substituted by, less predictable factors. All plant parts participate in the sensing of these interacting factors. In the case of floral induction by photoperiod, long-distance signalling is known to occur between the leaves and the shoot apical meristem (SAM) via the phloem. In the long-day plant, Sinapis alba, this long-distance signalling has also been shown to involve the root system and to include sucrose, nitrate, glutamine and cytokinins, but not gibberellins. In Arabidopsis thaliana, a number of genetic pathways controlling flowering time have been identified. Models now extend beyond ,primary' controlling factors and show an ever-increasing number of cross-talks between pathways triggered or influenced by various environmental factors and hormones (mainly gibberellins). Most of the genes involved are preferentially expressed in meristems (the SAM and the root tip), but, surprisingly, only a few are expressed preferentially or exclusively in leaves. However, long-distance signalling from leaves to SAM has been shown to occur in Arabidopsis during the induction of flowering by long days. In this review, we propose a model integrating physiological data and genes activated by the photoperiodic pathway controlling flowering time in early-flowering accessions of Arabidopsis. This model involves metabolites, hormones and gene products interacting as long- or short-distance signalling molecules. [source] | |||||||||||||