Biofilter aquaponic system for nutrients removal from fresh market wastewater

Aquaponics is a significant wastewater treatment system which refers to the combination of conventional aquaculture (raising aquatic organism) with hydroponics (cultivating plants in water) in a symbiotic environment. This system has a high ability in removing nutrients compared to conventional methods because it is a natural and environmentally friendly system (aquaponics). The current chapter aimed to review the possible application of aquaponics system to treat fresh market wastewater with the intention to highlight the mechanism of phytoremediation occurs in aquaponic system. The literature revealed that aquaponic system was able to remove nutrients in terms of nitrogen and phosphorus

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page

Threshold-dominated regulation hides genetic variation in gene expression networks

<p>Abstract</p> <p>Background</p> <p>In dynamical models with feedback and sigmoidal response functions, some or all variables have thresholds around which they regulate themselves or other variables. A mathematical analysis has shown that when the dose-response functions approach binary or on/off responses, any variable with an equilibrium value close to one of its thresholds is very robust to parameter perturbations of a homeostatic state. We denote this threshold robustness. To check the empirical relevance of this phenomenon with response function steepnesses ranging from a near on/off response down to Michaelis-Menten conditions, we have performed a simulation study to investigate the degree of threshold robustness in models for a three-gene system with one downstream gene, using several logical input gates, but excluding models with positive feedback to avoid multistationarity. Varying parameter values representing functional genetic variation, we have analysed the coefficient of variation (<it>CV</it>) of the gene product concentrations in the stable state for the regulating genes in absolute terms and compared to the <it>CV </it>for the unregulating downstream gene. The sigmoidal or binary dose-response functions in these models can be considered as phenomenological models of the aggregated effects on protein or mRNA expression rates of all cellular reactions involved in gene expression.</p> <p>Results</p> <p>For all the models, threshold robustness increases with increasing response steepness. The <it>CV</it>s of the regulating genes are significantly smaller than for the unregulating gene, in particular for steep responses. The effect becomes less prominent as steepnesses approach Michaelis-Menten conditions. If the parameter perturbation shifts the equilibrium value too far away from threshold, the gene product is no longer an effective regulator and robustness is lost. Threshold robustness arises when a variable is an active regulator around its threshold, and this function is maintained by the feedback loop that the regulator necessarily takes part in and also is regulated by. In the present study all feedback loops are negative, and our results suggest that threshold robustness is maintained by negative feedback which necessarily exists in the homeostatic state.</p> <p>Conclusion</p> <p>Threshold robustness of a variable can be seen as its ability to maintain an active regulation around its threshold in a homeostatic state despite external perturbations. The feedback loop that the system necessarily possesses in this state, ensures that the robust variable is itself regulated and kept close to its threshold. Our results suggest that threshold regulation is a generic phenomenon in feedback-regulated networks with sigmoidal response functions, at least when there is no positive feedback. Threshold robustness in gene regulatory networks illustrates that hidden genetic variation can be explained by systemic properties of the genotype-phenotype map.</p

Facilitated Variation: How Evolution Learns from Past Environments To Generalize to New Environments

One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions

Identification and Typing of Human Enterovirus: A Genomic Barcode Approach

Identification and typing of human enterovirus (HEVs) are important to pathogen detection and therapy. Previous phylogeny-based typing methods are mainly based on multiple sequence alignments of specific genes in the HEVs, but the results are not stable with respect to different choices of genes. Here we report a novel method for identification and typing of HEVs based on information derived from their whole genomes. Specifically, we calculate the k-mer based barcode image for each genome, HEV or other human viruses, for a fixed k, 1<k<7, where a genome barcode is defined in terms of the k-mer frequency distribution across the whole genome for all combinations of k-mers. A phylogenetic tree is constructed using a barcode-based distance and a neighbor-joining method among a set of 443 representative non-HEV human viruses and 395 HEV sequences. The tree shows a clear separation of the HEV viruses from all the non-HEV viruses with 100% accuracy and a separation of the HEVs into four distinct clads with 93.4% consistency with a multiple sequence alignment-based phylogeny. Our detailed analyses of the HEVs having different typing results by the two methods indicate that our results are in better agreement with known information about the HEVs

Reporting of Adverse Events in Published and Unpublished Studies of Health Care Interventions : A Systematic Review

BACKGROUND: We performed a systematic review to assess whether we can quantify the underreporting of adverse events (AEs) in the published medical literature documenting the results of clinical trials as compared with other nonpublished sources, and whether we can measure the impact this underreporting has on systematic reviews of adverse events. METHODS AND FINDINGS: Studies were identified from 15 databases (including MEDLINE and Embase) and by handsearching, reference checking, internet searches, and contacting experts. The last database searches were conducted in July 2016. There were 28 methodological evaluations that met the inclusion criteria. Of these, 9 studies compared the proportion of trials reporting adverse events by publication status. The median percentage of published documents with adverse events information was 46% compared to 95% in the corresponding unpublished documents. There was a similar pattern with unmatched studies, for which 43% of published studies contained adverse events information compared to 83% of unpublished studies. A total of 11 studies compared the numbers of adverse events in matched published and unpublished documents. The percentage of adverse events that would have been missed had each analysis relied only on the published versions varied between 43% and 100%, with a median of 64%. Within these 11 studies, 24 comparisons of named adverse events such as death, suicide, or respiratory adverse events were undertaken. In 18 of the 24 comparisons, the number of named adverse events was higher in unpublished than published documents. Additionally, 2 other studies demonstrated that there are substantially more types of adverse events reported in matched unpublished than published documents. There were 20 meta-analyses that reported the odds ratios (ORs) and/or risk ratios (RRs) for adverse events with and without unpublished data. Inclusion of unpublished data increased the precision of the pooled estimates (narrower 95% confidence intervals) in 15 of the 20 pooled analyses, but did not markedly change the direction or statistical significance of the risk in most cases. The main limitations of this review are that the included case examples represent only a small number amongst thousands of meta-analyses of harms and that the included studies may suffer from publication bias, whereby substantial differences between published and unpublished data are more likely to be published. CONCLUSIONS: There is strong evidence that much of the information on adverse events remains unpublished and that the number and range of adverse events is higher in unpublished than in published versions of the same study. The inclusion of unpublished data can also reduce the imprecision of pooled effect estimates during meta-analysis of adverse events

Regulation of GIP and GLP1 Receptor Cell Surface Expression by N-Glycosylation and Receptor Heteromerization

In response to a meal, Glucose-dependent Insulinotropic Polypeptide (GIP) and Glucagon-like Peptide-1 (GLP-1) are released from gut endocrine cells into the circulation and interact with their cognate G-protein coupled receptors (GPCRs). Receptor activation results in tissue-selective pleiotropic responses that include augmentation of glucose-induced insulin secretion from pancreatic beta cells. N-glycosylation and receptor oligomerization are co-translational processes that are thought to regulate the exit of functional GPCRs from the ER and their maintenance at the plasma membrane. Despite the importance of these regulatory processes, their impact on functional expression of GIP and GLP-1 receptors has not been well studied. Like many family B GPCRs, both the GIP and GLP-1 receptors possess a large extracellular N-terminus with multiple consensus sites for Asn-linked (N)-glycosylation. Here, we show that each of these Asn residues is glycosylated when either human receptor is expressed in Chinese hamster ovary cells. N-glycosylation enhances cell surface expression and function in parallel but exerts stronger control over the GIP receptor than the GLP-1 receptor. N-glycosylation mainly lengthens receptor half-life by reducing degradation in the endoplasmic reticulum. N-glycosylation is also required for expression of the GIP receptor at the plasma membrane and efficient GIP potentiation of glucose-induced insulin secretion from the INS-1 pancreatic beta cell line. Functional expression of a GIP receptor mutant lacking N-glycosylation is rescued by co-expressed wild type GLP1 receptor, which, together with data obtained using Bioluminescence Resonance Energy Transfer, suggests formation of a GIP-GLP1 receptor heteromer