Determination of minerals, vitamins, antinutrient and amino acid profile of pumpkin pie produced pumpkin (cucurbeta spp) puree and wheat (tritium aestivum) flour supplemented with spices and butter

Pumpkin (Cucurbita spp.), is one of the most popular vegetables consumed in the world, has been recently recognized as a functional food. Traditional crops including the pumpkins, which are rich in micronutrients, are not consumed widely by smallholder farmers in Africa. However, the cultivation of high yielding, nutrient-rich, multipurpose crops-like pumpkin is important in solving the problems of malnutrition and contributing to food security in Africa including Nigeria. Objectives: Therefore, this work aimed at producing Pumpkin pie from Pumpkin puree and wheat supplemented with some indigenous spices alongside butter. Methodology: Formulations into various formed were made using Pearson's method. The formulations were assayed for mineral, vitamin, antinutrient and amino acid composition using standard laboratory methods. A significant (P<0.05) difference was observed in Zn and Ca content of all the samples, with sample D recording the highest value for Zn (1.30±0.01) mg/g and Ca (0.47±0.01) mg/g. However, samples A and D had the least values for Na and Fe. An increasing and decreasing pattern was observed in all the vitamin contents(B 1, B 2 , B 6 , B12 and C), moving from samples A through to D. Vitamin contents of samples B1 and B6 and higher than he RDA, while B2 , B12 and C were below RDA. The overall antinutrient contents observed were generally low, with sample A having the lowest values for Phytate, Oxalate and tannins. The B, C and D are more enhanced in terms of essential amino acids compared to the control group (sample A). Conclusion: Pumpkin pie can be produced from pumpkin and its supplementation of the spices can boost the pie with essential amino acids, minerals, and vitamin composition. This shows the potential of using pumpkin pie as snacks in-between meals for the prevention of Protein Energy Malnutrition (PEM).&nbsp

Production and Evaluation of Nutritional Contents of Traditional Couscous from Sprouted Wheat Fortified with Glycine max (L.) merr (Soya Bean) and Cucurbita pepo (Pumpkin) Seeds

The study was carried to process, produce, and evaluate nutritional contents of traditional couscous from sprouted wheat (Triticum aestivum), fortified with Soya bean (Glycine max) and Pumpkin (Cucurbita pepo) seeds. The composite couscous blends were traditionally produced and compared with commercial couscous. The sprouted wheat couscous blends were blended in different ratios, they include; unprocessed (Raw wheat, 100), blend 1 (sprouted wheat mixed with soya bean and pumpkin seeds, 70:20:10), blend 2 (sprouted wheat mixed with soya bean, 60:40) and blend 3 (sprouted wheat mixed with pumpkin seeds, 60:40). Traditional wheat couscous blends were fed to experimental albino rats of wister strain weighing between (35 g and 45 g) for a period of 28 days. The nutritional and physiochemical analysis were determined using standard laboratory methods. The Statistical Package for Social Sciences (SPSS), version 20.0 was used to analyze the data collected which were expressed as means ± SE. One way analysis of variance (ANOVA) and Duncan’s multiple range tests were used to compare the means obtained after each experiment. Differences were considered significant at p < 0.05. Processing (Sprouting) decreases the levels of anti-nutrients, mineral elements and vitamins. Supplementation with soya bean and pumpkin seeds increased the nutritional composition of the sprouted wheat couscous blends. Results of chemical composition showed that blend 2, recorded high protein (29.95%), fat (8.95%) and low carbohydrate content (49.56%), followed by blend 1 and then blend 3, while commercial couscous crude protein, fat and carbohydrate were 12.53%, 1.42% and 75.10% respectively. There was improved level of in vitro protein digestibility at 1 hour (76.64% to 98.59%) and at 6 hours (96.80% to 99.33%). Results of in vivo studies showed that raw wheat couscous recorded protein quality when compared with spouted wheat couscous blends produced. The biological values of the composite couscous blends range from 95.04% to 95.73% and blend 2, recorded high net protein utilization (98.57%). In terms of sensory evaluation using hedonic method, blend 2 was most acceptable and differ significantly (p < 0.05) with other sprouted wheat couscous blends and commercial couscous. The cost of producing sprouted wheat couscous blends is cheaper than the commercial couscous. The study has therefore, revealed that with proper selection of locally available cereal, it is possible to produce nutritious complementary couscous blends that would be acceptable and nutritionally adequate to meet up the nutritional requirement for both children and adults. It also compares favourably with the commercial couscous in terms of nutrient contents

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

Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here.Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. is a promising step for further application of the proposed method

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210

Finding regulatory elements and regulatory motifs: a general probabilistic framework

Over the last two decades a large number of algorithms has been developed for regulatory motif finding. Here we show how many of these algorithms, especially those that model binding specificities of regulatory factors with position specific weight matrices (WMs), naturally arise within a general Bayesian probabilistic framework. We discuss how WMs are constructed from sets of regulatory sites, how sites for a given WM can be discovered by scanning of large sequences, how to cluster WMs, and more generally how to cluster large sets of sites from different WMs into clusters. We discuss how 'regulatory modules', clusters of sites for subsets of WMs, can be found in large intergenic sequences, and we discuss different methods for ab initio motif finding, including expectation maximization (EM) algorithms, and motif sampling algorithms. Finally, we extensively discuss how module finding methods and ab initio motif finding methods can be extended to take phylogenetic relations between the input sequences into account, i.e. we show how motif finding and phylogenetic footprinting can be integrated in a rigorous probabilistic framework. The article is intended for readers with a solid background in applied mathematics, and preferably with some knowledge of general Bayesian probabilistic methods. The main purpose of the article is to elucidate that all these methods are not a disconnected set of individual algorithmic recipes, but that they are just different facets of a single integrated probabilistic theory

Computational Modeling of the Hematopoietic Erythroid-Myeloid Switch Reveals Insights into Cooperativity, Priming, and Irreversibility

Hematopoietic stem cell lineage choices are decided by genetic networks that are turned ON/OFF in a switch-like manner. However, prior to lineage commitment, genes are primed at low expression levels. Understanding the underlying molecular circuitry in terms of how it governs both a primed state and, at the other extreme, a committed state is of relevance not only to hematopoiesis but also to developmental systems in general. We develop a computational model for the hematopoietic erythroid-myeloid lineage decision, which is determined by a genetic switch involving the genes PU.1 and GATA-1. Dynamical models based upon known interactions between these master genes, such as mutual antagonism and autoregulation, fail to make the system bistable, a desired feature for robust lineage determination. We therefore suggest a new mechanism involving a cofactor that is regulated as well as recruited by one of the master genes to bind to the antagonistic partner that is necessary for bistability and hence switch-like behavior. An interesting fallout from this architecture is that suppression of the cofactor through external means can lead to a loss of cooperativity, and hence to a primed state for PU.1 and GATA-1. The PU. 1-GATA-1 switch also interacts with another mutually antagonistic pair, C/EBP alpha-FOG-1. The latter pair inherits the state of its upstream master genes and further reinforces the decision due to several feedback loops, thereby leading to irreversible commitment. The genetic switch, which handles the erythroid-myeloid lineage decision, is an example of a network that implements both a primed and a committed state by regulating cooperativity through recruitment of cofactors. Perturbing the feedback between the master regulators and downstream targets suggests potential reprogramming strategies. The approach points to a framework for lineage commitment studies in general and could aid the search for lineage-determining genes

Automatic Design of Digital Synthetic Gene Circuits

De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input–output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions