An analysis of the metabolic patterns of two rural communities affected by soy expansion in the North of Argentina

The soy expansion model in Argentina generates structural changes in traditional lifestyles that can be associated with different biophysical and socioeconomic impacts. To explore this issue, we apply an innovative method for integrated assessment - the Multi Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) framework - to characterize two communities in the Chaco Region, Province of Formosa, North of Argentina. These communities have recently experienced the expansion of soy production, altering their economic activity, energy consumption patterns, land use, and human time allocation. The integrated characterization presented in the paper illustrates the differences (biophysical, socioeconomic, and historical) between the two communities that can be associated with different responses. The analysis of the factors behind these differences has important policy implications for the sustainable development of local communities in the area.

Small and long non-coding RNAs in cardiac homeostasis and regeneration

Cardiovascular diseases and in particular heart failure are major causes of morbidity and mortality in the Western world. Recently, the notion of promoting cardiac regeneration as a means to replace lost cardiomyocytes in the damaged heart has engendered considerable research interest. These studies envisage the utilization of both endogenous and exogenous cellular populations, which undergo highly specialized cell fate transitions to promote cardiomyocyte replenishment. Such transitions are under the control of regenerative gene regulatory networks, which are enacted by the integrated execution of specific transcriptional programs. In this context, it is emerging that the non-coding portion of the genome is dynamically transcribed generating thousands of regulatory small and long non-coding RNAs, which are central orchestrators of these networks. In this review, we discuss more particularly the biological roles of two classes of regulatory non-coding RNAs, i.e. microRNAs and long non-coding RNAs, with a particular emphasis on their known and putative roles in cardiac homeostasis and regeneration. Indeed, manipulating non-coding RNA-mediated regulatory networks could provide keys to unlock the dormant potential of the mammalian heart to regenerate. This should ultimately improve the effectiveness of current regenerative strategies and discover new avenues for repair. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Background: Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment andinnate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results:Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection arefrequent on genes that are known to be at bifurcation points, and that are identified as beingin key position by a network-level analysis such as MGAT3 and GCS1.Conclusions: These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.

Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

Metabolic intervention on lipid synthesis converging pathways abrogates prostate cancer growth.

One of the most conserved features of all cancers is a profound reprogramming of cellular metabolism, favoring biosynthetic processes and limiting catalytic processes. With the acquired knowledge of some of these important changes, we have designed a combination therapy in order to force cancer cells to use a particular metabolic pathway that ultimately results in the accumulation of toxic products. This innovative approach consists of blocking lipid synthesis, at the same time that we force the cell, through the inhibition of AMP-activated kinase, to accumulate toxic intermediates, such as malonyl-coenzyme A (malonyl-CoA) or nicotinamide adenine dinucleotide phosphate. This results in excess of oxidative stress and cancer cell death. Our new therapeutic strategy, based on the manipulation of metabolic pathways, will certainly set up the basis for new upcoming studies defining a new paradigm of cancer treatment.

Measured and predicted resting metabolic rate in obese and nonobese adolescents.

OBJECTIVES: The validity of equations for the calculation of resting metabolic rate (RMR) were studied and new predictive equations were developed. STUDY DESIGN: The RMR was measured in a sample of 371 10- to 16-year-old prepubertal and postpubertal children. The study group included 193 male (116 nonobese and 77 obese) and 178 female (119 nonobese and 59 obese) subjects; for each group the RMRs predicted from five equations recommended for this age group were compared. The RMR was assessed by indirect calorimetry with a ventilated hood system for 45 minutes after an overnight fast. Body composition was estimated from skin-fold measurements. RESULTS: The mean +/- SD RMR was found to be 5600 +/- 972 kJ/24 hr and 7223 +/- 1220 kJ/24 hr in nonobese and obese boys, and 5112 +/- 632 kJ/24 hr and 6665 +/- 1106 kJ/24 hr in nonobese and obese girls, respectively. All five equations applicable to 10- to 16-year-old children overestimated RMR by 7.5% to 18.1% (p < 0.001 for each equation). Stepwise regression analysis, with independent variables such as age, weight, height, and gender, allowed development of new predictive equations for the calculation of RMR in 10- to 16-year-old boys (RMR = 50.9 Weight (kg) + 25.3 Height (cm) -50.3 Age (yr) + 26.9; R2 = 0.884, p < 0.0001) and girls (RMR = 51.2 Weight (kg) + 24.5 Height (cm) - 207.5 Age (yr) + 1629.8; R2 = 0.824, p < 0.0001). These predictive equations were tested in a second, independent cohort of children (80 male and 61 female subject) and were found to give a reliable estimate of RMR in 10- to 16-year-old obese and nonobese adolescents. CONCLUSIONS: The currently used predictive equations overestimate RMR in 10- to 16-year-old children. The use of the newly developed equations is recommended.

Astrocyte-neuron metabolic relationships: for better and for worse.

In recent years, previously unsuspected roles of astrocytes have been revealed, largely owing to the development of new tools enabling their selective study in situ. These exciting findings add to the large body of evidence demonstrating that astrocytes play a central role in brain homeostasis, in particular via the numerous cooperative metabolic processes they establish with neurons, such as the supply of energy metabolites and neurotransmitter recycling functions. Furthermore, impairments in astrocytic function are increasingly being recognized as an important contributor to neuronal dysfunction and, in particular, neurodegenerative processes. In this review, we discuss recent evidence supporting important roles for astrocytes in neuropathological conditions such as neuroinflammation, amyotrophic lateral sclerosis and Alzheimer's disease. We also explore the potential for neuroprotective therapeutics based on the modulation of astrocytic functions.

Transcription, tagging and coding of bilingual corpora via LIDES

L'objectiu d'aquest informe és presentar l'aplicació d'una sèrie de propostes sobre transcripció, etiquetatge i codificació a dos corpus: el corpus bilingüe LC (La Canonja (Català-Espanyol)) i el corpus trilingüe CSCD (Code-switching as Communicative Design (Català-Espanyol-Anglès)). Aquestes propostes, que constitueixen l'aportació de l'equip IULA-LIPPS (Language Interaction in Plurilingual and Plurilectal Speakers) al manual de codificació del sistema LIDES (Language Interaction Database Exchange System), adoptat pel grup europeu LIPPS, poden ser útils per transcriure, etiquetar i codificar dades provinents de llengües tipològicament properes i distants.

Peroxisome proliferator-activated receptor beta/delta as a therapeutic target for metabolic diseases.

The peroxisome proliferator-activated receptor (PPAR) family comprises three distinct isotypes: PPARalpha, PPARbeta/delta and PPARgamma. PPARs are nuclear hormone receptors that mediate the effects of fatty acids and their derivatives at the transcriptional level. Until recently, the characterisation of the important role of PPARalpha in fatty acid oxidation and of PPARgamma in lipid storage contrasted with the sparse information concerning PPARbeta/delta. However, evidence is now emerging for a role of PPARbeta/delta in tissue repair and energy homeostasis. Experiments with tissue-specific overexpression of PPARbeta/delta or treatment of mice with selective PPARbeta/delta agonists demonstrated that activation of PPARbeta/delta in vivo increases lipid catabolism in skeletal muscle, heart and adipose tissue and improves the serum lipid profile and insulin sensitivity in several animal models. PPARbeta/delta activation also prevents the development of obesity and improves cholesterol homeostasis in obesity-prone mouse models. These new insights into PPARbeta/delta functions suggest that targeting PPARbeta/delta may be helpful for treating disorders associated with the metabolic syndrome. Although these perspectives are promising, several independent and contradictory reports raise concerns about the safety of PPARbeta/delta ligands with respect to tumourigenic activity in the gut. Thus, it appears that further exploration of PPARbeta/delta functions is necessary to better define its potential as a therapeutic target.

Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells.

BACKGROUND: Conserved non-coding sequences in the human genome are approximately tenfold more abundant than known genes, and have been hypothesized to mark the locations of cis-regulatory elements. However, the global contribution of conserved non-coding sequences to the transcriptional regulation of human genes is currently unknown. Deeply conserved elements shared between humans and teleost fish predominantly flank genes active during morphogenesis and are enriched for positive transcriptional regulatory elements. However, such deeply conserved elements account for <1% of the conserved non-coding sequences in the human genome, which are predominantly mammalian. RESULTS: We explored the regulatory potential of a large sample of these 'common' conserved non-coding sequences using a variety of classic assays, including chromatin remodeling, and enhancer/repressor and promoter activity. When tested across diverse human model cell types, we find that the fraction of experimentally active conserved non-coding sequences within any given cell type is low (approximately 5%), and that this proportion increases only modestly when considered collectively across cell types. CONCLUSIONS: The results suggest that classic assays of cis-regulatory potential are unlikely to expose the functional potential of the substantial majority of mammalian conserved non-coding sequences in the human genome.

Evaluation of oxidative stress parameters and metabolic activities of nurses working day and night shifts

The aim of this study was to evaluate the oxidative stress and metabolic activities of nurses working day and night shifts. Intensive care unit (ICU) (n=70) and ordinary service (OS) nurses (n=70) were enrolled in the study. Just before and the end of the shifts, blood samples were obtained to measure the participants' oxidative stress parameters. Metabolic activities were analyzed using the SenseWear Armband. Oxidative stress parameters were increased at the end of the shifts for all OS and ICU nurses compared to the beginning of the shifts. Compared to the OS nurses, the ICU nurses' TAS, TOS, and OSI levels were not significantly different at the end of the day and night shifts. The metabolic activities of the OS and ICU nurses were found to be similar. As a result, the OS and ICU nurses' oxidative stress parameters and metabolic activities were not different, and all of the nurses experienced similar effects from both the day and night shifts.

Identifying protein-coding genes in genomic sequences.

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.