Interrogating eleven fast-evolving genes for signatures of recent positive selection in worldwide human populations

Different signatures of natural selection persist over varying time scales in our genome, revealing possible episodes of adaptative evolution during human history. Here, we identify genes showing signatures of ancestral positive selection in the human lineage and investigate whether some of those genes have been evolving adaptatively in extant human populations. Specifically, we compared more than 11,000 human genes with their orthologs inchimpanzee, mouse, rat and dog and applied a branch-site likelihood method to test for positive selection on the human lineage. Among the significant cases, a robust set of 11 genes were then further explored for signatures of recent positive selection using SNP data. We genotyped 223 SNPs in 39 worldwide populations from the HGDP Diversity panel and supplemented this information with available genotypes for up to 4,814 SNPs distributed along 2 Mb centered on each gene. After exploring the allele frequency spectrum, population differentiation and the maintainance of long unbroken haplotypes, we found signals of recent adaptative phenomena in only one of the 11 candidate gene regions. However, the signal ofrecent selection in this region may come from a different, neighbouring gene (CD5) ratherthan from the candidate gene itself (VPS37C). For this set of positively-selected genes in thehuman lineage, we find no indication that these genes maintained their rapid evolutionarypace among human populations. Based on these data, it therefore appears that adaptation forhuman-specific and for population-specific traits may have involved different genes.

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

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 and innate 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. 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 are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1. 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.

Positive time-frequency distributions based on joint marginal constraints

This correspondence studies the formulation of members ofthe Cohen-Posch class of positive time-frequency energy distributions.Minimization of cross-entropy measures with respect to different priorsand the case of no prior or maximum entropy were considered. It isconcluded that, in general, the information provided by the classicalmarginal constraints is very limited, and thus, the final distributionheavily depends on the prior distribution. To overcome this limitation,joint time and frequency marginals are derived based on a "directioninvariance" criterion on the time-frequency plane that are directly relatedto the fractional Fourier transform.

Effect of cocoa powder in the prevention of cardiovascular disease: biological, consumption and inflammatory biomarkers. A metabolomic approach

Numerous health benefits have been attributed to cocoa and its derived products in the last decade including antioxidant, anti-platelet and positive effects on lipid metabolism and vascular function. Inflammation plays a key role in the initiation and progression of atherosclerosis. However, cocoa feeding trials focused on inflammation are still rare and the results yielded are controversial. Health effects derived from cocoa consumption have been partly attributed to its polyphenol content, in particular of flavanols. Bioavailability is a key issue for cocoa polyphenols in order to be able to exert their biological activities. In the case of flavanols, bioavailability is strongly influenced by several factors, such as their degree of polymerization and the food matrix in which the polyphenols are delivered. Furthermore, gut has become an active site for the metabolism of procyanidins (oligomeric and polymeric flavanols). Estimation of polyphenol consumption or exposure is also a very challenging task in Food and Nutrition Science in order to correlate the intake of phytochemicals with in vivo health effects. In the area of nutrition, modern analytical techniques based on mass spectrometry are leading to considerable advances in targeted metabolite analysis and particularly in Metabolomics or global metabolite analysis. In this chapter we have summarized the most relevant results of our recent research on the bioavailability of cocoa polyphenols in humans and the effect of the matrix in which cocoa polyphenols are delivered considering both targeted analysis and a metabolomic approach. Furthermore, we have also summarized the effect of long-term consumption of cocoa powder in patients at high risk of cardiovascular disease (CVD) on the inflammatory biomarkers of atherosclerosis.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

The SUD1 Gene Encodes a Putative E3 Ubiquitin Ligase and Is a Positive Regulator of 3-Hydroxy-3-Methylglutaryl Coenzyme A Reductase Activity in Arabidopsis

The 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) enzyme catalyzes the major rate-limiting step of the mevalonic acid (MVA) pathway from which sterols and other isoprenoids are synthesized. In contrast with our extensive knowledge of the regulation of HMGR in yeast and animals, little is known about this process in plants. To identify regulatory components of the MVA pathway in plants, we performed a genetic screen for second-site suppressor mutations of the Arabidopsis thaliana highly drought-sensitive drought hypersensitive2 (dry2) mutant that shows decreased squalene epoxidase activity. We show that mutations in SUPPRESSOR OF DRY2 DEFECTS1 (SUD1) gene recover most developmental defects in dry2 through changes in HMGR activity. SUD1 encodes a putative E3 ubiquitin ligase that shows sequence and structural similarity to yeast Degradation of a factor (Doa10) and human TEB4, components of the endoplasmic reticulum-associated degradation C (ERAD-C) pathway. While in yeast and animals, the alternative ERAD-L/ERAD-M pathway regulates HMGR activity by controlling protein stability, SUD1 regulates HMGR activity without apparent changes in protein content. These results highlight similarities, as well as important mechanistic differences, among the components involved in HMGR regulation in plants, yeast, and animals.

Positive Outcomes Influence the Rate and Time to Publication, but Not the Impact Factor of Publications of Clinical Trial Results

Objectives: Publication bias may affect the validity of evidence based medical decisions. The aim of this study is to assess whether research outcomes affect the dissemination of clinical trial findings, in terms of rate, time to publication, and impact factor of journal publications. Methods and Findings: All drug-evaluating clinical trials submitted to and approved by a general hospital ethics committee between 1997 and 2004 were prospectively followed to analyze their fate and publication. Published articles were identified by searching Pubmed and other electronic databases. Clinical study final reports submitted to the ethics committee, final reports synopses available online and meeting abstracts were also considered as sources of study results. Study outcomes were classified as positive (when statistical significance favoring experimental drug was achieved), negative (when no statistical significance was achieved or it favored control drug) and descriptive (for non-controlled studies). Time to publication was defined as time from study closure to publication. A survival analysis was performed using a Cox regression model to analyze time to publication. Journal impact factors of identified publications were recorded. Publication rate was 48·4% (380/785). Study results were identified for 68·9% of all completed clinical trials (541/785). Publication rate was 84·9% (180/212) for studies with results classified as positive and 68·9% (128/186) for studies with results classified as negative (p<0·001). Median time to publication was 2·09 years (IC95 1·61-2·56) for studies with results classified as positive and 3·21 years (IC95 2·69-3·70) for studies with results classified as negative (hazard ratio 1·99 (IC95 1·55-2·55). No differences were found in publication impact factor between positive (median 6·308, interquartile range: 3·141-28·409) and negative result studies (median 8·266, interquartile range: 4·135-17·157). Conclusions: Clinical trials with positive outcomes have significantly higher rates and shorter times to publication than those with negative results. However, no differences have been found in terms of impact factor.

Patterns of nucleotide diversity at the regions encompassing the Drosophila insulin-like peptide (dilp) genes: demography vs positive selection in Drosophila melanogaster.

In Drosophila, the insulin-signaling pathway controls some life history traits, such as fertility and lifespan, and it is considered to be the main metabolic pathway involved in establishing adult body size. Several observations concerning variation in body size in the Drosophila genus are suggestive of its adaptive character. Genes encoding proteins in this pathway are, therefore, good candidates to have experienced adaptive changes and to reveal the footprint of positive selection. The Drosophila insulin-like peptides (DILPs) are the ligands that trigger the insulin-signaling cascade. In Drosophila melanogaster, there are several peptides that are structurally similar to the single mammalian insulin peptide. The footprint of recent adaptive changes on nucleotide variation can be unveiled through the analysis of polymorphism and divergence. With this aim, we have surveyed nucleotide sequence variation at the dilp1-7 genes in a natural population of D. melanogaster. The comparison of polymorphism in D. melanogaster and divergence from D. simulans at different functional classes of the dilp genes provided no evidence of adaptive protein evolution after the split of the D. melanogaster and D. simulans lineages. However, our survey of polymorphism at the dilp gene regions of D. melanogaster has provided some evidence for the action of positive selection at or near these genes. The regions encompassing the dilp1-4 genes and the dilp6 gene stand out as likely affected by recent adaptive events.

The effects of milk as a food matrix for polyphenols on the excretion profile of cocoa (-)-Epicatechin metabolites in healthy humans subjects

The effect of different food matrices on the metabolism and excretion of polyphenols is uncertain. The objective of the study was to evaluate the possible effect of milk on the excretion of (2)-epicatechin metabolites from cocoa powder after its ingestion with and without milk. Twenty-one volunteers received the following three test meals each in a randomised cross-over design with a 1-week interval between meals: (1) 250 ml whole milk as a control; (2) 40 g cocoa powder dissolved in 250 ml whole milk (CC-M); (3) 40 g cocoa powder dissolved in 250 ml water (CC-W). Urine was collected before consumption and during the 0-6, 6-12 and 12-24 h periods after consumption. (2)-Epicatechin metabolite excretion was measured using liquid chromatography-MS. One (2)-epicatechin glucuronide and three (2)-epicatechin sulfates were detected in urine excreted after the intake of the two cocoa beverages (CC-M and CC-W). The results show that milk does not significantly affect the total amount of metabolites excreted in urine. However, differences in metabolite excretion profiles were observed; there were changes in the glucuronide and sulfate excretion rates, and the sulfation position between the period of excretion and the matrix. The matrix in which polyphenols are consumed can affect their metabolism and excretion, and this may affect their biological activity. Thus, more studies are needed to evaluate the effect of these different metabolite profiles on the body.

Conjugation of a Ru(II) Arene Complex to Neomycin or to Guanidinoneomycin Leads to Compounds with Differential Cytotoxicities and Accumulation between Cancer and Normal Cells

A straightforward methodology for the synthesis of conjugates between a cytotoxic organometallic ruthenium(II) complex and amino- and guanidinoglycosides, as potential RNA-targeted anticancer compounds, is described. Under microwave irradiation, the imidazole ligand incorporated on the aminoglycoside moiety (neamine or neomycin) was found to replace one triphenylphosphine ligand from the ruthenium precursor [(η6-p-cym)RuCl(PPh3)2]+, allowing the assembly of the target conjugates. The guanidinylated analogue was easily prepared from the neomycin-ruthenium conjugate by reaction with N,N′-di-Boc-N″-triflylguanidine, a powerful guanidinylating reagent that was compatible with the integrity of the metal complex. All conjugates were purified by semipreparative high-performance liquid chromatography (HPLC) and characterized by electrospray ionization (ESI) and matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and NMR spectroscopy. The cytotoxicity of the compounds was tested in MCF-7 (breast) and DU-145 (prostate) human cancer cells, as well as in the normal HEK293 (Human Embryonic Kidney) cell line, revealing a dependence on the nature of the glycoside moiety and the type of cell (cancer or healthy). Indeed, the neomycin-ruthenium conjugate (2) displayed moderate antiproliferative activity in both cancer cell lines (IC50 ≈ 80 μM), whereas the neamine conjugate (4) was inactive (IC50 ≈ 200 μM). However, the guanidinylated analogue of the neomycin-ruthenium conjugate (3) required much lower concentrations than the parent conjugate for equal effect (IC50 = 7.17 μM in DU-145 and IC50 = 11.33 μM in MCF-7). Although the same ranking in antiproliferative activity was found in the nontumorigenic cell line (3 2 > 4), IC50 values indicate that aminoglycoside-containing conjugates are about 2-fold more cytotoxic in normal cells (e.g., IC50 = 49.4 μM for 2) than in cancer cells, whereas an opposite tendency was found with the guanidinylated conjugate, since its cytotoxicity in the normal cell line (IC50 = 12.75 μM for 3) was similar or even lower than that found in MCF-7 and DU-145 cancer cell lines, respectively. Cell uptake studies performed by ICP-MS with conjugates 2 and 3 revealed that guanidinylation of the neomycin moiety had a positive effect on accumulation (about 3-fold higher in DU-145 and 4-fold higher in HEK293), which correlates well with the higher antiproliferative activity of 3. Interestingly, despite the slightly higher accumulation in the normal cell than in the cancer cell line (about 1.4-fold), guanidinoneomycin-ruthenium conjugate (3) was more cytotoxic to cancer cells (about 1.8-fold), whereas the opposite tendency applied for neomycin-ruthenium conjugate (2). Such differences in cytotoxic activity and cellular accumulation between cancer and normal cells open the way to the creation of more selective, less toxic anticancer metallodrugs by conjugating cytotoxic metal-based complexes such as ruthenium(II) arene derivatives to guanidinoglycosides.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Assessing positive mental health in people with chronic physical health problems: correlations with socio-demographic variables and physical health status

Background: A holistic perspective on health implies giving careful consideration to the relationship between physical and mental health. In this regard the present study sought to determine the level of Positive Mental Health (PMH) among people with chronic physical health problems, and to examine the relationship between the observed levels of PMH and both physical health status and socio-demographic variables. Methods: The study was based on the Multifactor Model of Positive Mental Health (Lluch, 1999), which comprises six factors: Personal Satisfaction (F1), Prosocial Attitude (F2), Self-control (F3), Autonomy (F4), Problem-solving and Self-actualization (F5), and Interpersonal Relationship Skills (F6). The sample comprised 259 adults with chronic physical health problems who were recruited through a primary care center in the province of Barcelona (Spain). Positive mental health was assessed by means of the Positive Mental Health Questionnaire (Lluch, 1999). Results: Levels of PMH differed, either on the global scale or on specific factors, in relation to the following variables: age: global PMH scores decreased with age (r=-0.129; p=0.038); b) gender: men scored higher on F1 (t=2.203; p=0.028) and F4 (t=3.182; p=0.002), while women scored higher on F2 (t -3.086; p=0.002) and F6 (t=-2.744; p=0.007); c) number of health conditions: the fewer the number of health problems the higher the PMH score on F5 (r=-0.146; p=0.019); d) daily medication: polymedication patients had lower PMH scores, both globally and on various factors; e) use of analgesics: occasional use of painkillers was associated with higher PMH scores on F1 (t=-2.811; p=0.006). There were no significant differences in global PMH scores according to the type of chronic health condition. The only significant difference in the analysis by factors was that patients with hypertension obtained lower PMH scores on the factor Autonomy (t=2.165; p=0.032). Conclusions: Most people with chronic physical health problems have medium or high levels of PMH. The variables that adversely affect PMH are old age, polypharmacy and frequent consumption of analgesics. The type of health problem does not influence the levels of PMH. Much more extensive studies with samples without chronic pathology are now required in order to be able to draw more robust conclusions.

Mueller matrix microscope with a dual continuous rotating compensator setup and digital demodulation

In this paper we describe a new Mueller matrix (MM) microscope that generalizes and makes quantitative the polarized light microscopy technique. In this instrument all the elements of the MU are simultaneously determined from the analysis in the frequency domain of the time-dependent intensity of the light beam at every pixel of the camera. The variations in intensity are created by the two compensators continuously rotating at different angular frequencies. A typical measurement is completed in a little over one minute and it can be applied to any visible wavelength. Some examples are presented to demonstrate the capabilities of the instrument.

Planarians as a model to assess in vivo the role of matrix metalloproteinase genes during homeostasis and regeneration

Matrix metalloproteinases (MMPs) are major executors of extracellular matrix remodeling and, consequently, play key roles in the response of cells to their microenvironment. The experimentally accessible stem cell population and the robust regenerative capabilities of planarians offer an ideal model to study how modulation of the proteolytic system in the extracellular environment affects cell behavior in vivo. Genome-wide identification of Schmidtea mediterranea MMPs reveals that planarians possess four mmp-like genes. Two of them (mmp1 and mmp2) are strongly expressed in a subset of secretory cells and encode putative matrilysins. The other genes (mt-mmpA and mt-mmpB) are widely expressed in postmitotic cells and appear structurally related to membrane-type MMPs. These genes are conserved in the planarian Dugesia japonica. Here we explore the role of the planarian mmp genes by RNA interference (RNAi) during tissue homeostasis and regeneration. Our analyses identify essential functions for two of them. Following inhibition of mmp1 planarians display dramatic disruption of tissues architecture and significant decrease in cell death. These results suggest that mmp1 controls tissue turnover, modulating survival of postmitotic cells. Unexpectedly, the ability to regenerate is unaffected by mmp1(RNAi). Silencing of mt-mmpA alters tissue integrity and delays blastema growth, without affecting proliferation of stem cells. Our data support the possibility that the activity of this protease modulates cell migration and regulates anoikis, with a consequent pivotal role in tissue homeostasis and regeneration. Our data provide evidence of the involvement of specific MMPs in tissue homeostasis and regeneration and demonstrate that the behavior of planarian stem cells is critically dependent on the microenvironment surrounding these cells. Studying MMPs function in the planarian model provides evidence on how individual proteases work in vivo in adult tissues. These results have high potential to generate significant information for development of regenerative and anti cancer therapies.

Effect of cocoa powder in the prevention of cardiovascular disease: biological, consumption and inflammatory biomarkers. A metabolomic approach

Numerous health benefits have been attributed to cocoa and its derived products in the last decade including antioxidant, anti-platelet and positive effects on lipid metabolism and vascular function. Inflammation plays a key role in the initiation and progression of atherosclerosis. However, cocoa feeding trials focused on inflammation are still rare and the results yielded are controversial. Health effects derived from cocoa consumption have been partly attributed to its polyphenol content, in particular of flavanols. Bioavailability is a key issue for cocoa polyphenols in order to be able to exert their biological activities. In the case of flavanols, bioavailability is strongly influenced by several factors, such as their degree of polymerization and the food matrix in which the polyphenols are delivered. Furthermore, gut has become an active site for the metabolism of procyanidins (oligomeric and polymeric flavanols). Estimation of polyphenol consumption or exposure is also a very challenging task in Food and Nutrition Science in order to correlate the intake of phytochemicals with in vivo health effects. In the area of nutrition, modern analytical techniques based on mass spectrometry are leading to considerable advances in targeted metabolite analysis and particularly in Metabolomics or global metabolite analysis. In this chapter we have summarized the most relevant results of our recent research on the bioavailability of cocoa polyphenols in humans and the effect of the matrix in which cocoa polyphenols are delivered considering both targeted analysis and a metabolomic approach. Furthermore, we have also summarized the effect of long-term consumption of cocoa powder in patients at high risk of cardiovascular disease (CVD) on the inflammatory biomarkers of atherosclerosis.