Evidence for an association of prenatal exposure to particulate matter with clinical severity of Autism Spectrum Disorder.

Early-life exposure to air pollutants, including ozone (O3), particulate matter (PM2.5 or PM10, depending on diameter of particles), nitrogen dioxide (NO2) and sulfur dioxide (SO2) has been suggested to contribute to the etiology of Autism Spectrum Disorder (ASD). In this study, we used air quality monitoring data to examine whether mothers of children with ASD were exposed to high levels of air pollutants during critical periods of pregnancy, and if higher exposure levels may lead to a higher clinical severity in their offspring. We used public data from the Portuguese Environment Agency to estimate exposure to these pollutants during the first, second and third trimesters of pregnancy, full pregnancy and first year of life of the child, for 217 subjects with ASD born between 2003 and 2016. These subjects were stratified in two subgroups according to clinical severity, as defined by the Autism Diagnostic Observational Schedule (ADOS). For all time periods, the average levels of PM2.5, PM10 and NO2 to which the subjects were exposed were within the admissible levels defined by the European Union. However, a fraction of these subjects showed exposure to levels of PM2.5 and PM10 above the admissible threshold. A higher clinical severity was associated with higher exposure to PM2.5 (p = 0.001), NO2 (p = 0.011) and PM10 (p = 0.041) during the first trimester of pregnancy, when compared with milder clinical severity. After logistic regression, associations with higher clinical severity were identified for PM2.5 exposure during the first trimester (p = 0.002; OR = 1.14, 95%CI: 1.05-1.23) and full pregnancy (p = 0.04; OR = 1.07, 95%CI: 1.00-1.15) and for PM10 (p = 0.02; OR = 1.07, 95%CI: 1.01-1.14) exposure during the third trimester. Exposure to PM is known to elicit neuropathological mechanisms associated with ASD, including neuroinflammation, mitochondrial disruptions, oxidative stress and epigenetic changes. These results offer new insights on the impact of early-life exposure to PM in ASD clinical severity.

Deep into the Apoplast: Grapevine and Plasmopara viticola Proteomes Reveal the Secret Beneath Host and Pathogen Communication at 6 h After Contact.

The apoplast is the first hub of plant-pathogen communication where pathogen effectors are recognized by plant defensive proteins and cell receptors, thus activating signal transduction pathways. As a result of this first contact, the host triggers a defense response that involves the modulation of extra- and intracellular proteins. In grapevine-pathogen interactions, little is known about the trafficking between extra- and intracellular spaces. Grapevine is an economically important crop that relies on heavy fungicide use to control several diseases, and a deeper knowledge on the activation of its immune response is crucial to define new control strategies. In this study, we focused on the first 6 h postinoculation with Plasmopara viticola to evaluate grapevine proteome modulation in the apoplast. The in planta P. viticola proteome was also assessed to enable a deeper understanding of plant-pathogen communication. Our results showed that several plant mechanisms are triggered in the tolerant grapevine cultivar Regent after inoculation, such as oomycete recognition, plant cell wall modifications, reactive oxygen species signaling, and secretion of proteins to disrupt oomycete structures. On the other hand, P. viticola proteins related to development and virulence were the most predominant. This pioneer study highlights the early dynamics of cellular communication in grapevine defense that leads to the successful establishment of an incompatible interaction.

Transcriptomic and methylation analysis of susceptible and tolerant grapevine genotypes following Plasmopara viticola infection.

Downy mildew, caused by the biotrophic oomycete Plasmopara viticola, is one of the most economically significant grapevine diseases worldwide. Current strategies to cope with this threat rely on the massive use of chemical compounds during each cultivation season. The economic costs and negative environmental impact associated with these applications increased the urge to search for sustainable strategies of disease control. Improved knowledge of plant mechanisms to counteract pathogen infection may allow the development of alternative strategies for plant protection. Epigenetic regulation, in particular DNA methylation, is emerging as a key factor in the context of plant-pathogen interactions associated with the expression modulation of defence genes. To improve our understanding of the genetic and epigenetic mechanisms underpinning grapevine response to P. viticola, we studied the modulation of both 5-mC methylation and gene expression at 6 and 24 h post-infection (hpi). Leaves of two table grape genotypes (Vitis vinifera), selected by breeding activities for their contrasting level of susceptibility to the pathogen, were analysed. Following pathogen infection, we found variations in the 5-mC methylation level and the gene expression profile. The results indicate a genotype-specific response to pathogen infection. The tolerant genotype (N23/018) at 6 hpi exhibits a lower methylation level compared to the susceptible one (N20/020), and it shows an early modulation (at 6 hpi) of defence and epigenetic-related genes during P. viticola infection. These data suggest that the timing of response is an important mechanism to efficiently counteract the pathogen attack.

Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease.

Transcriptome and metabolome reprogramming in Vitis vinifera cv. Trincadeira berries upon infection with Botrytis cinerea.

Vitis vinifera berries are sensitive towards infection by the necrotrophic pathogen Botrytis cinerea, leading to important economic losses worldwide. The combined analysis of the transcriptome and metabolome associated with fungal infection has not been performed previously in grapes or in another fleshy fruit. In an attempt to identify the molecular and metabolic mechanisms associated with the infection, peppercorn-sized fruits were infected in the field. Green and veraison berries were collected following infection for microarray analysis complemented with metabolic profiling of primary and other soluble metabolites and of volatile emissions. The results provided evidence of a reprogramming of carbohydrate and lipid metabolisms towards increased synthesis of secondary metabolites involved in plant defence, such as trans-resveratrol and gallic acid. This response was already activated in infected green berries with the putative involvement of jasmonic acid, ethylene, polyamines, and auxins, whereas salicylic acid did not seem to be involved. Genes encoding WRKY transcription factors, pathogenesis-related proteins, glutathione S-transferase, stilbene synthase, and phenylalanine ammonia-lyase were upregulated in infected berries. However, salicylic acid signalling was activated in healthy ripening berries along with the expression of proteins of the NBS-LRR superfamily and protein kinases, suggesting that the pathogen is able to shut down defences existing in healthy ripening berries. Furthermore, this study provided metabolic biomarkers of infection such as azelaic acid, a substance known to prime plant defence responses, arabitol, ribitol, 4-amino butanoic acid, 1-O-methyl- glucopyranoside, and several fatty acids that alone or in combination can be used to monitor Botrytis infection early in the vineyard.

Genome-Wide Admixture and Association Study of Serum Selenium Deficiency to Identify Genetic Variants Indirectly Linked to Selenium Regulation in Brazilian Adults.

Blood selenium (Se) concentrations differ substantially by population and could be influenced by genetic variants, increasing Se deficiency-related diseases. We conducted a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with serum Se deficiency in 382 adults with admixed ancestry. Genotyping arrays were combined to yield 90,937 SNPs. R packages were applied to quality control and imputation. We also performed the ancestral proportion analysis. The Search Tool for the Retrieval of Interacting Genes was used to interrogate known protein-protein interaction networks (PPIs). Our ancestral proportion analysis estimated 71% of the genome was from Caucasians, 22% was from Africans, and 8% was from East Asians. We identified the SNP rs1561573 in the TraB domain containing 2B (TRABD2B), rs425664 in MAF bZIP transcription factor (MAF), rs10444656 in spermatogenesis-associated 13 (SPATA13), and rs6592284 in heat shock protein nuclear import factor (HIKESHI) genes. The PPI analysis showed functional associations of Se deficiency, thyroid hormone metabolism, NRF2-ARE and the Wnt pathway, and heat stress. Our findings show evidence of a genetic association between Se deficiency and metabolic pathways indirectly linked to Se regulation, reinforcing the complex relationship between Se intake and the endogenous factors affecting the Se requirements for optimal health.

Changes in transcriptome of native nasal epithelium expressing F508del-CFTR and intersecting data from comparable studies.

BACKGROUND: Microarray studies related to cystic fibrosis (CF) airway gene expression have gone some way in clarifying the complex molecular background of CF lung diseases, but have made little progress in defining a robust "molecular signature" associated with mutant CFTR expression. Disparate methodological and statistical analyses complicate comparisons between independent studies of the CF transcriptome, and although each study may be valid in isolation, the conclusions reached differ widely. METHODS: We carried out a small-scale whole genome microarray study of gene expression in human native nasal epithelial cells from F508del-CFTR homozygotes in comparison to non-CF controls. We performed superficial comparisons with other microarray datasets in an attempt to identify a subset of regulated genes that could act as a signature of F508del-CFTR expression in native airway tissue samples. RESULTS: Among the alterations detected in CF, up-regulation of genes involved in cell proliferation, and down-regulation of cilia genes were the most notable. Other changes involved gene expression changes in calcium and membrane pathways, inflammation, defence response, wound healing and the involvement of estrogen signalling. Comparison of our data set with previously published studies allowed us to assess the consistency of independent microarray data sets, and shed light on the limitations of such snapshot studies in measuring a system as subtle and dynamic as the transcriptome. Comparison of in-vivo studies nevertheless yielded a small molecular CF signature worthy of future investigation. CONCLUSIONS: Despite the variability among the independent studies, the current CF transcriptome meta-analysis identified subsets of differentially expressed genes in native airway tissues which provide both interesting clues to CF pathogenesis and a possible CF biomarker.

Arrow plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on sample subgroups.

BACKGROUND: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. RESULTS: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. CONCLUSION: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Labellum transcriptome reveals alkene biosynthetic genes involved in orchid sexual deception and pollination-induced senescence.

One of the most remarkable pollination strategy in orchids biology is pollination by sexual deception, in which the modified petal labellum lures pollinators by mimicking the chemical (e.g. sex pheromones), visual (e.g. colour and shape/size) and tactile (e.g. labellum trichomes) cues of the receptive female insect species. The present study aimed to characterize the transcriptional changes occurring after pollination in the labellum of a sexually deceptive orchid (Ophrys fusca Link) in order to identify genes involved on signals responsible for pollinator attraction, the major goal of floral tissues. Novel information on alterations in the orchid petal labellum gene expression occurring after pollination demonstrates a reduction in the expression of alkene biosynthetic genes using O. fusca Link as the species under study. Petal labellum transcriptional analysis revealed downregulation of transcripts involved in both pigment machinery and scent compounds, acting as visual and olfactory cues, respectively, important in sexual mimicry. Regulation of petal labellum senescence was revealed by transcripts related to macromolecules breakdown, protein synthesis and remobilization of nutrients.

Cultivar-specific kinetics of gene induction during downy mildew early infection in grapevine.

The oomycete pathogen Plasmopara viticola (Berk. et Curt.) Berl. et de Toni is the causing agent of the destructive downy mildew disease in grapevine. Despite the advances towards elucidation of grapevine resistance mechanisms to downy mildew, increased knowledge of the biological and genetic components of the pathosystem is important to design suitable breeding strategies. Previously, a cDNA microarray approach was used to compare two Vitis vinifera genotypes Regent and Trincadeira (resistant and susceptible to downy mildew, respectively) in field conditions. The same cDNA microarray chip was used to confirm field-based results and to compare both genotypes under greenhouse conditions at 0, 6, and 12 h post-inoculation with P. viticola. Results show that when comparing both cultivars after pathogen inoculation, there is a preferential modulation of several defense, signaling, and metabolism associated transcripts in Regent. Early transcriptional changes are discussed in terms of genetic background and resistance mechanism. This study is the first to directly compare resistant and susceptible cultivars responses as early as 6 hpi with P. viticola, providing several candidate genes potentially related to the expression of resistance traits.

A Role for Gene-Environment Interactions in Autism Spectrum Disorder Is Supported by Variants in Genes Regulating the Effects of Exposure to Xenobiotics.

Heritability estimates support the contribution of genetics and the environment to the etiology of Autism Spectrum Disorder (ASD), but a role for gene-environment interactions is insufficiently explored. Genes involved in detoxification pathways and physiological permeability barriers (e.g., blood-brain barrier, placenta and respiratory airways), which regulate the effects of exposure to xenobiotics during early stages of neurodevelopment when the immature brain is extremely vulnerable, may be particularly relevant in this context. Our objective was to identify genes involved in the regulation of xenobiotic detoxification or the function of physiological barriers (the XenoReg genes) presenting predicted damaging variants in subjects with ASD, and to understand their interaction patterns with ubiquitous xenobiotics previously implicated in this disorder. We defined a panel of 519 XenoReg genes through literature review and database queries. Large ASD datasets were inspected for in silico predicted damaging Single Nucleotide Variants (SNVs) (N = 2,674 subjects) or Copy Number Variants (CNVs) (N = 3,570 subjects) in XenoReg genes. We queried the Comparative Toxicogenomics Database (CTD) to identify interaction pairs between XenoReg genes and xenobiotics. The interrogation of ASD datasets for variants in the XenoReg gene panel identified 77 genes with high evidence for a role in ASD, according to pre-specified prioritization criteria. These include 47 genes encoding detoxification enzymes and 30 genes encoding proteins involved in physiological barrier function, among which 15 are previous reported candidates for ASD. The CTD query revealed 397 gene-environment interaction pairs between these XenoReg genes and 80% (48/60) of the analyzed xenobiotics. The top interacting genes and xenobiotics were, respectively, CYP1A2, ABCB1, ABCG2, GSTM1, and CYP2D6 and benzo-(a)-pyrene, valproic acid, bisphenol A, particulate matter, methylmercury, and perfluorinated compounds. Individuals carrying predicted damaging variants in high evidence XenoReg genes are likely to have less efficient detoxification systems or impaired physiological barriers. They can therefore be particularly susceptible to early life exposure to ubiquitous xenobiotics, which elicit neuropathological mechanisms in the immature brain, such as epigenetic changes, oxidative stress, neuroinflammation, hypoxic damage, and endocrine disruption. As exposure to environmental factors may be mitigated for individuals with risk variants, this work provides new perspectives to personalized prevention and health management policies for ASD.

Transcript and metabolite analysis in Trincadeira cultivar reveals novel information regarding the dynamics of grape ripening.

BACKGROUND: Grapes (Vitis vinifera L.) are economically the most important fruit crop worldwide. However, the complexity of molecular and biochemical events that lead to the onset of ripening of nonclimacteric fruits is not fully understood which is further complicated in grapes due to seasonal and cultivar specific variation. The Portuguese wine variety Trincadeira gives rise to high quality wines but presents extremely irregular berry ripening among seasons probably due to high susceptibility to abiotic and biotic stresses. RESULTS: Ripening of Trincadeira grapes was studied taking into account the transcriptional and metabolic profilings complemented with biochemical data. The mRNA expression profiles of four time points spanning developmental stages from pea size green berries, through véraison and mature berries (EL 32, EL 34, EL 35 and EL 36) and in two seasons (2007 and 2008) were compared using the Affymetrix GrapeGen® genome array containing 23096 probesets corresponding to 18726 unique sequences. Over 50% of these probesets were significantly differentially expressed (1.5 fold) between at least two developmental stages. A common set of modulated transcripts corresponding to 5877 unigenes indicates the activation of common pathways between years despite the irregular development of Trincadeira grapes. These unigenes were assigned to the functional categories of "metabolism", "development", "cellular process", "diverse/miscellanenous functions", "regulation overview", "response to stimulus, stress", "signaling", "transport overview", "xenoprotein, transposable element" and "unknown". Quantitative RT-PCR validated microarrays results being carried out for eight selected genes and five developmental stages (EL 32, EL 34, EL 35, EL 36 and EL 38). Metabolic profiling using 1H NMR spectroscopy associated to two-dimensional techniques showed the importance of metabolites related to oxidative stress response, amino acid and sugar metabolism as well as secondary metabolism. These results were integrated with transcriptional profiling obtained using genome array to provide new information regarding the network of events leading to grape ripening. CONCLUSIONS: Altogether the data obtained provides the most extensive survey obtained so far for gene expression and metabolites accumulated during grape ripening. Moreover, it highlighted information obtained in a poorly known variety exhibiting particular characteristics that may be cultivar specific or dependent upon climatic conditions. Several genes were identified that had not been previously reported in the context of grape ripening namely genes involved in carbohydrate and amino acid metabolisms as well as in growth regulators; metabolism, epigenetic factors and signaling pathways. Some of these genes were annotated as receptors, transcription factors, and kinases and constitute good candidates for functional analysis in order to establish a model for ripening control of a non-climacteric fruit.

Use of chemometrics in the selection of a Saccharomyces cerevisiae expression system for recombinant cyprosin B production.

Two multivariate statistical methods, factor analysis (FA) and hierarchical cluster analysis (HCA), were applied to experimental data set to evaluate their usefulness in selecting the adequate expression system and optimal growth parameters for recombinant cyprosin B production. Using FA, the large data set was reduced to two factors representing 73.4% of variability. Factor 1, with 53.5% of variability, corresponds to recombinant cyprosin B expression and efficient secretion, while factor 2, accounting for 19.9% of variability, represents cell growth and physiological characteristics. FA and HCA allowed the establishment of correlations among different variables and the clusters obtained providing clear identification of the experimental parameters related to cyprosin B production, which results on more accurate scientific output and time saving when selection of an adequate expression system is concerned.

COVID-19: Nothing is Normal in this Pandemic.

This manuscript brings attention to inaccurate epidemiological concepts that emerged during the COVID-19 pandemic. In social media and scientific journals, some wrong references were given to a "normal epidemic curve" and also to a "log-normal curve/distribution". For many years, textbooks and courses of reputable institutions and scientific journals have disseminated misleading concepts. For example, calling histogram to plots of epidemic curves or using epidemic data to introduce the concept of a Gaussian distribution, ignoring its temporal indexing. Although an epidemic curve may look like a Gaussian curve and be eventually modelled by a Gauss function, it is not a normal distribution or a log-normal, as some authors claim. A pandemic produces highly-complex data and to tackle it effectively statistical and mathematical modelling need to go beyond the "one-size-fits-all solution". Classical textbooks need to be updated since pandemics happen and epidemiology needs to provide reliable information to policy recommendations and actions.

Organogenic nodule development in hop (Humulus lupulus L.): transcript and metabolic responses.

BACKGROUND: Hop (Humulus lupulus L.) is an economically important plant forming organogenic nodules which can be used for genetic transformation and micropropagation. We are interested in the mechanisms underlying reprogramming of cells through stress and hormone treatments. RESULTS: An integrated molecular and metabolomic approach was used to investigate global gene expression and metabolic responses during development of hop's organogenic nodules. Transcript profiling using a 3,324-cDNA clone array revealed differential regulation of 133 unigenes, classified into 11 functional categories. Several pathways seem to be determinant in organogenic nodule formation, namely defense and stress response, sugar and lipid metabolism, synthesis of secondary metabolites and hormone signaling. Metabolic profiling using 1H NMR spectroscopy associated to two-dimensional techniques showed the importance of metabolites related to oxidative stress response, lipid and sugar metabolism and secondary metabolism in organogenic nodule formation. CONCLUSION: The expression profile of genes pivotal for energy metabolism, together with metabolites profile, suggested that these morphogenic structures gain energy through a heterotrophic, transport-dependent and sugar-degrading anaerobic metabolism. Polyamines and auxins are likely to be involved in the regulation of expression of many genes related to organogenic nodule formation. These results represent substantial progress toward a better understanding of this complex developmental program and reveal novel information regarding morphogenesis in plants.

Transcriptional and metabolic profiling of grape (Vitis vinifera L.) leaves unravel possible innate resistance against pathogenic fungi.

Grapevine species (Vitis sp.) are prone to several diseases, fungi being the major pathogens compromising its cultivation and economic profit around the world. Knowledge of the complexity of mechanisms responsible for resistance to fungus infection of cultivars, such as Regent, is necessary for strategies to be defined which will improve resistance in highly susceptible crop species. Transcript and metabolic profiles of the Vitis vinifera cultivars Regent and Trincadeira (resistant and susceptible to fungi, respectively) were analysed by cDNA microarray, quantitative real-time PCR, and nuclear magnetic resonance spectroscopy. The integration of datasets obtained through transcriptome and metabolome analysis revealed differences in transcripts and metabolites between both cultivars. These differences are probably associated with the innate resistance of Regent towards the mildews. Several transcripts related to stress and defence, namely a subtilisin-like protease, phenylalanine ammonia lyase, S-adenosylmethionine synthase, WD-repeat protein like, and J2P, were up-regulated in Regent suggesting an intrinsic resistance capability of this cultivar. A metabolic profile revealed an accumulation of compounds such as inositol and caffeic acid, which are known to confer resistance to fungi. The differences in transcripts and metabolites detected are discussed in terms of the metabolic pathways and their possible role in plant defence against pathogen attack, as well as their potential interest to discriminate among resistant and susceptible grapevine cultivars.

Fungal transcript pattern during the preinfection stage (12 h) of ectomycorrhiza formed between Pisolithus tinctorius and Castanea sativa roots, identified using cDNA microarrays.

Transcriptional changes in Pisolithus tinctorius leading to ectomycorrhizal formation in P. tinctorius- Castanea sativa were investigated using a 12-h fungal interaction in vitro system. Using a 3107-cDNA clone microarray, 34 unique expressed sequence tags (ESTs) were found to be differentially expressed. These ESTs represent 14 known genes, 5 upregulated and 9 downregulated, and 20 orphan sequences. Some transcripts of upregulated genes (with unknown function) were previously identified in other mycorrhizal Pisolithus spp. associations. ESTs for S-adenosyl-L-homocysteine hydrolase and several orphan sequences were identified in our system. The identified transcript of downregulated genes involved hydrophobins, 5S, 18S, and 28S ribosomal RNA genes, large subunits of ribosomal RNA (mitochondrial gene), and two types of heat shock proteins. This study demonstrates the high complexity of molecular events involved in the preinfection steps and suggests the utilization of different fungal gene repertories before ectomycorrhizal formation. These data constitute a first contribution for the molecular understanding of early signaling events between P. tinctorius and C. sativa roots during ectomycorrhizal formation.

Bayesian classification and non-Bayesian label estimation via EM algorithm to identify differentially expressed genes: a comparative study.

Gene classification problem is studied considering the ratio of gene expression levels, X, in two-channel microarrays and a non-observed categorical variable indicating how differentially expressed the gene is: non differentially expressed, down-regulated or up-regulated. Supposing X from a mixture of Gamma distributions, two methods are proposed and results are compared. The first method is based on an hierarchical Bayesian model. The conditional predictive probability of a gene to belong to each group is calculated and the gene is assigned to the group for which this conditional probability is higher. The second method uses EM algorithm to estimate the most likely group label for each gene, that is, to assign the gene to the group which contains it with the higher estimated probability.

Validation of the Falls Efficacy Scale - International in a sample of Portuguese elderly.

OBJECTIVE: to translate and adapt Falls Efficacy Scale - International (FES-I). To analyze the psychometric properties of the FES-I Portugal version. METHOD: psychometric study. Sample consisting of 170 elderly people residing in the Autonomous Region of Madeira. A two- part form was used (sociodemographic characterization and FES-I Portugal). The cross-cultural adaptation was performed and the following psychometric properties were evaluated: validity (construct, predictive, and discriminant), reliability (Cronbach's alpha), and inter-rater reliability. RESULTS: the results allow us to verify a dimension of less demanding physical activities and another of more demanding physical activities. The inter-rater reliability study was 0.62, with an interclass correlation coefficient of 0.859, for a 95% confidence interval. The internal consistency of the Portuguese version was 0.962. CONCLUSION: the validity and reliability of the FES-I Portugal are consistent with the original version and proved to be appropriate instruments for evaluating the "impaired walking" and "risk of falls" nursing diagnoses in the older people.

Functional coherence metrics in protein families.

BACKGROUND: Biological sequences, such as proteins, have been provided with annotations that assign functional information. These functional annotations are associations of proteins (or other biological sequences) with descriptors characterizing their biological roles. However, not all proteins are fully (or even at all) annotated. This annotation incompleteness limits our ability to make sound assertions about the functional coherence within sets of proteins. Annotation incompleteness is a problematic issue when measuring semantic functional similarity of biological sequences since they can only capture a limited amount of all the semantic aspects the sequences may encompass. METHODS: Instead of relying uniquely on single (reductive) metrics, this work proposes a comprehensive approach for assessing functional coherence within protein sets. The approach entails using visualization and term enrichment techniques anchored in specific domain knowledge, such as a protein family. For that purpose we evaluate two novel functional coherence metrics, mUI and mGIC that combine aspects of semantic similarity measures and term enrichment. RESULTS: These metrics were used to effectively capture and measure the local similarity cores within protein sets. Hence, these metrics coupled with visualization tools allow an improved grasp on three important functional annotation aspects: completeness, agreement and coherence. CONCLUSIONS: Measuring the functional similarity between proteins based on their annotations is a non trivial task. Several metrics exist but due both to characteristics intrinsic to the nature of graphs and extrinsic natures related to the process of annotation each measure can only capture certain functional annotation aspects of proteins. Hence, when trying to measure the functional coherence of a set of proteins a single metric is too reductive. Therefore, it is valuable to be aware of how each employed similarity metric works and what similarity aspects it can best capture. Here we test the behaviour and resilience of some similarity metrics.