Trygve Almøy

Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra

Baselines are often chosen by visual inspection of their effect on selected spectra. A more objective procedure for choosing baseline correction algorithms and their parameter values for use in statistical analysis is presented. When the goal of the baseline correction is spectra with a pleasing appearance, visual inspection can be a satisfactory approach. If the spectra are to be used in a statistical analysis, objectivity and reproducibility are essential for good prediction. Variations in baselines from dataset to dataset means we have no guarantee that the best-performing algorithm from one analysis will be the best when applied to a new dataset. This paper focuses on choosing baseline correction algorithms and optimizing their parameter values based on the performance of the quality measure from the given analysis. Results presented in this paper illustrate the potential benefits of the optimization and points out some of the possible pitfalls of baseline correction.

Comparison of Prediction Methods when Only a Few Components are Relevant

Abstract We consider prediction in a multiple regression model where we also look on the explanatory variables as random. If the number of explanatory variables is large, then the common least squares multiple regression solution may not be the best one. We give a methodology for comparing certain alternative prediction methods by asymptotic calculations and perform such a comparisons for four specific methods. The results indicate that none of these methods dominates the others, and that the difference between the methods typically (but not always) is small when the number of observations is large. In particular, principal component regression does well when the eigenvalues corresponding to components not correlated with the dependent variables (i.e., the irrelevant eigenvalues) are extremely small or extremely large. Partial least squares regression does well for intermediate irrelevant eigenvalues. A maximum likelihood-type method dominates the others asymptotically, at least in the case of one relevan...

Microbial comparative pan-genomics using binomial mixture models

BackgroundThe size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology.ResultsWe estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection probabilities. Estimated pan-genome sizes range from small (around 2600 gene families) in Buchnera aphidicola to large (around 43000 gene families) in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely occurring genes in the population.ConclusionAnalyzing pan-genomics data with binomial mixture models is a way to handle dependencies between genomes, which we find is always present. A bottleneck in the estimation procedure is the annotation of rarely occurring genes.

CALIBRATION METHODS FOR NIRS INSTRUMENTS : A THEORETICAL EVALUATION AND COMPARISONS BY DATA SPLITTING AND SIMULATIONS

The properties of the recently proposed calibration method called restricted principal component regression (RPCR) were evaluated and compared with partial least-squares regression (PLSR) and two types of principal component regression (PCR1, selected according to the size of the eigenvalues, and PCR2, selected according to the t-value). RPCR can be considered a compromise between PCR and PLSR, since the first component of RPCR is equivalent to the first component of PLSR, while the rest can be regarded as principal components on a space orthogonal to the first. The methods showed almost the same properties when the irrelevant components had small eigenvalues. The prediction error of RPCR selected according to the size of the eigenvalues was intermediate to those of PCR1 and PLSR when the number of components was low, while RPCR and PCR1 nearly coincided when the number of components exceeded the number of relevant ones. The prediction error minimum was about the same for RPCR, PCR1, and PLSR, but the minimum of PLSR was obtained when a lower number of components were included in the calibration model.

A systematic search for discriminating sites in the 16S ribosomal RNA gene

BackgroundThe 16S rRNA is by far the most common genomic marker used for prokaryotic classification, and has been used extensively in metagenomic studies over recent years. Along the 16S gene there are regions with more or less variation across the kingdom of bacteria. Nine variable regions have been identified, flanked by more conserved parts of the sequence. It has been stated that the discriminatory power of the 16S marker lies in these variable regions. In the present study we wanted to examine this more closely, and used a supervised learning method to search systematically for sites that contribute to correct classification at either the phylum or genus level.ResultsWhen classifying phyla the site selection algorithm located 50 discriminative sites. These were scattered over most of the alignments and only around half of them were located in the variable regions. The selected sites did, however, have an entropy significantly larger than expected, meaning they are sites of large variation. We found that the discriminative sites typically have a large entropy compared to their closest neighbours along the alignments. When classifying genera the site selection algorithm needed around 80% of the sites in the 16S gene before the classification error reached a minimum. This means that all variation, in both variable and conserved regions, is needed in order to separate genera.ConclusionsOur findings does not support the statement that the discriminative power of the 16S gene is located only in the variable regions. Variable regions are important, but just as many discriminative sites are found in the more conserved parts. The discriminative power is typically found in sites of large variation located inside shorter regions of higher conservation.

Comparing K-mer based methods for improved classification of 16S sequences

BackgroundThe need for precise and stable taxonomic classification is highly relevant in modern microbiology. Parallel to the explosion in the amount of sequence data accessible, there has also been a shift in focus for classification methods. Previously, alignment-based methods were the most applicable tools. Now, methods based on counting K-mers by sliding windows are the most interesting classification approach with respect to both speed and accuracy. Here, we present a systematic comparison on five different K-mer based classification methods for the 16S rRNA gene. The methods differ from each other both in data usage and modelling strategies. We have based our study on the commonly known and well-used naïve Bayes classifier from the RDP project, and four other methods were implemented and tested on two different data sets, on full-length sequences as well as fragments of typical read-length.ResultsThe difference in classification error obtained by the methods seemed to be small, but they were stable and for both data sets tested. The Preprocessed nearest-neighbour (PLSNN) method performed best for full-length 16S rRNA sequences, significantly better than the naïve Bayes RDP method. On fragmented sequences the naïve Bayes Multinomial method performed best, significantly better than all other methods. For both data sets explored, and on both full-length and fragmented sequences, all the five methods reached an error-plateau.ConclusionsWe conclude that no K-mer based method is universally best for classifying both full-length sequences and fragments (reads). All methods approach an error plateau indicating improved training data is needed to improve classification from here. Classification errors occur most frequent for genera with few sequences present. For improving the taxonomy and testing new classification methods, the need for a better and more universal and robust training data set is crucial.

A Discussion Concerning the Inclusion of Variety Effect when Analysis of Variance is Used to Detect Differentially Expressed Genes

In order to investigate the possible mechanisms for eve stripe formation of Drosophila embryo, a spatio-temporal gene/protein interaction network model is proposed to mimic dynamic behaviors of protein synthesis, protein decay, mRNA decay, protein diffusion, transcription regulations and autoregulation to analyze the interplay of genes and proteins at different compartments in early embryogenesis. In this study, we use the maximum likelihood (ML) method to identify the stochastic 3-D Embryo Space-Time (3-DEST) dynamic model for gene/protein interaction network via 3-D mRNA and protein expression data and then use the Akaike Information Criterion (AIC) to prune the gene/protein interaction network. The identified gene/protein interaction network allows us not only to analyze the dynamic interplay of genes and proteins on the border of eve stripes but also to infer that eve stripes are established and maintained by network motifs built by the cooperation between transcription regulations and diffusion mechanisms in early embryogenesis. Literature reference with the wet experiments of gene mutations provides a clue for validating the identified network. The proposed spatio-temporal dynamic model can be extended to gene/protein network construction of different biological phenotypes, which depend on compartments, e.g. postnatal stem/progenitor cell differentiation.Vertebrae and other mammalian repetitive structures are formed from embryonic organs called somites. Somites arise sequentially from the unsegmented presomitic mesoderm (PSM). In mice, a new bilateral pair of somites arise every two hours from the rostral PSM. On the other hand, cells are added to the caudal side of the PSM due to cell proliferation of the tail bud. Somite formation correlates with cycles of cell-autonomous expression in the PSM of genes like Hes7. Because the somitogenesis is a highly dynamic and coordinated process, this event has been subjected to extensive theoretical modeling. Here, we describe the current understanding about the somitogenesis in mouse embryos with an emphasis on insights gained from computer simulations. It is worth noting that the combination of experiments and computer simulations has uncovered dynamical properties of the somitogenesis clock such as the transcription/translation delays, the half-life and the synchronization mechanism across the PSM. Theoretical models have also been useful to provide predictions and rigorous hypothesis about poorly understood processes such as the mechanisms by which the temporal PSM oscillations are arrested and converted into an spatial pattern. We aim at reviewing this theoretical literature in such a way that experimentalists might appreciate the resulting conclusions.Background Previous studies demonstrated that the vascular endothelial growth factor (VEGF) was being implicated in the airways inflammation and remodeling process in patients with asthma. Aims We explored the relationship of three polymorphisms in the VEGF gene with asthma in both case control and family studies. Methods We Genotyped a total of 210 children with asthma, 224 unrelated controls and 160 parents for the +936 C >T (rs3025039), −634 G > C (rs2010963) and −2549 −2567 del 18 of the VEGF promoter region. The Mutations were identified with polymerase chain reaction followed by restriction fragment length polymorphism (RFLP) analysis for the +936 C > T, and −634 G > C polymorphisms. Results Of the three polymorphisms studied, a borderline association with asthma was found for the G allele in the −634 G > C polymorphism (p = 0.059). No Statistically significant differences were observed for both +936 C > T, and −2549 −2567 del 18 polymorphisms between asthmatic patients and controls, considering either allelic or genotypic frequencies. The distribution of genotypes according to the severity status revealed a significant differences for the +936 C > T, and −2549 −2567 del 18 polymorphisms. In addition, association was found with the haplotypes inferred by the three polymorphisms and asthma susceptibility. Conclusion We suggest that VEGF Gene polymorphisms can be implicated in asthma.Insulin sensitizing thiazolidinediones (TZDs) are generally considered to work as agonists for the nuclear receptor peroxisome proliferative activated receptor-gamma (PPARγ). However, TZDs also have acute, non-genomic metabolic effects and it is unclear which actions are responsible for the beneficial pharmacology of these compounds. We have taken advantage of an analog, based on the metabolism of pioglitazone, which has much reduced ability to activate PPARγ. This analog (PNU-91325) was compared to rosiglitazone, the most potent PPARγ activator approved for human use, in a variety of studies both in vitro and in vivo. The data demonstrate that PNU-91325 is indeed much less effective than rosiglitazone at activating PPARγ both in vitro and in vivo. In contrast, both compounds bound similarly to a mitochondrial binding site and acutely activated PI-3 kinase-directed phosphorylation of AKT, an action that was not affected by elimination of PPARγ activation. The two compounds were then compared in vivo in both normal C57 mice and diabetic KKAy mice to determine whether their pharmacology correlated with biomarkers of PPARγ activation or with the expression of other gene transcripts. As expected from previous studies, both compounds improved insulin sensitivity in the diabetic mice, and this occurred in spite of the fact that there was little increase in expression of the classic PPARγ target biomarker adipocyte binding protein-2 (aP2) with PNU-91325 under these conditions. An examination of transcriptional profiling of key target tissues from mice treated for one week with both compounds demonstrated that the relative pharmacology of the two thiazolidinediones correlated best with an increased expression of an array of mitochondrial proteins and with expression of PPARγ coactivator 1-alpha (PGC1α), the master regulator of mitochondrial biogenesis. Thus, important pharmacology of the insulin sensitizing TZDs may involve acute actions, perhaps on the mitochondria, that are independent of direct activation of the nuclear receptor PPARγ. These findings suggest a potential alternative route to the discovery of novel insulin sensitizing drugs.The trans-regulatory circuit is considered as the regulatory interactions between upstream regulatory genes and transcription factor binding site motifs or cis elements. And the cis-regulatory circuit is viewed as a dynamic interactive circuit among binding site motifs with their effective action on the expression scheme of target gene. In brief, gene transcription depends on the trans/cis regulatory circuits. In this study, nonlinear trans/cis regulatory circuits for gene transcription in yeast are constructed using microarray data, translation time delay, and information of transcription factors (TFs) binding sites. We provide a useful nonlinear dynamic modeling and develop a parameter estimating method for the construction of trans/cis regulatory circuits, which is powerful for understanding gene transcription. We apply our method to construct trans/cis regulatory circuits of yeast cell cycle-related genes and successfully quantify their regulatory abilities and find possible cis-element interactions. Not only could the data of yeast be applied by our method, but those of other species also could. The proposed method can provide a quantitative basis for system analysis of gene circuits, which is potential for gene regulatory circuit design with a desired gene expression.The signal peptide of the luciferase secreted by the marine copepod Gaussia princeps has been shown to promote high-level protein synthesis/secretion of recombinant proteins, being far superior to mammalian counterparts. The main aim of the present study was to investigate the effects of seven selected signal peptides derived from oikosins, house proteins of the marine organism Oikopleura dioica, on synthesis/secretion of recombinant proteins. Vector constructs were made in which the coding regions of two naturally secreted proteins, Gaussia luciferase and human endostatin (hEndostatin), were “seamlessly” fused to the signal peptide coding sequences of interest. CHO cells were transfected with the plasmids and populations of stably transfected cells established. The amounts of reporter proteins in cell extract and medium samples were determined and the results compared to those obtained from cells stably transfected with a reference vector construct. In addition, the amounts of luciferase or hEndostatin encoding mRNAs in the cells were determined and related to the protein levels obtained. The levels of reporter protein produced varied greatly among the seven oikosin signal peptides tested. Whereas the oikosin 1 signal peptide resulted in about 40% production of Gaussia luciferase compared to the reference construct, oikosins 2–7 were extremely ineffective (<1%). mRNA levels were not dramatically affected such that inadequate availability of transcript for translation was not the underlying reason for the observations. The oikosin 1 signal peptide was also the most effective regarding synthesis/secretion of hEndostatin. No secreted product was observed using the oikosin 3 signal peptide. Interestingly, the molecular weight of hEndostatin in cell extracts prepared from cells transfected with oikosin 2 and 3 constructs was higher than that using the oikosin 1 signal peptide. The overall findings indicate that the signal peptide affects the efficiency of protein synthesis and secretion through a mechanism operating at the post-transcriptional level. The results described here provide substantial support to our previous observations which suggested that the choice of the signal peptide is imperative when aiming to achieve optimal synthesis and secretion of a recombinant protein using transfected mammalian cells.Integrins have been proposed to play a major role in lens morphogenesis. To determine the role of β1-integrin and its down-stream signaling partner, integrin linked kinase (ILK), in lens morphogenesis, eyes of WT mice and mice with a nestin-linked conditional knockout of β1-integrin or ILK were analyzed for defects in lens development. Mice, lacking the genes encoding the β1-integrin subunit (Itgb1) or ILK (Ilk), showed a perinatal degeneration of the lens. Early signs of lens degeneration included vacuolization, random distribution of lens cell nuclei, disrupted fiber morphology and attenuation and separation of the lens capsule. The phenotype became progressively more severe during the first postnatal week eventually leading to the complete loss of the lens. A more severe phenotype was observed in ILK mutants at similar stages. Eyes from embryonic day 13 β1-integrin-mutant embryos showed no obvious signs of lens degeneration, indicating that mutant lens develops normally until peri-recombination. Our findings suggest that β1-integrins and ILK cooperate to control lens cell survival and link lens fibers to the surrounding extracellular matrix. The assembly and integrity of the lens capsule also appears to be reliant on integrin signaling within lens fibers. Extrapolation of these results indicates a novel role of integrins in lens cell-cell adhesions as well as a potential role in the pathogenesis of congenital cataracts.Resistance to radio and chemotherapy is one of the major drawbacks in the progression of head and neck squamous cell cancer (HNSCC) patients, evidencing the importance of finding optimum molecular prognosis markers to develop personalized treatment schedules. TGF-β effector TAK1 activity has been related to a greater aggressiveness in several types of cancer (Kondo et al. 1998; Edlund et al. 2003; Kaur et al. 2005) and, although there has been described no significant implication of TAK1 in HNSCC development, we have further examined the role of its mRNA expression as a marker of prognosis in HNSCC. Fifty-nine advanced HNSCC patients were recruited for the study. The tumor expression of TAK1 mRNA was analyzed with RT-PCR using Taqman technology and its relationship with the clinical outcome of the patients studied. TAK1 mRNA expression was lower in patients that relapsed than in those that did not, but the difference was only significant between the patients that showed response to treatment (p < 0.001). ROC curve analyses pointed a 0.5 expression ratio TAK1/B2M value as an optimum cut-off point for relapse and response. Our data suggest the TAK1 mRNA analysis by Taqman RT-PCR can predict the risk of relapse in HNSCC patients.In microarray studies several statistical methods have been proposed with the purpose of identifying differentially expressed genes in two varieties. A commonly used method is an analysis of variance model where only the effect of interaction between variety and gene is tested. In this paper we argue that in addition to the interaction effects, the main effect of variety should simultaneously also be taken into account when posting the hypothesis.Prostanoids have a broad spectrum of biological activities in a variety of organs including the brain. However, their effects on synaptic plasticity in the brain, which have been recently revealed, are ambiguous in comparison to those in the other organs. Prostaglandin E2 (PGE2) is a prostanoid produced from arachidonic acid in the cellular membrane, and knowledge about its functions is increasing. Recently, a novel function of PGE2 in the brain has shed light on aspects of synaptic plasticity such as long-term potentiation (LTP). More recently, we have proposed a hypothesis for the mechanisms of this PGE2-related form of synaptic plasticity in the visual cortex. This involves the dynamics of two subtypes of PGE2 receptors that have opposing functions in intracellular signal transduction. Consequently, mechanisms that increase the level of cyclic AMP in the cytosol may explain for the mechanisms of LTP in the visual cortex. The current notion of bidirectional trafficking of PGE2 receptors under this hypothesis is reminiscent of the “silent synapse” mechanism of LTP on the trafficking of the AMPA receptors between the membrane and cytosol. Moreover, we propose the hypothesis that PGE2 acts as a “post-to-postsynaptic messenger” for the induction of LTP in the visual cortex. This review describes a complex mode of action of PGE2 receptors in synaptic plasticity in the brain.Purpose The present study predicts and tests genetic networks that modulate gene expression during the retinal wound-healing response. Methods Upstream modulators and target genes were defined using meta-analysis and bioinformatic approaches. Quantitative trait loci (QTLs) for retinal acute phase genes (Vazquez-Chona et al. 2005) were defined using QTL analysis of CNS gene expression (Chesler et al. 2005). Candidate modulators were defined using computational analysis of gene and motif sequences. The effect of candidate genes on wound healing was tested using animal models of gene expression. Results A network of early wound-healing genes is modulated by a locus on chromosome 12. The genetic background of the locus altered the wound-healing response of the retina. The C57BL/6 allele conferred enhanced expression of neuronal marker Thy1 and heat-shock-like crystallins, whereas the DBA/2J allele correlated with greater levels of the classic marker of retinal stress, glial fibrillary acidic protein (GFAP). Id2 and Lpin1 are candidate upstream modulators as they strongly correlated with the segregation of DBA/2J and C57BL/6 alleles, and their dosage levels correlated with the enhanced expression of survival genes (Thy1 and crystallin genes). Conclusion We defined a genetic network associated with the retinal acute injury response. Using genetic linkage analysis of natural transcript variation, we identified regulatory loci and can didate modulators that control transcript levels of acute phase genes. Our results support the convergence of gene expression profiling, QTL analysis, and bioinformatics as a rational approach to discover molecular pathways controlling retinal wound healing.Introduction advent of molecular biology caused a reductionist “fever” to spread throughout the biological research community that continues to this day. The new molecular insights and techniques enabled researchers to probe the constituent parts of complex biological systems at unprecedented scale and detail. The reductionist approach naturally emerged: if we could now isolate and study the component parts of a system, we should be able to synthesize the information about the individual components into a unifi ed understanding of the whole system. However, this “naive reductionism” (Bloom, 2001) needs to be balanced with a systems approach for a simple reason: the complex dynamics of a biological system often produce behaviors and properties that cannot be explained by the presence of a single component, but rather emerge from the interactions of the components of the system (so-called emergentThe aromatic hydrocarbon receptor (AhR) mediates biological responses to certain exogenous ligands, such as the environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), and has also been demonstrated to modulate the cell cycle and differentiated state of several cell lines independently of exogenous ligands. In this study, we used DNA micorarray analysis to elucidate the profile of genes responsive to the expression of unliganded AhR by re-introducing AhR into an AhR-deficient mouse derivative (c19) of the mouse hepatoma cell line Hepa1c1c7. 22 gene products were up-regulated and 8 were down-regulated two-fold or more in c19 cells infected with a retroviral vector expressing mouse AhR. Surprisingly, expression of genes involved in cell proliferation or differentiation were not affected by introduction of AhR. AhR also did not restore expression of the albumin gene in c19 cells. Introduction of AhR into c12, a similar AhR-defective mouse hepatoma cell line, also did not restore albumin expression, and furthermore, did not lead to changes in cellular morphology or cell cycle parameters. These observations fail to support the notion that unliganded AhR regulates proliferation and differentiation of liver-derived cells.With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.Bacterial RNA polymerase is composed of a core of subunits (β, β′, α1, α2, ω), which have RNA synthesizing activity, and a specificity factor (σ), which identifies the start of transcription by recognizing and binding to sequence elements within promoter DNA. Four core promoter consensus sequences, the −10 element, the extended −10 (TGn) element, the −35 element, and the UP elements, have been known for many years; the importance of a nontemplate G at position −5 has been recognized more recently. However, the functions of these elements are not the same. The AT-rich UP elements, the −35 elements (−35TTGACA−30), and the extended −10 (−15TGn−13) are recognized as double-stranded binding elements, whereas the −5 nontemplate G is recognized in the context of single-stranded DNA at the transcription bubble. Furthermore, the −10 element (−12TATAAT−7) is recognized as both double-stranded DNA for the T:A bp at position −12 and as nontemplate, single-stranded DNA from positions −11 to −7. The single-stranded sequences at positions −11 to −7 as well as the −5 contribute to later steps in transcription initiation that involve isomerization of polymerase and separation of the promoter DNA around the transcription start site. Recent work has demonstrated that the double-stranded elements may be used in various combinations to yield an effective promoter. Thus, while some minimal number of contacts is required for promoter function, polymerase allows the elements to be mixed and matched. Interestingly, which particular elements are used does not appear to fundamentally alter the transcription bubble generated in the stable complex. In this review, we discuss the multiple steps involved in forming a transcriptionally competent polymerase/promoter complex, and we examine what is known about polymerase recognition of core promoter elements. We suggest that considering promoter elements according to their involvement in early (polymerase binding) or later (polymerase isomerization) steps in transcription initiation rather than simply from their match to conventional promoter consensus sequences is a more instructive form of promoter classification.To perform a quantitative analysis with gene-arrays, one must take into account inaccuracies (experimental variations, biological variations and other measurement errors) which are seldom known. In this paper we investigated amplification and noise propagation related errors by measuring intensity dependent variations. Based on a set of control samples, we create confidence intervals for up and down regulations. We validated our method through a qPCR experiment and compared it to standard analysis methods (including loess normalization and filtering methods based on genetic variability). The results reveal that amplification related errors are a major concern.Fanconi anemia (FA) is an autosomal recessive disorder characterized by congenital abnormalities, bone marrow failure, chromosome fragility, and cancer susceptibility. At least eleven members of the FA gene family have been identified using complementation experiments. Ubiquitin-proteasome has been shown to be a key regulator of FA proteins and their involvement in the repair of DNA damage. Here, we identified a novel functional link between the FA/BRCA pathway and E2F-mediated cell cycle regulome. In silico mining of a transcriptome database and promoter analyses revealed that a significant number of FA gene members were regulated by E2F transcription factors, known to be pivotal regulators of cell cycle progression – as previously described for BRCA1. Our findings suggest that E2Fs partly determine cell fate through the FA/BRCA pathway.Microchimerism refers to the status of harboring cells from another individual at low levels. It is well known that cells traffic bidirectionally between fetus and mother during pregnancy. This situation resembles a naturally occurring long lasting fetal stem cell transplantation. The fetus acts as the donor and the mother acts as the recipient. To study the role of microchimerism in tissue regeneration, we constructed a murine microchimerism model with wild type C57BL/6J female mice carrying progenies which expressed green fluorescent proteins (GFP). Our data indicated that skin injuries in the female mice during pregnancy increased microchimerism of GFP expressing cells from the GFP transgenic progenies. The GFP positive cells also appeared at the site of spinal cord where injury occurred during pregnancy. Our study suggests that the amount of fetal cells in maternal mice significantly increased if injuries occurred during pregnancy. Fetal stem cells appear to respond to maternal injury signals and may play a role in maternal tissue regeneration during pregnancy.Receptor-like kinases (RLKs) in plants are a large superfamily of proteins that are structurally similar. RLKs are involved in a diverse array of plant responses including development, growth, hormone perception and the response to pathogens. Current studies have focused attention on plant receptor-like kinases as an important class of sentinels acting in plant defense responses. RLKs have been identified that act in both broad-spectrum, elicitor-initiated defense responses and as dominant resistance (R) genes in race-specific pathogen defense. Most defense-related RLKs are of the leucine-rich repeat (LRR) subclass although new data are highlighting other classes of RLKs as important players in defense responses. As our understanding of RLK structure, activation and signaling has expanded, the role of the ubiquitin/proteasome system in the regulation of these receptors has emerged as a central theme.Purpose Epileptic mutant EL mice show secondary generalized seizures. Seizure discharges initiate in the parietal cortex and generalize through the hippocampus. We have previously demonstrated an increase in the activity of inducible nitric oxide synthetase (iNOS) as well as a decrease in the activity of superoxide dismutase (SOD) in the hippocampus of EL mice, suggesting that cell toxic free radicals are increased in the brain of EL mice. In parallel with this, neurotrophic factors were significantly increased in the hippocampus of EL mice in earlier developmental stages before exhibiting frequent seizures. These findings were no longer present after frequent seizures, suggesting that these events may trigger ictogenesis. On the other hand, it is reported that limbic seizures rapidly induce cytokines and related inflammatory mediators. It remains to be seen, however, whether cytokines contribute to the transition from interictal to ictal state. The present study was designed to address this issue using EL mice. Methods EL mice at the age from 4 to 23 weeks and their control animal, DDY mice at the age of 10 and 20 weeks were used. Seizures were induced in EL mice once every week since 5 weeks. Cytokines, such as interleukin-1 alpha (IL-1a), interleukin 1-beta (IL-1b), IL-6, IL-1 receptor (IL-1r), IL-1 receptor antagonist (IL-ra) and tumor necrosis factor alpha (TNF-a) were examined by Western blotting in the ‘focus complex’ of brain (namely, in the parietal cortex and hippocampus) of EL mice in the interictal period at different developmental stages. In 15 week old EL mice, which show seizures once a week, these cytokines were similarly determined 5 min, 2 hr, 4 hr, 11 hr, 24 hr, 3 days and 6 days after the last seizure induced. Results A significant increase in the level of cytokines was observed in the brain of EL mice at any stages during development, compared with the level of cytokines in the brain of control DDY. Cytokines were increased predominantly before experiencing frequent seizures. In EL mice at the age of 15 weeks, the level of cytokines in the hippocampus was highest 6 days after seizures. In the parietal cortex, cytokines were most highly expressed 2 hr after seizures. The results indicate that cytokines were kept up-regulated until next seizures in the hippocampus, whereas they were transiently up-regulated immediately after seizures in the parietal cortex. Conclusion It is concluded that in the brain of EL mice, pro-inflammatory cytokines are increased progressively and periodically in association with the development and the seizure activity, respectively. A periodic increase of cytokines prior to the next seizure episode may play a role in triggering the ictal activity. Namely, alteration of region-specific cytokines may induce ictal activities from the interictal state. It is conceivable that inflammatory cytokines may work together with neuronal factors during epileptogenesis and in the transition from interictal to ictal state.Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU.DNA microarray is a powerful tool in biomedical research. However, transcriptomic profiling using DNA microarray is subject to many variations including biological variability. To evaluate the different sources of variation in mRNA gene expression profiles, gene expression profiles were monitored using the Affymetrix RatTox U34 arrays in cultured primary hepatocytes derived from six rats over a 26 hour period at 6 time points (0h, 2h, 5h, 8h, 14h and 26h) with two replicate arrays at each time point for each animal. In addition, the impact of sample size on the variability of differentially expressed gene lists and the consistency of biological responses were also investigated. Excellent intra-animal reproducibility was obtained at all time points with 0 out of 370 present probe sets across all time points showing significant difference between the 2 replicate arrays (3-way ANOVA, p ≤ 0.0001). However, large inter-animal biological variation in mRNA expression profiles was observed with 337 out of 370 present probe sets showing significant differences among 6 animals (3-way ANOVA, p ≤ 0.05). Principal Component Analysis (PCA) revealed that time effect (PC1) in this data set accounted for 47.4% of total variance indicating the dynamics of transcriptomics. The second and third largest effects came from animal difference, which accounted for 16.9% (PC2 and PC3) of the total variance. The reproducibility of gene lists and their functional classification was declined considerably when the sample size was decreased. Overall, our results strongly support that there is significant inter-animal variability in the time-course gene expression profiles, which is a confounding factor that must be carefully evaluated to correctly interpret microarray gene expression studies. The consistency of the gene lists and their biological functional classification are also sensitive to sample size with the reproducibility decreasing considerably under small sample size.Corticosteroids (CS) regulate many enzymes at both mRNA and protein levels. This study used microarrays to broadly assess regulation of various genes related to the greater urea cycle and employs pharmacokinetic/pharmacodynamic (PK/PD) modeling to quantitatively analyze and compare the temporal profiles of these genes during acute and chronic exposure to methylprednisolone (MPL). One group of adrenalectomized male Wistar rats received an intravenous bolus dose (50 mg/kg) of MPL, whereas a second group received MPL by a subcutaneous infusion (Alzet osmotic pumps) at a rate of 0.3 mg/kg/hr for seven days. The rats were sacrificed at various time points over 72 hours (acute) or 168 hours (chronic) and livers were harvested. Total RNA was extracted and Affymetrix® gene chips (RG_U34A for acute and RAE 230A for chronic) were used to identify genes regulated by CS. Besides five primary urea cycle enzymes, many other genes related to the urea cycle showed substantial changes in mRNA expression. Some genes that were simply up- or down-regulated after acute MPL showed complex biphasic patterns upon chronic infusion indicating involvement of secondary regulation. For the simplest patterns, indirect response models were used to describe the nuclear steroid-bound receptor mediated increase or decrease in gene transcription (e.g. tyrosine aminotransferase, glucocorticoid receptor). For the biphasic profiles, involvement of a secondary biosignal was assumed (e.g. ornithine decarboxylase, CCAAT/enhancer binding protein) and more complex models were derived. Microarrays were used successfully to explore CS effects on various urea cycle enzyme genes. PD models presented in this report describe testable hypotheses regarding molecular mechanisms and quantitatively characterize the direct or indirect regulation of various genes by CS.Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA) approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fits better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA) is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.Skin irritation is a complex phenomenon, and keratinocytes play an important role in it. We have recently characterized the expression and protective role of adipose differentiation related protein (ADRP) in skin irritation. In particular, ADRP expression is induced to recover functional cell membrane following the cell damage caused by skin irritants. The purpose of this study was to characterize in a human keratinocyte cells line (NCTC 2544) the biochemical events that lead to ADRP expression following SDS treatment, and in particular, to investigate the role of transcription factor SP-1. Analysis of ADRP promoter region revealed the presence of a potential binding site for the transcription factor SP-1 close to the start site. Evaluated by measuring the DNA binding activity, we found that SDS induced a dose and time related SP-1 activation, which was correlated with SDS-induced ADRP mRNA expression. Furthermore, SDS-induced SP-1 activation, ADRP mRNA expression and lipid droplets accumulation could be modulated by mithramycin A, an antibiotic that selectively binds to the GC box preventing SP-1 binding and gene expression. This demonstrated that SDS-induced ADRP expression was mediated in part through the transcription factor SP-1. In addition, SDS-induced SP-1 activation and ADRP expression could be modulated by the calcium chelator BAPTA, indicating a role of calcium in ADRP-induction. Thus, every time an irritant perturbs the membrane barrier, it renders the membrane leaky and allows extracellular calcium to enter the cells, an event that provides the upstream mechanisms initiating the signaling cascade that triggers the activation of SP-1 and culminates in the enhancement of ADRP expression, which helps to restore the normal homeostasis and ultimately repairs the to membrane.Intergenic repeat units of 127-bp (RU-1) and 168-bp (RU-2), as well as a newly-found class of 103-bp (RU-3), represent small mobile sequences in enterobacterial genomes present in multiple intergenic regions. These repeat sequences display similarities to eukaryotic miniature inverted-repeat transposable elements (MITE). The RU mobile elements have not been reported to encode amino acid sequences. An in silico approach was used to scan genomes for location of repeat units. RU sequences are found to have open reading frames, which are present in annotated gene loci whereby the RU amino acid sequence is maintained. Gene loci that display repeat units include those that encode large proteins which are part of super families that carry conserved domains and those that carry predicted motifs such as signal peptide sequences and transmembrane domains. A putative exported protein in Y. pestis and a phylogenetically conserved putative inner membrane protein in Salmonella species represent some of the more interesting constructs. We hypothesize that a major outcome of RU open reading frame fusions is the evolutionary emergence of new proteins.In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy.

Using NIR Spectroscopy for the Prediction of Free Amino Acids during Cheese Ripening

Introduction T his paper is a summary of the paper by Skeie et al. in which the correlation between near infrared (NIR) spectra of grated cheese and the development of selected free amino acids during ripening of rindless Norvegia and Präst cheese was evaluated. Traditionally, cheese ripening has been studied by regularly sampling cheeses at a cheese store and then performing sensory and/or chemical analysis on these samples. However, by this method, the cheeses will be punctured, followed by a modifi cation of the micro climate which again infl uences further ripening, so there is a need for non-destructive prediction methods. Near infrared spectroscopy has previously shown good prediction abilities with regard to fat, moisture and protein in natural and processed cheese, correlating well with chemical measurements. However, quantitative measurements of these components are not good indicators of how cheese ripening will proceed since they are more or less constant throughout the ripening process. On the other hand, changes in peptides and free amino acids provide very good indices of the ripening process. The types and amounts of free amino acids in cheese will infl uence fl avour and describe how far the ripening has proceeded; the composition of free amino acids will vary according to cheese variety and age. The objective of this work was to evaluate the ability of NIR spectra to predict the development of selected free amino acids during ripening of rindless Norvegia and Präst cheese. Rindless Norvegia is a Norwegian Dutch-type cheese produced in rindless blocks, while Präst is a Swedish open texture semi-hard circular cheese with rind. The earliest Norvegia is often sold after 45 days of ripening, while the earliest Präst is sold after 90 days of ripening; both are considered well-ripened after 270 days. The cheeses used for this experiment were part of an extensive study on similarities between cheeses from various dairy plants in Scandinavia producing the same cheese varieties. Cheeses were sampled monthly during part of 1999 from three Norwegian dairies producing Norvegia and three Swedish dairies producing Präst. The cheeses were analysed after 30, 90, 180 and 270 days of ripening.

Theoretical evaluation of prediction error in linear regression with a bivariate response variable containing missing data

ABSTRACT Methods for linear regression with multivariate response variables are well described in statistical literature. In this study we conduct a theoretical evaluation of the expected squared prediction error in bivariate linear regression where one of the response variables contains missing data. We make the assumption of known covariance structure for the error terms. On this basis, we evaluate three well-known estimators: standard ordinary least squares, generalized least squares, and a James–Stein inspired estimator. Theoretical risk functions are worked out for all three estimators to evaluate under which circumstances it is advantageous to take the error covariance structure into account.

Model and estimators for partial least squares regression

Partial least squares (PLS) regression has been a very popular method for prediction. The method can in a natural way be connected to a statistical model, which now has been extended and further developed in terms of an envelope model. Concentrating on the univariate case, several estimators of the regression vector in this model are defined, including the ordinary PLS estimator, the maximum likelihood envelope estimator, and a recently proposed Bayes PLS estimator. These are compared with respect to prediction error by systematic simulations. The simulations indicate that Bayes PLS performs well compared with the other methods.