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Background Circular RNAs are a class of endogenous RNAs with various functions in eukaryotic cells. Worthy of note, circular RNAs play a critical role in cancer. Currently, nothing is known about their role in head and neck squamous cell carcinoma (HNSCC). The identification of circular RNAs in HNSCC might become useful for diagnostic and therapeutic strategies in HNSCC. Results Using samples from 115 HNSCC patients, we find that circPVT1 is over-expressed in tumors compared to matched non-tumoral tissues, with particular enrichment in patients with TP53 mutations. circPVT1 up- and down-regulation determine, respectively, an increase and a reduction of the malignant phenotype in HNSCC cell lines. We show that circPVT1 expression is transcriptionally enhanced by the mut-p53/YAP/TEAD complex. circPVT1 acts as an oncogene modulating the expression of miR-497-5p and genes involved in the control of cell proliferation. Conclusions This study shows the oncogenic role of circPVT1 in HNSCC, extending current knowledge about the role of circular RNAs in cancer. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1368-y) contains supplementary material, which is available to authorized users.

Broader comprehension of gene expression regulatory mechanisms can be gained from a global analysis of how transcription and degradation are coordinated to orchestrate complex cell responses. The role of messenger RNA (mRNA) turnover modulation in gene expression levels has become increasingly recognized. From such perspective, in this review we briefly illustrate how a simple but effective mathematical model of mRNA turnover and some experimental findings, may together shed light on the molecular mechanisms underpinning the major role of mRNA decay rates in shaping the kinetics of gene activation and repression.

Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental resources more efficient. Every time one does an experiment we know that there will be some noise that can disrupt our measurements. Despite the noise certainly is a problem, the inverse problems already involve the inference of missing information, even if the data is entirely reliable. So the addition of a certain limited noise does not fundamentally change the situation but can be used to solve the so-called ill-posed problem, as defined by Hadamard. It can be seen as an extra source of information. Recent studies have shown that complex systems, among others the systems biology, are poorly constrained and ill-conditioned because it is difficult to use experimental data to fully estimate their parameters. For these reasons was born the concept of sloppy models, a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. Furthermore the concept of sloppy models contains also the concept of un-identifiability, because the models are characterized by many parameters that are poorly constrained by experimental data. Then a strategy needs to be designed to infer, analyze, and understand biological systems. The aim of this work is to provide a critical review to the inverse problems in systems biology defining a strategy to determine the minimal set of information needed to overcome the problems arising from dynamic biological models that generally may have many unknown, non-measurable parameters.

Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental resources more efficient. Every time one does an experiment we know that there will be some noise that can disrupt our measurements. Despite the noise certainly is a problem, the inverse problems already involve the inference of missing information, even if the data is entirely reliable. So the addition of a certain limited noise does not fundamentally change the situation but can be used to solve the so-called ill-posed problem, as defined by Hadamard. It can be seen as an extra source of information. Recent studies have shown that complex systems, among others the systems biology, are poorly constrained and ill-conditioned because it is difficult to use experimental data to fully estimate their parameters. For these reasons was born the concept of sloppy models, a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. Furthermore the concept of sloppy models contains also the concept of un-identifiability, because the models are characterized by many parameters that are poorly constrained by experimental data. Then a strategy needs to be designed to infer, analyze, and understand biological systems. The aim of this work is to provide a critical review to the inverse problems in systems biology defining a strategy to determine the minimal set of information needed to overcome the problems arising from dynamic biological models that generally may have many unknown, non-measurable parameters.

Scientific Reports 7: Article number: 44797; published online: 20 March 2017; updated: 16 June 2017. In the HTML version of this Article, Figure 6 was incorrect. The correct Figure 6 appears below as Figure 1. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called “fight-club hubs”, characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called “switch genes”, appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer.

Grapevine (Vitis vinifera) berry development involves a succession of physiological and biochemical changes reflecting the transcriptional modulation of thousands of genes. Although recent studies have investigated the dynamic transcriptome during berry development, most have focused on a single grapevine variety, so there is a lack of comparative data representing different cultivars. Here, we report, to our knowledge, the first genome-wide transcriptional analysis of 120 RNA samples corresponding to 10 Italian grapevine varieties collected at four growth stages. The 10 varieties, representing five red-skinned and five white-skinned berries, were all cultivated in the same experimental vineyard to reduce environmental variability. The comparison of transcriptional changes during berry formation and ripening allowed us to determine the transcriptomic traits common to all varieties, thus defining the core transcriptome of berry development, as well as the transcriptional dynamics underlying differences between red and white berry varieties. A greater variation among the red cultivars than between red and white cultivars at the transcriptome level was revealed, suggesting that anthocyanin accumulation during berry maturation has a direct impact on the transcriptomic regulation of multiple biological processes. The expression of genes related to phenylpropanoid/flavonoid biosynthesis clearly distinguished the behavior of red and white berry genotypes during ripening but also reflected the differential accumulation of anthocyanins in the red berries, indicating some form of cross talk between the activation of stilbene biosynthesis and the accumulation of anthocyanins in ripening berries.

Grapevine (Vitis vinifera) berry development involves a succession of physiological and biochemical changes reflecting the transcriptional modulation of thousands of genes. Although recent studies have investigated the dynamic transcriptome during berry development, most have focused on a single grapevine variety, so there is a lack of comparative data representing different cultivars. Here, we report, to our knowledge, the first genome-wide transcriptional analysis of 120 RNA samples corresponding to 10 Italian grapevine varieties collected at four growth stages. The 10 varieties, representing five red-skinned and five white-skinned berries, were all cultivated in the same experimental vineyard to reduce environmental variability. The comparison of transcriptional changes during berry formation and ripening allowed us to determine the transcriptomic traits common to all varieties, thus defining the core transcriptome of berry development, as well as the transcriptional dynamics underlying differences between red and white berry varieties. A greater variation among the red cultivars than between red and white cultivars at the transcriptome level was revealed, suggesting that anthocyanin accumulation during berry maturation has a direct impact on the transcriptomic regulation of multiple biological processes. The expression of genes related to phenylpropanoid/flavonoid biosynthesis clearly distinguished the behavior of red and white berry genotypes during ripening but also reflected the differential accumulation of anthocyanins in the red berries, indicating some form of cross talk between the activation of stilbene biosynthesis and the accumulation of anthocyanins in ripening berries.

There is evidence that nonalcoholic fatty liver disease (NAFLD) is affected by gut microbiota. Therefore, we investigated its modifications in pediatric NAFLD patients using targeted metagenomics and metabolomics. Stools were collected from 61 consecutive patients diagnosed with nonalcoholic fatty liver (NAFL), nonalcoholic steatohepatitis (NASH), or obesity and 54 healthy controls (CTRLs), matched in a case-control fashion. Operational taxonomic units were pyrosequenced targeting 16S ribosomal RNA and volatile organic compounds determined by solid-phase microextraction gas chromatography-mass spectrometry. The α-diversity was highest in CTRLs, followed by obese, NASH, and NAFL patients; and β-diversity distinguished between patients and CTRLs but not NAFL and NASH. Compared to CTRLs, in NAFLD patients Actinobacteria were significantly increased and Bacteroidetes reduced. There were no significant differences among the NAFL, NASH, and obese groups. Overall NAFLD patients had increased levels of Bradyrhizobium, Anaerococcus, Peptoniphilus, Propionibacterium acnes, Dorea, and Ruminococcus and reduced proportions of Oscillospira and Rikenellaceae compared to CTRLs. After reducing metagenomics and metabolomics data dimensionality, multivariate analyses indicated a decrease of Oscillospira in NAFL and NASH groups and increases of Ruminococcus, Blautia, and Dorea in NASH patients compared to CTRLs. Of the 292 volatile organic compounds, 26 were up-regulated and 2 down-regulated in NAFLD patients. Multivariate analyses found that combination of Oscillospira, Rickenellaceae, Parabacteroides, Bacteroides fragilis, Sutterella, Lachnospiraceae, 4-methyl-2-pentanone, 1-butanol, and 2-butanone could discriminate NAFLD patients from CTRLs. Univariate analyses found significantly lower levels of Oscillospira and higher levels of 1-pentanol and 2-butanone in NAFL patients compared to CTRLs. In NASH, lower levels of Oscillospira were associated with higher abundance of Dorea and Ruminococcus and higher levels of 2-butanone and 4-methyl-2-pentanone compared to CTRLs. Conclusion: An Oscillospira decrease coupled to a 2-butanone up-regulation and increases in Ruminococcus and Dorea were identified as gut microbiota signatures of NAFL onset and NAFL-NASH progression, respectively. (Hepatology 2017;65:451-464)

Investigating the RNA structure contributes greatly to understand RNA roles in cellular processes. Indeed, functional RNAs show specific instrumental sub-structures for their interaction with other molecules. The RNA structure prediction will provide fundamental insights into developing hypothesis connecting function to structure, but it is a challenging and unsolved task yet. We aim at discussing the current status of the widespread RNA folding tools and comparing their performances on RNA families with known structure, in order to estimate how much the predictions are close to the experimental folding. A comprehensive understanding of RNA folding could highlight further roles of long non-coding RNA in the gene expression regulation and in the epigenetic regulatory pathways in physiological and pathological conditions of a living cell.

In this work, we present an extensive analysis of protein contact network topology applied to a wide data set. We extended the concept of degree distribution to graphlets, describing local connectivity patterns. We compared results to those derived from artificial networks of the same size (number of nodes), reproducing the average degree of each protein network. The artificial networks resemble the coiling of immaterial cords and we tried to understand if they could catch the protein structure topology upon the sole constraint of backbone (cord). We found a surprisingly similar pattern for local topological descriptors (graphlets distribution) while real proteins and cords differ at large extent in the global topological invariant average shortest path that presumably catches the systemic nature of protein and the non egligible encumbrance of backbone (residues steric hindrance). We demonstrated average shortest path to link polymer length and physical size of the molecule, and its minimization plays the role of 'target function' of folding process.

Background Grapevine (Vitis vinifera L.) is an economically important crop with a wide geographical distribution, reflecting its ability to grow successfully in a range of climates. However, many vineyards are located in regions with seasonal drought, and these are often predicted to be global climate change hotspots. Climate change affects the entire physiology of grapevine, with strong effects on yield, wine quality and typicity, making it difficult to produce berries of optimal enological quality and consistent stability over the forthcoming decades. Results Here we investigated the reactions of two grapevine cultivars to water stress, the isohydric variety Montepulciano and the anisohydric variety Sangiovese, by examining physiological and molecular perturbations in the leaf and berry. A multidisciplinary approach was used to characterize the distinct stomatal behavior of the two cultivars and its impact on leaf and berry gene expression. Positive associations were found among the photosynthetic, physiological and transcriptional modifications, and candidate genes encoding master regulators of the water stress response were identified using an integrated approach based on the analysis of topological co-expression network properties. In particular, the genome-wide transcriptional study indicated that the isohydric behavior relies upon the following responses: i) faster transcriptome response after stress imposition; ii) faster abscisic acid-related gene modulation; iii) more rapid expression of heat shock protein (HSP) genes and iv) reversion of gene-expression profile at rewatering. Conversely, that reactive oxygen species (ROS)-scavenging enzymes, molecular chaperones and abiotic stress-related genes were induced earlier and more strongly in the anisohydric cultivar. Conclusions Overall, the present work found original evidence of a molecular basis for the proposed classification between isohydric and anisohydric grapevine genotypes. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3136-x) contains supplementary material, which is available to authorized users.

Direct-acting antiviral drugs (DAA) regimen improve the SVR rate. However, adverse effects often lead to therapy interruption. This underlines the importance to find some predictive parameters of response in order to consider the possibility of a shorter time of antiviral treatment in the appearance of adverse effects without affecting the success of the therapy.We aimed to examine the HCVAg kinetics in the early phase of treatment and its predictive value of SVR in patients undergoing TPV/Peg-IFN/RBV treatment.Twenty-three patients infected by HCV genotype 1 (1a n=11; 1b n=12) were included in this prospective study.At baseline the median Log of HCVAg concentration in RVR and EVR patients were 3.15 fmol/L and 3.45 fmol/L, respectively with no significant differences. The baseline median HCV-RNA to HCVAg ratio was 233.77, this ratio was significantly lower when measured on day 1 (27.52) and on day 6 (24.84) (p0.001). The two-tailed Fisher's exact test indicated that the SVR response is statistically significantly different in patients with detected HCVAg at week1 compared to patients with no detectable HCVAg (p=0.05). The sensitivity, specificity, and negative and positive predictive values (NPV, PPV) were 53.8, 87.5, 53.8 and 87.5%, respectively. The area under the ROC curve was 0.71 at day T6, the best cut-off of 3 fmol/L when evaluated with the HCVAg plasma concentration at day T6.Undetectable HCVAg in the early phase of TPV/Peg-IFN/RBV treatment could represent an important parameter for predicting SVR.

It is becoming increasingly clear that short and long noncoding RNAs critically participate in the regulation of cell growth, differentiation, and (mis)function. However, while the functional characterization of short non-coding RNAs has been reaching maturity, there is still a paucity of well characterized long noncoding RNAs, even though large studies in recent years are rapidly increasing the number of annotated ones. The long noncoding RNA PVT1 is encoded by a gene that has been long known since it resides in the well-known cancer risk region 8q24. However, a couple of accidental concurrent conditions have slowed down the study of this gene, that is, a preconception on the primacy of the protein-coding over noncoding RNAs and the prevalent interest in its neighbor MYC oncogene. Recent studies have brought PVT1 under the spotlight suggesting interesting models of functioning, such as competing endogenous RNA activity and regulation of protein stability of important oncogenes, primarily of the MYC oncogene. Despite some advancements in modelling the PVT1 role in cancer, there are many questions that remain unanswered concerning the precise molecular mechanisms underlying its functioning.

Background Detection of RNA structure similarities is still one of the major computational problems in the discovery of RNA functions. A case in point is the study of the new appreciated long non-coding RNAs (lncRNAs), emerging as new players involved in many cellular processes and molecular interactions. Among several mechanisms of action, some lncRNAs show specific substructures that are likely to be instrumental for their functioning. For instance, it has been reported in literature that some lncRNAs have a guiding or scaffolding role by binding chromatin-modifying protein complexes. Thus, a functionally characterized lncRNA (reference) can be used to infer the function of others that are functionally unknown (target), based on shared structural motifs. Methods In our previous work we presented a tool, MONSTER v1.0, able to identify structural motifs shared between two full-length RNAs. Our procedure is mainly composed of two ad-hoc developed algorithms: nbRSSP_extractor for characterizing the folding of an RNA sequence by means of a sequence-structure descriptor (i.e., an array of non-overlapping substructures located on the RNA sequence and coded by dot-bracket notation); and SSD_finder, to enable an effective search engine for groups of matches (i.e., chains) common to the reference and target RNA based on a dynamic programming approach with a new score function. Here, we present an updated version of the previous one (MONSTER v1.1) accounting for the peculiar feature of lncRNAs that are not expected to have a unique fold, but appear to fluctuate among a large number of equally-stable folds. In particular, we improved our SSD_finder algorithm in order to take into account all the alternative equally-stable structures. Results We present an application of MONSTER v1.1 on lincRNAs, which are a specific class of lncRNAs located in genomic regions which do not overlap protein-coding genes. In particular, we provide reliable predictions of the shared chains between HOTAIR, ANRIL and COLDAIR. The latter are lincRNAs which interact with the same protein complexes of the Polycomb group and hence they are expected to share structural motifs. Software availability: the software package is provided as additional file 1 ("archive_updated.zip").

Background: Direct-acting antiviral drugs (DAA) regimen improve the SVR rate. However, adverse effects often lead to therapy interruption. This underlines the importance to find some predictive parameters of response in order to consider the possibility of a shorter time of antiviral treatment in the appearance of adverse effects without affecting the success of the therapy. Objectives: We aimed to examine the HCVAg kinetics in the early phase of treatment and its predictive value of SVR in patients undergoing TPV/Peg-IFN/RBV treatment. Study design: Twenty-three patients infected by HCV genotype 1 (1a n = 11; 1b n = 12) were included in this prospective study. Results: At baseline the median Log of HCVAg concentration in RVR and EVR patients were 3.15 fmol/L and 3.45 fmol/L, respectively with no significant differences. The baseline median HCV-RNA to HCVAg ratio was 233.77, this ratio was significantly lower when measured on day 1 (27.52) and on day 6 (24.84) (p < 0.001). The two-tailed Fisher's exact test indicated that the SVR response is statistically significantly different in patients with detected HCVAg at week1 compared to patients with no detectable HCVAg (p = 0.05). The sensitivity, specificity, and negative and positive predictive values (NPV, PPV) were 53.8, 87.5, 53.8 and 87.5%, respectively. The area under the ROC curve was 0.71 at day T6, the best cut-off of 3 fmol/L when evaluated with the HCVAg plasma concentration at dayT6. Conclusion: Undetectable HCVAg in the early phase of TPV/Peg-IFN/RBV treatment could represent an important parameter for predicting SVR.

Broader comprehension of gene expression regulatory mechanisms can be gained from a global analysis of how transcription and degradation are coordinated to orchestrate complex cell responses. The role of messenger RNA (mRNA) turnover modulation in gene expression levels has become increasingly recognized. From such perspective, in this review we briefly illustrate how a simple but effective mathematical model of mRNA turnover and some experimental findings, may together shed light on the molecular mechanisms underpinning the major role of mRNA decay rates in shaping the kinetics of gene activation and repression.

RNA structure prediction and structural motifs analysis are challenging tasks in the investigation of RNA function. We propose a novel procedure to detect structural motifs shared between two RNAs (a reference and a target). In particular, we developed two core modules: (i) nbRSSP_extractor, to assign a unique structure to the reference RNA encoded by a set of non-branching structures; (ii) SSD_finder, to detect structural motifs that the target RNA shares with the reference, by means of a new score function that rewards the relative distance of the target non-branching structures compared to the reference ones. We integrated these algorithms with already existing software to reach a coherent pipeline able to perform the following two main tasks: prediction of RNA structures (integration of RNALfold and nbRSSP_extractor) and search for chains of matches (integration of Structator and SSD_finder).

Background Non-coding RNAs (ncRNAs) are emerging as key regulators of many cellular processes in both physiological and pathological states. Moreover, the constant discovery of new non-coding RNA species suggests that the study of their complex functions is still in its very early stages. This variegated class of RNA species encompasses the well-known microRNAs (miRNAs) and the most recently acknowledged long non-coding RNAs (lncRNAs). Interestingly, in the last couple of years, a few studies have shown that some lncRNAs can act as miRNA sponges, i.e. as competing endogenous RNAs (ceRNAs), able to reduce the amount of miRNAs available to target messenger RNAs (mRNAs). Results We propose a computational approach to explore the ability of lncRNAs to act as ceRNAs by protecting mRNAs from miRNA repression. A seed match analysis was performed to validate the underlying regression model. We built normal and cancer networks of miRNA-mediated sponge interactions (MMI-networks) using breast cancer expression data provided by The Cancer Genome Atlas. Conclusions Our study highlights a marked rewiring in the ceRNA program between normal and pathological breast tissue, documented by its “on/off” switch from normal to cancer, and vice-versa. This mutually exclusive activation confers an interesting character to ceRNAs as potential oncosuppressive, or oncogenic, protagonists in cancer. At the heart of this phenomenon is the lncRNA PVT1, as illustrated by both the width of its antagonist mRNAs in normal-MMI-network, and the relevance of the latter in breast cancer. Interestingly, PVT1 revealed a net binding preference towards the mir-200 family as the bone of contention with its rival mRNAs.

The identification of modules in protein structures has major relevance in structural biology, with consequences in protein stability and functional classification, adding new perspectives in drug design. In this work, we present the comparison between a topological (spectral clustering) and a geometrical (k-means) approach to module identification, in the frame of a multiscale analysis of the protein architecture principles. The global consistency of an adjacency matrix based technique (spectral clustering) and a method based on full rank geometrical information (k-means) give a proof-of-concept of the relevance of protein contact networks in structure determination. The peculiar "small-world" character of protein contact graphs is established as well, pointing to average shortest path as a mesoscopic crucial variable to maximize the efficiency of within-molecule signal transmission. The specific nature of protein architecture indicates topological approach as the most proper one to highlight protein functional domains, and two new representations linking sequence and topological role of aminoacids are demonstrated to be of use for protein structural analysis. Here we present a case study regarding azurin, a small copper protein implied in the Pseudomonas aeruginosa respiratory chain. Its pocket molecular shape and its electron transfer function have challenged the method, highlighting its potentiality to catch jointly the structure and function features of protein structures through their decomposition into modules.

The biological role of proteins has been analyzed from different perspectives, initially by considering proteins as isolated biological entities, then as cooperating entities that perform their function by interacting with other molecules. There are other dimensions that are important for the complete understanding of the biological processes: time and location. However a protein is rarely annotated with temporal and spatial information. Experimental Protein-Proteins Interaction (PPI) data are static; furthermore they generally do not include transient interactions which are a considerable fraction of the interactome of many organisms. One way to incorporate temporal and condition information is to use other sources of information, such as gene expression data and 3D structural data. Here we review work done to understand the insight that can be gained by enriching PPI data with gene expression and 3D structural data. In particular, we address the following questions: Can the dynamics of a single protein or of an interaction be accurately derived from these data? Can the assembly-disassembly of protein complexes be traced over time? What type of topological changes occur in a PPI network architecture over time?

In this article we present evidence for a relationship between chromosome gene loci and the topological properties of the protein-protein interaction network corresponding to the set of genes under consideration. Specifically, for each chromosome of the Saccharomyces cerevisiae genome, the distribution of the intra-chromosome inter-gene distances was analyzed and a positive correlation with the distance among the corresponding proteins of the protein-protein interaction network was found. In order to study this relationship we used concepts based on non-parametric statistics and information theory. We provide statistical evidence that if two genes are closely located, then it is likely that their protein products are closely located in the protein-protein interaction network, or in other words, that they are involved in the same biological process.

Topic: Psychological and stressful social situations, as well as factors of an unhealthy lifestyle (such as insufficient exercise, weight increase and/or social isolation) are potential causes of MUS (Medically Unexplained Symptoms) and obesity, usually overlooked by general practitioners. Obesity is often underestimated using BMI, since it does not reflect the real loss of fat mass after nutritional strategies. Scope: We analyzed the changes in fat mass (FM) and fat-free mass (FFM) in the presence of decreasing BMI, using a novel advanced bio-impedance device, BIA-ACC (Bioelectric Impedance Analyzer for Analisi Composizione Corporea) that measures numerous parameters of body composition. Methods: 109 patients were enrolled at the center for primary care for a routine check-up, all apparently free of disease but with problems of excess weight and MUS to varying degrees. The evaluation of the parameters BIA-ACC was performed at the first visit T0, and at follow-up T1, after about 2 months of a standard nutritional strategy. Results: BMI decreased in all patients. FFM, particularly skeletal muscle, was the 1st principal component (PCA1: 58%) that determines the well-being of the patients and a decrease of MUS. The 2nd component (PCA2: 22%) is the FM. We found 3 different patterns of patient response to BMI reduction: 75.23% showed loss of FM and minimally FFM; 17.43% showed loss of FM with preservation or increase FFM; 7.34% showed loss of FFM alone. Conclusions: Body composition analysis is a valuable non-invasive tool to monitor patients in the early stages of immune-metabolic dysregulation when clinical symptoms are not yet evident. Our results demonstrate the importance of the maintenance of FFM rather than the loss of FM alone during weight loss therapy. Preservation of skeletal muscle is essential to facilitate the stabilization of loss of only fat and thus to eliminate the MUS correlated to chronic stress.

Objectives Identifying the predictive factors of Sustained Virological Response (SVR) represents an important challenge in new interferon-based DAA therapies. Here, we analyzed the kinetics of antiviral response associated with a triple drug regimen, and the association between negative residual viral load at different time points during treatment. Methods Twenty-three HCV genotype 1 (GT 1a n = 11; GT1b n = 12) infected patients were included in the study. Linear Discriminant Analysis (LDA) was used to establish possible association between HCV RNA values at days 1 and 4 from start of therapy and SVR. Principal compo- nent analysis (PCA) was applied to analyze the correlation between HCV RNA slope and SVR. A ultrasensitive (US) method was established to measure the residual HCV viral load in those samples which resulted "detected

The scope of this review is, by briefly discussing some applications in the rapidly emerging field of protein contact network, to sketch an at least initial answer to the quest for a new "structural formula" language for proteins. This quest will be pursued by presenting side-by-side the different complex network invariants developed by graph theory and their protein counterparts.

Allostery is a very important feature of proteins; we propose a mesoscopic approach to allosteric mechanisms elucidation, based on protein contact matrices. The application of graph theory methods to the characterization of the allosteric process and, more broadly, to obtain the conformational changes upon binding, reveals key features of the protein function. The proposed method highlights the leading role played by topological over geometrical changes in allosteric transitions. Topological invariants were able to discriminate between true allosteric motions and generic protein motions upon binding.

The analysis of a large database of protein structures by means of topological and shape indexes inspired by complex network and fractal analysis shed light on some organizational principles of proteins. Proteins appear much more similar to "fractal" sponges than to closely packed spheres, casting doubts on the tenability of the hydrophobic core concept. Principal component analysis highlighted three main order parameters shaping the protein universe: (1) "size", with the consequent generation of progressively less dense and more empty structures at an increasing number of residues, (2) "microscopic structuring", linked to the existence of a spectrum going from the prevalence of heterologous (different hydrophobicity) to the prevalence of homologous (similar hydrophobicity) contacts, and (3) "fractal shape", an organizing protein data set along a continuum going from approximately linear to very intermingled structures. Perhaps the time has come for seriously taking into consideration the real relevance of time-honored principles like the hydrophobic core and hydrophobic effect.

The transcriptome in a cell is finely regulated by a large number of molecular mechanisms able to control the balance between mRNA production and degradation. Recent experimental findings have evidenced that fine and specific regulation of degradation is needed for proper orchestration of a global cell response to environmental conditions. We developed a computational technique based on stochastic modeling, to infer condition-specific individual mRNA half-lives directly from gene expression time-courses. Predictions from our method were validated by experimentally measured mRNA decay rates during the intraerythrocytic developmental cycle of Plasmodium falciparum. We then applied our methodology to publicly available data on the reproductive and metabolic cycle of budding yeast. Strikingly, our analysis revealed, in all cases, the presence of periodic changes in decay rates of sequentially induced genes and co-ordination strategies between transcription and degradation, thus suggesting a general principle for the proper coordination of transcription and degradation machinery in response to internal and/or external stimuli., Author Summary The amount of a given transcript in a cell is determined by a fine tuned balance of production and degradation in a complex regulatory network. Regulation of transcription controls when transcription occurs and how much mRNA is created, whereas regulation of degradation controls the rate at which messengers are destroyed. The latter mechanism has recently gained attention due to the increasing evidence of its key role in the overall co-ordination of gene expression. A long lifetime of mRNA enables a cell to produce more proteins from that mRNA. By contrast, a short lifetime rapidly alters protein levels in response to changing needs. Measuring mRNA stability is a complex and expensive experiment and, given the condition-specific response of the degradation pathway, it would be desirable to take advantage of the large variety of expression experiments stored in public databases. To this end, we developed a stochastic model to infer each specific mRNA lifetime from gene expression data. Predictions were validated using malaria data. We then applied our methodology to the reproductive and metabolic cycle of budding yeast and found, in all cases, the presence of a general principle for the proper coordination of transcription and degradation machinery.

A fully quantitative shape index relying upon the asymmetry of mass distribution of protein molecules along the three space dimensions is proposed. Multidimensional statistical analysis, based on principal component extraction and subsequent linear discriminant analysis, showed the presence of three major ‘attractor forms’ roughly correspondent to rod-like, discoidal and spherical shapes. This classification of protein shapes was in turn demonstrated to be strictly connected with topological features of proteins, as emerging from complex network invariants of their contact maps.

Background When to initiate antiretroviral therapy in HIV infected patients is a diffcult clinical decision. Actually, it is still a matter of discussion whether early highly active antiretroviral therapy (HAART) during primary HIV infection may influence the dynamics of the viral rebound, in case of therapy interruption, and overall the main disease course. Methods In this article we use a computational model and clinical data to identify the role of HAART timing on the residual capability to control HIV rebound after treatment suspension. Analyses of clinical data from three groups of patients initiating HAART respectively before seroconversion (very early), during the acute phase (early) and in the chronic phase (late), evidence differences arising from the very early events of the viral infection. Results The computational model allows a fine grain assessment of the impact of HAART timing on the disease outcome, from acute to chronic HIV-1 infection. Both patients' data and computer simulations reveal that HAART timing may indeed affect the HIV control capability after treatment discontinuation. In particular, we find a median time to viral rebound that is significantly longer in very early than in late patients. Conclusions A timing threshold is identified, corresponding to approximately three weeks post-infection, after which the capability to control HIV replication is lost. Conversely, HAART initiation occurring within three weeks from the infection could allow to preserve a significant control capability. This time could be related to the global triggering of uncontrolled immune activation, affecting residual immune competence preservation and HIV reservoir establishment.

Background The optimal stage for initiating antiretroviral therapies in HIV-1 bearing patients is still a matter of debate. Methods We present computer simulations of HIV-1 infection aimed at identifying the pro et contra of immediate as compared to deferred Highly Active Antiretroviral Therapy (HAART). Results Our simulations highlight that a prompt specific CD8+ cytotoxic T lymphocytes response is detected when therapy is delayed. Compared to very early initiation of HAART, in deferred treated patients CD8+ T cells manage to mediate the decline of viremia in a shorter time and, at interruption of therapy, the virus experiences a stronger immune pressure. We also observe, however, that the immunological effects of the therapy fade with time in both therapeutic regimens. Thus, within one year from discontinuation, viral burden recovers to the value at which it would level off in the absence of therapy. In summary, simulations show that immediate therapy does not prolong the disease-free period and does not confer a survival benefit when compared to treatment started during the chronic infection phase. Conclusion Our conclusion is that, since there is no therapy to date that guarantees life-long protection, deferral of therapy should be preferred in order to minimize the risk of adverse effects, the occurrence of drug resistances and the costs of treatment.

International audience; IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), is the reference in immunogenetics and immunoinformatics. IMGT standardizes and manages the complex immunogenetic data that include the immunoglobulins (IG) or antibodies, the T cell receptors (TR), the major histocompatibility complex (MHC) and the related proteins of the immune system (RPI), which belong to the immunoglobulin superfamily (IgSF) and the MHC superfamily (MhcSF). The accuracy and consistency of IMGT data and the coherence between the different IMGT components (databases, tools and Web resources) are based on IMGT-ONTOLOGY, the first ontology for immunogenetics and immunoinformatics. IMGT-ONTOLOGY manages the immunogenetics knowledge through diverse facets relying on seven axioms, 'IDENTIFICATION', 'DESCRIPTION', 'CLASSIFICATION', 'NUMEROTATION', 'LOCALIZATION', 'ORIENTATION' and 'OBTENTION', that postulate that objects, processes and relations have to be identified, described, classified, numerotated, localized, orientated, and that the way they are obtained has to be determined. These axioms constitute the Formal IMGT-ONTOLOGY, also designated as IMGT-Kaleidoscope. These axioms have been essential for the conceptualization of the molecular immunogenetics knowledge and for the creation of IMGT. Indeed all the components of the IMGT integrated system have been developed, based on standardized concepts and relations, thus allowing IMGT to bridge biological and computational spheres in bioinformatics. The same axioms can be used to generate concepts for multi-scale level approaches at the molecule, cell, tissue, organ, organism or population level, emphasizing the generalization of the application domain. In that way the Formal IMGT-ONTOLOGY represents a paradigm for the elaboration of ontologies in system biology.

Background The efficiency of lymph nodes depends on tissue structure and organization, which allow the coordination of lymphocyte traffic. Despite their essential role, our understanding of lymph node specific mechanisms is still incomplete and currently a topic of intense research. Results In this paper, we present a hybrid discrete/continuous model of the lymph node, accounting for differences in cell velocity and chemotactic response, influenced by the spatial compartmentalization of the lymph node and the regulation of cells migration, encounter, and antigen presentation during the inflammation process. Conclusion Our model reproduces the correct timing of an immune response, including the observed time delay between duplication of T helper cells and duplication of B cells in response to antigen exposure. Furthermore, we investigate the consequences of the absence of dendritic cells at different times during infection, and the dependence of system dynamics on the regulation of lymphocyte exit from lymph nodes. In both cases, the model predicts the emergence of an impaired immune response, i.e., the response is significantly reduced in magnitude. Dendritic cell removal is also shown to delay the response time with respect to normal conditions.

We present an immune system simulator based on a hybrid discrete/continuous approach. In particular, simulated lymphocytes, antigens and immunocomplexes are treated as stochastic discrete entities whereas interleukins, chemokines and in general small signalling molecules are described as continuous variables ruled by differential equations. The version of the model we present here is customized to reproduce the immune response to HIV and the effects of an anti-retroviral therapy. Our goal is to suggest new therapeutic strategies that can be tested in a computer.

Isotope effects (IEs) are powerful tool to probe directly the dependence of many physical properties on the lattice dynamics. In this paper we invenstigate the onset of anomalous IEs in the spinless Holstein model by employing the dynamical mean field theory. We show that the isotope coefficients of the electron effective mass and of the dressed phonon frequency are sizeable also far away from the strong coupling polaronic crossover and mark the importance of nonadiabatic lattice fluctuations in the weak to moderate coupling region. We characterize the polaronic regime by the appearence of huge IEs. We draw a nonadiabatic phase diagram in which we identify a novel crossover, not related to polaronic features, where the IEs attain their largest anomalies., 5 pages, 4 figures

In C 60 compounds the frequencies of the phonon involved in the superconductive processes (intra-molecular modes with ω ph up to 2300 K) are comparable with the typical electronic scale ( E F =2900 K) and thus the two dynamics cannot be treated separately (breakdown of the adiabatic hypothesis). This implies a generalization of the standard theory to include nonadiabatic effects. The strong electronic correlation in the fullerenes causes the contribution of the nonadiabatic processes to be positive with consequent increase of the effective electron–phonon (el–ph) pairing λ and of T c . We show that the inclusion of nonadiabatic terms in the el–ph interaction is a key element for the high values of T c in fullerenes. In particular T c as high as 100 K are shown to be compatible with moderate values of λ ≲1. This implies that it should be possible to increase the value of λ , and so T c , and still have a stable system.

High-$T_c$ superconductors have Fermi energies $E_F$ much smaller than conventional metals comparable to phonon frequencies. In such a situation nonadiabatic effects are important. A generalization of Eliashberg theory in the nonadiabatic regime has previously been shown to reproduce some anomalous features of the high-$T_c$ superconductors as for istance the enhancement of $T_c$ or the isotopic effects on $T_c$ and $m^*$. In this contribution we address the issue of the symmetry of the gap in the context of nonadiabatic superconductivity. We show that vertex corrections have a momentum structure which favours d-wave superconductivity when forward scattering is predominant. An additional increase of $T_c$ is also found., Comment: 6 pages, 3 eps figure, ijmpb-macros, proceeding of SATT10, to appear on Int. Journ. Mod. Phys. B

JARID1B/KDM5B histone demethylase's mRNA is markedly overexpressed in breast cancer tissues and cell lines and the protein has been shown to have a prominent role in cancer cell proliferation and DNA repair. However, the mechanism of its post-transcriptional regulation in cancer cells remains elusive. We performed a computational analysis of transcriptomic data from a set of 103 breast cancer patients, which, along with JARID1B upregulation, showed a strong downregulation of 2 microRNAs (miRNAs), mir-381 and mir-486, potentially targeting its mRNA. We showed that both miRNAs can target JARID1B 3'UTR and reduce luciferase's activity in a complementarity-driven repression assay. Moreover, MCF7 breast cancer cells overexpressing JARID1B showed a strong protein reduction when transfected with mir-486. This protein's decrease is accompanied by accumulation of DNA damage, enhanced radiosensitivity and increase of BRCA1 mRNA, 3 features previously correlated with JARID1B silencing. These results enlighten an important role of a miRNA's circuit in regulating JARID1B's activity and suggest new perspectives for epigenetic therapies. Funding information: Sapienza Research Grant. Grant Number: RM11715C53A3F678