Failure to achieve lupus low disease activity state (LLDAS) six months after diagnosis is associated with early damage accrual in Caucasian patients with systemic lupus erythematosus

Background: The aim was to assess the attainability and outcome of the lupus low disease activity state (LLDAS) in the early stages of systemic lupus erythematosus (SLE). Methods: LLDAS prevalence was evaluated at 6 (T1) and 18 (T2) months after diagnosis and treatment initiation (T0) in a monocentric cohort of 107 (median disease duration 9.7 months) prospectively followed Caucasian patients with SLE. Reasons for failure to achieve LLDAS were also investigated. Multivariate models were built to identify factors associated with lack of LLDAS achievement and to investigate the relationship between LLDAS and Systemic Lupus International Collaboration Clinics (SLICC)/Damage Index (SDI) accrual. Results: There were 47 (43.9%) patients in LLDAS at T1 and 48 (44.9%) at T2. The most frequent unmet LLDAS criterion was prednisolone dose >7.5 mg/day (83% of patients with no LLDAS at T1). Disease manifestations with the lowest remission rate during follow up were increased anti-double-stranded DNA (persistently present in 85.7% and 67.5% of cases at T1 and T2, respectively), low serum complement fractions (73.2% and 66.3%) and renal abnormalities (46.4% and 28.6%). Renal involvement at T0 was significantly associated with failure to achieve LLDAS both at T1 (OR 7.8, 95% CI 1.4-43.4; p = 0.019) and T2 (OR 3.9, 95% CI 1.4-10.6; p = 0.008). Presence of any organ damage (SDI â ¥1) at T2 was significantly associated with lack of LLDAS at T1 (OR 5.0, 95% CI 1.5-16.6; p = 0.009) and older age at diagnosis (OR 1.05 per year, 95% CI 1.01-1.09; p = 0.020). Conclusion: LLDAS is a promising treatment target in the early stages of SLE, being attainable and negatively associated with damage accrual, but it fit poorly to patients with renal involvement

MMsPred: a bioactivity and toxicology predictive system

In the last decade, the development and use of new methods in combinatorial chemistry and high-throughput screening has dramatically increased the number of known biologically active compounds. Paradoxically, the number of drugs reaching the market has not followed the same trend, often because many of the candidate drugs present poor qualities in absorption, distribution, metabolism, excretion, and toxicological properties (ADME-Tox). The ability to recognize and discard bad candidates early in the drug discovery steps would save lost investments in time and money. Machine learning techniques could provide solutions to this problem.
The goal of my research is to develop classifiers that accurately discriminate between active and inactive molecules for a specific target. To this end, I am comparing the effectiveness of the application of different machine learning techniques to this problem.	As a source of data we have selected a set of PubChem's public BioAssays1. In addition, with the objective of realizing a real-time query service with our predictors, we aim to keep the features describing the chemical compounds relatively simple.
At the end of this process, we should better understand how to build statistical models that are able to recognize molecules active in a specific bioassay, including how to select the most appropriate classification technique, and how to describe compounds in such a way that is not excessively resource-consuming to generate, yet contains sufficient information for the classification. We see immediate applications of such technology to recognize compounds with high-risk of toxicity, and also to suggest likely metabolic pathways that would process it

Thermoelasticity of Fe2+-bearing bridgmanite

We present LDA+U calculations of high temperature elastic properties of bridgmanite with composition (Mg$_{(1-x)}$Fe$_{x}^{2+}$)SiO$_3$ for $0\le{x}\le0.125$. Results of elastic moduli and acoustic velocities for the Mg-end member (x=0) agree very well with the latest high pressure and high temperature experimental measurements. In the iron-bearing system, we focus particularly on the change in thermoelastic parameters across the state change that occurs in ferrous iron above $\sim$30 GPa, often attributed to a high-spin (HS) to intermediate spin (IS) crossover but explained by first principles calculations as a lateral displacement of substitutional iron in the perovskite cage. We show that the measured effect of this change on the equation of state of this system can be explained by the lateral displacement of substitutional iron, not by the HS to IS crossover. The calculated elastic properties of (Mg$_{0.875}$Fe$_{0.125}^{2+}$)SiO$_3$ along an adiabatic mantle geotherm, somewhat overestimate longitudinal velocities but produce densities and shear velocities quite consistent with Preliminary Reference Earth Model data throughout most of the lower mantle.Comment: Accepted for Geophysical Research Letters (DOI: 10.1002/2014GL062888

A generalizable definition of chemical similarity for read-across

Background: Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results: This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions: Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain.Pubblicat

A Genomic map of positive selection in Sardinia

The recent production of population-scale genomic data offers an unprecedented opportunity to understand how natural selection has shaped human phenotypic variation within populations. To identify signatures of recent positive selection in Sardinia, we used 23 million single nucleotide polymorphisms from low-coverage whole genomes of 3,514 Sardinians along with data from the 1000 Genomes project. Using single-population (iHS, nSL) and cross-population (Fst, PBS, XP-EHH) based statistics, we found many genetic regions showing evidence of positive selection. We found that selection statistics computed for outlier variants cannot be explained by neutral forces alone. By intersecting genome-wide association study data for hundreds of traits measured in Sardinians with publicy available functional genomic databases, we found that autoimmunity-related genes are enriched for these putatively adaptive variants.Taken together, these results illustrate the importance of characterizing the phenotypic variation within a population, and especially the utility of whole-genome-sequence data, when proposing and interpreting genetic signatures of positive selection

EEG functional network topology is associated with disability in patients with amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is one of the most severe neurodegenerative diseases, which is known to affect upper and lower motor neurons. In contrast to the classical tenet that ALS represents the outcome of extensive and progressive impairment of a fixed set of motor connections, recent neuroimaging findings suggest that the disease spreads along vast non-motor connections. Here, we hypothesised that functional network topology is perturbed in ALS, and that this reorganization is associated with disability. We tested this hypothesis in 21 patients affected by ALS at several stages of impairment using resting-state electroencephalography (EEG) and compared the results to 16 age-matched healthy controls. We estimated functional connectivity using the Phase Lag Index (PLI), and characterized the network topology using the minimum spanning tree (MST). We found a significant difference between groups in terms of MST dissimilarity and MST leaf fraction in the beta band. Moreover, some MST parameters (leaf, hierarchy and kappa) significantly correlated with disability. These findings suggest that the topology of resting-state functional networks in ALS is affected by the disease in relation to disability. EEG network analysis may be of help in monitoring and evaluating the clinical status of ALS patients

A Genomic map of positive selection in Sardinia

The recent production of population-scale genomic data offers an unprecedented opportunity to understand how natural selection has shaped human phenotypic variation within populations. To identify signatures of recent positive selection in Sardinia, we used 23 million single nucleotide polymorphisms from low-coverage whole genomes of 3,514 Sardinians along with data from the 1000 Genomes project. Using single-population (iHS, nSL) and cross-population (Fst, PBS, XP-EHH) based statistics, we found many genetic regions showing evidence of positive selection. We found that selection statistics computed for outlier variants cannot be explained by neutral forces alone. By intersecting genome-wide association study data for hundreds of traits measured in Sardinians with publicy available functional genomic databases, we found that autoimmunity-related genes are enriched for these putatively adaptive variants. Taken together, these results illustrate the importance of characterizing the phenotypic variation within a population, and especially the utility of whole-genome-sequence data, when proposing and interpreting genetic signatures of positive selection

Splice-mediated Variants of Proteins (SpliVaP) – data and characterization of changes in signatures among protein isoforms due to alternative splicing

<p>Abstract</p> <p>Background</p> <p>It is often the case that mammalian genes are alternatively spliced; the resulting alternate transcripts often encode protein isoforms that differ in amino acid sequences. Changes among the protein isoforms can alter the cellular properties of proteins. The effect can range from a subtle modulation to a complete loss of function.</p> <p>Results</p> <p>(i) We examined human splice-mediated protein isoforms (as extracted from a manually curated data set, and from a computationally predicted data set) for differences in the annotation for protein signatures (Pfam domains and PRINTS fingerprints) and we characterized the differences & their effects on protein functionalities. An important question addressed relates to the extent of protein isoforms that may lack any known function in the cell. (ii) We present a database that reports differences in protein signatures among human splice-mediated protein isoform sequences.</p> <p>Conclusion</p> <p>(i) Characterization: The work points to distinct sets of alternatively spliced genes with varying degrees of annotation for the splice-mediated protein isoforms. Protein molecular functions seen to be often affected are those that relate to: binding, catalytic, transcription regulation, structural molecule, transporter, motor, and antioxidant; and the processes that are often affected are nucleic acid binding, signal transduction, and protein-protein interactions. Signatures are often included/excluded and truncated in length among protein isoforms; truncation is seen as the predominant type of change. Analysis points to the following novel aspects: (a) Analysis using data from the manually curated Vega indicates that one in 8.9 genes can lead to a protein isoform of no "known" function; and one in 18 expressed protein isoforms can be such an "orphan" isoform; the corresponding numbers as seen with computationally predicted ASD data set are: one in 4.9 genes and one in 9.8 isoforms. (b) When swapping of signatures occurs, it is often between those of same functional classifications. (c) Pfam domains can occur in varying lengths, and PRINTS fingerprints can occur with varying number of constituent motifs among isoforms – since such a variation is seen in large number of genes, it could be a general mechanism to modulate protein function. (ii) Data: The reported resource (at <url>http://www.bioinformatica.crs4.org/tools/dbs/splivap/</url>) provides the community ability to access data on splice-mediated protein isoforms (with value-added annotation such as association with diseases) through changes in protein signatures.</p