Repetition- and Linearity-Aware Rank/Select Dictionaries

We revisit the fundamental problem of compressing an integer dictionary that supports efficient rank and select operations by exploiting two kinds of regularities arising in real data: repetitiveness and approximate linearity. Our first contribution is a Lempel-Ziv parsing properly enriched to also capture approximate linearity in the data and still be compressed to the kth order entropy. Our second contribution is a variant of the block tree structure whose space complexity takes advantage of both repetitiveness and approximate linearity, and results highly competitive in time too. Our third and final contribution is an implementation and experimentation of this last data structure, which achieves new space-time trade-offs compared to known data structures that exploit only one of the two regularities

Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment

<p>Abstract</p> <p>Background</p> <p>Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and <it>universality </it>is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rather than a formula quantifying the similarity of two strings. Three approximations of USM are available, namely UCD (Universal Compression Dissimilarity), NCD (Normalized Compression Dissimilarity) and CD (Compression Dissimilarity). Their applicability and robustness is tested on various data sets yielding a first massive quantitative estimate that the USM methodology and its approximations are of value. Despite the rich theory developed around USM, its experimental assessment has limitations: only a few data compressors have been tested in conjunction with USM and mostly at a qualitative level, no comparison among UCD, NCD and CD is available and no comparison of USM with existing methods, both based on alignments and not, seems to be available.</p> <p>Results</p> <p>We experimentally test the USM methodology by using 25 compressors, all three of its known approximations and six data sets of relevance to Molecular Biology. This offers the first systematic and quantitative experimental assessment of this methodology, that naturally complements the many theoretical and the preliminary experimental results available. Moreover, we compare the USM methodology both with methods based on alignments and not. We may group our experiments into two sets. The first one, performed via ROC (Receiver Operating Curve) analysis, aims at assessing the <it>intrinsic </it>ability of the methodology to discriminate and classify biological sequences and structures. A second set of experiments aims at assessing how well two commonly available classification algorithms, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) and NJ (Neighbor Joining), can use the methodology to perform their task, their performance being evaluated against gold standards and with the use of well known statistical indexes, i.e., the F-measure and the partition distance. Based on the experiments, several conclusions can be drawn and, from them, novel valuable guidelines for the use of USM on biological data. The main ones are reported next.</p> <p>Conclusion</p> <p>UCD and NCD are indistinguishable, i.e., they yield nearly the same values of the statistical indexes we have used, accross experiments and data sets, while CD is almost always worse than both. UPGMA seems to yield better classification results with respect to NJ, i.e., better values of the statistical indexes (10% difference or above), on a substantial fraction of experiments, compressors and USM approximation choices. The compression program PPMd, based on PPM (Prediction by Partial Matching), for generic data and Gencompress for DNA, are the best performers among the compression algorithms we have used, although the difference in performance, as measured by statistical indexes, between them and the other algorithms depends critically on the data set and may not be as large as expected. PPMd used with UCD or NCD and UPGMA, on sequence data is very close, although worse, in performance with the alignment methods (less than 2% difference on the F-measure). Yet, it scales well with data set size and it can work on data other than sequences. In summary, our quantitative analysis naturally complements the rich theory behind USM and supports the conclusion that the methodology is worth using because of its robustness, flexibility, scalability, and competitiveness with existing techniques. In particular, the methodology applies to all biological data in textual format. The software and data sets are available under the GNU GPL at the supplementary material web page.</p

Kidney Involvement in Acute Hepatic Porphyrias: Pathophysiology and Diagnostic Implications

Porphyrias are a group of rare disorders originating from an enzyme dysfunction in the pathway of heme biosynthesis. Depending on the specific enzyme involved, porphyrias manifest under drastically different clinical pictures. The most dramatic presentation of the four congenital acute hepatic porphyrias (AHPs: acute intermittent porphyria—AIP, ALAD deficiency, hereditary coproporphyria—HCP, and porphyria variegata—VP) consists of potentially life-threatening neurovisceral attacks, for which givosiran, a novel and effective siRNA-based therapeutic, has recently been licensed. Nonetheless, the clinical manifestations of acute porphyrias are multifaceted and do not limit themselves to acute attacks. In particular, porphyria-associated kidney disease (PAKD) is a distinct, long-term degenerating condition with specific pathological and clinical features, for which a satisfactory treatment is not available yet. In PAKD, chronic tubule-interstitial damage has been most commonly reported, though other pathologic features (e.g., chronic fibrous intimal hyperplasia) are consistent findings. Given the relevant role of the kidney in porphyrin metabolism, the mechanisms possibly intervening in causing renal damage in AHPs are different: among others, d-aminolevulinic acid (ALA)-induced oxidative damage on mitochondria, intracellular toxic aggregation of porphyrins in proximal tubular cells, and derangements in the delicate microcirculatory balances of the kidney might be implicated. The presence of a variant of the human peptide transporter 2 (PEPT2), with a greater affinity to its substrates (including ALA), might confer a greater susceptibility to kidney damage in patients with AHPs. Furthermore, a possible effect of givosiran in worsening kidney function has been observed. In sum, the diagnostic workup of AHPs should always include a baseline evaluation of renal function, and periodic monitoring of the progression of kidney disease in patients with AHPs is strongly recommended. This review outlines the role of the kidney in porphyrin metabolism, the available evidence in support of the current etiologic and pathogenetic hypotheses, and the known clinical features of renal involvement in acute hepatic porphyrias

Hospitalization for pneumonia is associated with decreased 1-year survival in patients with type 2 diabetes results from a prospective cohort study

Diabetes mellitus is a frequent comorbid conditions among patients with pneumonia living in the community. The aim of our study is to evaluate the impact of hospitalization for pneumonia on early (30 day) and late mortality (1 year) in patients with type 2 diabetes mellitus. Prospective comparative cohort study of 203 patients with type 2 diabetes hospitalized for pneumonia versus 206 patients with diabetes hospitalized for other noninfectious causes from January 2012 to December 2013 at Policlinico Umberto I (Rome). Enrolled patients were followed up to discharge and up to 1 year after initial hospital admission or death. Overall, 203 patients with type 2 diabetes admitted to hospital for pneumonia were compared to 206 patients with type 2 diabetes admitted for other causes (39.3% decompensated diabetes, 21.4% cerebrovascular diseases, 9.2% renal failure, 8.3% acute myocardial infarction, and 21.8% other causes). Compared to control patients, those admitted for pneumonia showed a higher 30-day (10.8% vs 1%, P&lt;0.001) and 1-year mortality rate (30.3% vs 16.8%, P&lt;0.001). Compared to survivors, nonsurvivor patients with pneumonia had a higher incidence of moderate to severe chronic kidney disease, hemodialysis, and malnutrition were more likely to present with a mental status deterioration, and had a higher number of cardiovascular events during the follow-up period. Cox regression analysis found age, Charlson comorbidity index, pH&lt;7.35 at admission, hemodialysis, and hospitalization for pneumonia as variables independently associated with mortality. Hospitalization for pneumonia is associated with decreased 1-year survival in patients with type 2 diabetes, and appears to be a major determinant of long-term outcome in these patients

Climate variability and change in the Euro-Mediterranean Region: results from a global AOGCM coupled with an interactive high-resolution model of the Mediterranean Sea

In this work we present and discuss the results obtained from a set of present and future climate simulations performed with a high-resolution model able to represent the dynamics of the Mediterranean Sea. The ability of the model to reproduce the basic features of the observed climate in the Mediterranean region and the beneficial effects of both atmospheric improved resolution and interactive Mediterranean Sea are assessed. In particular, the major characteristics of the variability in the Mediterranean basin and its connection with the large-scale circulation are investigated. Furthermore, the mechanisms through which global warming might affect the regional features of the climate are explored, focusing especially on the characteristics of the hydrological cycle

EFFECTS OF TROPICAL CYCLONES ON OCEAN HEAT TRANSPORT AS SIMULATED BY A HIGH RESOLUTION COUPLED GENERAL CIRCULATION MODEL

In this study the interplay between Tropical Cyclones (TCs) and the Northern hemispheric Ocean Heat Transport (OHT) is investigated. In particular, results from a numerical simulation of the 20th and 21st Century climate, following the Intergovernmental Panel for Climate Change (IPCC) 20C3M and A1B scenario protocols respectively have been analyzed. The numerical simulations have been performed using a state-of-the-art global atmosphere-ocean-sea-ice coupled general circulation model - CGCM (CMCC-MED, Gualdi et al. 2010, Scoccimarro et al. 2010) with relatively high-resolution (T159) in the atmosphere. The model is an evolution of the INGV-SXG (Gualdi et al. 2008, Bellucci et al. 2008) and the ECHAM-OPA-LIM (Fogli et al. 2009, Vichi et al. 2010) The simulated TCs exhibit realistic structure, geographical distribution (Fig.2) and interannual variability, indicating that the model is able to capture the basic mechanisms linking the TC activity with the large scale circulation. The cooling of the surface ocean observed in correspondence of the TCs is well simulated by the model (Fig.3). TC activity is shown to significantly affect the poleward OHT out of the tropics, and the heat transport into the deep tropics (Fig.4). This effect, investigated by looking at the 100 most intense Northern Hemisphere TCs, is strongly correlated with the TC-induced momentum flux at the ocean surface (Fig.7). TCs frequency and intensity appear to be substantially stationary through the whole 1950-2069 simulated period as well as the effect of the TCs on the meridional OHT

Nondestructive Raman investigation on wall paintings at Sala Vaccarini in Catania (Sicily)

In this work, the results of a Raman campaign for studying seventeenth-century Sicilian frescoes, by using two portable Raman systems, equipped with different excitation sources (785 and 1064 nm), are proposed. The measurements were performed with the aim to provide an in situ diagnostic analysis of the wall paintings (in terms of colorants and preparation layer) and to support the conservators in the framework of the ongoing restoration. The combined use of the two Raman spectrometers has given a complete overview on the artist palette and on the state of preservation of frescoes, also informing us about the technique employed by the painter. Natural pigments as hematite, vermillion, goethite, lead red, lead white and carbon-based black pigments have been identified. Additionally, the application of a transitional Romanesque-Renaissance frescoes method has been noticed by the systematic combined presence of calcite and gypsum in the substrate. Finally, the analyses have highlighted the presence of degradation products, mainly related to alteration of lead-based pigments