On breaking truss-based communities

A k-truss is a graph such that each edge is contained in at least k-2 triangles. This notion has attracted much attention, because it models meaningful cohesive subgraphs of a graph. We introduce the problem of identifying a smallest edge subset of a given graph whose removal makes the graph k-truss-free. We also introduce a problem variant where the identified subset contains only edges incident to a given set of nodes and ensures that these nodes are not contained in any k-truss. These problems are directly applicable in communication networks: the identified edges correspond to vital network connections; or in social networks: the identified edges can be hidden by users or sanitized from the output graph. We show that these problems are NP-hard. We thus develop exact exponential-time algorithms to solve them. To process large networks, we also develop heuristics sped up by an efficient data structure for updating the truss decomposition under edge deletions. We complement our heuristics with a lower bound on the size of an optimal solution to rigorously evaluate their effectiveness. Extensive experiments on 10 real-world graphs show that our heuristics are effective (close to the optimal or to the lower bound) and also efficient (up to two orders of magnitude faster than a natural baseline)

Transcriptome and gene expression analysis of three developmental stages of the coffee berry borer, Hypothenemus hampei

Coffee production is a global industry valued at approximately 173 billion US dollars. One of the main challenges facing coffee production is the management of the coffee berry borer (CBB), Hypothenemus hampei, which is considered the primary arthropod pest of coffee worldwide. Current control strategies are inefficient for CBB management. Although biotechnological alternatives, including RNA interference (RNAi), have been proposed in recent years to control insect pests, characterizing the genetics of the target pest is essential for the successful application of these emerging technologies. In this study, we employed RNA-seq to obtain the transcriptome of three developmental stages of the CBB (larva, female and male) to increase our understanding of the CBB life cycle in relation to molecular features. The CBB transcriptome was sequenced using Illumina Hiseq and assembled de novo. Differential gene expression analysis was performed across the developmental stages. The final assembly produced 29,434 unigenes, of which 4,664 transcripts were differentially expressed. Genes linked to crucial physiological functions, such as digestion and detoxification, were determined to be tightly regulated between the reproductive and nonreproductive stages of CBB. The data obtained in this study help to elucidate the critical roles that several genes play as regulatory elements in CBB development

Transcriptome and gene expression analysis of three developmental stages of the coffee berry borer, Hypothenemus hampei

Coffee production is a global industry valued at approximately 173 billion US dollars. One of the main challenges facing coffee production is the management of the coffee berry borer (CBB), Hypothenemus hampei, which is considered the primary arthropod pest of coffee worldwide. Current control strategies are inefficient for CBB management. Although biotechnological alternatives, including RNA interference (RNAi), have been proposed in recent years to control insect pests, characterizing the genetics of the target pest is essential for the successful application of these emerging technologies. In this study, we employed RNA-seq to obtain the transcriptome of three developmental stages of the CBB (larva, female and male) to increase our understanding of the CBB life cycle in relation to molecular features. The CBB transcriptome was sequenced using Illumina Hiseq and assembled de novo. Differential gene expression analysis was performed across the developmental stages. The final assembly produced 29,434 unigenes, of which 4,664 transcripts were differentially expressed. Genes linked to crucial physiological functions, such as digestion and detoxification, were determined to be tightly regulated between the reproductive and nonreproductive stages of CBB. The data obtained in this study help to elucidate the critical roles that several genes play as regulatory elements in CBB development

Transcriptome and gene expression analysis of three developmental stages of the coffee berry borer, Hypothenemus hampei

Coffee production is a global industry valued at approximately 173 billion US dollars. One of the main challenges facing coffee production is the management of the coffee berry borer (CBB), Hypothenemus hampei, which is considered the primary arthropod pest of coffee worldwide. Current control strategies are inefficient for CBB management. Although biotechnological alternatives, including RNA interference (RNAi), have been proposed in recent years to control insect pests, characterizing the genetics of the target pest is essential for the successful application of these emerging technologies. In this study, we employed RNA-seq to obtain the transcriptome of three developmental stages of the CBB (larva, female and male) to increase our understanding of the CBB life cycle in relation to molecular features. The CBB transcriptome was sequenced using Illumina Hiseq and assembled de novo. Differential gene expression analysis was performed across the developmental stages. The final assembly produced 29,434 unigenes, of which 4,664 transcripts were differentially expressed. Genes linked to crucial physiological functions, such as digestion and detoxification, were determined to be tightly regulated between the reproductive and nonreproductive stages of CBB. The data obtained in this study help to elucidate the critical roles that several genes play as regulatory elements in CBB development

Comparing Degenerate Strings

Uncertain sequences are compact representations of sets of similar strings. They highlight common segments by collapsing them, and explicitly represent varying segments by listing all possible options. A generalized degenerate string (GD string) is a type of uncertain sequence. Formally, a GD string S is a sequence of n sets of strings of total size N, where the ith set contains strings of the same length ki but this length can vary between different sets. We denote by W the sum of these lengths k0, k1,... , kn-1. Our main result is an (N + M)-time algorithm for deciding whether two GD strings of total sizes N and M, respectively, over an integer alphabet, have a non-empty intersection. This result is based on a combinatorial result of independent interest: although the intersection of two GD strings can be exponential in the total size of the two strings, it can be represented in linear space. We then apply our string comparison tool to devise a simple algorithm for computing all palindromes in S in (min{W, n2}N)-time. We complement this upper bound by showing a similar conditional lower bound for computing maximal palindromes in S. We also show that a result, which is essentially the same as our string comparison linear-time algorithm, can be obtained by employing an automata-based approach

Hide and mine in strings: Hardness, algorithms, and experiments

Data sanitization and frequent pattern mining are two well-studied topics in data mining. Our work initiates a study on the fundamental relation between data sanitization and frequent pattern mining in the context of sequential (string) data. Current methods for string sanitization hide confidential patterns. This, however, may lead to spurious patterns that harm the utility of frequent pattern mining. The main computational problem is to minimize this harm. Our contribution here is as follows. First, we present several hardness results, for different variants of this problem, essentially showing that these variants cannot be solved or even be approximated in polynomial time. Second, we propose integer linear programming formulations for these variants and algorithms to solve them, which work in polynomial time under realistic assumptions on the input parameters. We complement the integer linear programming algorithms with a greedy heuristic. Third, we present an extensive experimental study, using both synthetic and real-world datasets, that demonstrates the effectiveness and efficiency of our methods. Beyond sanitization, the process of missing value replacement may also lead to spurious patterns. Interestingly, our results apply in this context as well

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

The “Diabetes Comorbidome”: A Different Way for Health Professionals to Approach the Comorbidity Burden of Diabetes

(1) Background: The disease burden related to diabetes is increasing greatly, particularly in older subjects. A more comprehensive approach towards the assessment and management of diabetes’ comorbidities is necessary. The aim of this study was to implement our previous data identifying and representing the prevalence of the comorbidities, their association with mortality, and the strength of their relationship in hospitalized elderly patients with diabetes, developing, at the same time, a new graphic representation model of the comorbidome called “Diabetes Comorbidome”. (2) Methods: Data were collected from the RePoSi register. Comorbidities, socio-demographic data, severity and comorbidity indexes (Cumulative Illness rating Scale CIRS-SI and CIRS-CI), and functional status (Barthel Index), were recorded. Mortality rates were assessed in hospital and 3 and 12 months after discharge. (3) Results: Of the 4714 hospitalized elderly patients, 1378 had diabetes. The comorbidities distribution showed that arterial hypertension (57.1%), ischemic heart disease (31.4%), chronic renal failure (28.8%), atrial fibrillation (25.6%), and COPD (22.7%), were the more frequent in subjects with diabetes. The graphic comorbidome showed that the strongest predictors of death at in hospital and at the 3-month follow-up were dementia and cancer. At the 1-year follow-up, cancer was the first comorbidity independently associated with mortality. (4) Conclusions: The “Diabetes Comorbidome” represents the perfect instrument for determining the prevalence of comorbidities and the strength of their relationship with risk of death, as well as the need for an effective treatment for improving clinical outcomes