A relevance index method to infer global properties of biological networks

Many complex systems, both natural and artificial, may be represented by networks of interacting nodes. Nevertheless, it is often difficult to find meaningful correspondences between the dynamics expressed by these systems and the topological description of their networks. In contrast, many of these systems may be well described in terms of coordinated behavior of their dynamically relevant parts. In this paper we use the recently proposed Relevance Index approach, based on information-theoretic measures. Starting from the observation of the dynamical states of any system, the Relevance Index is able to provide information about its organization. Moreover, we show how the application of the proposed approach leads to novel and effective interpretations in the T helper network case study

Can the Relevance Index be Used to Evolve Relevant Feature Sets?

The Relevance Index (RI) is an information theory-based measure that was originally defined to detect groups of functionally similar neurons, based on their dynamic behavior. More in general, considering the dynamical analysis of a generic complex system, the larger the RI value associated with a subset of variables, the more those variables are strongly correlated with one another and independent from the other variables describing the system status. We describe some early experiments to evaluate whether such an index can be used to extract relevant feature subsets in binary pattern classification problems. In particular, we used a PSO variant to efficiently explore the RI search space, whose size equals the number of possible variable subsets (in this case 2104) and find the most relevant and discriminating feature subsets with respect to pattern representation. We then turned such relevant subsets into a new smaller set of richer features, whose values depend on the values of the binary features they include. The paper reports some exploratory results we obtained in a simple character recognition task, comparing the performance of RI-based feature extraction and selection with other classical feature selection/extraction approaches

Can the Relevance Index be Used to Evolve Relevant Feature Sets?

The Relevance Index (RI) is an information theory-based measure that was originally defined to detect groups of functionally similar neurons, based on their dynamic behavior. More in general, considering the dynamical analysis of a generic complex system, the larger the RI value associated with a subset of variables, the more those variables are strongly correlated with one another and independent from the other variables describing the system status. We describe some early experiments to evaluate whether such an index can be used to extract relevant feature subsets in binary pattern classification problems. In particular, we used a PSO variant to efficiently explore the RI search space, whose size equals the number of possible variable subsets (in this case 2^{104}) and find the most relevant and discriminating feature subsets with respect to pattern representation. We then turned such relevant subsets into a new smaller set of richer features, whose values depend on the values of the binary features they include. The paper reports some exploratory results we obtained in a simple character recognition task, comparing the performance of RI-based feature extraction and selection with other classical feature selection/extraction approaches

An innovative test for non-invasive Kell genotyping on circulating fetal DNA by means of the allelic discrimination of K1 and K2 antigens

Objective: The aim of this study was to present a new method for fetal Kell genotyping by means of the allelic discrimination of K1 and K2 in real-time polymerase chain reaction (PCR). Methods: Real-time quantitative polymerase chain reaction incorporating an allele-specific primer was developed for detecting the K allele of KEL. Results: By means of this method, the K1/K2 genotype was able to be determined in all blood samples analyzed. Results using cell-free fetal DNA (cffDNA) from two Kell-negative pregnant women confirmed the Kell-positive genotype of fetuses. The real-time PCR analysis also allowed the determination of the fetal fraction using the quantification of Kell-positive DNA. Conclusion: An efficient and reliable strategy for Kell genotyping is herein presented. The method was optimized on cffDNA to create a non-invasive prenatal test which could be routinely used for the prevention of hemolytic disease of the fetus and the newborn (HDFN)

Efficient search of relevant structures in complex systems

In a previous work, Villani et al. introduced a method to identify candidate emergent dynamical structures in complex systems. Such a method detects subsets (clusters) of the system elements which behave in a coherent and coordinated way while loosely interacting with the remainder of the system. Such clusters are assessed in terms of an index that can be associated to each subset, called Dynamical Cluster Index (DCI). When large systems are analyzed, the \u201ccurse of dimensionality\u201d makes it impossible to compute the DCI for every possible cluster, even using massively parallel hardware such as GPUs. In this paper, we propose an efficient metaheuristic for searching relevant dynamical structures, which hybridizes an evolutionary algorithm with local search and obtains results comparable to an exhaustive search in a much shorter time. The effectiveness of the method we propose has been evaluated on a set of Boolean models of real-world systems

GPU-based parallel search of relevant variable sets in complex systems

Various methods have been proposed to identify emergent dynamical structures in complex systems. In this paper, we focus on the Dynamical Cluster Index (DCI), a measure based on information theory which allows one to detect relevant sets, i.e. sets of variables that behave in a coherent and coordinated way while loosely interacting with the rest of the system. The method associates a score to each subset of system variables; therefore, for a thorough analysis of the system, it requires an exhaustive enumeration of all possible subsets. For large systems, the curse of dimensionality makes the problem solvable only using metaheuristics. Even within such approaches, however, DCI computation has to be performed for a huge number of times; thus, an efficient implementation becomes a mandatory requirement. Considering that a candidate relevant set\u2019s DCI can be computed independently of the others, we propose a GPU-based massively parallel implementation of DCI computation. We describe the algorithm\u2019s structure and validate it by assessing the speedup in comparison with a single-thread sequential CPU implementation when analyzing a set of dynamical systems of different sizes

Long-term treatment of adult ADHD in a naturalistic setting: Clinical predictors of attrition, medication choice, improvement, and response

ObjectivesThe aim of this study was to identify clinical predictors of treatment attrition, medication choice, improvement and response to pharmacotherapy in adult attention-deficit/hyperactivity disorder (ADHD).Methods150 ADHD patients were enrolled and naturalistically followed-up for at least 4 months. Conners' Adult ADHD Rating Scales-Observer: Screening Version (CAARS-O:SV) were used to measure ADHD severity.Results58 subjects (38.7%) were lost at follow-up, while 75 (50%) completed follow-up assessment, on average after 26.05 +/- 11.99 weeks; 35 were treated with atomoxetine (ATX) and 40 with methylphenidate (MPH). Treatments were moderately effective (d = 0.72) and 37 patients (49.3%) were responders (>= 30% CAARS-O:SV decrease). Patients lost at follow-up had lower inattentive symptoms, less generalised anxiety and family history of bipolar disorder, more amphetamine use disorder than follow-up completers. Compared to ATX-treated subjects, MPH-treated patients had greater severity of hyperactivity/impulsivity and were more frequently diagnosed with alcohol use disorder. While MPH and ATX showed similar efficacy, more pronounced improvements were observed in patients with combined ADHD, anxiety and substance use disorders. ADHD severity and comorbid substance use positively predicted response.ConclusionsConsensus-based hierarchical treatment of ADHD comorbidity is not consistently supported. Comorbid anxiety, mood and substance use disorders should not discourage the treatment of adult ADHD

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32-0.77); P<0.01], but no difference in complication rates [OR 1.02 (0.88-1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62-0.92); P<0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61-0.88); P<0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine