Miracle-dz/UniFAR-FTUs huggingface dataset:
Importance of refractoriness heterogeneity in the enhanced vulnerability to atrial fibrillation induction caused by tachycardia-induced atrial electrical remodeling.

BACKGROUND Rapid atrial activation causes electrical remodeling that promotes the occurrence and the maintenance of atrial fibrillation (AF). Although remodeling has been shown to alter electrophysiological variables, the spatial uniformity of these changes is unknown. METHODS AND RESULTS Dogs subjected to rapid atrial pacing (400 bpm) for 24 hours (n=12) were compared with sham-operated dogs (instrumented but not paced, n=12). Epicardial mapping (240 bipolar electrodes) and extrastimulation at a large number of sites (mean+/-SEM, 66+/-4 per dog) were used to evaluate atrial activation and the heterogeneity of the effective refractory period (ERP), respectively. Rapid pacing increased both the percentage of sites at which AF could be induced by single premature stimuli (from 2.6+/-0.9% to 11.8+/-2.8%, P=0.007) and AF duration (from 39+/-28 to 146+/-49 seconds, P=0.03). Atrial tachycardia decreased atrial ERP (from 120+/-4 to 103+/-2 ms, P=0.003), increased the coefficient of variation of ERP (from 14.9+/-0.9% to 20.7+/-0.9%, P<0.0001), and accelerated conduction velocity (from 91+/-2 to 108+/-3 cm/s, P=0.0004), with no change in the wavelength. The increase in ERP heterogeneity was due both to interregional differences in the extent of ERP remodeling and to increased intersite variability within regions. Stepwise multilinear regression indicated that ERP heterogeneity was an independent determinant of the inducibility (P<0.0001) and duration (P<0.0001) of AF, whereas ERP per se and wavelength were not significant determinants. Combined mapping of AF induction and atrial ERP showed that premature extrastimuli induced AF at sites with short ERP by causing local conduction slowing and/or block in adjacent zones with longer ERP values. CONCLUSIONS Atrial tachycardia causes nonuniform remodeling of atrial refractoriness that plays an important role in increasing atrial vulnerability to AF induction and the duration of induced AF.
Accuracy of Perceived Risk of Recurrence Among Patients With Early-Stage Breast Cancer

Background: Accurate breast cancer recurrence risk perceptions might motivate health-promoting behaviors and alleviate undue anxiety. Although a few studies have examined early-stage breast cancer survivors' perceived risk of recurrence, none have assessed the accuracy of survivors' perceived risk of recurrence. Methods: First primary ductal carcinoma in situ and early-invasive breast cancer survivors reported their perceived risk of recurrence during 6- and 12-month postsurgery interviews. We estimated the patients' 10-year risk of recurrence from published clinical trials, and for early-invasive breast cancer patients, risk of distant recurrence was based on their breast cancer–specific mortality calculated using Adjuvant! Online. Patients' perceived risk was compared with their calculated risk and categorized as “Accurate,” “Underestimated,” “Overestimated,” and “Uncertain. ” Multinomial logit marginal effect models were fitted using Accurate as the reference. Results: Only 17% of 531 patients accurately perceived their risk at 6 months, most of whom inaccurately perceived their risk at 12 months (P = 0.0143). Patients who were nonwhite [odds ratio (OR), 1.70; 95% confidence interval (95% CI), 1.12-2.56] and received radiation therapy (OR, 2.01; 95% CI, 1.07-3.77) were more likely to underestimate their risk. Patients with ductal carcinoma in situ (OR, 1.69; 95% CI, 1.08-2.70), lower social support (OR, 0.71; 95% CI, 0.53-0.95), and anxiety (OR, 1.58; 95% CI, 1.01-2.47) were more likely to overestimate their risk. Conclusion: Few breast cancer survivors accurately perceived their risk of recurrence. Impact: The accuracy of perceived risk may be increased by better physician-patient communications about their prognosis, provision of social support, and treatment for coexisting anxiety. Cancer Epidemiol Biomarkers Prev; 19(3); 675–80
Comparison of the acceptability of a new scoring system with Misch's classification for dental implant success determination.

AIMS The present study aimed at evaluating the acceptability of the Implant Success Index (ISI) in comparison with the conventional classification system. MATERIALS AND METHODS A comparative questionnaire was designed to evaluate 10 criteria that were reported to be important for acceptance of a new classification system. We asked 20 experts who had at least 5 years of clinical experience in implant dentistry to complete a questionnaire based on a visual analog scale. Data were analyzed by a blinded statistician using a Wilcoxon non-parametric rank test. RESULTS Measuring all 10 criteria, the acceptability level of ISI was significantly higher than that of the Misch classification (70.90 and 54.90, respectively; P < 0.05). The most significant differences were found in the system's ability to detect early lesions, its lack of overestimation, its quantitative base, and its comprehensiveness. The simplicity and compatibility of the two understudy classification systems were not significantly different. CONCLUSIONS ISI seems to be a proper scoring system with a high level of acceptability for determining the success rate of dental implants and for selection of procedures used for improving the status of peri-implant tissue.
Telmisartan Improves Insulin Resistance in Patients With Low Cytokine Levels

Metabolic syndrome (MS) is a disease with an inflammatory component. Telmisartan improves insulin resistance in MS, but its relationship with the inflammatory state is unknown. We investigated the effect of 3-month telmisartan therapy on homeostatic model assessment-insulin resistance (HOMA-IR) in hypertensive subjects with MS with regard to the levels of circulating plasma cytokines. Methods A total of 42 patients were included in this study; 30 were men (71%), aged 50 ± 8.2 years (mean ± SD). Cytokines and metabolic parameters were analyzed before and after treatment with telmisartan. Results Twenty-eight patients showed low plasma levels of cytokines (group 1) similar to control subjects, and 14 showed high levels (group 2). Treatment with telmisartan diminished by 35% HOMA-IR in group 1 (4.5 ± 3.1 vs 2.9 ± 2.1), without improvement in group 2. In the multivariate analysis, the predictors of improvement of HOMA-IR in response to telmisartan treatment were low levels of cytokines, whereas systolic and diastolic blood pressure and the elevation of high-sensitivity C-reactive protein had a negative effect. Conclusions Our study provides evidence of a more favorable effect of telmisartan on glucose homeostasis in patients with MS and low levels of serum cytokines.
Vertical Association Rule Mining: Case study implementation with relational DBMS

Data mining remains as one of the most important research domain in Knowledge Discovery and Database (KDD). Moving deeper, Association Rule Mining (ARM) is one of the most prominent areas in detecting pattern analysis especially for crucial business decision making. It aims to extract interesting correlations, frequent patterns, association or casual structures among set of items in the transaction databases or other data repositories. Even though most of these data repositories are dealing with flat files, current trend is focusing on using relational Database Management System (DBMS) for the more systematic and structured management of data. In response to the importance of adopting relational database, in this paper we implement MySQL (My Structured Query Language) as our association rule mining database engine in testing benchmark dense datasets which available from Frequent Itemset Mining (FIMI) online repository. Our study is focusing on Eclat algorithm as well as its variants in generating frequent and interesting rule, as a continual from our previous studies. The performance result shows a promising signal as to confirm on the benefits of relational database mechanism in storing any transaction data.
DISABILITY AND PROGRESSION IN PARKINSON'S DISEASE

Disability and progression in Parkinson's disease prior to levodopa treatment was investigated in a random group of 442 patients representing 91 per cent of all known cases with Parkinson's disease in a defined area. Almost half the patients were totally independent, 27 per cent needed help occasionally, and 25 per cent were dependent on other people. Ten per cent of the patients had only unilateral symptoms, 57 per cent had bilateral involvement with mild disability, 20 per cent had a moderately advanced disease, and 13 per cent were severely disabled. A great variation was found in progression rates. In individual cases, however, the progression rate seemed to be relatively fixed. Concurrent arteriosclerosis was found to worsen the prognosis, whereas the beginning of the disease with tremor and the occurrence of prominent tremor promised a slower progression. Twenty‐six patients with only unilateral symptoms 10 years after onset of the disease were found to correspond to postencephalitic patients in age structure, and in such cases a history of preceeding viral infection of the central nervous system was observed on four occasions.
Bipartite consensus of multi‐agent systems over signed graphs: State feedback and output feedback control approaches

This paper studies bipartite consensus problems for continuous‐time multi‐agent system over signed directed graphs. We consider general linear agents and design both state feedback and dynamic output feedback control laws for the agents to achieve bipartite consensus. Via establishing an equivalence between bipartite consensus problems and the conventional consensus problems under both state feedback and output feedback control approaches, we make direct application of existing state feedback and output feedback consensus algorithms to solve bipartite consensus problems. Moreover, we propose a systematical approach to design bipartite consensus control laws. Copyright © 2016 John Wiley & Sons, Ltd.
Increase in Th17 and T-reg Lymphocytes and Decrease of IL22 Correlate with the Recovery Phase of Acute EAE IN Rat

Experimental autoimmune encephalomyelitis (EAE), a well-established model of multiple sclerosis, is characterised by microglial activation and lymphocyte infiltration. Induction of EAE in Lewis rats produces an acute monophasic disease characterised by a single peak of disability followed by a spontaneous and complete recovery and a subsequent tolerance to further immunizations. In the current study we have performed a detailed analysis of the dynamics of different lymphocyte populations and cytokine profile along the induction, peak, recovery and post-recovery phases in this paradigm. MBP-injected rats were sacrificed attending exclusively to their clinical score, and the different populations of T-lymphocytes as well as the dynamics of different pro- and anti-inflammatory cytokines were analysed in the spinal cord by flow cytometry, immunohistochemistry and ELISA. Our results revealed that, during the induction and peak phases, in parallel to an increase in symptomatology, the number of CD3+ and CD4+ cells increased progressively, showing a Th1 phenotype, but unexpectedly during recovery, although clinical signs progressively decreased, the number and proportion of CD3+ and CD4+ populations remained unaltered. Interestingly, during this recovery phase, we observed a marked decrease of Th1 and an important increase in Th17 and T-reg cells. Moreover, our results indicate a specific cytokine expression profile along the EAE course characterized by no changes of IL10 and IL17 levels, decrease of IL21 on the peak, and high IL22 levels during the induction and peak phases that markedly decrease during recovery. In summary, these results revealed the existence of a specific pattern of lymphocyte infiltration and cytokine secretion along the different phases of the acute EAE model in Lewis rat that differs from those already described in chronic or relapsing-remitting mouse models, where Th17-cells were found mostly during the peak, suggesting a specific role of these lymphocytes and cytokines in the evolution of this acute EAE model.
A novel quantitative trait locus on chromosome A9 controlling oleic acid content in Brassica napus

Summary One of the most important goals in the breeding of oilseed crops, including Brassica napus, is to improve the quality of edible vegetable oil, which is mainly determined by the seed fatty acid composition, particularly the C18:1 content. Previous studies have indicated that the C18:1 content is a polygenic trait, and no stable quantitative trait loci (QTLs) except for FAD2 have been reported. By performing a GWAS using 375 low erucic acid B. napus accessions genotyped with the Brassica 60K SNP array and constructing a high‐density SNP‐based genetic map of a 150 DH population, we identified a novel QTL on the A9 chromosome. The novel locus could explain 11.25%, 5.72% and 6.29% of phenotypic variation during three consecutive seasons and increased the C18:1 content by approximately 3%–5%. By fine mapping and gene expression analysis, we found three potential candidate genes and verified the fatty acids in a homologous gene mutant of Arabidopsis. A metal ion‐binding protein was found to be the most likely candidate gene in the region. Thus, the C18:1 content can be further increased to about 80% with this novel locus together with FAD2 mutant allele without compromise of agronomic performance. A closely linked marker, BnA129, for this novel QTL (OLEA9) was developed so that we can effectively identify materials with high C18:1 content at an early growth stage by marker‐assisted selection. Our results may also provide new insight for understanding the complex genetic mechanism of fatty acid metabolism.
Calibration of Mutation Rates Reveals Diverse Subfamily Structure of Galliform CR1 Repeats

Chicken Repeat 1 (CR1) repeats are the most abundant family of repeats in the chicken genome, with more than 200,000 copies accounting for ∼80% of the chicken interspersed repeats. CR1 repeats are believed to have arisen from the retrotransposition of a small number of master elements, which gave rise to the 22 CR1 subfamilies as previously reported in Repbase. We performed a global assessment of the divergence distributions, phylogenies, and consensus sequences of CR1 repeats in the chicken genome. We identified and validated 57 chicken CR1 subfamilies and further analyzed the correlation between these subfamilies and their regional GC contents. We also discovered one novel lineage-specific CR1 subfamilies in turkeys when compared with chickens. We built an evolutionary tree of these subfamilies and concluded that CR1 repeats may play an important role in reshaping the structure of bird genomes.
Identiﬁcation and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31

Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully char-acterized. Most identiﬁed common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3 0 untranslated region at putative microRNA (miRNA)-binding sites represent functional targets that inﬂuence EOC susceptibility. Here, we evaluate the association between 767 miRNA-related single-nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene–environment Study. We identify several miRSNPs associated with invasive serous EOC risk (odds ratio ¼ 1.12, P ¼ 10 (cid:2) 8 ) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion ( P ¼ 10 (cid:2) 10 ). Variation at 17q21.31 is associated with neurological diseases, and our collaboration is the ﬁrst to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.
Efficient parent selection for Approximation-Guided Evolutionary multi-objective optimization

The Pareto front of a multi-objective optimization problem is typically very large and can only be approximated. Approximation-Guided Evolution (AGE) is a recently presented evolutionary multi-objective optimization algorithm that aims at minimizing iteratively the approximation factor, which measures how well the current population approximates the Pareto front. It outperforms state-of-the-art algorithms for problems with many objectives. However, AGE's performance is not competitive on problems with very few objectives. We study the reason for this behavior and observe that AGE selects parents uniformly at random, which has a detrimental effect on its performance. We then investigate different algorithm-specific selection strategies for AGE. The main difficulty here is finding a computationally efficient selection scheme which does not harm AGEs linear runtime in the number of objectives. We present several improved selections schemes that are computationally efficient and substantially improve AGE on low-dimensional objective spaces, but have no negative effect in high-dimensional objective spaces.
Towards human-like behaviour in spoken dialog systems

We and others have found it fruitful to assume that users, when interacting with spoken dialogue systems, perceive the systems and their actions metaphorically. Common metaphors include the human metaphor and the interface metaphor (cf. Edlund, Heldner, & Gustafson, 2006). In the interface metaphor, the spoken dialogue system is perceived as a machine interface – often but not always a computer interface. Speech is used to accomplish what would have otherwise been accomplished by some other means of input, such as a keyboard or a mouse. In the human metaphor, on the other hand, the computer is perceived as a creature (or even a person) with humanlike conversational abilities, and speech is not a substitute or one of many alternatives, but rather the primary means of communicating with this creature. We are aware that more “natural ” or human-like behaviour does not automatically make a spoken dialogue system “better ” (i.e. more efficient or more well-liked by its users). Indeed, we are quite convinced that the advantage (or disadvantage) of humanlike behaviour will be highly dependent on the application. However, a dialogue system that is coherent with a human metaphor may profit from a number of characteristics.
Chunking and Dependency Parsing

Since chunking can be performed efficiently and accurately, it is attractive to use it as a preprocessing step in full parsing stages. We analyze whether providing chunk data to a statistical dependency parser can benefit its accuracy. We present a set of experiments meant to select first a set of features that provide the greates improvement to a Shift/Reduce dependency parser, then to determine an appropriate feature model. We report on accuracy gain obtained using features from chunks produced using a statistical chunker as well as from an approximate representation of noun phrases induced directly by the parser. Finally we analyze the degree of accuracy that such a parser can achieve in chunking compared to a specialized statistical chunker.
Collision-Free Trajectory Planning for a 3-DoF Robot with a Passive Joint

This paper studies motion planning from one zero-velocity state to another for a three-joint robot in a horizontal plane with a passive revolute third joint. Such a robot is small-time locally controllable on an open subset of its zero-velocity section, allowing it to follow any path in this subset arbitrarily closely. However, some paths are “preferred” by the dynamics of the manipulator in that they can be followed at higher speeds. In this paper, the authors describe a computationally efficient trajectory planner that finds fast, collision-free trajectories among obstacles. The planner decouples the problem of planning feasible trajectories in the robot’s six-dimensional state space into the computationally simpler problems of planning paths in the three-dimensional configuration space and time scaling the paths according to the manipulator dynamics. This decoupling is made possible by the existence of velocity directions, fixed in the passive link frame, which can be executed at arbitrary speeds. Results of the planner have been implemented on an experimental underactuated manipulator. To the authors’ knowledge, it is the first implementation of a collision-free motion-planning algorithm for a manipulator subject to a second-order nonholonomic constraint.
Vasopeptidase Inhibitors: A New Therapeutic Concept in Cardiovascular Disease?

The cardiovascular system is regulated by hemodynamic and neurohumoral mechanisms. These regulatory systems play a key role in modulating cardiac function, vascular tone, and structure. Although neurohumoral systems are essential in vascular homeostasis, they become maladaptive in disease states such as hypertension, coronary disease, and heart failure. The clinical success of ACE inhibitors has led to efforts to block other humoral systems. Neutral endopeptidase (NEP) is an endothelial cell surface zinc metallopeptidase with similar structure and catalytic site. NEP is the major enzymatic pathway for degradation of natriuretic peptides, a secondary enzymatic pathway for degradation of kinins, and adrenomedullin. The natriuretic peptides can be viewed as endogenous inhibitors of the renin angiotensin system. Inhibition of NEP increases levels of atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP) of myocardial cell origin, and C-type natriuretic peptide (CNP) of endothelial cell origin as well as bradykinin and adrenomedullin. By simultaneously inhibiting the renin-angiotensin-aldosterone system and potentiating the natriuretic peptide and kinin systems, vasopeptidase inhibitors reduce vasoconstriction, enhance vasodilation, improve sodium/water balance, and, in turn, decrease peripheral vascular resistance and blood pressure and improve local blood flow. Within the blood vessel wall, this leads to a reduction of vasoconstrictor and proliferative mediators such as angiotensin II and increased local levels of bradykinin (and, in turn, nitric oxide) and natriuretic peptides. Preliminary clinical experiences with vasopeptidase inhibitors are encouraging. Thus, the combined inhibition of ACE and neutral endopeptidase is a new and promising approach to treat patients with hypertension, atherosclerosis, or heart failure.
Tight Data-Robust Bounds to Mutual Information Combining Shuffling and Model Selection Techniques

The estimation of the information carried by spike times is crucial for a quantitative understanding of brain function, but it is difficult because of an upward bias due to limited experimental sampling. We present new progress, based on two basic insights, on reducing the bias problem. First, we show that by means of a careful application of data-shuffling techniques, it is possible to cancel almost entirely the bias of the noise entropy, the most biased part of information. This procedure provides a new information estimator that is much less biased than the standard direct one and has similar variance. Second, we use a nonparametric test to determine whether all the information encoded by the spike train can be decoded assuming a low-dimensional response model. If this is the case, the complexity of response space can be fully captured by a small number of easily sampled parameters. Combining these two different procedures, we obtain a new class of precise estimators of information quantities, which can provide data-robust upper and lower bounds to the mutual information. These bounds are tight even when the number of trials per stimulus available is one order of magnitude smaller than the number of possible responses. The effectiveness and the usefulness of the methods are tested through applications to simulated data and recordings from somatosensory cortex. This application shows that even in the presence of strong correlations, our methods constrain precisely the amount of information encoded by real spike trains recorded in vivo.