First-line treatment of persistent and long-standing persistent atrial fibrillation with single-stage hybrid ablation:a 2-year follow-up study

AIMS: This study evaluates the efficacy and safety of first-line single-stage hybrid ablation of (long-standing) persistent atrial fibrillation (AF), over a follow-up period of 2 years, and provides additional information on arrhythmia recurrences and electrophysiological findings at repeat ablation. METHODS AND RESULTS: This is a prospective cohort study that included 49 patients (65% persistent AF; 35% long-standing persistent AF) who underwent hybrid ablation as first-line ablation treatment (no previous endocardial ablation). Patients were relatively young (57.0 ± 8.5 years) and predominantly male (89.8%). Median CHA2DS2-VASc score was 1.0 (0.5; 2.0) and mean left atrium volume index was 43.7 ± 10.9 mL/m2. Efficacy was assessed by 12-lead electrocardiography and 72-h Holter monitoring after 3, 6, 12, and 24 months. Recurrence was defined as AF/atrial flutter (AFL)/tachycardia (AT) recorded by electrocardiography or Holter monitoring lasting >30 s during 2-year follow-up. At 2-year follow-up, single and multiple procedure success rates were 67% and 82%, respectively. Two (4%) patients experienced a major complication (bleeding) requiring intervention following hybrid ablation. Among the 16 (33%) patients who experienced an AF/AFL/AT recurrence, 13 (81%) were ATs/AFLs and only 3 (19%) were AF. Repeat ablation was performed in 10 (20%) patients and resulted in sinus rhythm in 7 (70%) at 2-year follow-up. CONCLUSION: First-line single-stage hybrid AF ablation is an effective treatment strategy for patients with persistent and long-standing persistent AF with an acceptable rate of major complications. Recurrences are predominantly AFL/AT that can be successfully ablated percutaneously. Hybrid ablation seems a feasible approach for first-line ablation of (long-standing) persistent AF

Primary skin fibroblasts as a model of Parkinson's disease

Parkinson's disease is the second most frequent neurodegenerative disorder. While most cases occur sporadic mutations in a growing number of genes including Parkin (PARK2) and PINK1 (PARK6) have been associated with the disease. Different animal models and cell models like patient skin fibroblasts and recombinant cell lines can be used as model systems for Parkinson's disease. Skin fibroblasts present a system with defined mutations and the cumulative cellular damage of the patients. PINK1 and Parkin genes show relevant expression levels in human fibroblasts and since both genes participate in stress response pathways, we believe fibroblasts advantageous in order to assess, e.g. the effect of stressors. Furthermore, since a bioenergetic deficit underlies early stage Parkinson's disease, while atrophy underlies later stages, the use of primary cells seems preferable over the use of tumor cell lines. The new option to use fibroblast-derived induced pluripotent stem cells redifferentiated into dopaminergic neurons is an additional benefit. However, the use of fibroblast has also some drawbacks. We have investigated PARK6 fibroblasts and they mirror closely the respiratory alterations, the expression profiles, the mitochondrial dynamics pathology and the vulnerability to proteasomal stress that has been documented in other model systems. Fibroblasts from patients with PARK2, PARK6, idiopathic Parkinson's disease, Alzheimer's disease, and spinocerebellar ataxia type 2 demonstrated a distinct and unique mRNA expression pattern of key genes in neurodegeneration. Thus, primary skin fibroblasts are a useful Parkinson's disease model, able to serve as a complement to animal mutants, transformed cell lines and patient tissues

Adults with corrected oesophageal atresia: is oesophageal function associated with complaints and/or quality of life?

The aim of this study was to evaluate oesophageal function after correction of oesophageal atresia in adults, and to investigate the association between complaints, oesophageal function and quality of life (QoL). Twenty-five adults were included who participated in previous follow-up studies, during which complaints of dysphagia and gastro-oesophageal reflux (GOR), results of upper gastrointestinal endoscopy, oesophageal biopsies and QoL had been collected. Manometry was performed in 20 patients, 24 h pH-measurements were performed in 21 patients. pH-values (sample time 5 s) were calculated using criteria of Johnson and DeMeester. Associations were tested with ANOVA and χ2-tests. Ten patients (48%) reported complaints of dysphagia, seven (33%) of GOR. The amplitude of oesophageal contractions was low (<15 mmHg) in four patients (20%). pH-measurements showed pathological reflux in three patients (14%). Patients reporting dysphagia more often had disturbed motility (P = 0.011), and lower scores on the domains “general health perceptions” (SF-36) (P = 0.026), “standardised physical component” (SF-36) (P = 0.013), and “physical well-being” (GIQLI) (0.047). No other associations were found. This study shows a high percentage of oesophageal motility disturbances and a moderate percentage of GOR after correction of oesophageal atresia. Patients reporting dysphagia, whom more often had disturbed motility, seemed to be affected by these symptoms in their QoL

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

The Impact of Mouse Passaging of Mycobacterium tuberculosis Strains prior to Virulence Testing in the Mouse and Guinea Pig Aerosol Models

It has been hypothesized that the virulence of lab-passaged Mycobacterium tuberculosis and recombinant M. tuberculosis mutants might be reduced due to multiple in vitro passages, and that virulence might be augmented by passage of these strains through mice before quantitative virulence testing in the mouse or guinea pig aerosol models.By testing three M. tuberculosis H37Rv samples, one deletion mutant, and one recent clinical isolate for survival by the quantitative organ CFU counting method in mouse or guinea pig aerosol or intravenous infection models, we could discern no increase in bacterial fitness as a result of passaging of M. tuberculosis strains in mice prior to quantitative virulence testing in two animal models. Surface lipid expression as assessed by neutral red staining and thin-layer chromatography for PDIM analysis also failed to identify virulence correlates.These results indicate that animal passaging of M. tuberculosis strains prior to quantitative virulence testing in mouse or guinea pig models does not enhance or restore potency to strains that may have lost virulence due to in vitro passaging. It is critical to verify virulence of parental strains before genetic manipulations are undertaken and comparisons are made

Early Epidemiological Assessment of the Virulence of Emerging Infectious Diseases: A Case Study of an Influenza Pandemic

Background: The case fatality ratio (CFR), the ratio of deaths from an infectious disease to the number of cases, provides an assessment of virulence. Calculation of the ratio of the cumulative number of deaths to cases during the course of an epidemic tends to result in a biased CFR. The present study develops a simple method to obtain an unbiased estimate of confirmed CFR (cCFR), using only the confirmed cases as the denominator, at an early stage of epidemic, even when there have been only a few deaths. Methodology/Principal Findings: Our method adjusts the biased cCFR by a factor of underestimation which is informed by the time from symptom onset to death. We first examine the approach by analyzing an outbreak of severe acute respiratory syndrome in Hong Kong (2003) with known unbiased cCFR estimate, and then investigate published epidemiological datasets of novel swine-origin influenza A (H1N1) virus infection in the USA and Canada (2009). Because observation of a few deaths alone does not permit estimating the distribution of the time from onset to death, the uncertainty is addressed by means of sensitivity analysis. The maximum likelihood estimate of the unbiased cCFR for influenza may lie in the range of 0.16-4.48% within the assumed parameter space for a factor of underestimation. The estimates for influenza suggest that the virulence is comparable to the early estimate in Mexico. Even when there have been no deaths, our model permits estimating a conservative upper bound of the cCFR. Conclusions: Although one has to keep in mind that the cCFR for an entire population is vulnerable to its variations among sub-populations and underdiagnosis, our method is useful for assessing virulence at the early stage of an epidemic and for informing policy makers and the public. © 2009 Nishiura et al.published_or_final_versio

Detecting change via competence model

In real world applications, interested concepts are more likely to change rather than remain stable, which is known as concept drift. This situation causes problems on predictions for many learning algorithms including case-base reasoning (CBR). When learning under concept drift, a critical issue is to identify and determine "when" and "how" the concept changes. In this paper, we developed a competence-based empirical distance between case chunks and then proposed a change detection method based on it. As a main contribution of our work, the change detection method provides an approach to measure the distribution change of cases of an infinite domain through finite samples and requires no prior knowledge about the case distribution, which makes it more practical in real world applications. Also, different from many other change detection methods, we not only detect the change of concepts but also quantify and describe this change. © 2010 Springer-Verlag