LLukas22/scidocs huggingface dataset:
The impact of image integration on catheter ablation of atrial fibrillation using electroanatomic mapping: a prospective randomized study.

AIMS
A detailed appreciation of the left atrial/pulmonary venous (LA/PV) anatomy may be important in improving the safety and success of catheter ablation for AF. The aim of this randomized study was to determine the impact of computed tomographic (CT) integration into an electroanatomic mapping (EAM) system on clinical outcome in patients undergoing catheter ablation for atrial fibrillation (AF).


METHODS AND RESULTS
Eighty patients with AF were randomized to undergo first-time wide encirclement of ipsilateral PV pairs using EAM alone (40 patients) or with CT (40 patients, Cartomerge). Wide encirclement of the pulmonary veins was performed using irrigated radiofrequency ablation with the electrophysiological endpoint of electrical isolation (EI). The primary endpoint was single-procedure success at 6 month follow up. Acute and long-term procedural outcomes were also determined. There was no significant difference in single procedure success between EAM (56%) and cavotricuspid isthmus image (CTI) (50%) groups (P = 0.9). Acute procedural outcomes (EI, PV reconnection, sinus rhythm restored by ablation in persistent AF), fluoroscopy, and procedure durations (EI of right PVs, EI of left PVs, total) did not differ significantly between EAM and CTI groups.


CONCLUSION
Image integration to guide catheter ablation for AF did not significantly improve the clinical outcome. Achieving PV EI is the critical determinant of procedural success rather than the mapping tools used to achieve it.
Higher infliximab trough levels are associated with perianal fistula healing in patients with Crohn's disease.

BACKGROUND
Infliximab has been found to be efficacious in the treatment of fistulas in the setting of Crohn's disease, even though some patients do not benefit from therapy.


AIM
To assess the correlation between perianal fistula healing and trough levels of infliximab.


METHODS
In this cross-sectional study, we identified patients with Crohn's disease who had perianal fistulas and were treated with infliximab for at least 24 weeks. We excluded patients who underwent a faecal diversion procedure or proctectomy. Predictive variables included demographics, disease phenotype, disease activity, infliximab levels, anti-infliximab antibodies. The primary outcome was fistula healing defined as the absence of drainage. The secondary outcome was complete fistula closure and mucosal healing.


RESULTS
117 patients were included. Patients with fistula healing had significantly higher median serum infliximab levels when compared to those with active fistulas [15.8 vs. 4.4 μg/mL, respectively (P < 0.0001)]. There was an incremental gain in fistula healing with higher infliximab levels. The AUC for the association between fistula healing and infliximab levels was 0.82 (P < 0.0001), while the AUC for the association of infliximab levels and fistula closure was 0.69 (P = 0.014). Patients with anti-infliximab antibodies had a lower chance of achieving fistula healing (OR: 0.04 [95%CI: 0.005-0.3], P < 0.001).


CONCLUSIONS
There is a significant association between serum infliximab levels and rates of fistula healing. Achieving infliximab levels ≥10.1 mcg/mL in patients with Crohn's disease and perianal fistulas may improve outcomes as part of a treat-to-target strategy.
Patient referral is influenced by dialysis centre structure in the Diamant Alpin Dialysis cohort study.

BACKGROUND
Late referral (LR) to the nephrologist of patients with progressing chronic kidney disease (CKD) has numerous deleterious effects and is observed in many countries. The contributing factors associated with LR are controversial and poorly defined. We hypothesized that these factors might be better identified by analysing patients starting dialysis in three distinct European countries within the same area.


METHOD
The referral and progression of kidney failure patterns were analysed with demographic, clinical and biological data in 279 non-selected consecutive patients starting dialysis in eight centres of three adjacent regions in France, Italy and Switzerland.


RESULTS
Early referral (>6 months before the start of dialysis) was seen in 200 patients (71.6%), intermediate referral (1-6 months) in 42 (15.1%) and LR (<1 month) in 37 (13.3%). However inter-centre variations were between 2 and 19% for LR and 6-50% for combined late and intermediate referral. There were no differences at the national levels, but LR was more frequent in the large city centres than in the private or regional structures, with 31 out of 169 (18.3%), two out of 55 (5.4%) and four out of 55 (7.3%), respectively, of their patients (P<0.01). By multivariate analysis, it appears that, besides the presence of an active cancer and the CKD progression rate, the centre structure and the referring physician (primary care physicians and nephrologists are less responsible for LR than other medical specialists) play a significant role in the practice of LR.


CONCLUSIONS
Within a dialysis cohort spread over adjacent regions of three countries, LR has the same global distribution pattern, indicating that different health and social security systems do not play a major role in inducing or preventing this practice. The contributing factors for LR that were identified are the type of the referring physician and the structure of the dialysis unit. Both factors are potential targets for an educational and collaborative approach.
A Visual Interface for Multivariate Temporal Data: Finding Patterns of Events across Multiple Histories

Finding patterns of events over time is important in searching patient histories, Web logs, news stories, and criminal activities. This paper presents PatternFinder, an integrated interface for query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets. We define temporal patterns as sequences of events with inter-event time spans. PatternFinder allows users to specify the attributes of events and time spans to produce powerful pattern queries that are difficult to express with other formalisms. We characterize the range of queries PatternFinder supports as users vary the specificity at which events and time spans are defined. Pattern Finder's query capabilities together with coupled ball-and-chain and tabular visualizations enable users to effectively query, explore and analyze event patterns both within and across data entities (e.g. patient histories, terrorist groups, Web logs, etc.)
Cost-Optimization of the IPv4 Zeroconf Protocol

We develop a stochastic model of a simple protocol for the self-configuration of IP network interfaces. We describe the mean cost that incurs during a selfconfiguration phase and describe a trade-off between reliability and speed. We derive a cost function which we use to derive optimal parameters. We show that optimal cost and optimal reliability are qualities that cannot be achieved at the same time. Keywords—Embedded control software; IP; zeroconf protocol; cost optimisation
Acute transverse myelitis with normal brain MRI

To investigate the long-term risk of developing MS in patients presenting with acute transverse myelitis (ATM) and normal brain MRI scans at onset. We studied 58 ATM patients with normal brain MRI at presentation for up to 5 years with serial neurologic and imaging studies. All patients underwent CSF analysis at onset which was defined positive if two or more IgG oligoclonal bands and/or elevated IgG index were present. Brain and spinal cord MRI scans were obtained every 6 months for the first 2 years, and annually thereafter unless the patient experienced a second neurologic attack different from the initial episode to confirm CDMS or there was demonstration of MRI lesions confirming dissemination in time and space to fulfill McDonald imaging criteria to diagnose MS. Seventeen of 58 (29%) patients developed MS of which 7 (41%) patients developed CDMS and 10 (59%) developed MS using McDonald Imaging Criteria. Mean time to CDMS by a second clinical attack was 11. 1 months compared to 19. 2 months by MRI lesions (P = 0. 03). None of the patients developed MS after 24 months of onset. All 17 patients who developed MS had positive CSF although 15 patients who had positive CSF did not develop MS during the 5 years of follow-up. The majority of patients with ATM and normal brain MRI do not develop MS after 5 years of follow-up confirming the relatively low risk compared to patients with abnormal brain MRI scans. CSF is helpful in distinguishing patients more likely to develop MS. Compared to clinical attacks, serial imaging may not lead to an earlier diagnosis in ATM patients with normal brain MRI.
A Petri Nets Model for Blockchain Analysis

Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Piazza D’Armi, 09100 Cagliari, Italy. Computer Science Dept. — Technion IIT Technion City, CS Taub Building, 3200003 Haifa, Israel. 3 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy. Email: a.pinna@diee.unica.it, roberto.tonelli@dsf.unica.it, matteo.orru@cs.technion.ac.il, marchesi@unica.it
Metabolic map and bioactivation of the anti-tumour drug noscapine.

BACKGROUND AND PURPOSE
Noscapine is a promising anti-tumour agent. The purpose of the present study was to describe the metabolic map and investigate the bioactivation of noscapine.


EXPERIMENTAL APPROACH
Ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry-based metabolomics was used to analyse the in vitro incubation mixtures, urine and faeces samples from mice treated with noscapine. Recombinant drug-metabolizing enzymes were employed to identify those involved in noscapine metabolism. Hepatic GSH levels and serum biochemistry were also carried out to determine reactive metabolites of noscapine.


KEY RESULTS
Several novel phase I metabolites of noscapine were detected after oral gavage of mice, including an N-demethylated metabolite, two hydroxylated metabolites, one metabolite undergoing both demethylation and cleavage of the methylenedioxy group and a bis-demethylated metabolite. Additionally, several novel glucuronides were detected, and their structures were elucidated through MS/MS fragmentology. Recombinant enzymes screening showed the involvement of several cytochromes P450, flavin-containing mono-oxygenase 1 and the UDP-glucuronosyltransferases UGT1A1, UGT1A3, UGT1A9 and UGT2B7, in noscapine metabolism. In vitro glutathione trapping revealed the existence of an ortho-quinone reactive intermediate formed through further oxidation of a catechol metabolite. However, this bioactivation process of noscapine does not occur in vivo. Similar to this result, altered glutathione levels in liver and serum biochemistry revealed no evidence of hepatic damage, thus indicating that, at least in mice, noscapine does not induce hepatotoxicity through bioactivation.


CONCLUSIONS AND IMPLICATIONS
A comprehensive metabolic map and bioactivation evaluation provides important information for the development of noscapine as an anti-tumour drug.
Outer trench-slope faulting and the 2011 M_w 9.0 off the Pacific coast of Tohoku Earthquake

The 11 March 2011 off the Pacific coast of Tohoku Earthquake (Mw 9.0) produced megathrust displacements of at least 40 m. The resulting tsunami devastated the Honshu coast southwest of regions struck by earthquakegenerated tsunami in 1611, 1896 and 1933. The 1896 Meiji-Sanriku earthquake was also an underthrusting earthquake, but the 1933 Sanriku-oki earthquake was a trench-slope normal faulting event; both generated inundation heights of 10 to 25 m along the coast of Iwate prefecture. Possible occurrence of a great outer trenchslope earthquake seaward of the 2011 Tohoku Earthquake along a southwestward extension of the 1933 fault zone is a concern. The second largest 2011 aftershock, an outer rise Mw 7.7 normal faulting earthquake occurred near the southern end of the 1933 rupture. Additional aftershock activity has been distributed along a trend below the trench and diffusely spread in the outer rise, seaward of the megathrust region where the largest slip occurred. Coulomb stress perturbations of at least 5–10 bars are calculated for outer rise normal fault geometries for mainshock slip models. Whether a future great trench slope event will occur is uncertain, but the potential tsunamigenic hazard can be gauged by the huge inundations accompanying the 1933 rupture.
Activation of YAP1 is associated with poor prognosis and response to taxanes in ovarian cancer.

AIM
We aimed to investigate the clinical significance of the activation of Yes-Associated Protein 1 (YAP1), a key downstream effector of Hippo tumor-suppressor pathway, in ovarian cancer.


MATERIALS AND METHODS
A gene expression signature reflecting activation of YAP1 was developed from gene expression data of 267 samples from patients with ovarian cancer. A refined ovarian cancer YAP1 signature was validated in an independent ovarian cancer cohort (n=185). Associations between the YAP1 signature and prognosis were assessed using Kaplan-Meier plots, the log-rank test, and a Cox proportional hazards model.


RESULTS
We identified a 612-gene expression signature reflecting YAP1 activation in ovarian cancer. In multivariate analysis, the signature was an independent predictor of overall survival (hazard ratio=1.66; 95% confidence interval=1.1 to 2.53; p=0.01). In subset analysis, the signature identified patients likely to benefit from taxane-based adjuvant chemotherapy.


CONCLUSION
Activation of YAP1 is significantly associated with prognosis and the YAP1 signature can predict response to taxane-based adjuvant chemotherapy in patients with ovarian cancer.
An acoustic segment model approach to incorporating temporal information into speaker modeling for text-independent speaker recognition

We propose an acoustic segment model (ASM) approach to incorporating temporal information into speaker modeling in text-independent speaker recognition. In training, the proposed framework first estimates a collection of ASM-based universal background models (UBMs). Multiple sets of speaker-specific ASMs are then obtained by adapting the ASM-based UBMs with speaker-specific enrollment data. A novel usage of language models of the ASM units is also proposed to characterize transitions among ASMs. In the testing phase the ASM sets for the claimed speaker and UBMs, along with a bigram ASM language model, are used to calculate detection scores for each given test utterance. We report on speaker recognition experiments using the NIST 2001 SRE database. The results clearly indicate that the proposed ASM-based method achieves a notable improvement over the GMM-based speaker modeling in which no temporal modeling is considered. Moreover, a further error reduction is obtained by integrating the language model, another inclusion of temporal properties made possibly by ASM based speaker modeling.
Does Active Learning Work ? A Review of the Research

This study examines the evidence for the effectiveness of active learning. It defines the common forms of active learning most relevant for engineering faculty and critically examines the core element of each method. It is found that there is broad but uneven support for the core elements of active, collaborative, cooperative and problem-based learning.
BERDS-BERkeley EneRgy Disaggregation Data Set

We first review some of the suggested methods for energy disaggregation. We then provide a real-life data set for researchers to help developing novel energy disaggregation algorithms. We also present a publicly available experimental data set captured from a typical building on the University of California, Berkeley campus.
Wind Speed Estimation Based Sensorless Output Maximization Control for a Wind Turbine Driving a DFIG

This paper proposes a wind speed estimation based sensorless maximum wind power tracking control for variable-speed wind turbine generators (WTGs). A specific design of the proposed control algorithm for a wind turbine equipped with a doubly fed induction generator (DFIG) is presented. The aerodynamic characteristics of the wind turbine are approximated by a Gaussian radial basis function network based nonlinear input-output mapping. Based on this nonlinear mapping, the wind speed is estimated from the measured generator electrical output power while taking into account the power losses in the WTG and the dynamics of the WTG shaft system. The estimated wind speed is then used to determine the optimal DFIG rotor speed command for maximum wind power extraction. The DFIG speed controller is suitably designed to effectively damp the low-frequency torsional oscillations. The resulting WTG system delivers maximum electrical power to the grid with high efficiency and high reliability without mechanical anemometers. The validity of the proposed control algorithm is verified by simulation studies on a 3.6MW WTG system. In addition, the effectiveness of the proposed wind speed estimation algorithm is demonstrated by experimental studies on a small emulational WTG system.
Traffic particles and occurrence of acute myocardial infarction: a case–control analysis

OBJECTIVES
We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry.


METHODS
Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI.


RESULTS
Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association.


CONCLUSIONS
These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale.
Alu elements: know the SINEs

Alu elements are primate-specific repeats and comprise 11% of the human genome. They have wide-ranging influences on gene expression. Their contribution to genome evolution, gene regulation and disease is reviewed.
DeepBound: accurate identification of transcript boundaries via deep convolutional neural fields

Motivation
Reconstructing the full-length expressed transcripts ( a.k.a. the transcript assembly problem) from the short sequencing reads produced by RNA-seq protocol plays a central role in identifying novel genes and transcripts as well as in studying gene expressions and gene functions. A crucial step in transcript assembly is to accurately determine the splicing junctions and boundaries of the expressed transcripts from the reads alignment. In contrast to the splicing junctions that can be efficiently detected from spliced reads, the problem of identifying boundaries remains open and challenging, due to the fact that the signal related to boundaries is noisy and weak.


Results
We present DeepBound, an effective approach to identify boundaries of expressed transcripts from RNA-seq reads alignment. In its core DeepBound employs deep convolutional neural fields to learn the hidden distributions and patterns of boundaries. To accurately model the transition probabilities and to solve the label-imbalance problem, we novelly incorporate the AUC (area under the curve) score into the optimizing objective function. To address the issue that deep probabilistic graphical models requires large number of labeled training samples, we propose to use simulated RNA-seq datasets to train our model. Through extensive experimental studies on both simulation datasets of two species and biological datasets, we show that DeepBound consistently and significantly outperforms the two existing methods.


Availability and implementation
DeepBound is freely available at https://github.com/realbigws/DeepBound .


Contact
mingfu.shao@cs.cmu.edu or realbigws@gmail.com.
The pi-index: a new indicator for assessing scientific impact

There are several simple and sophisticated scientometric indicators generally applied in the literature (e.g. total number of publications and citations, citations per journal paper, relative citedness indexes, Hirsch index, etc.), which may characterize the publications of scientists both qualitatively and quantitatively. The calculation methods generally use data referring to the total set of papers studied. Scientific progress, however, may be attributed primarily to information in the highly cited publications. Therefore, a new indicator (π-index) is suggested for comparative assessment of scientists active in similar subject fields. The π-index is equal to one hundredth of the number of citations obtained to the top square root of the total number of journal papers (‘elite set of papers’) ranked by the decreasing number of citations. The relation of the π-index to other indexes and its dependence on the field is studied, using data of journal papers of ‘highly cited researchers’.
Low omega-6 vs. low omega-6 plus high omega-3 dietary intervention for Chronic Daily Headache: Protocol for a randomized clinical trial

BACKGROUND
Targeted analgesic dietary interventions are a promising strategy for alleviating pain and improving quality of life in patients with persistent pain syndromes, such as chronic daily headache (CDH). High intakes of the omega-6 (n-6) polyunsaturated fatty acids (PUFAs), linoleic acid (LA) and arachidonic acid (AA) may promote physical pain by increasing the abundance, and subsequent metabolism, of LA and AA in immune and nervous system tissues. Here we describe methodology for an ongoing randomized clinical trial comparing the metabolic and clinical effects of a low n-6, average n-3 PUFA diet, to the effects of a low n-6 plus high n-3 PUFA diet, in patients with CDH. Our primary aim is to determine if: A) both diets reduce n-6 PUFAs in plasma and erythrocyte lipid pools, compared to baseline; and B) the low n-6 plus high n-3 diet produces a greater decline in n-6 PUFAs, compared to the low n-6 diet alone. Secondary clinical outcomes include headache-specific quality-of-life, and headache frequency and intensity.


METHODS
Adults meeting the International Classification of Headache Disorders criteria for CDH are included. After a 6-week baseline phase, participants are randomized to a low n-6 diet, or a low n-6 plus high n-3 diet, for 12 weeks. Foods meeting nutrient intake targets are provided for 2 meals and 2 snacks per day. A research dietitian provides intensive dietary counseling at 2-week intervals. Web-based intervention materials complement dietitian advice. Blood and clinical outcome data are collected every 4 weeks.


RESULTS
Subject recruitment and retention has been excellent; 35 of 40 randomized participants completed the 12-week intervention. Preliminary blinded analysis of composite data from the first 20 participants found significant reductions in erythrocyte n-6 LA, AA and %n-6 in HUFA, and increases in n-3 EPA, DHA and the omega-3 index, indicating adherence.


TRIAL REGISTRATION
ClinicalTrials.gov (NCT01157208).