Discovering and Visualizing Disease-Specific Electrocardiogram Features Using Deep Learning: Proof-of-Concept in Phospholamban Gene Mutation Carriers

BACKGROUND: ECG interpretation requires expertise and is mostly based on physician recognition of specific patterns, which may be challenging in rare cardiac diseases. Deep neural networks (DNNs) can discover complex features in ECGs and may facilitate the detection of novel features which possibly play a pathophysiological role in relatively unknown diseases. Using a cohort of PLN (phospholamban) p.Arg14del mutation carriers, we aimed to investigate whether a novel DNN-based approach can identify established ECG features, but moreover, we aimed to expand our knowledge on novel ECG features in these patients. METHODS: A DNN was developed on 12-lead median beat ECGs of 69 patients and 1380 matched controls and independently evaluated on 17 patients and 340 controls. Differentiating features were visualized using Guided Gradient Class Activation Mapping++. Novel ECG features were tested for their diagnostic value by adding them to a logistic regression model including established ECG features. RESULTS: The DNN showed excellent discriminatory performance with a c-statistic of 0.95 (95% CI, 0.91-0.99) and sensitivity and specificity of 0.82 and 0.93, respectively. Visualizations revealed established ECG features (low QRS voltages and T-wave inversions), specified these features (eg, R- and T-wave attenuation in V2/V3) and identified novel PLN-specific ECG features (eg, increased PR-duration). The logistic regression baseline model improved significantly when augmented with the identified features (P<0.001). CONCLUSIONS: A DNN-based feature detection approach was able to discover and visualize disease-specific ECG features in PLN mutation carriers and revealed yet unidentified features. This novel approach may help advance diagnostic capabilities in daily practice

Internal and external cooling methods and their effect on body temperature, thermal perception and dexterity

© 2018 The Authors. Published by PLOS. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0191416© 2018 Maley et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective The present study aimed to compare a range of cooling methods possibly utilised by occupational workers, focusing on their effect on body temperature, perception and manual dexterity. Methods Ten male participants completed eight trials involving 30 min of seated rest followed by 30 min of cooling or control of no cooling (CON) (34C, 58% relative humidity). The cooling methods utilised were: ice cooling vest (CV0), phase change cooling vest melting at 14C (CV14), evaporative cooling vest (CVEV), arm immersion in 10C water (AI), portable water-perfused suit (WPS), heliox inhalation (HE) and ice slushy ingestion (SL). Immediately before and after cooling, participants were assessed for fine (Purdue pegboard task) and gross (grip and pinch strength) manual dexterity. Rectal and skin temperature, as well as thermal sensation and comfort, were monitored throughout. Results Compared with CON, SL was the only method to reduce rectal temperature (P = 0.012). All externally applied cooling methods reduced skin temperature (P0.05). Conclusion The present study observed that ice ingestion or ice applied to the skin produced the greatest effect on rectal and skin temperature, respectively. AI should not be utilised if workers require subsequent fine manual dexterity. These results will help inform future studies investigating appropriate pre-cooling methods for the occupational worker.This project is financially supported by the US Government through the Technical Support Working Group within the Combating Terrorism Technical Support Office.Published versio

Coming from behind to win - A Qualitative research about psychological conditions of adolescents who have undergone open-heart surgery for single ventricle between the ages 0-5

Early recognition of congenital cardiac pathologies and their treatment by means of palliative or corrective surgery at birth or infancy has vital importance. Successful repair of congenital cardiac defects by surgical methods has gained importance especially during the last twenty years. As the scope of the surveillance increased so did the interest in the outcomes of these treatments when the patients had reached puberty and adulthood. The purpose of our research was to study the psychological framework of the adolescents who had experienced these surgeries by listening both the children and the parents talk about their feelings and experiences. Our data was accumulated through interviews with 17 adolescents and their families, using qualitative methods. The main theme at the end of the analysis was "to be strong and resistive". We reached the conclusion that this condition was not a pathological build up but an attitude of coping, as it did not cause loss of functionality. The defensive psychological mechanisms used by these adolescents consisted of repression, compensation and reaction formation. We believe that this information is important to understand the real meaning of the manners displayed when these adolescents and their families pursue their daily lives, communicate and make relationships with their environment and especially professionals in the health services

Characterization, high-resolution mapping and differential expression of three homologous PAL genes in Coffea canephora Pierre (Rubiaceae)

Phenylalanine ammonia lyase (PAL) is the first entry enzyme of the phenylpropanoid pathway producing phenolics, widespread constituents of plant foods and beverages, including chlorogenic acids, polyphenols found at remarkably high levels in the coffee bean and long recognized as powerful antioxidants. To date, whereas PAL is generally encoded by a small gene family, only one gene has been characterized in Coffea canephora (CcPAL1), an economically important species of cultivated coffee. In this study, a molecular- and bioinformatic-based search for CcPAL1 paralogues resulted successfully in identifying two additional genes, CcPAL2 and CcPAL3, presenting similar genomic structures and encoding proteins with close sequences. Genetic mapping helped position each gene in three different coffee linkage groups, CcPAL2 in particular, located in a coffee genome linkage group (F) which is syntenic to a region of Tomato Chromosome 9 containing a PAL gene. These results, combined with a phylogenetic study, strongly suggest that CcPAL2 may be the ancestral gene of C. canephora. A quantitative gene expression analysis was also conducted in coffee tissues, showing that all genes are transcriptionally active, but they present distinct expression levels and patterns. We discovered that CcPAL2 transcripts appeared predominantly in flower, fruit pericarp and vegetative/lignifying tissues like roots and branches, whereas CcPAL1 and CcPAL3 were highly expressed in immature fruit. This is the first comprehensive study dedicated to PAL gene family characterization in coffee, allowing us to advance functional studies which are indispensable to learning to decipher what role this family plays in channeling the metabolism of coffee phenylpropanoids

On the Computational Overhead of MPC with Dishonest Majority

We consider the situation where a large number $n$ of players want to securely compute a large function $f$ with security against an adaptive, malicious adversary which might corrupt $t < cn$ of the parties for some given $c \in [0,1)$. In other words, only some arbitrarily small constant fraction of the parties are assumed to be honest. For any fixed $c$, we consider the asymptotic complexity as $n$ and the size of $f$ grows. We are in particular interested in the computational overhead, defined as the total computational complexity of all parties divided by the size of $f$. We show that it is possible to achieve poly-logarithmic computational overhead for all $c < 1$. Prior to our result it was only known how to get poly-logarithmic overhead for $c < \frac{1}{2}$. We therefore significantly extend the area where we can do secure multiparty computation with poly-logarithmic overhead. Since we allow that more than half the parties are corrupted, we can only get security with abort, i.e., the adversary might make the protocol abort before all parties learn their outputs. We can, however, for all $c$ make a protocol for which there exists $d > 0$ such that if at most $d n$ parties are actually corrupted in a given execution, then the protocol will not abort. Our result is solely of theoretical interest

Challenges Predicting Ligand-Receptor Interactions of Promiscuous Proteins: The Nuclear Receptor PXR

Transcriptional regulation of some genes involved in xenobiotic detoxification and apoptosis is performed via the human pregnane X receptor (PXR) which in turn is activated by structurally diverse agonists including steroid hormones. Activation of PXR has the potential to initiate adverse effects, altering drug pharmacokinetics or perturbing physiological processes. Reliable computational prediction of PXR agonists would be valuable for pharmaceutical and toxicological research. There has been limited success with structure-based modeling approaches to predict human PXR activators. Slightly better success has been achieved with ligand-based modeling methods including quantitative structure-activity relationship (QSAR) analysis, pharmacophore modeling and machine learning. In this study, we present a comprehensive analysis focused on prediction of 115 steroids for ligand binding activity towards human PXR. Six crystal structures were used as templates for docking and ligand-based modeling approaches (two-, three-, four- and five-dimensional analyses). The best success at external prediction was achieved with 5D-QSAR. Bayesian models with FCFP_6 descriptors were validated after leaving a large percentage of the dataset out and using an external test set. Docking of ligands to the PXR structure co-crystallized with hyperforin had the best statistics for this method. Sulfated steroids (which are activators) were consistently predicted as non-activators while, poorly predicted steroids were docked in a reverse mode compared to 5α-androstan-3β-ol. Modeling of human PXR represents a complex challenge by virtue of the large, flexible ligand-binding cavity. This study emphasizes this aspect, illustrating modest success using the largest quantitative data set to date and multiple modeling approaches

The 12p13.33/RAD52 locus and genetic susceptibility to squamous cell cancers of upper aerodigestive tract

Acknowledgments: The authors thank all of the participants who took part in this research and the funders and support and technical staff who made this study possible. We also acknowledge and thank The Cancer Genome Atlas initiative whose data contributed heavily to this study. Funding: Funding for study coordination, genotyping of replication studies and statistical analysis was provided by the US National Institutes of Health (R01 CA092039 05/05S1) and the National Institute of Dental and Craniofacial Research (1R03DE020116). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

IPCC reasons for concern regarding climate change risks

The reasons for concern framework communicates scientific understanding about risks in relation to varying levels of climate change. The framework, now a cornerstone of the IPCC assessments, aggregates global risks into five categories as a function of global mean temperature change. We review the framework's conceptual basis and the risk judgments made in the most recent IPCC report, confirming those judgments in most cases in the light of more recent literature and identifying their limitations. We point to extensions of the framework that offer complementary climate change metrics to global mean temperature change and better account for possible changes in social and ecological system vulnerability. Further research should systematically evaluate risks under alternative scenarios of future climatic and societal conditions

The Spread of Inequality

The causes of socioeconomic inequality have been debated since the time of Plato. Many reasons for the development of stratification have been proposed, from the need for hierarchical control over large-scale irrigation systems to the accumulation of small differences in wealth over time via inheritance processes. However, none of these explains how unequal societies came to completely displace egalitarian cultural norms over time. Our study models demographic consequences associated with the unequal distribution of resources in stratified societies. Agent-based simulation results show that in constant environments, unequal access to resources can be demographically destabilizing, resulting in the outward migration and spread of such societies even when population size is relatively small. In variable environments, stratified societies spread more and are also better able to survive resource shortages by sequestering mortality in the lower classes. The predictions of our simulation are provided modest support by a range of existing empirical studies. In short, the fact that stratified societies today vastly outnumber egalitarian societies may not be due to the transformation of egalitarian norms and structures, but may instead reflect the more rapid migration of stratified societies and consequent conquest or displacement of egalitarian societies over time