Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in ...medicine by transforming collected data into clinically significant information. The objective of this research is to assess the performance of a deep learning algorithm to detect murmurs and clinically significant valvular heart disease using recordings from a commercial digital stethoscope platform. Methods and Results Using >34 hours of previously acquired and annotated heart sound recordings, we trained a deep neural network to detect murmurs. To test the algorithm, we enrolled 962 patients in a clinical study and collected recordings at the 4 primary auscultation locations. Ground truth was established using patient echocardiograms and annotations by 3 expert cardiologists. Algorithm performance for detecting murmurs has sensitivity and specificity of 76.3% and 91.4%, respectively. By omitting softer murmurs, those with grade 1 intensity, sensitivity increased to 90.0%. Application of the algorithm at the appropriate anatomic auscultation location detected moderate-to-severe or greater aortic stenosis, with sensitivity of 93.2% and specificity of 86.0%, and moderate-to-severe or greater mitral regurgitation, with sensitivity of 66.2% and specificity of 94.6%. Conclusions The deep learning algorithm's ability to detect murmurs and clinically significant aortic stenosis and mitral regurgitation is comparable to expert cardiologists based on the annotated subset of our database. The findings suggest that such algorithms would have utility as front-line clinical support tools to aid clinicians in screening for cardiac murmurs caused by valvular heart disease. Registration URL: https://clinicaltrials.gov; Unique Identifier: NCT03458806.
Accurate and timely characterization of physical properties pertinent to plutonium bearing materials is important for fulfilling nuclear nonproliferation and safeguards goals. Physical properties ...include the fissile mass, leakage multiplication, and the α-ratio, defined as the ratio of (α,n) neutrons to spontaneous fission neutrons. Traditionally, these properties can be inferred by relating the measured neutron multiplicity count rates to the well-established point kinetics moments equations; the current state-of-the-art utilizes 3He-based detection systems. Organic scintillators have been used extensively to study and measure characteristic signatures in the neutron angular and energy distributions. Previous work has proposed techniques that independently leverage the energy and angle sensitivity of organic scintillators to estimate the α-ratio of plutonium bearing material; however, it is expected that the energy and angular distributions are correlated to one another due to the underlying physics of fission and (α,n) neutron emissions. This work presents experimental results that characterize neutron-neutron angular distribution and subsequently the neutron-neutron energy-angle correlations for plutonium samples of similar mass and multiplication, but varying α-ratio due to the type of low-Z impurity. Full neutron-neutron angular distributions are presented using a low-energy detection threshold of 0.10, 0.15, and 0.20 MeVee (0.73, 0.96, 1.16 MeV neutron-equivalent energy). Neutron anisotropy was quantified by taking the ratio of neutron-neutron coincidences at 180°to those at 90°, where a value of unity indicates a purely isotropic source. The results show that the observed neutron-neutron correlations transition away from fission-induced signal to the cross-talk signal associated with single (α,n) neutrons with increasing α-ratio. Energy-angle correlations are characterized by calculating the neutron anisotropy at various detection thresholds and show positive correlation between the observed anisotropy and the energy of the neutrons.
The reactivity and the k-effective multiplication factor (keff) of a fissionable assembly are quantities of widespread interest. These values can be inferred from Rossi-alpha measurements of the ...prompt neutron decay constant (or the inverse: α−1). It has been shown that 3He-gas proportional counter-based detection systems are insensitive to α−1 of fast assemblies (much faster than tens of microseconds). Therefore, it is of interest to investigate fast detection systems such as those based on organic scintillation detectors. In this work, an array of 12 cylindrical, 5.08 cm × 5.08 cm diameter trans-stilbene organic scintillators was used to measure five subcritical assemblies. One assembly was a sphere of approximately 4.5 kg of alpha-phase, weapons-grade plutonium (keff=0.773, α−1=11.84ns) known as the BeRP ball encased in a thin stainless-steel clad. The other assemblies used the same encased sphere and 7.62 cm of iron, nickel, copper, or tungsten reflectors (keff=0.884,0.916,0.924,0.939, respectively and α−1=36.60,41.56,49.60,70.32ns, respectively). This work (1) validates Rossi-alpha measurements with organic scintillators by demonstrating good agreement between measurements and simulations; and (2), demonstrates that organic scintillator-based systems are sensitive to α−1 on the order of 10–100 ns.
We present cisTopic, a probabilistic framework used to simultaneously discover coaccessible enhancers and stable cell states from sparse single-cell epigenomics data ( ...http://github.com/aertslab/cistopic ). Using a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain and transcription factor perturbations, we demonstrate that topic modeling can be exploited for robust identification of cell types, enhancers and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity in cell populations.
Inferring a Gene Regulatory Network (GRN) from gene expression data is a computationally expensive task, exacerbated by increasing data sizes due to advances in high-throughput gene profiling ...technology, such as single-cell RNA-seq. To equip researchers with a toolset to infer GRNs from large expression datasets, we propose GRNBoost2 and the Arboreto framework. GRNBoost2 is an efficient algorithm for regulatory network inference using gradient boosting, based on the GENIE3 architecture. Arboreto is a computational framework that scales up GRN inference algorithms complying with this architecture. Arboreto includes both GRNBoost2 and an improved implementation of GENIE3, as a user-friendly open source Python package.
Arboreto is available under the 3-Clause BSD license at http://arboreto.readthedocs.io.
Supplementary data are available at Bioinformatics online.
Aim
To explore the experience of parents of children diagnosed with Phelan–McDermid syndrome (PMS) with regard to the diagnostic process, treatment, and medical care.
Method
A qualitative descriptive ...study was conducted. Participants were recruited using non‐probabilistic purposeful sampling. In total, 32 parents with children with PMS were included. In‐depth interviews and researcher field notes were used. An inductive thematic analysis was performed.
Results
Five themes were identified: (1) the ‘diagnostic process’ describes the diagnostic process and how it is communicated to the parents; (2) ‘treatment and expectations’ describes the expectations and hopes placed on future treatment; (3) ‘family planning’ describes how parents deal with genetic counselling when planning to have more children after a diagnosis of PMS; (4) ‘the world of disability’ describes the entry of parents into an environment of dependency and disability after the diagnosis; (5) ‘family's financial situation’ highlights the financial difficulties due to the high cost of therapies and daily care products.
Interpretation
Our results provide insight on how a diagnosis of PMS and its consequences are experienced by parents of children with PMS. These results can be used by health professionals to help and support parents.
In this study, we describe the perceptions of parents of children with Phelan–McDermid syndrome and their experience in the process of diagnosis and care.
This original article is commented on by Phelan on pages 862–863 of this issue.
Spanish translation of this Original Article are available in the online issue.
Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides ...attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.
The diversity of cell types and regulatory states in the brain, and how these change during aging, remains largely unknown. We present a single-cell transcriptome atlas of the entire adult Drosophila ...melanogaster brain sampled across its lifespan. Cell clustering identified 87 initial cell clusters that are further subclustered and validated by targeted cell-sorting. Our data show high granularity and identify a wide range of cell types. Gene network analyses using SCENIC revealed regulatory heterogeneity linked to energy consumption. During aging, RNA content declines exponentially without affecting neuronal identity in old brains. This single-cell brain atlas covers nearly all cells in the normal brain and provides the tools to study cellular diversity alongside other Drosophila and mammalian single-cell datasets in our unique single-cell analysis platform: SCope (http://scope.aertslab.org). These results, together with SCope, allow comprehensive exploration of all transcriptional states of an entire aging brain.
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•A single-cell atlas of the adult fly brain during aging•Network inference reveals regulatory states related to oxidative phosphorylation•Cell identity is retained during aging despite exponential decline of gene expression•SCope: An online tool to explore and compare single-cell datasets across species
A single-cell atlas of adult fly brains identifies the ensemble of neuronal and glial cell types and their dynamic changes during aging.
To carry out a systematic review about the information about the application of of virtual reality and videogames in cardiac rehabilitation.
A systematic review was conducted. Jadad scale was applied ...to evaluate the methodological quality of the articles included and the degree of evidence and the level of recommendation were determined through the Oxford Center for Evidence-Based Medicine. PRISMA guidelines statement for systematic reviews were followed.
The total number of articles included in the present review was 10, with heterogeneity in the study populations, cardiac rehabilitation phases, technology used and protocols. Most of the studies showed an increase in heart rate, less pain, a greater ability to walk, higher energy levels, an increase in physical activity and improvements of motivation and adherence. The methodological quality of the studies was between acceptable and poor.
The use of virtual reality and videogames could be considered as complementary tools of physical training in patients with cardiovascular diseases in the different phases of cardiac rehabilitation. However, it is also necessary to carry out studies with adequate methodological quality to determine the ideal technological systems, target populations and clearly protocols to study their effects in the short, medium and long-term assessments.
Implications for rehabilitation
The use of virtual reality and videogames could be considered as complementary tools for physical training in patients with cardiovascular diseases.
Interactive virtual reality using exergames may promote heart rate, fatigue perception, physical activity and reduce pain in patients with cardiovascular diseases.
Virtual reality and videogames enhance motivation and adherence in cardiac rehabilitation programs.
Purpose
Coffee is rich in bioactive compounds with health beneficial properties, with green coffee presenting higher phenol content than roasted. We evaluated the effects of regularly consuming ...realistic amounts of a green/roasted coffee blend on cardiovascular health-related biomarkers.
Methods
A randomized, cross-over, controlled study was carried out in 25 normocholesterolemic total cholesterol (TC) < 200 mg/dL and 27 hypercholesterolemic (TC 200–240 mg/dL) subjects. During 8 weeks, volunteers consumed 6 g/day of soluble green/roasted (35:65) coffee or a control beverage (water or an isotonic drink). Blood pressure, heart rate and body weight were monitored at the end of each intervention, and serum lipids TC, HDL-C, LDL-C, VLDL-C, triglycerides and phospholipids, cytokines and chemokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-10, IL-12, IL-13, IL-17, G-CSF, GM-CSF, MCP-1, MIP-1β, TNF-α, INF-γ), adhesion molecules (ICAM-1, VCAM-1), and C-reactive protein were measured. Plasma antioxidant capacity (FRAP, ORAC and ABTS methods), and lipid (malondialdehyde, MDA) and protein (carbonyl groups, CG) oxidation were also determined.
Results
Attending to the general lineal model of variance for repeated measures, after the green/roasted coffee intervention significant reductions in TC, LDL-C, VLDL-C and triglycerides levels (
p
= 0.006, 0.001, 0.003 and 0.017, respectively), and a significant group effect were observed (0.001, < 0.001, 0.019 and 0.027, respectively). Only within the hypercholesterolemic group, attending to the Bonferroni test, the aforementioned lipid parameters were significantly lower after regular green/roasted coffee intake compared to baseline values. Moreover, after the coffee stage, plasma antioxidant capacity improved, according to the increase in ORAC and FRAP values (
p
< 0.001 and
p
< 0.001, respectively) and decrease of MDA (
p
= 0.015) and CG (
p
< 0.001) levels, without differences between groups. Systolic (
p
= 0.001) and diastolic (
p
< 0.001) blood pressure, heart rate (
p
= 0.035), and body weight (
p
= 0.017) were reduced in both normo- and hypercholesterolemic groups.
Conclusion
Regular consumption of moderate amounts of a soluble green/roasted (35:65) coffee blend may contribute to improve cardiovascular health in moderately hypercholesterolemic people, as reducing serum lipids, blood pressure and body weight effects, as well as increasing plasma antioxidant capacity, have been observed. Moreover, positive influences on blood pressure, body weight, and plasma antioxidant capacity were obtained in the healthy group. Therefore, incorporation of green coffee beans into the coffee brew can be recommended as part of a dietary strategy to protect from cardiovascular disease.
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