Deep learning for healthcare applications based on physiological signals: A review

Background and objective: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.2017. Methods: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review. Results: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input. Conclusions: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosi

Global fjords as transitory reservoirs of labile organic carbon modulated by organo-mineral interactions

Funding: This work is financially supported by the Shanghai Frontiers Science Center of Polar Science (SCOPS), National Natural Science Foundation of China (NSFC) for Excellent Young Scientists Fund Program (Overseas). J.C.F. has been supported by the European Community’s 7th Framework Programme FP7 2007/2013, Marie-Curie Actions (grant no. 238111).The global carbon cycle is strongly modulated by organic carbon (OC) sequestration and decomposition. Whereas the extent of OC sequestration is relatively well-constrained in marine sedimentary basins, there are few quantitative estimates of its susceptibility to decomposition. Fjords are widely distributed hotspots of sedimentation, and currently account for 11% of annual OC burial in marine sediments. Here, we adopt fjords as model systems to investigate the reactivity of sedimentary OC by assessing the distribution of the activation energy (termed E) required to break OC covalent bonds. Our results reveal that OC in fjord sediments is more labile than that in global sediments, which is governed by unique OC provenance and organo-mineral interactions. We estimated that 61±16% of the sedimentary OC in fjords is degradable. Once this OC is remobilized and remineralized during glacial periods (sea level lowstands), the CO2 produced could counterbalance up to 50 ppm of atmospheric CO2 decrease in glacial times, making fjords critical actors in dampening glacial-interglacial climate fluctuations through negative carbon cycling loops.Publisher PDFPeer reviewe

Occurrence of Rhabditid Nematodes in the Pet Giant African Land Snails (Achatina fulica)

Gastropods comprise nearly 60,000 species of aquatic as well as terrestrial mollusks, primarily snails and slugs. The giant African land snail (Achatina fulica) is one of the most popular pet snails worldwide. This gastropod mollusk is known as the intermediate host of several parasites that cause severe diseases in pets, free-ranging vertebrates, and humans. The aim of this survey was to investigate the occurrence of parasites in giant African land snails kept as pets in southern Italy. Fresh fecal samples were collected from a total of 60 giant African land snails kept in three private collections in Campania region (Italy). In addition, microscopic analysis of mucus and histological examination of biopsy samples from the foot muscle of 30 individual snails were performed. Coprological examination revealed the presence of rhabditid nematodes identified by both morphological and molecular assessment as Rhabditella axei in two out of three examined samples, and Rhabditis terricola, Cruznema sp., and Pristionchus entomophagus in one coprological sample. No parasites were detected in the muscle biopsy samples, or in the mucus. Due to the potential harm of rhabditid nematodes, their presence in giant African land snails potentially in contact with both pets and humans should not be disregarded

Experimental realization of on-chip topological nanoelectromechanical metamaterials

Topological mechanical metamaterials translate condensed matter phenomena, like non-reciprocity and robustness to defects, into classical platforms. At small scales, topological nanoelectromechanical metamaterials (NEMM) can enable the realization of on-chip acoustic components, like unidirectional waveguides and compact delay-lines for mobile devices. Here, we report the experimental realization of NEMM phononic topological insulators, consisting of two-dimensional arrays of free-standing silicon nitride (SiN) nanomembranes that operate at high frequencies (10-20 MHz). We experimentally demonstrate the presence of edge states, by characterizing their localization and Dirac cone-like frequency dispersion. Our topological waveguides also exhibit robustness to waveguide distortions and pseudospin-dependent transport. The suggested devices open wide opportunities to develop functional acoustic systems for high-frequency signal processing applications

Application of Social Network Analysis to Health Care Sectors

Objectives: This study aimed to examine the feasibility of social network analysis as a valuable research tool for indicating a change in research topics in health care and medicine. Methods: Papers used in the analysis were collected from the PubMed database at the National Library of Medicine. After limiting the search to papers affiliated with the National Institutes of Health, 27,125 papers were selected for the analysis. From these papers, the top 100 non-duplicate and most studied Medical Subject Heading terms were extracted. NetMiner V.3 was used for analysis. Weighted degree centrality was applied to the analysis to compare the trends in the change of research topics. Changes in the core keywords were observed for the entire group and in three-year intervals. Results: The core keyword with the highest centrality value was “Risk Factor, ” followed b

HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments

Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited scalability and hence inability to cater to the requirements of centralized Internet of Things (IoT) based compute environments. The main reason for this is that latency-sensitive applications like health monitoring and surveillance systems now require computation over large amounts of data (Big Data) transferred to centralized database and from database to cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide innovative solutions by bringing resources closer to the user and provide low latency and energy-efficient solutions for data processing compared to cloud domains. Still, the current fog models have many limitations and focus from a limited perspective on either accuracy of results or reduced response time but not both. We proposed a novel framework called HealthFog for integrating ensemble deep learning in Edge computing devices and deployed it for a real-life application of automatic Heart Disease analysis. HealthFog delivers healthcare as a fog service using IoT devices and efficiently manages the data of heart patients, which comes as user requests. Fog-enabled cloud framework, FogBus is used to deploy and test the performance of the proposed model in terms of power consumption, network bandwidth, latency, jitter, accuracy and execution time. HealthFog is configurable to various operation modes that provide the best Quality of Service or prediction accuracy, as required, in diverse fog computation scenarios and for different user requirements

Preliminary Assessment of the Efficacy of a T-Cell–Based Influenza Vaccine, MVA-NP+M1, in Humans

A single vaccination with MVA-NP+M1 boosts T-cell responses to conserved influenza antigens in humans. Protection against influenza disease and virus shedding was demonstrated in an influenza virus challenge study

Enantio‐ and Diastereoselective Cyclopropanation of 1‐Alkenylboronates : Synthesis of 1‐Boryl‐2,3‐Disubstituted Cyclopropanes

A novel, highly enantio- and diastereoselective synthesis of 1-boryl-2,3-disubstituted cyclopropanes has been developed by means of the cyclopropanation of alkenylboronates with ethyl diazoacetate in the presence of catalytic amounts of a chiral copper(I) complex. The products can also be directly accessed from alkynes through an operationally simple, sequential hydroboration–cyclopropanation protocol. The resulting enantioenriched 1-boryl-2,3-disubstituted cyclopropanes are versatile synthetic intermediates that undergo further transformations at the carbon–boron bond.We thank MINECO for financial support (CTQ2014-52769- C03-01-R and Juan de la Cierva fellow for J.C.) and Junta de Andaluc a (P12-FQM-1765). We also thank Riccardo Gava and Cristina Gonzalez for additional experiments and Francisco Molina for X-ray diffraction studies

A major QTL controlling apple skin russeting maps on the linkage group 12 of 'Renetta Grigia di Torriana'

Background: Russeting is a disorder developed by apple fruits that consists of cuticle cracking followed by the replacement of the epidermis by a corky layer that protects the fruit surface from water loss and pathogens. Although influenced by many environmental conditions and orchard management practices, russeting is under genetic control. The difficulty in classifying offspring and consequent variable segregation ratios have led several authors to conclude that more than one genetic determinant could be involved, although some evidence favours a major gene (Ru). Results: In this study we report the mapping of a major genetic russeting determinant on linkage group 12 of apple as inferred from the phenotypic observation in a segregating progeny derived from 'Renetta Grigia di Torriana', the construction of a 20 K Illumina SNP chip based genetic map, and QTL analysis. Recombination analysis in two mapping populations restricted the region of interest to approximately 400 Kb. Of the 58 genes predicted from the Golden Delicious sequence, a putative ABCG family transporter has been identified. Within a small set of russeted cultivars tested with markers of the region, only six showed the same haplotype of 'Renetta Grigia di Torriana'. Conclusions: A major determinant (Ru_RGT) for russeting development putatively involved in cuticle organization is proposed as a candidate for controlling the trait. SNP and SSR markers tightly co-segregating with the Ru_RGT locus may assist the breeder selection. The observed segregations and the analysis of the 'Renetta Grigia di Torriana' haplotypic region in a panel of russeted and non-russeted cultivars may suggest the presence of other determinants for russeting in apple

Variations in TcdB Activity and the Hypervirulence of Emerging Strains of Clostridium difficile

Hypervirulent strains of Clostridium difficile have emerged over the past decade, increasing the morbidity and mortality of patients infected by this opportunistic pathogen. Recent work suggested the major C. difficile virulence factor, TcdB, from hypervirulent strains (TcdBHV) was more cytotoxic in vitro than TcdB from historical strains (TcdBHIST). The current study investigated the in vivo impact of altered TcdB tropism, and the underlying mechanism responsible for the differences in activity between the two forms of this toxin. A combination of protein sequence analyses, in vivo studies using a Danio rerio model system, and cell entry combined with fluorescence assays were used to define the critical differences between TcdBHV and TcdBHIST. Sequence analysis found that TcdB was the most variable protein expressed from the pathogenicity locus of C. difficile. In line with these sequence differences, the in vivo effects of TcdBHV were found to be substantially broader and more pronounced than those caused by TcdBHIST. The increased toxicity of TcdBHV was related to the toxin's ability to enter cells more rapidly and at an earlier stage in endocytosis than TcdBHIST. The underlying biochemical mechanism for more rapid cell entry was identified in experiments demonstrating that TcdBHV undergoes acid-induced conformational changes at a pH much higher than that of TcdBHIST. Such pH-related conformational changes are known to be the inciting step in membrane insertion and translocation for TcdB. These data provide insight into a critical change in TcdB activity that contributes to the emerging hypervirulence of C. difficile