1,007 research outputs found
Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change
BACKGROUND: Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs. RESULTS: Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA. CONCLUSION: The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a comparable or more accurate tool than RNAz or QRNA in genomic screens, especially for low-identity regions. Dynalign provides a method for discovering ncRNAs in sequenced genomes that other methods may not identify. Significant improvements in Dynalign runtime have also been achieved
High LET, passive space radiation dosimetry and spectrometry
The development of high linear energy transfer (LET), passive radiation dosimetry and spectrometry is needed for the purpose of accurate determination of equivalent doses and assessment of health risks to astronauts on long duration missions. Progress in the following research areas is summerized: intercomparisons of cosmic ray equivalent dose and LET spectra measurements between STS missions and between astronauts; increases LET spectra measurement accuracy with ATAS; space radiation measurements for intercomparisons of passive (PNTD, TLD, TRND, Emulsion) and active (TEPC, RME-111) dosimeters; interaction of cosmic ray particles with nuclei in matter; radiation measurements after long duration space exposures; ground based dosimeter calibrations; neutron detector calibrations; radiation measurements on Soviet/Russian spacecraft; space radiation measurements under thin shielding; and space radiation
Identifying well‐being profiles and resilience characteristics in ex‐members of fundamentalist Christian faith communities
There is a lack of empirical research on the heterogeneity in well-being of individuals who disaffiliated (i.e., left or were expelled) from an exclusionary and demanding faith community. Thus, little quantitative knowledge exists on factors related to resilience in these individuals. Therefore, the study aims were twofold: (1) to identify profiles of well-being in ex-members; and (2) to examine the characteristics of the identified profiles. A cross-sectional online survey assessed ex-members of various fundamentalist Christian faith communities. Latent profile analysis identified latent heterogeneity within the sample. Well-being profile indicators included perceived stress, psychopathological symptoms, affect, and satisfaction with life. Profile-related characteristics included socio-demographics (i.e., gender, age), membership (i.e., reason for joining, duration, extent of involvement, reasons for exit, social support during exit, and time since the exit), and resilience-supporting resources (i.e., social support, self-esteem, sense of coherence, personality, socio-economic status). In the final sample (N = 622, Mage = 41.34 years; 65.60% female), four distinct profiles were identified: resilient (25.70%), normative (36.40%), vulnerable (27.20%), and adverse (10.70%). The resilient profile was characterised by higher age, lower reporting of abuse or maltreatment as exit reason, and highest levels of resilience-supporting resources. Ex-members of fundamentalist Christian faith communities differ substantially in their well-being. Membership aspects were only weakly related to current well-being, with the exception of the exit reason of abuse or maltreatment. This study provided novel quantitative insights into the well-being profiles of individuals who disaffiliated from a fundamentalist Christian faith community in German-speaking countries
Fast fully automatic segmentation of the severely abnormal human right ventricle from cardiovascular magnetic resonance images using a multi-scale 3D convolutional neural network
Cardiac magnetic resonance (CMR) is regarded as the reference examination for cardiac morphology in tetralogy of Fallot (ToF) patients allowing images of high spatial resolution and high contrast. The detailed knowledge of the right ventricular anatomy is critical in ToF management. The segmentation of the right ventricle (RV) in CMR images from ToF patients is a challenging task due to the high shape and image quality variability. In this paper we propose a fully automatic deep learning-based framework to segment the RV from CMR anatomical images of the whole heart. We adopt a 3D multi-scale deep convolutional neural network to identify pixels that belong to the RV. Our robust segmentation framework was tested on 26 ToF patients achieving a Dice similarity coefficient of 0.8281±0.1010 with reference to manual annotations performed by expert cardiologists. The proposed technique is also computationally efficient, which may further facilitate its adoption in the clinical routine
The extreme melt across the Greenland ice sheet in 2012
The discovery of the 2012 extreme melt event across almost the entire surface of the Greenland ice sheet is presented. Data from three different satellite sensors – including the Oceansat-2 scatterometer, the Moderate-resolution Imaging Spectroradiometer, and the Special Sensor Microwave Imager/Sounder – are combined to obtain composite melt maps, representing the most complete melt conditions detectable across the ice sheet. Satellite observations reveal that melt occurred at or near the surface of the Greenland ice sheet across 98.6% of its entire extent on 12 July 2012, including the usually cold polar areas at high altitudes like Summit in the dry snow facies of the ice sheet. This melt event coincided with an anomalous ridge of warm air that became stagnant over Greenland. As seen in melt occurrences from multiple ice core records at Summit reported in the published literature, such a melt event is rare with the last significant one occurring in 1889 and the next previous one around seven centuries earlier in the Medieval Warm Period. Given its rarity, the 2012 extreme melt across Greenland provides an exceptional opportunity for new studies in broad interdisciplinary geophysical research
Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River
Knowledge of the diversity and ecological function of the microbial consortia of James River in Virginia, USA, is essential to developing a more complete understanding of the ecology of this model river system. Metagenomic analysis of James River\u27s planktonic microbial community was performed for the first time using an unamplified genomic library and a 16S rDNA amplicon library prepared and sequenced by Ion PGM and MiSeq, respectively. From the 0.46-Gb WGS library (GenBank:SRR1146621; MG-RAST:4532156.3), 4 × 10 6 reads revealed \u3e3 × 10 6 genes, 240 families of prokaryotes, and 155 families of eukaryotes. From the 0.68-Gb 16S library (GenBank:SRR2124995; MG-RAST:4631271.3; EMB:2184), 4 × 10 6 reads revealed 259 families of eubacteria. Results of the WGS and 16S analyses were highly consistent and indicated that more than half of the bacterial sequences were Proteobacteria, predominantly Comamonadaceae. The most numerous genera in this group were Acidovorax (including iron oxidizers, nitrotolulene degraders, and plant pathogens), which accounted for 10 % of assigned bacterial reads.Polaromonas were another 6 % of all bacterial reads, with many assignments to groups capable of degrading polycyclic aromatic hydrocarbons. Albidiferax (iron reducers) and Variovorax(biodegraders of a variety of natural biogenic compounds as well as anthropogenic contaminants such as polycyclic aromatic hydrocarbons and endocrine disruptors) each accounted for an additional 3 % of bacterial reads. Comparison of these data to other publically-available aquatic metagenomes revealed that this stretch of James River is highly similar to the upper Mississippi River, and that these river systems are more similar to aquaculture and sludge ecosystems than they are to lakes or to a pristine section of the upper Amazon River. Taken together, these analyses exposed previously unknown aspects of microbial biodiversity, documented the ecological responses of microbes to urban effects, and revealed the noteworthy presence of 22 human-pathogenic bacterial genera (e.g., Enterobacteriaceae, pathogenic Pseudomonadaceae, and ‘Vibrionales\u27) and 6 pathogenic eukaryotic genera (e.g., Trypanosomatidae and Vahlkampfiidae). This information about pathogen diversity may be used to promote human epidemiological studies, enhance existing water quality monitoring efforts, and increase awareness of the possible health risks associated with recreational use of James River
Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River
Knowledge of the diversity and ecological function of the microbial consortia of James River in Virginia, USA, is essential to developing a more complete understanding of the ecology of this model river system. Metagenomic analysis of James River\u27s planktonic microbial community was performed for the first time using an unamplified genomic library and a 16S rDNA amplicon library prepared and sequenced by Ion PGM and MiSeq, respectively. From the 0.46-Gb WGS library (GenBank:SRR1146621; MG-RAST:4532156.3), 4 × 106 reads revealed \u3e3 × 106 genes, 240 families of prokaryotes, and 155 families of eukaryotes. From the 0.68-Gb 16S library (GenBank:SRR2124995; MG-RAST:4631271.3; EMB:2184), 4 × 106 reads revealed 259 families of eubacteria. Results of the WGS and 16S analyses were highly consistent and indicated that more than half of the bacterial sequences were Proteobacteria, predominantly Comamonadaceae. The most numerous genera in this group were Acidovorax (including iron oxidizers, nitrotolulene degraders, and plant pathogens), which accounted for 10 % of assigned bacterial reads. Polaromonas were another 6 % of all bacterial reads, with many assignments to groups capable of degrading polycyclic aromatic hydrocarbons. Albidiferax (iron reducers) and Variovorax (biodegraders of a variety of natural biogenic compounds as well as anthropogenic contaminants such as polycyclic aromatic hydrocarbons and endocrine disruptors) each accounted for an additional 3 % of bacterial reads. Comparison of these data to other publically-available aquatic metagenomes revealed that this stretch of James River is highly similar to the upper Mississippi River, and that these river systems are more similar to aquaculture and sludge ecosystems than they are to lakes or to a pristine section of the upper Amazon River. Taken together, these analyses exposed previously unknown aspects of microbial biodiversity, documented the ecological responses of microbes to urban effects, and revealed the noteworthy presence of 22 human-pathogenic bacterial genera (e.g., Enterobacteriaceae, pathogenic Pseudomonadaceae, and ‘Vibrionales\u27) and 6 pathogenic eukaryotic genera (e.g., Trypanosomatidae and Vahlkampfiidae). This information about pathogen diversity may be used to promote human epidemiological studies, enhance existing water quality monitoring efforts, and increase awareness of the possible health risks associated with recreational use of James River
Analysis for Science Librarians of the 2018 Nobel Prize in Physiology or Medicine: The Life and Work of James P. Allison and Tasuku Honjo
On October 1, 2018, James P. Allison and Tasuku Honjo were awarded the 2018 Physiology or Medicine Nobel for their work leading to Immune Checkpoint Inhibition (ICI). ICI is the fourth pillar of cancer treatment and has been used to treat previously un-treatable cancers. Allison discovered that the protein CTLA-4 acts as a T cell brake while Honjo discovered another T cell brake, PD-1. Releasing these brakes allows the immune system to attack tumors, sometimes leading to complete elimination. While there is still more research to be done, Allison’s and Honjo’s work is a breakthrough in cancer immunotherapy
T-systems and Y-systems in integrable systems
The T and Y-systems are ubiquitous structures in classical and quantum
integrable systems. They are difference equations having a variety of aspects
related to commuting transfer matrices in solvable lattice models, q-characters
of Kirillov-Reshetikhin modules of quantum affine algebras, cluster algebras
with coefficients, periodicity conjectures of Zamolodchikov and others,
dilogarithm identities in conformal field theory, difference analogue of
L-operators in KP hierarchy, Stokes phenomena in 1d Schr\"odinger problem,
AdS/CFT correspondence, Toda field equations on discrete space-time, Laplace
sequence in discrete geometry, Fermionic character formulas and combinatorial
completeness of Bethe ansatz, Q-system and ideal gas with exclusion statistics,
analytic and thermodynamic Bethe ans\"atze, quantum transfer matrix method and
so forth. This review article is a collection of short reviews on these topics
which can be read more or less independently.Comment: 156 pages. Minor corrections including the last paragraph of sec.3.5,
eqs.(4.1), (5.28), (9.37) and (13.54). The published version (JPA topical
review) also needs these correction
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