Miracle-dz/UniFAR-FTUs huggingface dataset:
A Selective Bottleneck Shapes the Evolutionary Mutant Spectra of Enterovirus A71 during Viral Dissemination in Humans

ABSTRACT RNA viruses accumulate mutations to rapidly adapt to environmental changes. Enterovirus A71 (EV-A71) causes various clinical manifestations with occasional severe neurological complications. However, the mechanism by which EV-A71 evolves within the human body is unclear. Utilizing deep sequencing and haplotype analyses of viruses from various tissues of an autopsy patient, we sought to define the evolutionary pathway by which enterovirus A71 evolves fitness for invading the central nervous system in humans. Broad mutant spectra with divergent mutations were observed at the initial infection sites in the respiratory and digestive systems. After viral invasion, we identified a haplotype switch and dominant haplotype, with glycine at VP1 residue 31 (VP1-31G) in viral particles disseminated into the integumentary and central nervous systems. In vitro viral growth and fitness analyses indicated that VP1-31G conferred growth and a fitness advantage in human neuronal cells, whereas VP1-31D conferred enhanced replication in human colorectal cells. A higher proportion of VP1-31G was also found among fatal cases, suggesting that it may facilitate central nervous system infection in humans. Our data provide the first glimpse of EV-A71 quasispecies from oral tissues to the central nervous system within humans, showing broad implications for the surveillance and pathogenesis of this reemerging viral pathogen. IMPORTANCE EV-A71 continues to be a worldwide burden to public health. Although EV-A71 is the major etiological agent of hand, foot, and mouth disease, it can also cause neurological pulmonary edema, encephalitis, and even death, especially in children. Understanding selection processes enabling dissemination and accurately estimating EV-A71 diversity during invasion in humans are critical for applications in viral pathogenesis and vaccine studies. Here, we define a selection bottleneck appearing in respiratory and digestive tissues. Glycine substitution at VP1 residue 31 helps viruses break through the bottleneck and invade the central nervous system. This substitution is also advantageous for replication in neuronal cells in vitro. Considering that fatal cases contain enhanced glycine substitution at VP1-31, we suggest that the increased prevalence of VP1-31G may alter viral tropism and aid central nervous system invasion. Our findings provide new insights into a dynamic mutant spectral switch active during acute viral infection with emerging viral pathogens.
Using AMOS graphics to enhance the understanding and communication of multiple regression

Support for the saying “a picture is worth a 1000 words’ has been consistently found within statistics education. Graphical images are effective in promoting understanding and communication of statistical concepts and results to a variety of audiences. The computer software package, AMOS, was developed for the analysis of structural equation models (SEM) and has a user-friendly graphical interface. However, courses in SEM are generally found only at the postgraduate level. This paper argues that the graphical interface of AMOS has the potential to enhance conceptual understanding and communication of results in undergraduate statistical courses. More specifically, approaches to the teaching and communication of results of multiple regression models when using SPSS and AMOS will be examined and compared.
El Niño-Southern Oscillation Is Linked to Decreased Energetic Condition in Long-Distance Migrants

Predicting how migratory animals respond to changing climatic conditions requires knowledge of how climatic events affect each phase of the annual cycle and how those effects carry-over to subsequent phases. We utilized a 17-year migration dataset to examine how El Niño-Southern Oscillation climatic events in geographically different regions of the Western hemisphere carry-over to impact the stopover biology of several intercontinental migratory bird species. We found that migratory birds that over-wintered in South America experienced significantly drier environments during El Niño years, as reflected by reduced Normalized Difference Vegetation Index (NDVI) values, and arrived at stopover sites in reduced energetic condition during spring migration. During El Niño years migrants were also more likely to stopover immediately along the northern Gulf coast of the southeastern U.S. after crossing the Gulf of Mexico in small suboptimal forest patches where food resources are lower and migrant density often greater than larger more contiguous forests further inland. In contrast, NDVI values did not differ between El Niño and La Niña years in Caribbean-Central America, and we found no difference in energetic condition or use of coastal habitats for migrants en route from Caribbean-Central America wintering areas. Birds over-wintering in both regions had consistent median arrival dates along the northern Gulf coast, suggesting that there is a strong drive for birds to maintain their time program regardless of their overall condition. We provide strong evidence that not only is the stopover biology of migratory landbirds influenced by events during the previous phase of their life-cycle, but where migratory birds over-winter determines how vulnerable they are to global climatic cycles. Increased frequency and intensity of ENSO events over the coming decades, as predicted by climatic models, may disproportionately influence long-distance migrants over-wintering in South America.
Experiences of meaning of occupation at day centers among people with psychiatric disabilities

Abstract Background: There is a need for intervention studies of persons with psychiatric disabilities who attend day centers (DCs). Aim: The aim of this study was to investigate how people living with psychiatric disability experience and describe the meaning of occupation at DCs after taking part in an intervention. Methods: An interpretative phenomenological approach was used and 11 participants in the intervention were interviewed. Results: The superordinate theme describing the experienced meaning at the DC was As a substitute for work, and the sub-themes were; A feeling of belonging to a subculture; Flexibility and adaptation of occupation in accordance with the individual’s needs and recovery process; and Influence. Conclusions: The results indicated that the intervention played an important role for the creation of meaning at the DC’s for the participants in their daily lives and appeared to promote their well-being. Activities that promoted structure and were experienced as work-like as well as activities that promoted social belonging and influence at the DC were experienced as meaningful. Further intervention studies are needed to gain more knowledge about how to tailor different approaches and activities at DCs in the municipalities that could be experienced as meaningful by their members.
Groningen The Transcriptional and Gene Regulatory Network of Lactococcus lactis MG 1363 during Growth in Milk

In the present study we examine the changes in the expression of genes of Lactococcus lactis subspecies cremoris MG1363 during growth in milk. To reveal which specific classes of genes (pathways, operons, regulons, COGs) are important, we performed a transcriptome time series experiment. Global analysis of gene expression over time showed that L. lactis adapted quickly to the environmental changes. Using upstream sequences of genes with correlated gene expression profiles, we uncovered a substantial number of putative DNA binding motifs that may be relevant for L. lactis fermentative growth in milk. All available novel and literature-derived data were integrated into network reconstruction building blocks, which were used to reconstruct and visualize the L. lactis gene regulatory network. This network enables easy mining in the chrono-transcriptomics data. A freely available website at http://milkts.molgenrug. nl gives full access to all transcriptome data, to the reconstructed network and to the individual network building blocks. Citation: de Jong A, Hansen ME, Kuipers OP, Kilstrup M, Kok J (2013) The Transcriptional and Gene Regulatory Network of Lactococcus lactis MG1363 during Growth in Milk. PLoS ONE 8(1): e53085. doi:10.1371/journal.pone. 0053085 Editor: Raya Khanin, Memorial Sloan Kettering Cancer Center, United States of America Received May 30, 2012; Accepted November 27, 2012; Published January 17, 2013 Copyright: 2013 de Jong 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. Funding: Morten Ejby was supported by a grant from the Danish Dairy Research Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study. Competing Interests: The authors have declared that no competing interests exist. * E-mail: mki@bio.dtu. dk
NUMERICAL AND EXPERIMENTAL IMAGES OF MULTIPHASE PLASMA JET DURING PLASMA PROCESSING OF DISPERSED MATERIALS

This study presents results of analytical and experimental investigation on behaviour of dispersed particles, granules, also melted and concentrated ceramic material domains in the entrance region of plasma jet outflowing from plasma chemical reactor exhaust nozzle. High thermal resistant granules, fibre and fine particles have been produced from zeolites employing a specific plasma spray technique generating non-equilibrium plasma jet at atmospheric pressure. Experimental installation was developed for operating by feeding air, nitrogen or hydrocarbon containing gases mixed with dispersed particles. The power of plasma torch was in the range of 70 - 80 kW, temperature of gas leaving the reactor - 2500 - 3500 K, flow velocity in the outlet - 900 - 1500 m/s. Performed experimental and analytical studies showed that process of plasma melting and conversion of melt into fibre depend on following main factors: i) plasma generator characteristics and operating regime; ii) plasma flow formation, characteristics and its interaction with walls of the reactor; iii) plasma forming gas and powder injection approach and place; iiii) powder composition, size and fraction, its injection rate parameters; iiiii) initial domain formation, splat layering and process of spray pyrolysis.
Object-based Conditional Random Fields for Road Extraction from Remote Sensing Image

To make full use of spatially contextual information and topological information in the procedure of Object-based Image Analysis (OBIA), an object-based conditional random field is proposed and used for road extraction. Objects are produced with an initial segmentation, then their neighbours are constructed. Each object is represented by three kinds of features, including the colour, the gradient of histogram and the texture. Formulating the road extraction as a binary classification problem, a Conditional Random Fields model learns and is used for inference. The experimental results demonstrate that the proposed method is effective.
Glutathione Conjugation at the Blood–CSF Barrier Efficiently Prevents Exposure of the Developing Brain Fluid Environment to Blood-Borne Reactive Electrophilic Substances

Exposure of the developing brain to toxins, drugs, or deleterious endogenous compounds during the perinatal period can trigger alterations in cell division, migration, differentiation, and synaptogenesis, leading to lifelong neurological impairment. The brain is protected by cellular barriers acting through multiple mechanisms, some of which are still poorly explored. We used a combination of enzymatic assays, live tissue fluorescence microscopy, and an in vitro cellular model of the blood–CSF barrier to investigate an enzymatic detoxification pathway in the developing male and female rat brain. We show that during the early postnatal period the choroid plexus epithelium forming the blood–CSF barrier and the ependymal cell layer bordering the ventricles harbor a high detoxifying capacity that involves glutathione S-transferases. Using a functional knock-down rat model for choroidal glutathione conjugation, we demonstrate that already in neonates, this metabolic pathway efficiently prevents the penetration of blood-borne reactive compounds into CSF. The versatility of the protective mechanism results from the multiplicity of the glutathione S-transferase isoenzymes, which are differently expressed between the choroidal epithelium and the ependyma. The various isoenzymes display differential substrate specificities, which greatly widen the spectrum of molecules that can be inactivated by this pathway. In conclusion, the blood–CSF barrier and the ependyma are identified as key cellular structures in the CNS to protect the brain fluid environment from different chemical classes of potentially toxic compounds during the postnatal period. This metabolic neuroprotective function of brain interfaces ought to compensate for the liver postnatal immaturity. SIGNIFICANCE STATEMENT Brain homeostasis requires a stable and controlled internal environment. Defective brain protection during the perinatal period can lead to lifelong neurological impairment. We demonstrate that the choroid plexus forming the blood–CSF barrier is a key player in the protection of the developing brain. Glutathione-dependent enzymatic metabolism in the choroidal epithelium inactivates a broad spectrum of noxious compounds, efficiently preventing their penetration into the CSF. A second line of detoxification is located in the ependyma separating the CSF from brain tissue. Our study reveals a novel facet of the mechanisms by which the brain is protected at a period of high vulnerability, at a time when the astrocytic network is still immature and liver xenobiotic metabolism is limited.
Genetic and environmental contributions to the Child Behavior Checklist Obsessive-Compulsive Scale: a cross-cultural twin study.

CONTEXT We have reported elsewhere on the development of an 8-item Obsessive-Compulsive Scale (OCS) contained in the Child Behavior Checklist (CBCL) to identify children who meet criteria for DSM-IV obsessive-compulsive disorder. Twin studies of obsessive-compulsive disorder have indicated a significant genetic component to its expression. OBJECTIVE To determine the relative contributions of genetic and environmental influences on childhood obsessive-compulsive behavior using the CBCL OCS in twin samples. DESIGN The CBCL data were received by survey of twins in the Netherlands Twin Registry (NTR) and the Missouri Twin Study (USA/MOTWIN). SETTING General community twin samples. PARTICIPANTS Participants were 4246 twin pairs aged 7 years, 2841 aged 10 years, and 1562 aged 12 years (who also participated in the study at 7 and 10 years of age) from the NTR and 1461 mixed-age twin pairs (average age, approximately 9 years) from the USA/MOTWIN. MAIN OUTCOME MEASURES Model fitting to test for genetic and environmental influences, sex differences, and sibling interaction/rater contrast effects on the CBCL OCS. RESULTS In each case, the best-fitting model was one that indicated significant additive genetic influences (range, 45%-58%; 95% confidence interval [CI], 45%-61%), and unique environmental influences (range, 42%-55%; 95% CI, 39%-55%), with shared environmental influences in the NTR sample aged 12 years (16%). Sex differences were seen in the mixed-age USA/MOTWIN model, but not in the NTR samples. No evidence of dominance, sibling interaction, or rater-contrast effects was seen. These data were relatively consistent across age and cultures. CONCLUSIONS The CBCL OCS is influenced by genetic factors (approximately 55%) and unique environmental factors (approximately 45%) in the younger sample, with common environmental influences only at 12 years of age. These effects do not vary with differences in sex or sibling interaction/rater contrast effects. Our data reveal higher genetic influences for obsessive-compulsive behavior and do not demonstrate genetic differences across sex.
Music Genre Classification using Machine Learning Techniques

Categorizing music files according to their genre is a challenging task in the area of music information retrieval (MIR). In this study, we compare the performance of two classes of models. The first is a deep learning approach wherein a CNN model is trained end-to-end, to predict the genre label of an audio signal, solely using its spectrogram. The second approach utilizes hand-crafted features, both from the time domain and the frequency domain. We train four traditional machine learning classifiers with these features and compare their performance. The features that contribute the most towards this multi-class classification task are identified. The experiments are conducted on the Audio set data set and we report an AUC value of 0.894 for an ensemble classifier which combines the two proposed approaches.
E-Spector: Online energy inspection for Android applications

Energy consumption is one of the most important aspects of mobile apps. During energy testing, it is important for developers to understand not only the energy consumption rate of an app, but also why energy is consumed. However, existing energy testing tools are more concerned about the accuracy of energy estimation, while typically not providing explanations on why and how exactly energy has been consumed. This paper presents E-Spector, an online energy inspection method for Android apps, which can not only visualize the energy consumption of an app in an instant online manner, but also can tell what happened behind each energy hotspot on the energy curve. E-Spector relies on static analysis and app instrumentation to collect the activities from an app execution in real-time. Then it presents the activities on an instant energy curve, such that the user can easily tell what happened behind each energy spike. Experimental result shows that the energy estimation error of E-Spector is less than 10% and its overhead on energy consumption is about 4%. We also show case studies to demonstrate the applicability and effectiveness of E-Spector in energy monitoring, analysis and bug inspection.
Paraphrases for Statistical Machine Translation

Statistical Machine Translation (SMT) is the task of automatic translation between two natural languages (source language and target language) by using bilingual corpora. To accomplish this goal, machine learning models try to capture human translation patterns inside a bilingual corpus. An open challenge for SMT is finding translations for phrases which are missing in the training data (out-of-vocabulary phrases). We propose to use paraphrases to provide translations for out-of-vocabulary (OOV) phrases. We compare two major approaches to automatically extract paraphrases from corpora: distributional profile (DP) and bilingual pivoting. The multilingual Paraphrase Database (PPDB) is a freely available automatically created (using bilingual pivoting) resource of paraphrases in multiple languages. We show that a graph propagation approach that uses PPDB paraphrases can be used to improve overall translation quality. We provide an extensive comparison with previous work and show that our PPDB-based method improves the BLEU score by up to 1.79 percent points. We show that our approach improves on the state of the art in three different settings: when faced with limited amount of parallel training data; a domain shift between training and test data; and handling a morphologically complex source language.
Positive biodiversity–productivity relationships in forests: climate matters

While it is widely acknowledged that forest biodiversity contributes to climate change mitigation through improved carbon sequestration, conversely how climate affects tree species diversity–forest productivity relationships is still poorly understood. We combined the results of long-term experiments where forest mixtures and corresponding monocultures were compared on the same site to estimate the yield of mixed-species stands at a global scale, and its response to climatic factors. We found positive mixture effects on productivity using a meta-analysis of 126 case studies established at 60 sites spread across five continents. Overall, the productivity of mixed-species forests was 15% greater than the average of their component monocultures, and not statistically lower than the productivity of the best component monoculture. Productivity gains in mixed-species stands were not affected by tree age or stand species composition but significantly increased with local precipitation. The results should guide better use of tree species combinations in managed forests and suggest that increased drought severity under climate change might reduce the atmospheric carbon sequestration capacity of natural forests.
New chimeric RNAs in acute myeloid leukemia

Background: High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric RNA (chRNA). Methods: We used Crac, a tool that uses genomic locations and local coverage to classify biological events and directly infer splice and chimeric junctions within a single read. Crac’s algorithm extracts transcriptional chimeric events irrespective of annotation with a high sensitivity, and CracTools was used to aggregate, annotate and filter the chRNA reads. The selected chRNA candidates were validated by real time PCR and sequencing. In order to check the tumor specific expression of chRNA, we analyzed a publicly available dataset using a new tag search approach. Results: We present data related to acute myeloid leukemia (AML) RNA-seq analysis. We highlight novel biological cases of chRNA, in addition to previously well characterized leukemia chRNA. We have identified and validated 17 chRNAs among 3 AML patients: 10 from an AML patient with a translocation between chromosomes 15 and 17 (AML-t(15;17), 4 from patient with normal karyotype (AML-NK) 3 from a patient with chromosomal 16 inversion (AML-inv16). The new fusion transcripts can be classified into four groups according to the exon organization. Conclusions: All groups suggest complex but distinct synthesis mechanisms involving either collinear exons of different genes, non-collinear exons, or exons of different chromosomes. Finally, we check tumor-specific expression in a larger RNA-seq AML cohort and identify new AML biomarkers that could improve diagnosis and prognosis of AML.
Topical Positioning: A New Method for Predicting Opinion Changes in Conversation

In this paper, we describe a novel approach to automatically detecting and tracking discussion dynamics in Internet social media by focusing on attitude modeling of topics. We characterize each participant’s attitude towards topics as Topical Positioning, employ Topical Positioning Map to represent the positions of participants with respect to each other and track attitude shifts over time. We also discuss how we used participants’ attitudes towards system-detected meso-topics to reflect their attitudes towards the overall topic of conversation. Our approach can work across different types of social media, such as Twitter discussion and online chat room. In this article, we show results on Twitter data.