bluuebunny/crossref_metadata_2025_split huggingface dataset:
What rhythmic perception and amusia can tell us about vocal social communication in schizophrenia
Authors: Mitchell Rachel L. C. , Gamez Krystal , Bolgar Joshua , Neustadter Eli S. , Calkins Monica E. , Moore Tyler M. , Leitman David I. 
Published: December 2016

ABSTRACTBackgroundPerceiving social intent throughvocal intonation is impaired in schizophrenia; thisdysprosodia partly arisingfrom impaired pitch perception.Individuals with amusia (tone-deafness) are insensitive to pitch change andalso demonstrate prosody deficits. Sensitivity to rhythm is reduced in amusia when tonal sequences contain pitch changes (polytonic), but is normal for monotonic sequences, suggesting perceptual impairment originates at a secondary processing stage where pitch- and time-relatedcues are yoked. Here, we sought to ascertain: 1) whether schizophreniapatients demonstrate rhythmic deficits, 2) whether suchdeficits are restricted to polytonic sequences, and 3) how pitch and rhythm perception relate to prosodic processing.MethodsSeventy-sixparticipants (33 schizophrenia) completed tasks assessing pitch and prosody perception, as well as monotonic and polytonic rhythmic perception.ResultsIncreasing tone-deafness correlated with pitch-dependent rhythm detection impairments. Pitch and prosody correlated across all participants. Schizophreniapatients displayed basic time and pitch deficits. Correlations and path analyses indicated prosodic processing is an associatedfunction of pitch and pitch-dependent rhythm perception,with pure temporal processing playing an indirect role.In schizophrenia, deficits in monotonic and polytonic rhythmic perception did not contribute to prosodic processing dysfunction, and montonic rhythmic dysfunction and pitch perception did not covary.ConclusionsExploring similarities between amusia and schizophrenia focused our characterization of prosodic processing as the function of sub-processes reflecting pitch and time perception,whichare prerequisite for prosodic processing. The uniqueness of dysprosodia in schizophrenia relative to other illnesses may be measured by idiosyncrasy in the pattern and magnitude of the sub-process task relationships.
Neural Homophily: Similar Neural Responses Predict Friendship
Authors: Parkinson Carolyn M. , Kleinbaum Adam M. , Wheatley Thalia 
Published: December 2016

AbstractWe resemble our friends on a wide range of dimensions (e.g., age, gender), but do similarities between friends reflect deeper similarities in how we perceive, interpret, and respond to the world? To find out, we characterized the social network of a cohort of 279 students, a subset of whom participated in a functional magnetic resonance imaging (fMRI) study involving free-viewing of video stimuli. We compared fMRI response time series between corresponding brain regions across pairs of individuals and found that neural response similarity decreased with increasing distance in the social network. These effects persisted after controlling for demographic similarity. Further, it was possible to accurately classify the distance between individuals in their social network based on the similarity of their fMRI response time series across brain regions. These results suggest that we are exceptionally similar to our friends in how we perceive and react to the world around us.
Pan-Cancer Analysis Reveals Technical Artifacts in TCGA Germline Variant Calls
Authors: Buckley Alexandra R. , Standish Kristopher A. , Bhutani Kunal , Ideker Trey , Carter Hannah , Harismendy Olivier , Schork Nicholas J. 
Published: December 2016

AbstractThe degree to which germline variation drives cancer development and shapes tumor phenotypes remains largely unexplored, possibly due to a lack of large scale publicly available germline data for a cancer cohort. Here we called germline variants on 9,618 cases from The Cancer Genome Atlas (TCGA) database representing 31 cancer types. We identified batch effects affecting loss of function (LOF) variant calls that can be traced back to differences in the way the sequence data were generated both within and across cancer types. Overall, LOF indel calls were more sensitive to technical artifacts than LOF Single Nucleotide Variant (SNV) calls. In particular, whole genome amplification of DNA prior to sequencing led to an artificially increased burden of LOF indel calls, which confounded association analyses relating germline variants to tumor type despite stringent indel filtering strategies. Due to the inherent noise we chose to remove all 614 amplified DNA samples, including all acute myeloid leukemia and virtually all ovarian cancer samples, from the final dataset. This study demonstrates how insufficient quality control can lead to false positive germlinetumor type associations and draws attention to the need to be sensitive to problems associated with a lack of uniformity in data generation in TCGA data.Author SummaryCancer research to date has largely focused on genetic aberrations specific to tumor tissue. In contrast, the degree to which germline, or inherited, variation contributes to tumorigenesis remains unclear, possibly due to a lack of accessible germline variant data. In this study we identify germline variants in 9,618 samples using raw germline exome data from The Cancer Genome Atlas (TCGA). There are substantial differences in the way exome sequence data was generated both across and within cancer types in TCGA. We observe that differences in sequence data generation introduced batch effects, or variation that is due to technical factors not true biological variation, in our variant data. Most notably, we observe that amplification of DNA prior to sequencing resulted in an excess of predicted damaging indel variants. We show how these batch effects can confound germline association analyses if not properly addressed. Our study highlights the difficulties of working with large public genomic datasets like TCGA where samples are collected over time and across data centers, and particularly cautions the use of amplified DNA samples for genetic association analyses.
Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software
Authors: Gardner Paul P. , Paterson James M. , McGimpsey Stephanie , Ashari-Ghomi Fatemeh , Umu Sinan U. , Pawlik Aleksandra , Gavryushkin Alex , Black Michael A. 
Published: December 2016

AbstractBackgroundComputational biology provides widely used and powerful software tools for testing and making inferences about biological data. In the face of rapidly increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We are have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors are indicative of accurate software.MethodWe have extracted accuracy and speed ranks from independent benchmarks of different bioinformatic software tools, and evaluated whether the speed, author reputation, journal impact, recency and developer efforts are indicative of accuracy.ResultsWe found that software speed, author reputation, journal impact, number of citations and age are all unreliable predictors of software accuracy. This is unfortunate because citations, author and journal reputation are frequently cited reasons for selecting software tools. However, GitHub-derived records and high version numbers show that the accurate bioinformatic software tools are generally the product of many improvements over time, often from multiple developers.DiscussionWe also find that the field of bioinformatics has a large excess of slow and inaccurate software tools, and this is consistent across many sub-disciplines. Meanwhile, there are few tools that are middle-of-road in terms of accuracy and speed trade-offs. We hypothesise that a form of publication-bias influences the publication and development of bioinformatic software. In other words, software that is intermediate in terms of both speed and accuracy may be difficult to publish - possibly due to author, editor and reviewer practices. This leaves an unfortunate hole in the literature as the ideal tools may fall into this gap. For example, high accuracy tools are not always useful if years of CPU time are required, while high speed is not useful if the results are also inaccurate.
Decoding visual stimuli in human brain by using Anatomical Pattern Analysis on fMRI images
Authors: Yousefnezhad Muhammad , Zhang Daoqiang 
Published: December 2016

AbstractA universal unanswered question in neuroscience and machine learning is whether computers can decode the patterns of the human brain. Multi-Voxels Pattern Analysis (MVPA) is a critical tool for addressing this question. However, there are two challenges in the previous MVPA methods, which include decreasing sparsity and noises in the extracted features and increasing the performance of prediction. In overcoming mentioned challenges, this paper proposes Anatomical Pattern Analysis (APA) for decoding visual stimuli in the human brain. This framework develops a novel anatomical feature extraction method and a new imbalance AdaBoost algorithm for binary classification. Further, it utilizes an Error-Correcting Output Codes (ECOC) method for multi-class prediction. APA can automatically detect active regions for each category of the visual stimuli. Moreover, it enables us to combine homogeneous datasets for applying advanced classification. Experimental studies on 4 visual categories (words, consonants, objects and scrambled photos) demonstrate that the proposed approach achieves superior performance to state-of-the-art methods.
Decoding Single Molecule Time Traces with Dynamic Disorder
Authors: Hwang Wonseok , Lee Il-Buem , Hong Seok-Cheol , Hyeon Changbong 
Published: December 2016

Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed. Here we report a new algorithm – Variational Bayes-double chain Markov model (VB-DCMM) – to analyze single molecule time trajectories that display dynamic disorder. The proposed analysis employing VB-DCMM allows us to detect the presence of dynamic disorder, if any, in each trajectory, identify the number of internal states, and estimate transition rates between the internal states as well as the rates of conformational transition within each internal state. Applying VB-DCMM algorithm to single molecule FRET data of H-DNA in 100 mM-Na+solution, followed by data clustering, we show that at least 6 kinetic paths linking 4 distinct internal states are required to correctly interpret the duplex-triplex transitions of H-DNA.Author SummaryWe have developed a new algorithm to better decode single molecule data with dynamic disorder. Our new algorithm, which represents a substantial improvement over other methodologies, can detect the presence of dynamic disorder in each trajectory and quantify the kinetic characteristics of underlying energy landscape. As a model system, we applied our algorithm to the single molecule FRET time traces of H-DNA. While duplex-triplex transitions of H-DNA are conventionally interpreted in terms of two-state kinetics, slowly varying dynamic patterns corresponding to hidden internal states can also be identified from the individual time traces. Our algorithm reveals that at least 4 distinct internal states are required to correctly interpret the data.
VIP36 preferentially binds to core-fucosylated N-glycans: a molecular docking study
Authors: Fiedler Klaus 
Published: December 2016

AbstractAlpha 1-6 fucosyltransferase (Fut8) is known for its properties as an enhancer of nonsmall cell lung cancer metastasis and as a suppressor in hepatocellular carcinoma cells (Hep3B). Promising candidates of affected molecules include E-cadherin. In its absence, during epithelial-mesenchymal transition, the pathway triggers signaling to the nucleus via β-catenin-TCF/LEF. Contrarily, in less metastatic tumors, Fut8 stimulates cell-cell adhesion. Regulated classes of molecules could also include the sorting machinery of polarized epithelial cells, sorted ligands or both, that may be altered in cellular transformation. I have analyzed here the cargo receptor VIP36 (Vesicular-integral membrane protein of 36 kD) for carbohydrate interaction. It has been described as a lectin in the ERGIC (endoplasmic reticulum-Golgi intermediate compartment), Golgi apparatus and plasma membrane. The docking reveals top-interacting carbohydrates of the N-glycan and O-glycan class that encompass N-linked glycans of high mannose and equally complex type which likely function as sorted ligands in epithelial cells. O-glycans score lower and include core 2 residue binding. I show that fucose core modifications by Fut8 stimulate binding of N-linked glycans to VIP36, which is known to be different from binding of galectins 3 and 9. This suggests that Fut8-upregulation may directly alter the affinity of sorted cargo and may enhance the sorting to the apical pathway as exemplified in hepatocytes and traffic to bile. High affinity binding of the ganglioside GM1 carbohydrate headgroup to VIP36 suggests a linkage with protein and glycosphingolipid apical transfer in epithelial cells. Thus, this fundamental approach with large scale docking of 165 carbohydrates including 19 N-glycan high mannose, 17 Nglycan hybrid, 9 N-glycan complex, 17 O-glycan core, 27 Sialoside, 25 Fucoside and 51 other glycan residues suggests, that linked cargo-receptor apical transport may provide a path to epithelial polarization that may be modulated by core fucosylation.
Neural dynamics at successive stages of the ventral visual stream are consistent with hierarchical error signals
Authors: Issa Elias B. , Cadieu Charles F. , DiCarlo James J. 
Published: December 2016

ABSTRACTVentral visual stream neural responses are dynamic, even for static image presentations. However, dynamical neural models of visual cortex are lacking as most progress has been made modeling static, time-averaged responses. Here, we studied population neural dynamics during face detection across three cortical processing stages. Remarkably, ~30 milliseconds after the initially evoked response, we found that neurons in intermediate level areas decreased their preference for faces, becoming anti-face preferring on average even while neurons in higher level areas achieved and maintained a face preference. This pattern of hierarchical neural dynamics was inconsistent with extensions of standard feedforward circuits that implemented recurrence within a cortical stage. Rather, recurrent models computing errors between stages captured the observed temporal signatures. Without additional parameter fitting, this model of neural dynamics, which simply augments the standard feedforward model of online vision to encode errors, also explained seemingly disparate dynamical phenomena in the ventral stream.
Mobile introns shape the genetic diversity of their host genes
Authors: Repar Jelena , Warnecke Tobias 
Published: December 2016

AbstractSelf-splicing introns populate several highly conserved protein-coding genes in fungal and plant mitochondria. In fungi, many of these introns have retained their ability to spread to intron-free target sites, often assisted by intron-encoded endonucleases that initiate the homing process. Here, leveraging population genomic data fromSaccharomyces cerevisiae, Schizosaccharomyces pombe, andLachancea kluyveri, we expose non-random patterns of genetic diversity in exons that border self-splicing introns. In particular, we show that, in all three species, the density of single nucleotide polymorphisms increases as one approaches a mobile intron. Through multiple lines of evidence we rule out relaxed purifying selection as the cause of uneven nucleotide diversity. Instead, our findings implicate intron mobility as a direct driver of host gene diversity. We discuss two mechanistic scenarios that are consistent with the data: either endonuclease activity and subsequent error-prone repair have left a mutational footprint on the insertion environment of mobile introns or non-random patterns of genetic diversity are caused by exonic co-conversion, which occurs when introns spread to empty target sites via homologous recombination. Importantly, however, we show that exonic co-conversion can only explain diversity gradients near intron-exon boundaries if the conversion templates comes from outside the population. In other words, there must be pervasive and ongoing horizontal gene transfer of self-splicing introns into extant fungal populations.
Import and Export of Gold Nanoparticles: Exchange Rate in Cancer Cells and Fibroblasts
Authors: Ivošev Vladimir , Jiménez Sánchez Gloria , Abi Haidar Darine , Bazzi Rana , Roux Stéphane , Lacombe Sandrine 
Published: December 2016

AbstractCancer is one of the leading causes of death. Radiation therapy is an important modality used in cancer treatment being highly cost-effective. Major flaw of radiotherapy is lack of selectivity between cancerous and healthy tissues. Amelioration of radiotherapy by using high-Z nanoparticles as radiation enhancers is one of potential solutions. Gold nanoparticles (AuNPs) are commonly used as radioenhancers. Understanding the interaction between cancer cells and AuNPs is essential in order to achieve best possible radioenhancing effects, while sparing healthy tissues. This work aims to elucidate interactions of ultrasmall (core size: 2.4 nm and hydrodynamic diameter (Dh): 4.5 nm) fluorescently labeled AuNPs with various human cell lines. In this perspective we measured uptake dynamics, characterized route of internalization and time of intracellular retention in various cancer cell lines and fibroblasts. Our results show that uptake dynamics and internalization pathways are strongly cell line-dependant. We also demonstrate that higher proportion of internalized nanoparticles resides in cancer cells, compared to fibroblasts, inin vitroconditions. This work highlights great complexity of cancerous cells and underlines the necessity for excellent knowledge of biological behaviour for each type of cancer. It also emphasizes the major effort needed for efficient cancer treatments and makes an appeal for further development of highly selective nanoparticles in order to hasten their utilization in clinical conditions.
Household food waste and eating behavior: empirical survey
Authors: Lanfranchi Maurizio , Calabrò Grazia , De Pascale Angelina , Fazio Alessandro , Giannetto Carlo 
Published: December 2016

PurposeIn the food chain the identification of household food wastes represents the most problematic aspect to analyze: both as regards the assessment of its qualitative and quantitative aspects and for the detection of measures to reduce or control its generation. In 2012, in fact, the analyzed area showed an inequality index for disposable income of 6.3, and a relative poverty risk index of 42.3. The paper aims to discuss these issues.Design/methodology/approachIn order to get deeper insights into consumers’ wasting behaviors, a survey on food waste generation in households was carried out in a province of Sicily (Italy). The questionnaire has been formulated taking into account the socio-demographic characteristics for the person who, in the family, usually makes the expenditure, in particular: gender, age, marital status, number of household members, education level, type (single, with or without children, married with or without children), worker and/or student if responsible for food shopping, the number of monthly meals, the kind of ready meal eaten (frozen, fresh, canned or freeze-dried), net monthly income for the family, etc. (adapted by Baeet al., 2010). The data collected from the statistical return of the consumers were drawn up to transform the same data into information of simpler and more concise interpretation.FindingsThe results of the survey are presented in this paper. They can help understand the reasons for discarding edible food and to identify the food groups that are most wasted.Research limitations/implicationsThe analysis of a larger land area or community allows most relevant conclusions. The research has an exploratory perspective since the sample strategy is not probabilistic.Social implicationsThe findings could be susceptible to support practical and social implications for the identification of measures and instruments aimed at reducing food waste and at increasing consumers’ awareness on that issue.Originality/valueThe study can stimulate sustainable consumption and consumer behavior especially in light of the current economic crisis.
Effect of product attribute beliefs of ready-to-drink coffee beverages on consumer-perceived value and repurchase intention
Authors: Wang Edward S.-T. , Yu Jia-Rong 
Published: December 2016

Purpose
The purpose of this paper is to explore the effect of the product attribute beliefs of ready-to-drink (RTD) coffee beverages (i.e. content sensory, packaging and branding, and content functional attributes) on perceived value (i.e. utilitarian and hedonic value) and repurchase intention.

Design/methodology/approach
In the study survey, 401 participants who had purchased RTD coffee beverages within the previous month were included. Structural equation modelling was employed to analyse the survey data.

Findings
The findings indicate that consumers of RTD coffee beverages form utilitarian and hedonic value perceptions through content sensory, packaging and branding, and content functional attribute beliefs. Furthermore, utilitarian value is one of the most crucial determinants of repurchase intentions. The findings further reveal that whereas content functional attribute beliefs have a dominant influence on utilitarian value, content sensory attribute beliefs have a greater influence on hedonic value.

Originality/value
The findings of this study can serve as a reference for RTD coffee beverage companies to develop new products and communication strategies.