bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dissecting the coma spectrum using Bayesian classification
Authors: Dietz Martin J. , Zareini Bochra , Näätänen Risto , Overgaard Morten 
Published: November 2019

AbstractA patient who does not regain full consciousness after coma is typically classified as being in a vegetative state or a minimally conscious state. While the key determinants in this differential diagnosis are inferred uniquely from the observed behaviour of the patient, nothing can, in principle, be known about the patient’s awareness of the external world. Given the subjective nature of current diagnostic practice, the quest for neurophysiological markers that could complement the nosology of the coma spectrum is becoming more and more acute. We here present a method for the classification of patients based on electrophysiological responses using Bayesian model selection. We validate the method in a sample of fourteen patients with a clinical disorder of consciousness (DoC) and a control group of fifteen healthy adults. By formally comparing a set of alternative hypotheses about the nosology of DoC patients, the results of our validation study show that we can disambiguate between alternative models of how patients are classified. Although limited to this small sample of patients, this allowed us to assert that there is no evidence of subgroups when looking at the MMN response in this sample of patients. We believe that the methods presented in this article are an important contribution to testing alternative hypotheses about how patients are grouped at both the group and single-patient level and propose that electrophysiological responses, recorded invasively or non-invasively, may be informative for the nosology of the coma spectrum on a par with behavioural diagnosis.
Dppa2/4 target chromatin bivalency enabling multi-lineage commitment
Authors: Eckersley-Maslin Mélanie A. , Parry Aled , Blotenburg Marloes , Krueger Christel , Roamio Franklin Valar Nila , Clark Stephen J. , D’Santos Clive S. , Reik Wolf 
Published: November 2019

AbstractBivalent chromatin marks developmental promoters in pluripotent cells, yet their targeting and precise impact on lineage commitment remains unclear. We uncover Developmental Pluripotency Associated 2 (Dppa2) and 4 (Dppa4) as epigenetic priming factors, establishing chromatin bivalency. Single-cell transcriptomics and differentiation assays reveal Dppa2/4 double knockout embryonic stem cells fail to exit pluripotency and differentiate efficiently. Dppa2/4 associate with COMPASS and Polycomb complexes and are required to recruit and maintain their binding at a subset of developmentally important bivalent promoters which are characterised by low expression and poised RNA polymerase. Consequently, upon Dppa2/4 knockout, these dependent promoters gain DNA methylation and are unable to be activated upon differentiation. Our findings uncover a novel targeting principle for bivalency to developmental promoters, poising them for future lineage specific activation.
Switching metalloporphyrin binding specificity of a b-type cytochrome to fluorogenic zinc by design
Authors: Bowen B. J. , McGarrity A. R. , Szeto J-Y. A. , Pudney C. R. , Jones D. D. 
Published: November 2019

AbstractMetalloporphyrins play important roles in areas ranging from biology to nanoscience. Biology uses a narrow set of metal centres comprising mainly of iron and magnesium. Here, we convert metalloporphyrin specificity of cytochrome b562 from iron (haem) to fluorogenic zinc protoporphyrin IX (ZnPP). Through a computationally guided iterative design process, a variant with a near total preference for ZnPP was generated representing a switch in specificity. The new variant greatly enhanced (≥60 fold) the negligible aqueous fluorescence of free ZnPP in vitro and in vivo.Abstract Figure
Ribosome-targeting antibiotics impair T cell effector function and ameliorate autoimmunity by blocking mitochondrial protein synthesis
Authors: Almeida L , Dhillon-LaBrooy A , Castro CN , Ayele N , Bartel J , Carriche GM , Guderian M , Lippens S , Dennerlein S , Hesse C , Lambrecht BN , Schauser L , Blazar BR , Kalesse M , Müller R , Moita LF , Sparwasser T 
Published: November 2019

AbstractWhile antibiotics are intended to specifically target bacteria, most are known to affect host cell physiology. In addition, some antibiotic classes are reported as immunosuppressive, for reasons that remain unclear. Here we show that linezolid, a ribosomal-targeting antibiotic (RAbo), effectively blocked the course of a T cell-mediated autoimmune disease. Linezolid and other RAbos were strong inhibitors of Th17 effector function in vitro, showing that this effect was independent of their antibiotic activity. Perturbing mitochondrial translation in differentiating T cells, either with RAbos or through the inhibition of mitochondrial elongation factor G1 (mEF-G1) progressively compromises the integrity of the electron transport chain (ETC). Ultimately, this leads to loss of mitochondrial metabolism and cytokine production in differentiating Th cells. In accordance, mice lacking Gfm1 in T cells are protected from EAE, demonstrating that this pathway plays a key role in maintaining T cell function and pathogenicity.
Assessing white matter pathway reproducibility from human whole-brain tractography clustering
Authors: Kai Jason , Khan Ali R. 
Published: November 2019

AbstractDiffusion MRI, together with tractography techniques, is a non-invasive tool to investigate the brain’s structural pathways (tracts). These tracts join together different regions of the brain and tract identification often involves the use of manual ROIs or automated techniques such as clustering. By studying these connections, current understanding of the connectome can be improved and changes due to disease in patient populations may be identified. We developed a tool to automatically identify all pathways in the human brain, including the short-range, U-shaped tracts, and map quantitative scalar metrics along the pathway trajectory for subsequent analysis. Pathways are identified via a spectral clustering technique on two datasets: Human Connectome Project (intersubject) and MyConnectome Project (intrasubject) and the reliability of the extracted tract and scalar values are evaluated. Average Euclidean distances and volumetric overlap were computed and indicated good spatial reliability. Intraclass correlations of the fractional anisotropy value mapped along the tract was calculated and exhibited good reproducibility within each dataset. Additionally, these evaluation metrics, together with the coefficient of variation of the mean streamline count is used to determine reliably identified U-shaped tracts across the datasets. The developed tract identification tool is an additional resource to studying the human connectome with increased confidence in the results. The identified reliable U-shaped tracts contributes to the identification of common structural connections across individuals and aids in advancing our understanding of the brain’s short-range pathways.
Development of SSR markers related to seed storability traits in maize subjected to artificial seed aging conditions
Authors: Guo Xiaoyang , Gong Chengxu , Liu Shan , Feng Chenchen , Han Xiao , Lv Tingting , Sun Xiaohui , Yang Xiuwei , Zhou Yu , Wang Zhenhua , Di Hong 
Published: November 2019

AbstractSeed storability is an important and complex agronomic trait in maize because annual seed production considerably exceeds consumption. The viability of seeds decreases over time, even when stored at low temperature, until seeds finally lose viability. In our previous study, two inbred lines with significantly different storability, Dong156 with high storage tolerance and Dong237 with low storage tolerance, were selected over six years using a natural seed aging test. In the present study, an F2:3 population and a RIL (recombinant inbred line) population were constructed from these two inbred lines and used to map QTL (quantitative trait loci) with SSR (simple sequence repeat) markers. A phenotypic index of traits related to seed storability that includes germination rate, germination potential, a germination index, a vigor index, seedling weight, and seedling length was generated using the results of an artificial aging treatment. Two consistent regions,cQTL-7 on chromosome 7 andcQTL-10 on chromosome 10, were identified by comparing QTL analysis results from these two populations. After genotyping SSR markers in these two regions,cQTL-7 was remapped to between umc1671 and phi328175 in a 7.97-Mb region, andcQTL-10 was remapped to between umc1648 and phi050 in a 39.15-Mb region. Four SSR markers linked tocQTL-7 andcQTL-10, including umc1671, phi328175, umc1648, and phi050, were identified using a Chi-squared test. The combined selection efficiency of these four markers was 83.94% in 85 RIL lines with high storability, and marker umc1648 exhibited the highest efficiency value of 88.89%. These results indicated that the four SSR markers developed in this study could be used for selection of maize germplasm with high seed storability.
Pick-ya actin: A method to purify actin isoforms with bespoke key post-translational modifications
Authors: Hatano Tomoyuki , Sivashanmugam Lavanya , Suchenko Andrejus , Hussain Hamdi , Balasubramanian Mohan K. 
Published: November 2019

AbstractActin is one of the most abundant eukaryotic cytoskeletal polymer-forming proteins, which in the filamentous form regulates a number of physiological processes, ranging from cell division and migration to development and tissue function. Actins are differentially post-translationally modified (PTMs) in different organisms, which include Met, Ala, Asp, and GluN-acetylation,N-arginylation, and the 73th His residue (His-73) methylation, with different organisms displaying a distinct signature of PTMs. Currently methods are not available to produce actin isoforms with organism specific PTM profile. Here we report Pick-ya actin, a method to express actin isoforms from any eukaryote with its own key characteristic PTM pattern. We achieve this using a synthetic biology strategy in a yeast strain that expresses 1. actin isoforms with the desiredN-end via ubiquitin fusion and 2. mammalian enzymes that promote acetylation and methylation. Pick-ya actin should greatly facilitate biochemical, structural, and physiological studies of the actin cytoskeleton and its PTMs.
PhenomeXcan: Mapping the genome to the phenome through the transcriptome
Authors: Pividori Milton , Rajagopal Padma S. , Barbeira Alvaro , Liang Yanyu , Melia Owen , Bastarache Lisa , Park YoSon ,   The GTEx Consortium, Wen Xiaoquan , Im Hae K. 
Published: November 2019

AbstractLarge-scale genomic and transcriptomic initiatives offer unprecedented ability to study the biology of complex traits and identify target genes for precision prevention or therapy. Translation to clinical contexts, however, has been slow and challenging due to lack of biological context for identified variant-level associations. Moreover, many translational researchers lack the computational or analytic infrastructures required to fully use these resources. We integrate genome-wide association study (GWAS) summary statistics from multiple publicly available sources and data from Genotype-Tissue Expression (GTEx) v8 using PrediXcan and provide a user-friendly platform for translational researchers based on state-of-the-art algorithms. We develop a novel Bayesian colocalization method, fastENLOC, to prioritize the most likely causal gene-trait associations. Our resource, PhenomeXcan, synthesizes 8.87 million variants from GWAS on 4,091 traits with transcriptome regulation data from 49 tissues in GTEx v8 into an innovative, gene-based resource including 22,255 genes. Across the entire genome/phenome space, we find 65,603 significant associations (Bonferroni-corrected p-value of 5.5 × 10−10), where 19,579 (29.8 percent) were colocalized (locus regional colocalization probability > 0.1). We successfully replicate associations from PheWAS Catalog (AUC=0.61) and OMIM (AUC=0.64). We provide examples of (a) finding novel and underreported genome-to-phenome associations, (b) exploring complex gene-trait clusters within PhenomeXcan, (c) studying phenome-to-phenome relationships between common and rare diseases via further integration of PhenomeXcan with ClinVar, and (d) evaluating potential therapeutic targets. PhenomeXcan (phenomexcan.org) broadens access to complex genomic and transcriptomic data and empowers translational researchers.One-Sentence SummaryPhenomeXcan is a gene-based resource of gene-trait associations with biological context that supports translational research.
A Sparse Deep Learning Approach for Automatic Segmentation of Human Vasculature in Multispectral Optoacoustic Tomography
Authors: Chlis Nikolaos-Kosmas , Karlas Angelos , Fasoula Nikolina-Alexia , Kallmayer Michael , Eckstein Hans-Henning , Theis Fabian J , Ntziachristos Vasilis , Marr Carsten 
Published: November 2019

AbstractMultispectral Optoacoustic Tomography (MSOT) resolves oxy- (HbO2) and deoxy-hemoglobin (Hb) to perform vascular imaging. MSOT suffers from gradual signal attenuation with depth due to light-tissue interactions: an effect that hinders the precise manual segmentation of vessels. Furthermore, vascular assessment requires functional tests, which last several minutes and result in recording thousands of images. Here, we introduce a deep learning approach with a sparse UNET (S-UNET) for automatic vascular segmentation in MSOT images to avoid the rigorous and time-consuming manual segmentation. We evaluated the S-UNET on a test-set of 33 images, achieving a median DICE score of 0.88. Apart from high segmentation performance, our method based its decision on two wavelengths with physical meaning for the task-at-hand: 850 nm (peak absorption of oxy-hemoglobin) and 810 nm (isosbestic point of oxy-and deoxy-hemoglobin). Thus, our approach achieves precise data-driven vascular segmentation for automated vascular assessment and may boost MSOT further towards its clinical translation.
LiGIoNs: A Computational Method for the Detection and Classification of Ligand-Gated Ion Channels
Authors: Apostolakou Avgi E. , Nastou Katerina C. , Petichakis Georgios N. , Litou Zoi I. , Iconomidou Vassiliki A. 
Published: November 2019

ABSTRACTLigand-Gated Ion Channels (LGICs) are one of the largest groups of transmembrane proteins. Due to their major role in synaptic transmission, both in the nervous system and the somatic neuromuscular junction, LGICs present attractive therapeutic targets. During the last few years several computational methods for the detection of LGICs have been developed. These methods are based on machine learning approaches utilizing features extracted solely from amino acid composition. Here we report the development of LiGIoNs, a profile Hidden Markov Model (pHMM) method for the prediction and ligand-based classification of LGICs. The method consists of a library of 10 pHMMs, one per LGIC subfamily, built from the alignment of representative LGIC sequences. In addition, 14 Pfam pHMMs are used to further annotate and classify unknown protein sequences into one of the 10 LGIC subfamilies. Evaluation of the method showed that it outperforms existent methods in the detection of LGICs. On top of that, LiGIoNs is the only currently available method that classifies LGICs into subfamilies.The method is available online at http://bioinformatics.biol.uoa.gr/ligions/.
bioRxiv: the preprint server for biology
Authors: Sever Richard , Roeder Ted , Hindle Samantha , Sussman Linda , Black Kevin-John , Argentine Janet , Manos Wayne , Inglis John R. 
Published: November 2019

AbstractThe traditional publication process delays dissemination of new research, often by months, sometimes by years. Preprint servers decouple dissemination of research papers from their evaluation and certification by journals, allowing researchers to share work immediately, receive feedback from a much larger audience, and provide evidence of productivity long before formal publication. Launched in 2013 as a non-profit community service, the bioRxiv server has brought preprint practice to the life sciences and recently posted its 64,000th manuscript. The server now receives more than four million views per month and hosts papers spanning all areas of biology. Initially dominated by evolutionary biology, genetics/genomics and computational biology, bioRxiv has been increasingly populated by papers in neuroscience, cell and developmental biology, and many other fields. Changes in journal and funder policies that encourage preprint posting have helped drive adoption, as has the development of bioRxiv technologies that allow authors to transfer papers easily between the server and journals. A bioRxiv user survey found that 42% of authors post their preprints prior to journal submission whereas 37% post concurrently with journal submission. Authors are motivated by a desire to share work early; they value the feedback they receive, and very rarely experience any negative consequences of preprint posting. Rapid dissemination via bioRxiv is also encouraging new initiatives that experiment with the peer review process and the development of novel approaches to literature filtering and assessment.
Read trimming is not required for mapping and quantification of RNA-seq reads
Authors: Liao Yang , Shi Wei 
Published: November 2019

AbstractRNA sequencing (RNA-seq) is currently the standard method for genome-wide gene expression profiling. RNA-seq reads often need to be mapped to a reference genome before read counts can be produced for genes. Read trimming methods have been developed to assist read mapping by removing adapter sequences and low-sequencing-quality bases. It is however unclear what is the impact of read trimming on the quantification of RNA-seq gene expression, an important task in the analysis of RNA-seq data. In this study, we used a benchmark RNA-seq dataset generated in the SEQC project to assess the impact of read trimming on mapping and quantification of RNA-seq reads. We found that adapter sequences can be effectively removed by the read aligner via its ‘soft-clipping’ procedure and many low-sequencing-quality bases, which would be removed by read trimming tools, were rescued by the aligner. Accuracy of gene expression quantification from using untrimmed reads was found to be comparable to or slightly better than that from using trimmed reads, based on expression of >900 genes measured by real-time PCR. Total data analysis time was reduced by up to an order of magnitude when read trimming was not performed. Our study suggests that read trimming is a redundant process in the quantification of RNA-seq expression data.
Sparse Ensemble Machine Learning to improve robustness of long-term decoding in iBMIs
Authors: Shaikh Shoeb , So Rosa , Sibindi Tafadzwa , Libedinsky Camilo , Basu Arindam 
Published: November 2019

AbstractThis paper presents a novel sparse ensemble based machine learning approach to enhance robustness of intracortical Brain Machine Interfaces (iBMIs) in the face of non-stationary distribution of input neural data across time. Each classifier in the ensemble is trained on a randomly sampled (with replacement) set of input channels. These sparse connections ensure that with a high chance, few of the base classifiers should be less affected by the variations in some of the recording channels. We have tested the generality of this technique on different base classifiers - linear discriminant analysis (LDA), support vector machine (SVM), extreme learning machine (ELM) and multilayer perceptron (MLP). Results show decoding accuracy improvements of up to ≈ 21%, 13%, 19%, 10% in non-human primate (NHP) A and 7%, 9%, 7%, 9% in NHP B across test days while using the sparse ensemble approach over a single classifier model for LDA, SVM, ELM and MLP algorithms respectively. The technique also holds ground when the most informative electrode on the test day is dropped. Accordingly, improvements of up to ≈ 24%, 11%, 22%, 9% in NHP A and 14%, 19%, 7%, 28% in NHP B are obtained for LDA, SVM, ELM and MLP respectively.
PAMOGK: A Pathway Graph Kernel based Multi-Omics Clustering Approach for Discovering Cancer Patient Subgroups
Authors: Tepeli Yasin Ilkagan , Ünal Ali Burak , Akdemir Furkan Mustafa , Tastan Oznur 
Published: November 2019

AbstractAccurate classification of patients into molecular subgroups is critical for the development of effective therapeutics and for deciphering what drives these subgroups to cancer. The availability of multi-omics data cat-alogs for large cohorts of cancer patients provides multiple views into the molecular biology of the tumors with unprecedented resolution. We develop PAMOGK (Pathway basedMultiOmicGraphKernel clustering) that not only integrates multi-omics patient data with existing biological knowledge on pathways. We develop a novel graph kernel that evaluates patient similarities based on a single molecular alteration type in the context of a pathway. To corroborate multiple views of patients evaluated by hundreds of pathways and molecular alteration combinations, we use multi-view kernel clustering. Applying PAMOGK to kidney renal clear cell carcinoma (KIRC) patients results in four clusters with significantly different survival times (p-value = 1.24e-11). When we compare PAMOGK to eight other state-of-the-art multi-omics clustering methods, PAMOGK consistently outperforms these in terms of its ability to partition KIRC patients into groups with different survival distributions. The discovered patient subgroups also differ with respect to other clinical parameters such as tumor stage and grade, and primary tumor and metastasis tumor spreads. The pathways identified as important are highly relevant to KIRC. PAMOGK is available at github.com/tastanlab/pamogk
Being a vegetarian traveller is not easy
Authors: Huang Yu-Chin , Chen Li-Hsin , Lu Cih-Wei , Shen Jui-Lin 
Published: November 2019

Purpose
Previous empirical studies have not documented the link between vegetarians’ dietary constraints and travel intentions. Therefore, the purpose of this paper is to utilise a mixed-methods approach to examine the interrelationships of this group’s travel motivations, travel constraints, constraint negotiations and behavioural intentions, with special reference to how dietary constraints deter its members from travelling, and its extent.

Design/methodology/approach
An online questionnaire was administered to outbound Taiwanese vegetarian travellers (n=418), and this was followed by in-depth, semi-structured interviews (n=9) to complement the quantitative data.

Findings
The results indicated that vegetarians’ dietary constraints significantly deterred them from travelling in certain circumstances: notably, in the company of non-vegetarians. Nevertheless, it was found that some vegetarians efficiently negotiated their constraints and persisted in travelling, in some cases, by compromising their dietary preferences.

Practical implications
Travel agents and planners should explore more strategies to meet the needs of vegetarian travellers to increase this group’s travel satisfaction.

Originality/value
This study established the first theoretical model explaining the relationships among vegetarians’ travel motivations, dietary constraints, constraint negotiations and travel intentions.