bluuebunny/crossref_metadata_2025 huggingface dataset:
Tailor: non-parametric and rapid score calibration method for database search-based peptide identification in shotgun proteomics
Authors: Sulimov Pavel , Kertész-Farkas Attila
Published: November 2019

Peptide-spectrum-match (PSM) scores used in database searching are calibrated to spectrum- or spectrum-peptide-specific null distributions. Some calibration methods rely on specific assumptions and use analytical models (e.g. binomial distributions), whereas other methods utilize exact empirical null distributions. The former may be inaccurate because of unjustified assumptions, while the latter are accurate, albeit computationally exhaustive. Here, we introduce a novel, non-parametric, heuristic PSM score calibration method, called Tailor, which calibrates PSM scores by dividing it with the top 100-quantile of the empirical, spectrum-specific null distributions (i.e. the score with an associated p-value of 0.01 at the tail, hence the name) observed during database searching. Tailor does not require any optimization steps or long calculations; it does not rely on any assumptions on the form of the score distribution, it works with any score functions with high- and low-resolution information. In our benchmark, we re-calibrated the match scores of XCorr from Crux, HyperScore scores from X!Tandem, and the p-values from OMSSA with Tailor method, and obtained more spectrum annotation than with raw scores at any false discovery rate level. Moreover, Tailor provided slightly more annotations than E-values of X!Tandem and OMSSA and approached the performance of the computationally exhaustive exact p-value method for XCorr on spectrum datasets containing low-resolution fragmentation information (MS2) around 20-150 times faster. On high-resolution MS2 datasets, the Tailor method with XCorr achieved state-of-the-art performance, and produced more annotations than the well-calibrated Res-ev score around 50-80 times faster.

Graphical TOC Entry
Allosteric coupling between α-rings of the 20S proteasome
Authors: Yu Zanlin , Yu Yadong , Wang Feng , Myasnikov Alexander G. , Coffino Philip , Cheng Yifan
Published: November 2019

The proteasomal machinery performs essential regulated protein degradation in eukaryotes. Classic proteasomes are symmetric, with a regulatory ATPase docked at each end of the cylindrical 20S. Asymmetric complexes are also present in cells, either with a single ATPase or with an ATPase and non-ATPase at two opposite ends. The mechanism that populates these different proteasomal complexes is unknown. Using archaea homologs, we constructed asymmetric forms of proteasomes. We demonstrate that the gate conformation of two opposite ends of 20S are coupled: binding one ATPase opens a gate locally, and also the remote opposite gate allosterically. Such allosteric coupling leads to cooperative binding of proteasomal ATPases to 20S, and promotes formation of proteasomes symmetrically configured with two identical ATPases. It may also promote formation of asymmetric complexes with an ATPase and a non-ATPase at opposite ends. We propose that in eukaryotes a similar mechanism regulates the composition of the proteasomal population.
Adaptations to Oral and Pharyngeal Swallowing Function Induced by Injury to the Mylohyoid Muscle
Authors: King Suzanne N. , Fletcher Brittany , Kimbel Bradley , Bonomo Nicholas , Pitts Teresa
Published: November 2019

Muscle injury is a frequent side effect of radiation treatment for head and neck cancer. To understand the pathophysiology of injury-related dysfunction, we investigated the effects of a single muscle injury to the mylohyoid on oropharyngeal swallowing function in the rat. The mylohyoid protects the airway from food/liquid via hyolaryngeal elevation and plays an active role during both oral and pharyngeal swallowing. We hypothesized (1) that fibrosis to the mylohyoid alters swallowing bolus flow and licking patterns; (2) that injury to the mylohyoid changes normal activity of submental, laryngeal, and pharyngeal muscles during swallowing. A chilled cryoprobe was applied to the rat mylohyoid muscle to create a localized injury. After 1- and 2-weeks post-injury, swallowing bolus transit was assessed via videofluoroscopy and licking behavior via an electrical lick sensor. The motor activity of five swallow-related muscles were analyzed immediately after injury using electromyography (EMG). Comparisons were made pre- and post-injury. Fibrosis was confirmed in the mylohyoid at 2-weeks post-injury by measuring collagen content. One-week after injury, bolus size decreased, swallowing rate reduced, and licking patterns were altered. Immediately post-injury, there was a significant depression in mylohyoid and thyropharyngeus EMG amplitudes during swallowing. Our results demonstrated that injury to the mylohyoid is sufficient to cause changes in deglutition. These disruptions in oral and pharyngeal swallowing were detected prior to long-term fibrotic changes, including delays in tongue movement, alterations in bolus flow, and changes in sensorimotor function. Therefore, injuring a single important swallowing muscle can have dramatic clinical effects.
Development and validation of a deep learning framework for Alzheimer’s disease classification
Authors: Kolachalama Vijaya B. , Qiu Shangran , Joshi Prajakta S. , Miller Matthew I. , Xue Chonghua , Karjadi Cody , Chang Gary H. , Joshi Anant S. , Dwyer Brigid , Zhu Shuhan , Kaku Michelle , Zhou Yan , Alderazi Yazan J. , Swaminathan Arun , Kedar Sachin , Saint-Hilaire Marie-Helene , Auerbach Sanford H. , Yuan Jing , Sartor E. Alton , Au Rhoda
Published: November 2019

Alzheimer’s disease (AD) is the primary cause of dementia worldwide (1), with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and magnetic resonance imaging (MRI) to identify likely cases, yet effective practices remain variably-applied and lacking in sensitivity and specificity (2). Here we report an explainable deep learning strategy that delineates unique AD signatures from multimodal inputs of MRI, age, gender, and mini-mental state examination (MMSE) score. Our framework linked a fully convolutional network (FCN) to a multilayer perceptron (MLP) to construct high resolution maps of disease probability from local brain structure. This enabled precise, intuitive visualization of individual AD risk en route to accurate diagnosis. The model was trained using clinically-diagnosed AD and cognitively normal (NC) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset (n=417) (3), and validated on three independent cohorts: the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL, n=382) (4), the Framingham Heart Study (FHS, n=102) (5), and the National Alzheimer’s Coordinating Center (NACC, n=582) (6). Model performance was consistent across datasets, with mean accuracy values of 0.966, 0.948, 0.815, and 0.916 for ADNI, AIBL, FHS and NACC, respectively. Moreover, our approach exceeded the diagnostic performance of a multi-institutional team of practicing neurologists (n=11), and high-risk cerebral regions predicted by the model closely tracked postmortem histopathological findings. This framework provides a clinically-adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for AD diagnosis, as well as a generalizable approach for linking deep learning to pathophysiological processes in human disease.
Blocks in tricarboxylic acid cycle ofSalmonella entericacause global perturbation of carbon storage, motility and host-pathogen-interaction
Authors: Noster Janina , Hansmeier Nicole , Persicke Marcus , Chao Tzu-Chiao , Kurre Rainer , Popp Jasmin , Liss Viktoria , Reuter Tatjana , Hensel Michael
Published: November 2019

The tricarboxylic acid cycle is a central metabolic hub in most cells. Virulence functions of bacterial pathogens such as facultative intracellularSalmonella entericaserovar Typhimurium (STM) are closely connected to cellular metabolism. During systematic analyses of mutant strains with defects in TCA cycle, a strain deficient in all fumarase isoforms (ΔfumABC) elicited a unique metabolic profile. Alongside fumarate STM ΔfumABCaccumulates intermediates of glycolysis and pentose phosphate pathway. Analyses by metabolomics and proteomics revealed that fumarate accumulation redirects carbon fluxes towards glycogen synthesis due to high (p)ppGpp levels. In addition, we observed reduced abundance of CheY, leading to altered motility and increased phagocytosis of STM by macrophages. Deletion of glycogen synthase restored normal carbon fluxes and phagocytosis, and partially levels of CheY. We propose that utilization of accumulated fumarate as carbon source induces a status similar to exponential to stationary growth phase transition by switching from preferred carbon sources to fumarate, which increases (p)ppGpp levels and thereby glycogen synthesis. Thus, we observed a new form of interplay between metabolism of STM, and cellular functions and virulence.

Importance

We performed perturbation analyses of the tricarboxylic acid cycle of the gastrointestinal pathogenSalmonella entericaserovar Typhimurium. The defect of fumarase activity led to accumulation of fumarate, but also resulted in a global alteration of carbon fluxes, leading to increased storage of glycogen. Gross alterations were observed in proteome and metabolome compositions of fumarase-deficientSalmonella. In turn, these changes were linked to aberrant motility patterns of the mutant strain, and resulted in highly increased phagocytic uptake by macrophages. Our findings indicate that basic cellular functions and specific virulence functions inSalmonellacritically depend on the proper function of the primary metabolism.
Species delimitation in the grey zone: introgression obfuscates phylogenetic inference and species boundaries in a cryptic frog complex (Ranidae: Pulchrana picturata)
Authors: Chan Kin Onn , Hutter Carl R. , Wood Perry L. , Lee Grismer L. , Brown Rafe M.
Published: November 2019

As molecular methods continue to elucidate genetic structure at increasingly finer resolutions, delimiting species in the grey zone of the speciation continuum is becoming more relevant in biodiversity research, especially in under-studied biodiversity hotspots such as Southeast Asia where new species are being described at an unprecedented rate. Obvious species at both ends of the speciation continuum have mostly been described and attention is now turning towards the “grey zone:” an intermediate stage in which species criteria are in conflict and boundaries between populations and species are less clear. This study demonstrates that widely-used criteria (phylogenetic placement, genetic divergence, phylogeny- and distance-based species delimitation methods) can overestimate species diversity/boundaries when introgression is present. However, a comprehensive species delimitation framework that considers spatial and genetic population structure, introgression, and the use of species delimitation methods based on parameter estimation, can provide a more accurate characterization of species boundaries in this grey zone. We applied this approach to a group of Southeast Asian frogs from the Pulchrana picturata Complex that exhibits continuous morphological variation and high genetic divergences. Results showed that introgression was rampant among Bornean populations, which led to phylogenetic discordance and an overestimation of species. We suspect that our results do not form an isolated case; and that introgression among cryptic populations, occurring continuously across a wide geographic area (e.g., the topographically complex island of Borneo, and Earth’s major continents), may be more common than previously thought.
Dissecting the coma spectrum using Bayesian classification
Authors: Dietz Martin J. , Zareini Bochra , Näätänen Risto , Overgaard Morten
Published: November 2019

A 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

Bivalent 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

Metalloporphyrins 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

While 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

Diffusion 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

Seed 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

Actin 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

Large-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 Summary

PhenomeXcan 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

Multispectral 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

Ligand-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

The 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

RNA 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

This 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

Accurate 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
Context-specific regulation of cell survival by a miRNA-controlled BIM rheostat
Authors: Labi Verena , Peng Siying , Klironomos Filippos , Munschauer Mathias , Kastelic Nicolai , Chakraborty Tirtha , Schoeler Katia , Derudder Emmanuel , Martella Manuela , Mastrobuoni Guido , Hernandez-Miranda Luis R. , Lahmann Ines , Kocks Christine , Birchmeier Carmen , Kempa Stefan , Quintanilla-Martinez de Fend Leticia , Landthaler Markus , Rajewsky Nikolaus , Rajewsky Klaus
Published: November 2019

Knockout of the ubiquitously expressed miRNA-17∼92 cluster in mice produces a lethal developmental lung defect, skeletal abnormalities, and blocked B lymphopoiesis. A shared target of miR-17∼92 miRNAs is the pro-apoptotic protein BIM, central to life-death decisions in mammalian cells. To clarify the contribution of miR-17∼92:Bim interactions to the complex miR-17∼92 knockout phenotype, we used a system of conditional mutagenesis of the nine Bim 3′ UTR miR-17∼92 seed matches. Blocking miR-17∼92:Bim interactions early in development phenocopied the lethal lung phenotype of miR-17∼92 ablation and generated a skeletal kinky tail. In the hematopoietic system, instead of causing the predicted B cell developmental block, it produced a selective inability of B cells to resist cellular stress; and prevented B and T cell hyperplasia caused by Bim haploinsufficiency. Thus, the interaction of miR-17∼92 with a single target is essential for life, and BIM regulation by miRNAs serves as a rheostat controlling cell survival in specific physiological contexts.
Clonal copy-number mosaicism in autoreactive T lymphocytes in diabetic NOD mice
Authors: Alriyami Maha , Marchand Luc , Li Quan , Du Xiaoyu , Olivier Martin , Polychronakos Constantin
Published: November 2019

Concordance for type 1 diabetes (T1D) is far from 100% in monozygotic twins and in inbred nonobese diabetic (NOD) mice, despite genetic identity and shared environment during incidence peak years. This points to stochastic determinants, such as postzygotic mutations (PZMs) in the expanding antigen-specific autoreactive T cell lineages, by analogy to their role in the expanding tumor lineage in cancer. Using comparative genomic hybridization of DNA from pancreatic lymph-node memory CD4+ T cells of 25 diabetic NOD mice, we found lymphocyte-exclusive mosaic somatic copy-number aberrations (CNAs) with highly nonrandom independent involvement of the same gene(s) across different mice, some with an autoimmunity association (e.g., Ilf3 and Dgka). We confirmed genes of interest using the gold standard approach for CNA quantification, multiplex ligation-dependent probe amplification (MLPA), as an independent method. As controls, we examined lymphocytes expanded during normal host defense (17 NOD and BALB/c mice infected with Leishmania major parasite). Here, CNAs found were fewer and significantly smaller compared to those in autoreactive cells (P = 0.0019). We determined a low T cell clonality for our samples suggesting a prethymic formation of these CNAs. In this study, we describe a novel, unexplored phenomenon of a potential causal contribution of PZMs in autoreactive T cells in T1D pathogenesis. We expect that exploration of point mutations and studies in human T cells will enable the further delineation of driver genes to target for functional studies. Our findings challenge the classical notions of autoimmunity and open conceptual avenues toward individualized prevention and therapeutics.
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.
Equity incentive schemes, investor protection and corporate performance
Authors: Su Zili , Alexiou Constantinos
Published: November 2019

Purpose

On the basis of corporate governance and agency cost theory, using the fifth sub-indicator of Fan et al. China Marketization Index as the regional investor protection index (IPI), the purpose of this paper is to explore the impact of equity incentives and regional investor protection on corporate payout policies and corporate performance.

Design/methodology/approach

This paper establishes ordinary least squares regression model to examine interactions between the effects of equity incentives and regional investor protection upon firms’ dividend payouts. In addition, the authors also explore whether the joint effects on payouts are altered in the presence of growth opportunities, and investigate the effects of interactions between equity incentives and regional investor protection on corporate performance.

Findings

The authors observe that firm managers appear to abuse equity incentives by increasing dividend payouts. However, regional investor protection can potentially restrain such behavior. The restraining effect depends on the firms’ growth opportunities, on the basis of which the effect on cash (stock) dividends is found to be weaker (stronger) in high-growth firms – and stronger (weaker) in low-growth firms. Further evidence indicates that the restraining effect of regional investor protection on selfish dividend-related behavior encouraged by equity incentives may also prove valuable in encouraging exploitation of these incentives so as to enhance corporate performance.

Practical implications

Since reforming investor protection laws and improving judicial quality are difficult and lengthy at a country level. Improving regional levels of investor protection, however, seems more feasible and effective. Through measures encouraging the development of intermediaries, increases in the number of lawyers – all of which seem likely to constrain behavior harmful to the interests of investors – the provincial administrations can reasonably expect to contribute toward improvements in the performance of firms and the development of the economy in their region. This paper provides encouragement to regional policy makers in China and in other developing countries.

Originality/value

This paper uses a regional index of investor protection to study the impact on corporate dividends and performance, in contrast with most previous studies, which have examined these issues at country or individual firm levels. The use of a regional-level investor IPI in this paper therefore fills a gap by coming in between the country- and firm-level indicators typically used in previous research, thus providing a new perspective on investor protection issues.
The impact of digital transformation on formal and informal organizational structures of large architecture and engineering firms
Authors: Bonanomi Marcella M. , Hall Daniel M. , Staub-French Sheryl , Tucker Aubrey , Talamo Cinzia Maria Luisa
Published: November 2019

Purpose

The purpose of this paper is to understand the impact of digital technologies adoption on the forms of organization of large architecture and engineering (A/E) firms. Network theory has attracted scholarly and managerial attention, particularly from the perspective of the changes of project organization. However, little research focuses on network theory as a lens for understanding and managing the new forms of firms’ organization. Additionally, conventional organizational analyses are hampered by the lack of methods for understanding the changes in roles and relationships due to the adoption of digital technologies and examining their impact on organizational structures.

Design/methodology/approach

To address this gap, this research adopted a mixed-method case-study approach. This approach combined interviews, regular check-ins, and document analysis with data mining and social network analysis (SNA) to capture the changes of intra-organizational roles and relationships and for understanding their impact on the firm’s organizational structure. Using the data gathered, the authors created a dendrogram that shows the formal organizational structure, a sociogram that displays the informal organizational structure and a network map that visualizes the interplay between the two structures.

Findings

From this analysis, the authors identified four main findings: informal roles – as go-to people for advice and information about digital technologies – play within A/E firms facing digital transformation; such go-to people operate through informal networked relationships and beyond their formal roles; most of these relationships do not overlap with the formal reporting relationships; the combination of both these roles and relationships create an informal social network. The authors also show how managers can use SNA to understand the changes in roles and relationships due to the adoption of digital technologies and to diagnose their impact on organizational structures.

Originality/value

This research contributes to the literature of organizational design and change management from a network perspective in the context of the digital transformation of large A/E firms. It provides a systematic data-driven approach to understanding the changes of intra-organizational roles and relationships within A/E firms facing digital transformation and to diagnosing the impact of these changes on firms’ organizational structures.
Overcoming barriers to climate smart agriculture in India
Authors: Tankha Sunil , Fernandes Denise , Narayanan N.C.
Published: November 2019

Purpose

This paper aims to report on a case in which encouraging climate-smart agriculture in the form of better irrigation techniques in India can contribute to both climate change mitigation and adaptation goals by improving resource-use efficiency. It provides grounded institutional analysis on how these transformations can occur.

Design/methodology/approach

The authors based their research on three complementary approaches: institutional, sociological and technical. The institutional approach analyzed actors and interests in the water-energy nexus in India via over 25 semi-structured key informant interviews. The sociological approach surveyed over 50 farmers and equipment suppliers for insight into technology adoption. The technical component analyzed water and energy consumption data to calculate potential benefits from transitioning to more efficient techniques.

Findings

Because policymakers have a preference for voluntary policy instruments over coercive reforms, distortions in policy and market arenas can provide opportunities for embedded actors to leverage technology and craft policy bargains which facilitate Pareto superior reforms and, thereby, avoid stalemates in addressing climate change. Enlarging the solution space to include more actors and interests can facilitate such bargains more than traditional bilateral exchanges.

Practical implications

The analysis provides insights into crafting successful climate action policies in an inhospitable institutional terrain.

Originality/value

Studies about climate change politics generally focus on stalemates and portray the private sector as resistant and a barrier to climate action. This paper analyzes a contrary phenomenon, showing how reforms can be packaged in Pareto superior formats to overcome policy stalemates and generate technology-based climate and environmental co-benefits in even unpromising terrain such as technologically laggard and economically constrained populations.
Analysis of an optimal hybrid power system for an off-grid community in Nigeria
Authors: Babatunde Olubayo Moses , Babatunde Damilola Elizabeth , Denwigwe Iheanacho Henry , Adedoja Toyosi Beatrice , Adedoja Oluwaseye Samson , Okharedia Taiwo Emmanuel
Published: November 2019

Purpose

This study aims to analyze the effects of variations in annual real interest rates in the assessment of the techno-economic feasibility of a hybrid renewable energy system (HRES) for an off-grid community.

Design/methodology/approach

Hybrid Optimization of Multiple Energy Resources (HOMER) software is used to propose an HRES for Abadam community in northern Nigeria. The HRES was designed to meet the basic needs of the community over a 25-year project lifespan. Based on the available energy resources in the community, photovoltaic (PV), wind turbine, diesel generator and battery were suggested for integration to serve the load requirements.

Findings

When the annual real interest rates were taken as 10 and 8 per cent, the total amount of total energy fraction from PV, wind turbine and the diesel generator is 28, 57 and 15 per cent, respectively. At these interest rates, wind turbines contributed more energy across all months than other energy resources. The energy resource distribution for 0, 2,4 and 6 per cent annual real interest rates have a similar pattern, but PV contributed a majority of the energy.

Practical implications

This study has used annual real interest and inflation rates dynamic behavior to determine optimal HRES for remote communities. Hence, its analysis will equip decision-makers with the necessary information for accurate planning.

Originality/value

The results of this study can be used to plan and design HRES infrastructure for off-grid communities around the world.