bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Pan-Cancer assessment of alterations of the kinase domain of ULK1, an upstream regulator of autophagy
Authors: Kumar Mukesh , Papaleo Elena 
Published: July 2019

ABSTRACTAutophagy is a key clearance process to recycle damaged cellular components. One important upstream regulator of autophagy is the ULK1 kinase. Several structures of the ULK1 kinase domain have been solved, but a comprehensive study, including molecular dynamics, is missing. Also, an exhaustive description of ULK1 alterations found in cancer samples is presently lacking. We here applied a framework which links -omics data to structural protein ensembles to study ULK1 alterations from genomics data available for more that 30 cancer types. Moreover, we predicted the effects of mutations on ULK1 function and structural stability, accounting for protein dynamics and the different layers of changes that a mutation can induce in a protein at the functional and structural level.We find that ULK1 is down-regulated in gynecological tumors. In other cancer types, ULK2 could compensate for ULK1 downregulation and, in the majority of the cases, no marked changes in expression have been found. 36 missense mutations of ULK1 are co-occurring with mutations in a large number of ULK1 interactors, suggesting a pronounced effect of the upstream steps of autophagy in many cancer types. Moreover, our results pinpoint that more than 50% of the ULK1 mutations that we studied are predicted to affect protein stability. Three mutations (S184F, D102N, and A28V) are predicted with only impact on kinase activity, either modifying the functional dynamics or the capability to exert effects from distal site to the functional and catalytic regions. The framework here applied could be extended to other protein targets to aid the classification of missense mutations from cancer genomics studies, as well as to prioritize variants for experimental validation, or to select the appropriate biological readouts for experiments.
Finite Element and deformation analyses predict pattern of bone failure in loaded zebrafish spines
Authors: Newman Elis , Kague Erika , Aggleton Jessye A. , Fernee Christianne , Brown Kate Robson , Hammond Chrissy L 
Published: July 2019

AbstractThe spine is the central skeletal support structure in vertebrates consisting of repeated units of bone, the vertebrae, separated by intervertebral discs that enable the movement of the spine. Spinal pathologies such as idiopathic back pain, vertebral compression fractures and intervertebral disc failure affect millions of people world-wide. Animal models can help us to understand the disease process, and zebrafish are increasingly used as they are highly genetically tractable, their spines are axially loaded like humans, and they show similar pathologies to humans during ageing. However biomechanical models for the zebrafish are largely lacking. Here we describe the results of loading intact zebrafish spinal motion segments on a material testing stage within a micro Computed Tomography machine. We show that vertebrae and their arches show predictable patterns of deformation prior to their ultimate failure, in a pattern dependent on their position within the segment. We further show using geometric morphometrics which regions of the vertebra deform the most during loading, and that Finite Element models of the trunk subjected reflect the real patterns of deformation and strain seen during loading and can therefore be used as a predictive model for biomechanical performance.
CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression
Authors: Mu Quanhua , Wang Jiguang 
Published: July 2019

AbstractCopy number alteration (CNA), the abnormal number of copies of genomic regions, plays a key role in cancer initiation and progression. Current high-throughput CNA detection methods, including DNA arrays and genomic sequencing, are relatively expensive and require DNA samples at a microgram level, which are not achievable in certain occasions such as clinical biopsies or single-cell genomes. Here we proposed an alternative method—CNAPE to computationally infer CNA using gene expression data. A prior knowledge-aided machine learning model was proposed, trained and tested on the transcriptomic profiles with matched CNA data of 9,740 cancers from The Cancer Genome Atlas. Using brain tumors as a proof-of-concept study, CNAPE achieved over 90% accuracy in the prediction of arm-level CNAs. Prediction performance for 12 gene-level CNAs (commonly altered genes in glioma) was also evaluated, and CNAPE achieved reasonable accuracy. CNAPE is developed as an easy-to-use tool at http://wang-lab.ust.hk/software/Software.html.
UDSMProt: Universal Deep Sequence Models for Protein Classification
Authors: Strodthoff Nils , Wagner Patrick , Wenzel Markus , Samek Wojciech 
Published: July 2019

AbstractMotivationInferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification tasks are tailored to single classification tasks and rely on handcrafted features such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple finetuning step.ResultsWe put forward a universal deep sequence model that is pretrained on unlabeled protein sequences from Swiss-Prot and finetuned on protein classification tasks. We apply it to three prototypical tasks, namely enzyme class prediction, gene ontology prediction and remote homology and fold detection. The proposed method performs on par with state-of-the-art algorithms that were tailored to these specific tasks or, for two out of three tasks, even outperforms them. These results stress the possibility of inferring protein properties from the sequence alone and, on more general grounds, the prospects of modern natural language processing methods in omics.AvailabilitySource code is available under https://github.com/nstrodt/UDSMProt.Contactfirstname.lastname@hhi.fraunhofer.de
Extracellular matrix-inducing Sox9 orchestrates basal progenitor proliferation and gliogenesis in developing neocortex
Authors: Güven Ayse , Stenzel Denise , Long Katherine R. , Florio Marta , Brandl Holger , Huttner Wieland B. 
Published: July 2019

AbstractNeocortex expansion is largely based on the proliferative capacity of basal progenitors (BPs), which is increased by extracellular matrix (ECM) components via integrin signaling. Here we show that Sox9 drives expression of ECM components and that laminin 211 increases BP proliferation in embryonic mouse neocortex. Examination of Sox9 expression reveals that Sox9 is expressed in BPs of developing ferret and human, but not mouse neocortex. Functional studies by conditional Sox9 expression in the mouse BP lineage demonstrate increased BP proliferation, reduced Tbr2 and induction of Olig2 expression, indicative of premature gliogenesis. Conditional Sox9 expression also results in cell non-autonomous stimulation of BP proliferation followed by increased production of upper-layer neurons. Collectively, our findings demonstrate that Sox9 exerts concerted effects on transcription, BP proliferation, neuron production, and neurogenic as well as gliogenic BP cell fate, suggesting that Sox9 acts a master regulator in the subventricular zone to promote neocortical expansion.
Pro-inflammatory cytokines disrupt β-cell circadian clocks in diabetes
Authors: Javeed Naureen , Brown Matthew R. , Rakshit Kuntol , Her Tracy , Ye Zhenqing , Lee Jeong Heon , Ordog Tamas , Matveyenko Aleksey V. 
Published: July 2019

ABSTRACTIntrinsic β-cell circadian clocks are a prerequisite for the control of glucose homeostasis through regulation of β-cell function and turnover. However, little is known about the contributions of circadian clock disruption to the natural progression of β-cell failure in diabetes. To address this, we examined the effects of cytokine-mediated inflammation, common to the pathophysiology of Type 1 and Type 2 diabetes, on the physiological, molecular, and epigenetic regulation of circadian clocks in β-cells. Specifically, we provide evidence that the key diabetogenic cytokine IL-1β disrupts functionality of the β-cell circadian clock and circadian regulation of insulin secretion through impaired expression of the key transcription factor Bmal1, evident at the level of promoter activation, mRNA, and protein expression. Additionally, IL-1β-mediated inflammation was shown to augment genome-wide DNA-binding patterns ofBmal1(and its heterodimer,Clock) in β-cells towards binding sites in the proximity of genes annotated to pathways regulating β-cell apoptosis, inflammation, and dedifferentiation. Finally, we identified that the development of hyperglycemia in humans is associated with compromised β-cell BMAL1 expression suggestive of a causative link between circadian clock disruption and β-cell failure in diabetes.
Demography, genetic, and extinction process in a spatially structured population of lekking bird
Authors: Cayuela Hugo , Prunier Jérôme G. , Laporte Martin , Gippet Jérôme , Boualit Laurent , Preiss Françoise , Laurent Alain , Foletti Francesco , Jacob Gwenaël 
Published: July 2019

AbstractUnderstanding the mechanisms underlying biological extinctions is a critical challenge for conservation biologists. Both deterministic (e.g. habitat loss, fragmentation) and stochastic (i.e. demographic stochasticity, Allee effect) demographic processes are involved in population decline. Simultaneously, a decrease of population size has far-reaching consequences for genetics of populations by increasing the risk of inbreeding and the effects of genetic drift, which together inevitably results in a loss of genetic diversity and a reduced effective population size (Ne). These genetic factors may retroactively affect vital rates (a phenomenon coined ‘inbreeding depression’), and therefore reduce population growth and accelerate the extinction process of small populations. To date, few studies have simultaneously examined the demographic and genetic mechanisms driving the extinction of wild populations, and have most of the time neglected the spatial structure of populations. In this study, we examined demographic and genetic factors involved in the extinction process of a spatially structured population of a lekking bird, the western capercaillie (Tetrao urogallus). To address this issue, we collected capture-recapture and genetic data over a 6-years period in Vosges mountains, France. Our study showed that the population ofT.urogallusexperienced a severe decline between 2010 and 2015. We did not detect any Allee effect on survival and recruitment. By contrast, individuals of both sexes dispersed to avoid small leks, suggesting a behavioral response to a mate finding Allee effect. In parallel to this demographic decline, the population showed a low genetic diversity and high inbreeding. In addition, the effective population sizes at both lek and population levels was low. Despite this, we did not detected evidence of inbreeding depression: neither survival nor recruitment were affected by individual inbreeding level. Our study underlines the benefit from combining demographic and genetic approaches to investigate processes that are involved in biological extinctions.
Multiple acyl-CoA thioesterases occupy distinct functional niches within the mitochondrial matrix
Authors: Bekeova Carmen , Anderson-Pullinger Lauren , Boye Kevin , Boos Felix , Sharpadskaya Yana , Herrmann Johannes M. , Seifert Erin L. 
Published: July 2019

SUMMARYAcyl-CoA thioesterases (Acots) hydrolyze fatty acyl-CoA esters. Acots in the mitochondrial matrix are poised to mitigate β-oxidation overload that may contribute to lipotoxicity. Several Acots associate with mitochondria, but whether they all localize to the matrix, and are redundant or have different roles is unresolved. We compared mitochondrial Acots (Acot2, 7, 9, and 13) in terms of suborganellar localization, activity, expression and regulation, in mitochondria from multiple mouse tissues and from a new model of Acot2 depletion. Acot7, 9 and 13 localized to the matrix, joining Acot2 that was previously shown to localize there. Mitochondria from heart, skeletal muscle, brown adipose tissue and kidney robustly expressed Acot2, 9 and 13, though Acot9 was substantially higher in brown adipose tissue and kidney mitochondria, as was activity for C4:0-CoA, a unique substrate of Acot9. In all these tissues, Acot2 accounted for ∼half of the thioesterase activity for C14-CoA and C16:0-CoA. In contrast, liver mitochondria from fed and fasted mice expressed little Acot activity, and this activity was confined to long-chain CoAs, and due mainly to Acot7 and Acot13 activity. Matrix Acots occupied different functional niches, based on substrate specificity (Acot9vs. Acot2 and 13) and strong CoA inhibition (Acot7, 9, 13 but not Acot2). Interpreting these results in the context of β-oxidation, CoA inhibition would prevent Acot-mediated suppression of β-oxidation while providing for an Acot-mediated release valve when CoA is limiting. This release valve would operate across a wide range of acyl-CoA chain lengths. In contrast, CoA-insensitive Acot2 could provide a constitutive syphon for long-chain fatty acyl-CoAs. These results reveal how the family of matrix Acots can help to mitigate β-oxidation overload and prevent a CoA limitation.
Searching for Simple Rules in Pseudomonas aeruginosa Biofilm Formation
Authors: Deveaux William , Selvarajoo Kumar 
Published: July 2019

AbstractLiving cells display complex and non-linear behaviors, especially when posed to environmental threats. Here, to understand the self-organizing cooperative behavior of a microorganism Pseudomonas aeruginosa, we developed a discrete spatiotemporal cellular automata model based on simple physical rules, similar to Conway’s game of life. The time evolution model simulations were experimentally verified for P. aeroginosa biofilm for both control and antibiotic azithromycin (AZM) treated condition. Our model suggests that AZM regulates the single cell motility, thereby resulting in delayed, but not abolished, biofilm formation. In addition, the model highlights the importance of reproduction by cell to cell interaction is key for biofilm formation. Overall, this work highlights another example where biological evolutionary complexity may be interpreted using rules taken from theoretical disciplines.
DNA mismatches reveal widespread conformational penalties in protein-DNA recognition
Authors: Afek Ariel , Shi Honglue , Rangadurai Atul , Sahay Harshit , Al-Hashimi Hashim M. , Gordan Raluca 
Published: July 2019

ABSTRACTTranscription-factor (TF) proteins recognize specific genomic sequences, despite an overwhelming excess of non-specific DNA, to regulate complex gene expression programs1–3. While there have been significant advances in understanding how DNA sequence and shape contribute to recognition, some fundamental aspects of protein-DNA binding remain poorly understood2,3. Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. How the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study and measure experimentally because the distorted DNA structures exist as low-abundance conformations in the naked B-DNA ensemble4–10. Here, we use a novel high-throughput assay called SaMBA (Saturation Mismatch-Binding Assay) to investigate the role of DNA conformational penalties in TF-DNA recognition. The approach introduces mismatched base-pairs (i.e. mispairs) within TF binding sites to pre-induce a variety of DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, while most mismatches either weakened TF binding (~70%) or had negligible effects (~20%), approximately 10% of mismatches increased binding and at least one mismatch was found that increased the binding affinity for each of 21 examined TFs. Mismatches also converted sites from the non-specific affinity range into specific sites, and high-affinity sites into “super-sites” stronger than any known canonical binding site. These findings reveal a complex binding landscape that cannot be explained based on DNA sequence alone. Analysis of crystal structures together with NMR and molecular dynamics simulations revealed that many of the mismatches that increase binding induce distortions similar to those induced by TF binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell11,12.
Blastula stage specification of avian neural crest
Authors: Prasad Maneeshi S. , Uribe-Querol Eileen , Marquez Jonathan , Vadasz Stephanie , Yardley Nathan , Shelar Patrick B. , Charney Rebekah M. , Garcia-Castro Martin I. 
Published: July 2019

AbstractCell fate specification defines the earliest steps towards a distinct cell lineage. Neural crest, a multipotent stem cell population, is thought to be specified from the ectoderm, but its varied contributions defy canons of segregation potential and challenges its embryonic origin. Aiming to resolve this conflict, we have assayed the earliest specification of neural crest using blastula stage chick embryos. Specification assays on isolated chick epiblast explants identify an intermediate region specified towards the neural crest cell fate. Furthermore, low density culture suggests that the specification of intermediate cells towards the neural crest lineage is independent of contact mediated induction. Finally, we have validated the regional identity of the intermediate region towards the neural crest cell fate using fate map studies in blastula stage chick embryos. Our results suggest a model of neural crest specification at blastula stage, with restricted ectoderm and mesoderm capacities.
BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)
Authors: Naseem Muhammad Tayyib , Ashfaq Muhammad , Khan Arif Muhammad , Rasool Akhtar , Asif Muhammad , Hebert Paul D.N. 
Published: July 2019

AbstractDNA barcoding is highly effective for identifying specimens once a reference sequence library is available for the species assemblage targeted for analysis. Despite the great need for an improved capacity to identify the insect pests of crops, the use of DNA barcoding is constrained by the lack of a well-parameterized reference library. The current study begins to address this limitation by developing a DNA barcode reference library for the pest aphids of Pakistan. It also examines the affinities of these taxa with conspecific taxa from other geographic regions based on both conventional taxonomy and Barcode Index Numbers (BINs). A total of 809 aphids were collected from 123 plant species at 87 sites across Pakistan. Morphological study and DNA barcoding allowed 774 specimens to be identified to one of 42 species while the others were placed to a genus or subfamily. The 801 sequences obtained from these specimens were assigned to 52 BINs whose monophyly were supported by neighbor-joining (NJ) clustering and Bayesian inference. The 42 species were assigned to 41 BINs with 38 showing BIN concordance; one species (Rhopalosiphum padi) was assigned to two BINs, while two others (Aphis affinis, Aphis gossypii) were assigned to the same BIN, while one species (Aphis astragalina) lacked a qualifying sequence. The 42 Linnaean species were represented on BOLD by 7,870 records from 69 countries. Combining these records with those from Pakistan produced to 60 BINs with 12 species showing a BIN split and three a BIN merger. Geo-distance correlations showed that intraspecific divergence values for 18 of 37 species were not affected by the distance between populations. Forty four of the 52 BINs from Pakistan had counterparts in 73 countries across six continents, documenting the broad distributions of pest aphids.
A hierarchical Bayesian latent class mixture model with censorship for detection of linear temporal changes in antibiotic resistance
Authors: Zhang Min , Wang Chong , O’Connor Annette 
Published: July 2019

AbstractIdentifying and controlling the emergence of antimicrobial resistance (AMR) is a high priority for researchers and public health officials. One critical component of this control effort is timely detection of emerging or increasing resistance using surveillance programs. Currently, detection of temporal changes in AMR relies mainly on analysis of the proportion of resistant isolates based on the dichotomization of minimum inhibitory concentration (MIC) values. In our work, we developed a hierarchical Bayesian latent class mixture model that incorporates a linear trend for the mean log2MIC of the non-resistant population. By introducing latent variables, our model addressed the challenges associated with the AMR MIC values, compensating for the censored nature of the MIC observations as well as the mixed components indicated by the censored MIC distributions. Inclusion of linear regression with time as a covariate in the hierarchical structure allowed modelling of the linear creep of the mean log2MIC in the non-resistant population. The hierarchical Bayesian model was accurate and robust as assessed in simulation studies. The proposed approach was illustrated using Salmonella enterica I,4,[5],12:i:- treated with chloramphenicol and ceftiofur in human and veterinary samples, revealing some significant linearly increasing patterns from the applications. Implementation of our approach to the analysis of an AMR MIC dataset would provide surveillance programs with a more complete picture of the changes in AMR over years by exploring the patterns of the mean resistance level in the non-resistant population. Our model could therefore serve as a timely indicator of a need for antibiotic intervention before an outbreak of resistance, highlighting the relevance of this work for public health. Currently, however, due to extreme right censoring on the MIC data, this approach has limited utility for tracking changes in the resistant population.
Chinese culture, materialism and corporate supply of trade credit
Authors: Chen Xian , Arnoldi Jakob , Chen Xin 
Published: July 2019

Purpose
The purpose of this paper is to investigate how cultural value in materialism affects corporate supply of trade credits.

Design/methodology/approach
Using a sample of 14,710 firm-year observations of Chinese listed firms from 1998 to 2012, the authors examine the influence of regional materialism on accounts receivable.

Findings
The authors find that listed firms within more materialistic tend to extend less trade credit to their customers, in particular in long-term categories of trade credit. Such negative effects can be significantly mitigated by state control, suggesting the effects are more pronounced in privately controlled listed firms. The negative effects of materialism still hold after controlling for other regional factors, such as trust, GDP per capita or institutional development.

Research limitations/implications
The authors show materialism as a cultural construct varies across Chinese regions, and it could have important impact on corporate supply of trade credits, besides the previous found effects on consumer use of credit.

Originality/value
This paper expands the literature about the influence of materialism on economic decision making from the individual level to the corporate level.