bluuebunny/crossref_metadata_2025_split huggingface dataset:
PRECISE: A domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors
Authors: Mourragui Soufiane , Loog Marco , Reinders Marcel JT , Wessels Lodewyk FA 
Published: February 2019

AbstractMotivationCell lines and patient-derived xenografts (PDX) have been used extensively to understand the molecular underpinnings of cancer. While core biological processes are typically conserved, these models also show important differences compared to human tumors, hampering the translation of findings from pre-clinical models to the human setting. In particular, employing drug response predictors generated on data derived from pre-clinical models to predict patient response, remains a challenging task. As very large drug response datasets have been collected for pre-clinical models, and patient drug response data is often lacking, there is an urgent need for methods that efficiently transfer drug response predictors from pre-clinical models to the human setting.ResultsWe show that cell lines and PDXs share common characteristics and processes with human tumors. We quantify this similarity and show that a regression model cannot simply be trained on cell lines or PDXs and then applied on tumors. We developed PRECISE, a novel methodology based on domain adaptation that captures the common information shared amongst pre-clinical models and human tumors in a consensus representation. Employing this representation, we train predictors of drug response on pre-clinical data and apply these predictors to stratify human tumors. We show that the resulting domain-invariant predictors show a small reduction in predictive performance in the pre-clinical domain but, importantly, reliably recover known associations between independent biomarkers and their companion drugs on human tumors.AvailabilityPRECISE and the scripts for running our experiments are available on our GitHub page (https://github.com/NKI-CCB/PRECISE).Contactl.wessels@nki.nlSupplementary informationSupplementary data are available. online.
Identification of lncRNAs associated with early stage breast cancer and their prognostic implications
Authors: Magendhra Rao Arunagiri Kuha Deva , Patel Krishna , Jyothi Sunitha Korivi , Meenakumari Balaiah , Sundersingh Shirley , Sridevi Velusami , Rajkumar Thangarajan , Pandey Akhilesh , Chatterjee Aditi , Gowda Harsha , Mani Samson 
Published: February 2019

AbstractBreast cancer is a common malignancy among women with the highest incidence rate worldwide. Dysregulation of long non-coding RNAs occurring in the preliminary stages of breast carcinogenesis is poorly understood. In this study, RNA sequencing was done to identify long non-coding RNA expression profiles associated with early-stage breast cancer. RNA sequencing was done in 6 invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, 7 ductal carcinomain situ(DCIS) tissues and 5 apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (∼58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was done in n=52 IDC and paired normal tissue by qRT-PCR for the identified targets (ADAMTS9-AS2, EPB41L4A-AS1, WDFY3-AS2, RP11-295M3.4, RP11-161M6.2, RP11-490M8.1, CTB-92J24.3 and FAM83H-AS)1. We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and overexpression of FAM83H-AS1 was associated with patient poor survival. We confirmed that the down-regulation of ADAMTS9-AS2 in breast cancer was due to promoter hypermethylation through in-vitro silencing experiments and pyrosequencing.
When do big problems far away become smaller than the problems closer to home
Authors: Donker Tjibbe , Hopkins Katie L. , Hopkins Susan , Muller-Pebody Berit , Peto Tim E.A. , Johnson Alan P. , Woodford Neil , Crook Derrick W. , Walker A. Sarah , Robotham Julie V. 
Published: February 2019

AbstractInfection prevention and control strategies aimed at reducing the occurrence of Carbapenemase-Producing Enterobacteriaceae (CPE) and other antimicrobial-resistant organisms often include advice about screening patients coming from hospitals with a known resistance problem, to prevent introductions into new hospitals by shared patients. We argue that, despite being an efficient method of identifying cases, admission screening for introduction prevention is only effective if the absolute number of imported cases from other hospitals outnumbers the cases coming from the hospital’s own patient population, and therefore is only a feasible control strategy during the start of an epidemic.
Intracortical dynamics underlying repetitive stimulation predicts changes in network connectivity
Authors: Huang Yuhao , Hajnal Boglárka , Entz László , Fabó Dániel , Herrero Jose L. , Mehta Ashesh D. , Keller Corey J. 
Published: February 2019

AbstractTargeted stimulation can be used to modulate the activity of brain networks. Previously we demonstrated that direct electrical stimulation produces predictable post-stimulation changes in brain excitability. However, understanding the neural dynamics during stimulation and its relationship to post-stimulation effects is limited but critical for treatment optimization. Here, we applied 10Hz direct electrical stimulation across several cortical regions in 14 patients implanted with intracranial electrodes for seizure monitoring. The stimulation train was characterized by a consistent increase in high gamma (70-170Hz) power. Immediately post-train, low-frequency (1-8Hz) power increased, resulting in an evoked response that was highly correlated with the neural response during stimulation. Using two measures of network connectivity, cortico-cortical evoked potentials (indexing effective connectivity) and theta coherence (indexing functional connectivity), we found a stronger response to stimulation in regions that were highly connected to the stimulation site. In these regions, repeated cycles of stimulation trains and rest progressively altered the stimulation response. Finally, after just 2 minutes (10%) of repetitive stimulation, we were able to predict post-stimulation connectivity changes with high discriminability. Taken together, this work reveals a relationship between stimulation dynamics and post-stimulation connectivity changes in humans. Thus, measuring neural activity during stimulation can inform future plasticity-inducing protocols.
Executive control of positive and negative information and adolescent depressive symptoms: cross-sectional and longitudinal associations in a population-based cohort
Authors: Lewis Gemma , Button Katherine S. , Pearson Rebecca M , Munafo Marcus R , Lewis Glyn 
Published: February 2019

AbstractBackgroundLarge population-based studies of neuropsychological factors that characterize or precede depressive symptoms are rare. Most studies use small case-control or cross-sectional designs, which may cause selection bias and cannot test temporality. In a large UK population-based cohort we investigated cross-sectional and longitudinal associations between executive control of positive and negative information and adolescent depressive symptoms.MethodsCohort study of 2315 UK adolescents (ALSPAC) who completed an affective go/no-go task at age 18. Depressive symptoms were assessed with the Clinical Interview Schedule Revised (CIS-R) and short Mood and Feeling Questionnaire (sMFQ) at age 18, and with the sMFQ 15 months later. Analyses were linear multilevel regressions (for cross-sectional associations) and traditional linear regressions (for longitudinal associations), before and after adjustment for confounders.ResultsCross-sectionally, at age 18, there was some evidence that adolescents with more depressive symptoms made more errors in executive control (after adjustments, errors increased by 0.17 of a point per 1 SD increase in sMFQ score, 95% CI 0.08 to 0.25). However, this cross-sectional association was not observed for the CIS-R (.03, 95% CI -.06 to .12). There was no evidence of a difference in executive control errors according to valence. Longitudinally, there was no evidence that reduced executive control was associated with future depressive symptoms.ConclusionsExecutive control of positive and negative information does not appear to be a marker of current or future depressive symptoms in adolescents and would therefore not be a useful target in interventions to prevent adolescent depression. According to our evidence, the affective go/no-go task is also not a good candidate for future neuroimaging studies of adolescent depression.
Pixel personality for dense object tracking in a 2D honeybee hive
Authors: Bozek Katarzyna , Hebert Laetitia , Mikheyev Alexander S , Stephens Greg J 
Published: February 2019

AbstractTracking large numbers of densely-arranged, interacting objects is challenging due to occlusions and the resulting complexity of possible trajectory combinations, as well as the sparsity of relevant, labeled datasets. Here we describe a novel technique of collective tracking in the model environment of a 2D honeybee hive in which sample colonies consist ofN∼ 103highly similar individuals, tightly packed, and in rapid, irregular motion. Such a system offers universal challenges for multiobject tracking, while being conveniently accessible for image recording. We first apply an accurate, segmentation-based object detection method to build initial short trajectory segments by matching object configurations based on class, position and orientation. We then join these tracks into full single object trajectories by creating an object recognition model which is adaptively trained to recognize honeybee individuals through their visual appearance across multiple frames, an attribute we denote as pixel personality. Overall, we reconstruct ∼ 46% of the trajectories in 5 min recordings from two different hives and over 71% of the tracks for at least 2 min. We provide validated trajectories spanning 3, 000 video frames of 876 unmarked moving bees in two distinct colonies in different locations and filmed with different pixel resolutions, which we expect to be useful in the further development of general-purpose tracking solutions.
Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize
Authors: Aguirre-Liguori Jonás A , Ramírez-Barahona Santiago , Tiffin Peter , Eguiarte Luis E 
Published: February 2019

AbstractClimate change is one of the most important threats to biodiversity and crop sustainability. The impact of climate change is often evaluated on the basis of expected changes in species’ geographical distributions. Genomic diversity, local adaptation, and migration are seldom integrated into projections of species’ responses to climate change. Here we predict that climate change will impact populations of two wild relatives of maize, the teosintesZea maysssp.mexicanaandZ. maysssp.parviglumis, by altering patterns of local adaptation and decreasing migration probabilities. These alterations appear to be geographically heterogeneous across populations, suggesting that the possible impacts of climate change will vary considerably among populations. This in spite that most populations exhibit high levels of genetic diversity and are predicted to lie within future suitable areas. The heterogeneous patterns of local adaptation uncovered in teosintes are also evident across maize landraces, which suggests that climate change may give way to future maladaptation of several landraces within currently cultivated areas, possibly leading to increased chances of production shocks under increased temperatures. The predicted alterations to habitat distribution, migration potential, and patterns of local adaptation in wild and cultivated maize, raises a red flag for the future of populations. This underscores the need for continued integration of agronomical practices, genomic data, and climate models to better understand the impacts of a rapidly changing climate on cultivated and wild species.
Detecting RyR clusters with CaCLEAN: influence of spatial distribution and structural heterogeneity
Authors: Ladd David , Tilunaite Agne , Soeller Christian , Roderick H. Llewelyn , Crampin Edmund , Rajagopal Vijay 
Published: February 2019

AbstractIn cardiomyocytes, the coordinated release of calcium ions from intracellular stores through ryanodine receptor (RyR) clusters is key to the generation of a calcium transient and induction of contraction. Recently, a deconvolution algorithm from radio astronomy was adapted and applied to analysis of calcium fluorescence imaging of cardiomyocytes. The algorithm, CaCLEAN, showed potential in revealing both the spatial locations of RyR clusters and their functional response in living cells. However, whether the RyR clusters identified by CaCLEAN analysis of the imaging data were true or false positives remained unvalidated in the absence of ground truth values. In this work, a structurally realistic finite element model was developed to simulate reaction-diffusion of calcium emanating from RyR clusters during the rising phase (first 30 ms) of the calcium transient. The effect of two sets of factors were examined with the model: (1) the number and spacing of simulated RyR clusters and (2) the effect of mitochondria acting as barriers to diffusion. Confocal fluorescence microscopy images were simulated from the model results and analysed using CaCLEAN. The performance of CaCLEAN was found to be sensitive to cluster spacing and distance from the imaging plane. In a case with sparsely-packed clusters, detection recall and precision were 0.82 for clusters up to 610 nm from the imaging plane; in a densely-packed cluster case, recall and precision were 0.69 for clusters up to 280 nm from the imaging plane. Users interested in applying CaCLEAN to their data should therefore consider the likely density of cluster distributions and the trade-off between precision and recall when determining the maximum relevant depth of RyR clusters in their application.
Enterococcus faeciumgenome dynamics during long-term asymptomatic patient gut colonization
Authors: Bayjanov Jumamurat R. , Baan Jery , Rogers Malbert R.C. , Troelstra Annet , Willems Rob J.L. , van Schaik Willem 
Published: February 2019

AbstractBackgroundE. faeciumis a gut commensal of humans and animals. In addition, it has recently emerged as an important nosocomial pathogen through the acquisition of genetic elements that confer resistance to antibiotics and virulence. We performed a whole-genome sequencing based study on 96 multidrug-resistantE. faeciumstrains that asymptomatically colonized five patients with the aim to describe the genome dynamics of this species.ResultsThe patients were hospitalized on multiple occasions and isolates were collected over periods ranging from 15 months to 6.5 years. Ninety-five of the sequenced isolates belonged toE. faeciumclade A1, which was previously determined to be responsible for the vast majority of clinical infections. The clade A1 strains clustered into six clonal groups of highly similar isolates, three of which entirely consisted of isolates from a single patient. We also found evidence of concurrent colonization of patients by multiple distinct lineages and transfer of strains between patients during hospitalisation. We estimated the evolutionary rate of two clonal groups that colonized a single patient at 12.6 and 25.2 single nucleotide polymorphisms (SNPs)/genome/year. A detailed analysis of the accessory genome of one of the clonal groups revealed considerable variation due to gene gain and loss events, including the chromosomal acquisition of a 37 kbp prophage and the loss of an element containing carbohydrate metabolism-related genes. We determined the presence and location of twelve different Insertion Sequence (IS) elements, with ISEfa5showing a unique pattern of location in 24 of the 25 isolates, suggesting widespread ISEfa5excision and insertion into the genome during gut colonization.ConclusionsOur findings show that theE. faeciumgenome is highly dynamic during asymptomatic colonization of the patient gut. We observe considerable genomic flexibility due to frequent horizontal gene transfer and recombination, which can contribute to the generation of genetic diversity within the species and, ultimately, can contribute to its success as a nosocomial pathogen.
Stability of an adaptively controlled pathway maximising specific flux under varying conditions
Authors: Overal Gosse B. , Hulshof Josephus , Planqué Robert 
Published: February 2019

AbstractMicrobial cells need to adapt to changing environmental conditions to survive. There is an evolutionary advantage to grow fast; this requires high metabolic rates, and an efficient allocation of enzymatic resources. Here we study a general control theory called qORAC, developed previously, which allows cells to adaptively control their enzyme allocations to achieve maximal steady state flux. The control is robust to perturbations in the environment, but those perturbations themselves do not feature in the control. In this paper we focus on the archetypical pathway, the linear chain with reversible Michaelis-Menten kinetics, together with qORAC control. First we assume that the metabolic pathway is in quasi-steady state with respect to enzyme synthesis. Then we show that the map between steady state metabolite and enzyme concentrations is a smooth bijection. Using this information, we finally show that the unique (and hence flux-maximising) steady state of this system is locally stable. We provide further evidence that it may in fact be globally stable.
Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage
Authors: Lau Anna Katharina , Leimeister Chris-André , Morgenstern Burkhard 
Published: February 2019

AbstractIn many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. Herein, we adapt our previously developed software programFiltered Spaced-Word Matches (FSWM)for alignment-free phylogeny reconstruction to work on unassembled reads; we call this implementationRead-SpaM. Test runs on simulated reads from bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage.Contact:bmorgen@gwdg.de
NNAlign_MA; semi-supervised MHC peptidome deconvolution for accurate characterization of MHC binding motifs and improved T cell epitope prediction
Authors: Alvarez Bruno , Reynisson Birkir , Barra Carolina , Buus Søren , Ternette Nicola , Connelley Tim , Andreatta Massimo , Nielsen Morten 
Published: February 2019

AbstractAntigen presentation by Major Histocompatibility Complex (MHC) is a cornerstone of the cellular immune system, and characterization of the rules defining which peptides are suitable for MHC presentation is of key interest for understanding T cell immunogenicity and the development of T cell driven therapeutics. The collective set of peptides presented on a cell surface by MHC molecules is known as the immunopeptidome. Due to the vast MHC polymorphism, this peptidome is unique between individuals. Current state-of-the-art liquid chromatography mass spectrometry (LC-MS) technologies allow the identification of large peptidomes specific for a given host or cell line, and numerous studies have proven this data to be a rich source of information for learning the rules of MHC-mediated antigen presentation. The data obtained with MS techniques is usually poly-specific – i.e. it contains multiple sequence motifs matching the different MHC molecules expressed in the system under investigation. Deconvolution of this poly-specificity has proven a challenge, and imposes a substantial limitation for learning MHC specific rules for antigen presentation from immunopeptidome data. This since each ligand first must be unambiguously associated to its presenting MHC molecule(s) within the haplotype of the cell line.Here, we describe NNAlign_MA, a method that is able to address this challenge. NNAlign_MA is capable of taking a mixed training set composed of single-allele (SA) data (peptides assigned to single MHCs) and multi-allele (MA) data (peptides with multiple options for MHCs assignments) as input, and in a fully automated manner deconvolute the individual MHC restriction of all MA sequences while learning the binding specificities of all the MHCs present in the training set.The NNAlign_MA method was benchmarked on a large and diverse dataset, covering human MHC class I and class II, and bovine class I (BoLA) data. For all cases, the method was demonstrated to have unprecedented performance compared to state-of-the-art methods, achieving a complete deconvolution of binding motifs contained within poly-specificity MS eluted ligand data and an improved predictive performance for identification of both eluted ligands and T cell epitopes.Given its very high flexibility and ease of use, we expect NNAlign_MA to serve as an effective tool to increase our understanding of the rules for MHC antigen presentation and guide the development of novel T cell-based therapeutics.
Variable Genome Evolution in Fungi After Transposon-Mediated Amplification of a Housekeeping Gene
Authors: Dhillon Braham , Kema Gert H. J. , Hamelin Richard , Bluhm Burt H. , Goodwin Stephen B. 
Published: February 2019

AbstractBackgroundTransposable elements (TEs) can be key drivers of evolution, but the mechanisms and scope of how they impact gene and genome function are largely unknown. Previous analyses revealed that TE-mediated gene amplifications can have variable effects on fungal genomes, from inactivation of function to production of multiple active copies. For example, a DNA methyltransferase gene in the wheat pathogenZymoseptoria tritici(synonymMycosphaerella graminicola) was amplified to tens of copies, all of which were inactivated by Repeat-Induced Point mutation (RIP) including the original, resulting in loss of cytosine methylation. In another wheat pathogen,Pyrenophora tritici-repentis, a histone H3 gene was amplified to tens of copies with little evidence of RIP, leading to many potentially active copies. To further test the effects of transposon-aided gene amplifications on genome evolution and architecture, the repetitive fraction of the significantly expandedPseudocercospora fijiensisgenome was analyzed in greater detail.ResultsThese analyses identified a housekeeping gene, histone H3, which was captured and amplified to hundreds of copies by ahATDNA transposon, all of which were inactivated by RIP, except for the original. InP. fijiensisthe original H3 gene probably was not protected from RIP, but most likely was maintained intact due to strong purifying selection. Comparative analyses revealed that a similar event occurred in five additional genomes representing the fungal generaCercospora, PseudocercosporaandSphaerulina.ConclusionsThese results indicate that the interplay of TEs and RIP can result in different and unpredictable fates of amplified genes, with variable effects on gene and genome evolution.