bluuebunny/crossref_metadata_2025_split huggingface dataset:
Augmenting protein network embeddings with sequence information
Authors: Kané Hassan , Coulibali Mohamed , Abdalla Ali , Ajanoh Pelkins 
Published: August 2019

ABSTRACTComputational methods that infer the function of proteins are key to understanding life at the molecular level. In recent years, representation learning has emerged as a powerful paradigm to discover new patterns among entities as varied as images, words, speech, molecules. In typical representation learning, there is only one source of data or one level of abstraction at which the learned representation occurs. However, proteins can be described by their primary, secondary, tertiary, and quaternary structure or even as nodes in protein-protein interaction networks. Given that protein function is an emergent property of all these levels of interactions in this work, we learn joint representations from both amino acid sequence and multilayer networks representing tissue-specific protein-protein interactions. Using these hybrid representations, we show that simple machine learning models trained using these hybrid representations outperform existing network-based methods on the task of tissue-specific protein function prediction on 13 out of 13 tissues. Furthermore, these representations outperform existing ones by 14% on average.
Quantification of malaria antigens PfHRP2 and pLDH by quantitative suspension array technology in whole blood, dried blood spot and plasma
Authors: Martiáñez-Vendrell Xavier , Jiménez Alfons , Vásquez Ana , Campillo Ana , Incardona Sandra , González Raquel , Gamboa Dionicia , Torres Katherine , Oyibo Wellington , Faye Babacar , Macete Eusebio , Menéndez Clara , Ding Xavier C. , Mayor Alfredo 
Published: August 2019

ABSTRACTBackgroundMalaria diagnostics by rapid diagnostic tests (RDTs) relies primarily on the qualitative detection ofPlasmodium falciparumhistidine-rich protein 2 (PfHRP2) andPlasmodium splactate dehydrogenase (pLDH). As novel RDTs with increased sensitivity are being developed and implemented as point of care diagnostics, highly sensitive laboratory based assays are needed for evaluating RDTs performance. Here, a quantitative suspension array technology (qSAT) was developed, validated and applied for the simultaneous detection of PfHRP2 and pLDH in a variety of clinical samples (whole blood, plasma and dried blood spots) from different endemic countries.ResultsThe qSAT was specific for the target antigens, with analytical ranges of 6.8 to 762.8 pg/ml for PfHRP2 and 78.1 to 17076.6 pg/ml forP. falciparum(Pf-LDH). The assay detectedP. vivaxLDH (Pv-LDH) at a lower sensitivity than Pf-LDH (analytical range of 1093.20 to 187288.5 pg/ml). Both PfHRP2 and pLDH levels determined using the qSAT showed to positively correlate with parasite densities determined by quantitative PCR (Spearman r=0.59 and 0.75, respectively) as well as microscopy (Spearman r=0.40 and 0.75, respectively), suggesting the assay to be a good predictor of parasite density.ConclusionThis immunoassay can be used as a reference test for the detection and quantification of PfHRP2 and pLDH, and could serve for external validation of RDTs performance, to determine antigen persistence after parasite clearance, as well as a complementary tool to assess malaria burden in endemic settings.
Quantifying genetic effects on disease mediated by assayed gene expression levels
Authors: Yao Douglas W. , O’Connor Luke J. , Price Alkes L. , Gusev Alexander 
Published: August 2019

AbstractDisease variants identified by genome-wide association studies (GWAS) tend to overlap with expression quantitative trait loci (eQTLs). However, it remains unclear whether this overlap is driven by mediation of genetic effects on disease by expression levels, or whether it primarily reflects pleiotropic relationships instead. Here we introduce a new method, mediated expression score regression (MESC), to estimate disease heritability mediated by the cis-genetic component of assayed steady-state gene expression levels, using summary association statistics from GWAS and eQTL studies. We show that MESC produces robust estimates of expression-mediated heritability across a wide range of simulations. We applied MESC to GWAS summary statistics for 42 diseases and complex traits (averageN= 323K) and cis-eQTL data across 48 tissues from the GTEx consortium. We determined that a statistically significant but low proportion of disease heritability (mean estimate 11% with S.E. 2%) is mediated by the cis-genetic component of assayed gene expression levels, with substantial variation across diseases (point estimates from 0% to 38%). We further partitioned expression-mediated heritability across various gene sets. We observed an inverse relationship between cis-heritability of expression and disease heritability mediated by expression, suggesting that genes with weaker eQTLs have larger causal effects on disease. Moreover, we observed broad patterns of expression-mediated heritability enrichment across functional gene sets that implicate specific gene sets in disease, including loss-of-function intolerant genes and FDA-approved drug targets. Our results demonstrate that eQTLs estimated from steady-state expression levels in bulk tissues are informative of regulatory disease mechanisms, but that such eQTLs are insufficient to explain the majority of disease heritability. Instead, additional assays are necessary to more fully capture the regulatory effects of GWAS variants.
Antibody Targeting of B7-H4 Enhances the Immune Response in Urothelial Carcinoma
Authors: Podojil Joseph R. , Glaser Alexander P. , Baker Dylan , Courtois Elise T. , Fantini Damiano , Yu Yanni , Eaton Valerie , Sivajothi Santhosh , Robson Paul , Miller Stephen D. , Meeks Joshua J. 
Published: August 2019

AbstractLocally advanced urothelial carcinoma has a poor survival despite a response to immunotherapy in approximately 25% of patients. To develop new therapies targeting other immune checkpoints, we identified increased expression of the T cell inhibitor protein, B7-H4 (VTCN1, B7S1, B7X), during tumor development of murine bladder cancer. Evaluation of B7-H4 in human bladder cancer by single-cell RNA-Seq and immune mass cytometry showed that B7-H4 is expressed by luminal tumors that are not normally responsive to PD-1 inhibitors. Additionally, overexpression B7-H4 was associated with significantly worse patient survival. In support of clinical translation, treatment of human monocyte and T cell co-cultures with a B7-H4 blocking antibody resulted in enhanced IFN-γ secretion by CD4+and CD8+T cell. While the study of B7-H4 in mouse cancer models has been difficult using tumor cell lines, our findings show that B7-H4 expression increased at 3 months after exposure to BBN on CD11b+monocytes/macrophages and delivery of anti-B7-H4 antibody resulted in decreased tumor size and increased CD8 immune cell infiltration with increased CD8+/IFN-γ-producing T cells and a complimentary decrease in tumor infiltrating T regulatory cells (Tregs). Furthermore, treatment with a combination of anti-PD-1 and anti-B7-H4 antibodies resulted in a significant reduction in tumor stage. This data suggests that novel anti-B7-H4 antibodies maybe a viable target for bladder cancers unresponsive to PD-1 checkpoint inhibitors.
Silencing epigenetic writer DOT1L attenuates intimal hyperplasia
Authors: Huang Yitao , Urabe Go , Zhang Mengxue , Li Jing , Wang Bowen , Craig Kent K. , Guo Lian-Wang 
Published: August 2019

AbstractObjectiveHistone methyltransferases are emerging targets for epigenetic therapy. DOT1L (disruptor of telomeric silencing 1-like) is the H3K79 methylation writer. We investigated its role in the development of intimal hyperplasia (IH).Approach and ResultsIH was induced via balloon angioplasty in rat carotid arteries. DOT1L and its catalytic products H3K79me2 and H3K79me3 (immunostaining) increased by 4.69 ±0.34, 2.38 ±0.052, and 3.07 ±0.27 fold, respectively, in injured (versus uninjured) carotid arteries at post-injury day 7. DOT1L silencing via shRNA-lentivirus infusion in injured arteries reduced DOT1L, H3K79me2, and IH at day 14 by 54.5%, 37.1%, and 76.5%, respectively. Moreover, perivascular administration of a DOT1L-selective inhibitor (EPZ5676) reduced H3K79me2, H3K79me3, and IH by 56.1%, 58.6%, and 39.9%, respectively.ConclusionsDOT1L inhibition mitigates the development of IH.
Transferrin binding protein B and Transferrin binding protein A 2 expand the transferrin recognition range ofHistophilus somni
Authors: Pogoutse Anastassia K. , Moraes Trevor F. 
Published: August 2019

AbstractThe bacterial bipartite transferrin receptor is an iron acquisition system that is required for survival by several key human and animal pathogens. It consists of the TonB-dependent transporter Transferrin binding protein A (TbpA) and the surface lipoprotein Transferrin binding protein B (TbpB). Curiously, the Tbps are only found in host specific pathogens, and are themselves host specific, meaning that they will bind to the transferrin of their host species, but not to those of other animal species. While this phenomenon has long been established, neither the steps in the evolutionary process that led to this exquisite adaptation for the host, nor the steps that could alter it, are known. We sought to gain insight into these processes by studying Tbp specificity inHistophilus somni, a major pathogen of cattle. A past study showed that whole cells ofH. somnispecifically bind bovine transferrin, but not transferrin from sheep and goats, two bovids whose transferrins share 93% amino acid sequence identity with bovine transferrin. To our surprise, we found thatH. somnican use sheep and goat transferrins as iron sources for growth, and thatHsTbpB, but notHsTbpA, has detectable affinity for sheep and goat transferrins. Furthermore, a third transferrin binding protein,HsTbpA2, also showed affinity for sheep and goat transferrins. Our results show thatH. somniTbpB and TbpA2 act to broaden the host transferrin recognition range ofH. somni.ImportanceHost restricted pathogens infect a single host species or a narrow range of host species.Histophilussomni, a pathogen that incurs severe economic losses for the cattle industry, infects cattle, sheep, and goats, but not other mammals. The transferrin binding proteins, TbpA and TbpB, are thought to be a key iron acquisition system inH. somni, however, surprisingly, they were also shown to be cattle transferrin-specific. In our study we find thatH. somniTbpB, and another little-studied Tbp, TbpA2, bind sheep and goat transferrins as well as bovine transferrin. Our results suggest that TbpA2 may have allowed for host range expansion, and provide a mechanism for how host specificity in Tbp containing pathogens can be altered.
A Dysbiotic Gut Microbiome Suppresses Antibody Mediated-Protection AgainstVibrio cholerae
Authors: Macbeth John , Hsiao Ansel 
Published: August 2019

AbstractVibrio choleraeis the etiologic agent of cholera, a severe diarrheal disease that represents a significant burden on global health and productivity. Despite the pressing need, available preventative measures such as oral cholera vaccines exhibit highly variable protective efficacy. We hypothesized that one contributor to vaccine efficacy variability across geographical regions may be due to differences in gut microbiome, which in cholera-endemic areas is strongly and repeatedly modulated by malnutrition, cholera, and non-cholera infectious diarrhea. Here, we assemble representative model communities of either human gut microbes resembling those of healthy individuals or those of individuals recovering from diarrhea or malnutrition. We establish these communities in a murine immunization model, and show that the dysbiotic gut microbiome, commonly present in areas where malnutrition and diarrhea are common, suppresses the immune response againstVibrio choleraethrough the action of CD4+cells. Our findings suggest that the composition of the gut microbiome at time of immunization may be pivotal for providing robust immunity from oral cholera vaccines, and highlight the importance of the gut microbiome on mucosal immunization responses and vaccine development strategies.ImportanceDiarrhea caused by enteric bacterial pathogens is a recurring and important issue for worldwide health. Cholera, the severe watery diarrhea caused by the bacteriumVibrio cholerae, affects millions of people annually. Currently, there is a lack of effective preventative measures for cholera, due to the uneven performance of oral cholera vaccines. Thus, it is essential to better understand the factors that may affect vaccine efficacy. One aspect may be variations in the resident community of gut microbes, the gut microbiome, across populations living in developed versus developing regions as a function of host genetics, diet, and infection. Our findings suggest that specific structures of the gut microbiome are involved in disrupting the immune responses toV. choleraevaccination.
Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data
Authors: Terry J. Christopher D. , Roy Helen E. , August Tom A. 
Published: August 2019

AbstractThe accurate identification of species in images submitted by citizen scientists is currently a bottleneck for many data uses. Machine learning tools offer the potential to provide rapid, objective and scalable species identification for the benefit of many aspects of ecological science. Currently, most approaches only make use of image pixel data for classification. However, an experienced naturalist would also use a wide variety of contextual information such as the location and date of recording.Here, we examine the automated identification of ladybird (Coccinellidae) records from the British Isles submitted to the UK Ladybird Survey, a volunteer-led mass participation recording scheme. Each image is associated with metadata; a date, location and recorder ID, which can be cross-referenced with other data sources to determine local weather at the time of recording, habitat types and the experience of the observer. We built multi-input neural network models that synthesise metadata and images to identify records to species level.We show that machine learning models can effectively harness contextual information to improve the interpretation of images. Against an image-only baseline of 48.2%, we observe a 9.1 percentage-point improvement in top-1 accuracy with a multi-input model compared to only a 3.6% increase when using an ensemble of image and metadata models. This suggests that contextual data is being used to interpret an image, beyond just providing a prior expectation. We show that our neural network models appear to be utilising similar pieces of evidence as human naturalists to make identifications.Metadata is a key tool for human naturalists. We show it can also be harnessed by computer vision systems. Contextualisation offers considerable extra information, particularly for challenging species, even within small and relatively homogeneous areas such as the British Isles. Although complex relationships between disparate sources of information can be profitably interpreted by simple neural network architectures, there is likely considerable room for further progress. Contextualising images has the potential to lead to a step change in the accuracy of automated identification tools, with considerable benefits for large scale verification of submitted records.
Low rank mechanisms underlying flexible visual representations
Authors: Ruff Douglas A. , Xue Cheng , Kramer Lily E. , Baqai Faisal , Cohen Marlene R. 
Published: August 2019

AbstractNeuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex depend on stimulus properties (e.g. contrast), processes that affect all stages of visual processing (e.g. adaptation), and cognitive processes (e.g attention or task switching). The effects of all of these processes on trial-averaged responses of individual neurons are well-described by divisive normalization, in which responses are scaled by the total stimulus drive. Normalization describes how a staggering variety of sensory, cognitive, and motor processes affect individual neurons (1), but whether different normalization processes could be mediated by the same mechanism remains poorly understood. We and others recently showed that attention has low rank effects on the covariability of populations of neurons in visual area V4 (2–4), which strongly constrains mechanistic models mechanism (2). We hypothesized that measuring changes in population covariability associated with other normalization processes could clarify whether they might share a mechanism. Our experimental design included measurements in multiple visual areas using four normalization processes. We found that contrast, adaptation, attention, and task switching affect the responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit uses a common mechanism to perform many forms of normalization and likely reflect a general principle that applies to a wide range of brain areas and sensory, cognitive, or motor processes.
Orbit Image Analysis: An open-source whole slide image analysis tool
Authors: Stritt Manuel , Stalder Anna K. , Vezzali Enrico 
Published: August 2019

AbstractWe describe the open-source whole slide image analysis tool Orbit Image Analysis. It is a generic tile-processing engine which allows the execution of various image analysis algorithms provided by either Orbit itself or other open-source solutions using a tile-based map-reduce execution framework. We show its sophisticated machine-learning approach for WSI quantification, and its flexibility by integrating a deep learning segmentation method for complex object detection. It can run locally standalone or connect to the open-source image server OMERO, and provides scale-out functionality to use the Spark framework for distributed computing. We demonstrate the application of Orbit in three real-world use-cases: Idiopathic lung fibrosis, nerve fibre density quantification, and glomeruli detection in kidney.Author summaryWhole slide images (WSI) are digital scans of samples, e.g. tissue sections. It is very convenient to view samples in this digital form, and with the increasing computation power it can also be used for quantification. These images are often too large to be analysed with standard tools. To overcome this issue, we created on open-source tool called Orbit Image Analysis which divides the images into smaller parts and allows the analysis of it with either embedded algorithms or the integration of existing tools. It also provides mechanisms to process huge amounts of images in distributed computing environments such as clusters or cloud infrastructures. In this paper we describe the Orbit system and demonstrate its application based on three real-word use-cases.
SAPH-ire TFx – A Recommendation-based Machine Learning Model Captures a Broad Feature Landscape Underlying Functional Post-Translational Modifications
Authors: English Nolan , Torres Matthew 
Published: August 2019

ABSTRACTProtein post-translational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functional PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Therefore, computational approaches that can confidently recommend the functional potential of experimental PTMs are essential. To address this challenge, we developed SAPH-ire TFx (https://saphire.biosci.gatech.edu/): a multi-feature neural network model and web resource optimized for recommending experimental PTMs with high potential for biological impact. The model is rigorously benchmarked against independent datasets and alternative models, exhibiting unmatched performance in the recall of known functional PTM sites and the recommendation of PTMs that were later confirmed experimentally. An analysis of feature contributions to model outcome provides further insight on the need for multiple rather than single features to capture the breadth of functional data in the public domain.Contactmtorres35@gatech.eduSupplementary InformationSee Tables S1-S6 & Figures S1-S4.
The effect of overnight consolidation in the perceptual learning of non-native tonal contrasts
Authors: Qin Zhen , Zhang Caicai 
Published: August 2019

AbstractSleep-mediated overnight consolidation was found to facilitate perceptual learning by promoting learners’ generalization across talkers in their perception of novel segmental categories. Lexical tone differs from most segmental contrasts in that it is highly variable across talkers, and displays dynamic change over time. It remains unclear whether a similar (or a larger) effect of overnight consolidation would be found for perceptual learning of novel tonal contrasts. Thus, this study aims to examine whether overnight consolidation facilitates generalization across talkers in the discrimination and identification of novel Cantonese level tones by Mandarin listeners. Two groups of Mandarin listeners were perceptually trained either in the morning or in the evening. Listeners were trained in a tone identification (ID) task using stimuli produced by a trained talker. Their development was then tested in the ID and AX discrimination tasks using stimuli produced by trained and untrained talkers in three posttests following training: immediately after training, 12-hour delay, and 24-hour delay. While the evening group slept between the first and second posttests, the morning group did not. The results of accuracy rates in the ID task showed that while Mandarin listeners trained in the evening showed an improved trend, predicted by their individual sleep time, in identifying the level tones produced by both the trained and untrained talkers, Mandarin listeners trained in the morning showed a declining trend. In contrast, the results of d-prime scores in the AX discrimination task did not show different developmental patterns between the two groups. Consistent with previous studies on segmental learning, the finding suggests that overnight consolidation might have assisted the evening trainees’ formation of a more abstract (talker-independent) representation of novel tone categories in memory traces. The results are discussed regarding the features of lexical tones to shed light on the mechanism of phonetic learning.
Prebiotically Plausible ‘Patching’ of RNA Backbone Cleavage Through a 3′-5′ Pyrophosphate Linkage
Authors: Wright Tom H. , Giurgiu Constantin , Radakovic Aleksandar , O’Flaherty Derek K. , Zhou Lijun , Szostak Jack W. 
Published: August 2019

ABSTRACTAchieving multiple cycles of RNA replication within a model protocell would be a critical step towards demonstrating a path from prebiotic chemistry to cellular biology. Any model for early life based on an ‘RNA world’ must account for RNA strand cleavage and hydrolysis, which would degrade primitive genetic information and lead to an accumulation of truncated, phosphate-terminated strands. We show here that cleavage of the phosphodiester backbone is not an endpoint for RNA replication. Instead, 3′ -phosphate terminated RNA strands are able to participate in template-directed copying reactions with activated ribonucleotide monomers. These reactions form a pyrophosphate linkage, the stability of which we have characterized in the context of RNA copying chemistry. We found that the pyrophosphate bond is relatively stable within an RNA duplex and in the presence of chelated magnesium. Under these conditions, pyrophosphate-RNA can act as a temporary ‘patch’ to template the polymerization of canonical ribonucleotides, suggesting a plausible non-enzymatic pathway for the salvage and recovery of genetic information following strand cleavage.