bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteome-by-phenome Mendelian Randomisation detects 38 proteins with causal roles in human diseases and traits
Authors: Bretherick Andrew D. , Canela-Xandri Oriol , Joshi Peter K. , Clark David W. , Rawlik Konrad , Boutin Thibaud S. , Zeng Yanni , Amador Carmen , Navarro Pau , Rudan Igor , Wright Alan F. , Campbell Harry , Vitart Veronique , Hayward Caroline , Wilson James F. , Tenesa Albert , Ponting Chris P. , Kenneth Baillie J. , Haley Chris 
Published: May 2019

AbstractTarget identification remains a crucial challenge in drug development. To enable unbiased detection of proteins and pathways that have a causal role in disease pathogenesis or progression, we propose proteome-by-phenome Mendelian Randomisation (P2MR). We first detected genetic variants associated with plasma concentration of 249 proteins. We then used 64 replicated variants in two-sample Mendelian Randomisation to quantify evidence of a causal role for each protein across 846 phenotypes: this yielded 509 robust protein-outcome links. P2MR provides substantial promise for drug target prioritisation. We provide confirmatory evidence for a causal role for the proteins encoded at multiple cardiovascular disease risk loci (FGF5, IL6R, LPL, LTA), and discovered that intestinal fatty acid binding protein (FABP2) contributes to disease pathogenesis. Additionally, we find and replicate evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia. Our results provide specific prediction of the effects of changes of plasma protein concentration on complex phenotypes in humans.
A new clinical tool to predict outcome in early-stage melanoma patients
Authors: Mancuso Filippo , Lage Sergio , Rasero Javier , Díaz-Ramón José Luis , Apraiz Aintzane , Pérez-Yarza Gorka , Ezkurra Pilar A. , Penas Cristina , Sánchez-Diez Ana , García-Vazquez María Dolores , Gardeazabal Jesús , Izu Rosa , Mujika Karmele , Cortés Jesús , Asumendi Aintzane , Boyano María Dolores 
Published: May 2019

AbstractAround 25% of early-stage melanoma patients eventually develop metastasis. Thus, we set out to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict these events. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with IL-4, IL-6, IL-10, IL-17A, IFNγ TGFβ and GM-CSF. We included 448 melanoma patients, 323 of whom were diagnosed as stages I-II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex and obtained data were analyzed employing Machine Learning and Kaplan-Meier techniques to define an algorithm capable of accurately classifying early-stage melanoma patients with a high and low risk of developing metastasis. The results show that in early-stage melanoma patients, serum levels of the cytokines IL-4, GM-CSF and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.Novelty and ImpactWe have developed a prognostic equation that considers the serum IL-4, GM-CSF and DCD levels, along with the Breslow thickness to accurately classify melanoma outcome in patients. In this sense, a rigorous follow-up is recommended for early-stage melanoma patients with a high Breslow thickness, high serum IL-4 levels and low GM-CSF and DCD levels at the time of diagnosis, given the elevated risk for these patients to develop metastasis during follow-up.
Quantitative Models of Phage-Antibiotics Combination Therapy
Authors: Rodriguez-Gonzalez Rogelio A. , Leung Chung-Yin , Chan Benjamin K. , Turner Paul E. , Weitz Joshua S. 
Published: May 2019

AbstractThe spread of multi-drug resistant (MDR) bacteria is a global public health crisis. Bacteriophage therapy (or “phage therapy”) constitutes a potential alternative approach to treat MDR infections. However, the effective use of phage therapy may be limited when phage-resistant bacterial mutants evolve and proliferate during treatment. Here, we develop a nonlinear population dynamics model of combination therapy that accounts for the system-level interactions between bacteria, phage and antibiotics for in-vivo application given an immune response against bacteria. We simulate the combination therapy model for two strains of Pseudomonas aeruginosa, one which is phage-sensitive (and antibiotic resistant) and one which is antibiotic-sensitive (and phage-resistant). We find that combination therapy outperforms either phage or antibiotic alone, and that therapeutic effectiveness is enhanced given interaction with innate immune responses. Notably, therapeutic success can be achieved even at sub-inhibitory concentrations of antibiotics, e.g., ciprofloxacin. These in-silico findings provide further support to the nascent application of combination therapy to treat MDR bacterial infections, while highlighting the role of innate immunity in shaping therapeutic outcomes.
TBK1-mediated phosphorylation of LC3C and GABARAP-L2 controls autophagosome shedding by ATG4 protease
Authors: Herhaus Lina , Bhaskara Ramachandra M. , Håkon Lystad Alf , Simonsen Anne , Hummer Gerhard , Dikic Ivan 
Published: May 2019

AbstractAutophagy is a highly conserved catabolic process through which defective or otherwise harmful cellular components are targeted for degradation via the lysosomal route. Regulatory pathways, involving post-translational modifications such as phosphorylation, play a critical role in controlling this tightly orchestrated process. Here, we demonstrate that TBK1 regulates autophagy by phosphorylating autophagy modifiers LC3C and GABARAP-L2 on surface-exposed serine residues (LC3C S93 and S96; GABARAP-L2 S87 and S88). This phosphorylation event impedes their binding to the processing enzyme ATG4 by destabilizing the complex. Phosphorylated LC3C/GABARAP-L2 cannot be removed from liposomes by ATG4 and are thus protected from ATG4-mediated premature removal from nascent autoph-agosomes. This ensures a steady coat of lipidated LC3C/GABARAP-L2 throughout the early steps in autophagosome formation and aids in maintaining a unidirectional flow of the autophagosome to the lysosome. Taken together, we present a new regulatory mechanism of autophagy, which influences the conjugation and de-conjugation of LC3C and GABARAP-L2 to autophagosomes by TBK1-mediated phosphorylation.
Chromosome-levelde novoassembly of the pig-tailed macaque genome using linked-read sequencing and HiC proximity scaffolding
Authors: Roodgar Morteza , Babveyh Afshin , Huong Lan , Zhou Wenyu , Sinha Rahul , Lee Hayan , Hanks John B. , Avula Mohan , Jiang Lihua , Lee Hoyong , Song Giltae , Chaib Hassan , Weissman Irv L. , Batzoglou Serafim , Holmes Susan , Smith David G. , Mankowski Joseph L. , Prost Stefan , Snyder Michael P. 
Published: May 2019

AbstractOld world monkey species share over 93% genome homology with humans and develop many disease phenotypes similar to those of humans, making them highly valuable animal models for the study of numerous human diseases. However, the quality of genome assembly and annotation for old world monkeys including macaque species lags behind the human genome effort. To close this gap and enhance functional genomics approaches, we employed a combination ofde novolinked-read assembly and scaffolding using proximity ligation assay (HiC) to assemble the pig-tailed macaque (Macaca nemestrina) genome. This combinatorial method yielded large scaffolds at chromosome-level with a scaffold N50 of 127.5 Mb; the 23 largest scaffolds covered 90% of the entire genome. This assembly revealed large-scale rearrangements between pig-tailed macaque chromosomes 7,12, and13 and human chromosomes 2, 14, and 15.
Global ecotypes in the ubiquitous marine clade SAR86
Authors: Hoarfrost Adrienne , Nayfach Stephen , Ladau Joshua , Yooseph Shibu , Arnosti Carol , Dupont Chris L , Pollard Katherine S. 
Published: May 2019

AbstractSAR86 is an abundant and ubiquitous heterotroph in the surface ocean that plays a central role in the function of marine ecosystems. We hypothesized that despite its ubiquity, different SAR86 subgroups may be endemic to specific ocean regions and functionally specialized for unique marine environments. However, the global biogeographical distributions of SAR86 genes, and the manner in which these distributions correlate with marine environments, have not been investigated. We quantified SAR86 gene content across globally-distributed metagenomic samples and modeled these gene distributions as a function of 51 environmental variables. We identified five distinct clusters of genes within the SAR86 pangenome, each with a unique geographic distribution associated with specific environmental characteristics. Gene clusters are characterized by strong taxonomic enrichment of distinct SAR86 genomes and partial assemblies, as well as differential enrichment of certain functional groups, suggesting differing functional and ecological roles of SAR86 ecotypes. We then leveraged our models and high-resolution, remote sensing-derived environmental data to predict the distributions of SAR86 gene clusters across the world’s oceans, creating global maps of SAR86 ecotype distributions. Our results reveal that SAR86 exhibits previously unknown, complex biogeography, and provide a framework for exploring geographic distributions of genetic diversity from other microbial clades.
Sepsis-associated Pathways Segregate Cancer Groups
Authors: Tripathi Himanshu , Mukhopadhyay Samanwoy , Mohapatra Saroj Kant 
Published: May 2019

AbstractBackgroundSepsis and cancer are both leading causes of death, and occurrence of any one, increases the likelihood of the other. While cancer patients are susceptible to sepsis, survivors of sepsis are also susceptible to develop certain cancers. This mutual dependence for susceptibility suggests shared biology between the two disease categories. Earlier analysis had revealed cancer-related pathway to be up-regulated in Septic Shock (SS), an advanced stage of sepsis. This has motivated a more comprehensive comparison of the transcriptomes of SS and cancer.MethodsGene Set Enrichment Analysis was performed to detect the pathways enriched in SS and cancer. Thereafter, hierarchical clustering was applied to identify relative segregation of 17 cancer types in to two groupsvis-a-visSS. Biological significance of the selected pathways was explored by network analysis. Clinical significance of the pathways was tested by survival analysis. A robust classifier of cancer groups was developed based on machine learning.ResultsA total of 66 pathways were observed to be enriched in both SS and cancer. However, clustering segregated cancer types into two categories based on the direction of transcriptomic change. In general, there was up-regulation in SS and one group of cancer (termed Sepsis-Like Cancers, or SLC), but not in other cancers. SLC group mainly consisted of malignancies of the gastrointestinal tract (head and neck, oesophagus, stomach, liver and biliary system) often associated with infection. Machine learning classifier successfully segregated the two cancer groups with high accuracy (> 98%). Additionally, pathway up-regulation was observed to be associated with survival in the SLC group of cancers.ConclusionTranscriptome-based systems biology approach segregates cancer into two groups (SLC and CA) based on similarity with SS. Host response to infection plays a key role in pathogenesis of SS and SLC. However, we hypothesize that some component of the host response is protective in both SS and SLC.
Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility
Authors: Kachuri Linda , Johansson Mattias , Rashkin Sara R. , Graff Rebecca E. , Bossé Yohan , Manem Venkata , Caporaso Neil E. , Landi Maria Teresa , Christiani David C. , Vineis Paolo , Liu Geoffrey , Scelo Ghislaine , Zaridze David , Shete Sanjay S. , Albanes Demetrius , Aldrich Melinda C. , Tardón Adonina , Rennert Gad , Chen Chu , Goodman Gary E. , Doherty Jennifer A. , Bickeböller Heike , Field John K. , Davies Michael P. , Dawn Teare M. , Kiemeney Lambertus A. , Bojesen Stig E. , Haugen Aage , Zienolddiny Shanbeh , Lam Stephen , Marchand Loïc Le , Cheng Iona , Schabath Matthew B. , Duell Eric J. , Andrew Angeline S. , Manjer Jonas , Lazarus Philip , Arnold Susanne , McKay James D. , Emami Nima C. , Warkentin Matthew T. , Brhane Yonathan , Obeidat Ma’en , Martin Richard M. , Relton Caroline , Smith George Davey , Haycock Philip C. , Amos Christopher I. , Brennan Paul , Witte John S. , Hung Rayjean J. 
Published: May 2019

ABSTRACTImpaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1:rg=0.098, p=2.3×10−8) and the ratio of FEV1to forced vital capacity (FEV1/FVC:rg=0.137, p=2.0×10−12). Mendelian randomization analyses demonstrate that reduced FEV1increases squamous cell carcinoma risk (odds ratio (OR)=1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR=1.17, 1.01-1.35) and lung cancer in never smokers (OR=1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.
A computational pipeline to predict cardiotoxicity: From the atom to the rhythm
Authors: Yang Pei-Chi , DeMarco Kevin R. , Aghasafari Parya , Jeng Mao-Tsuen , Noskov Sergei Y. , Yarov-Yarovoy Vladimir , Vorobyov Igor , Clancy Colleen E. 
Published: May 2019

SUMMARYWe simulate and predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.ABSTRACTDrug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation has become widely accepted as a surrogate marker for arrhythmia. The problem is that QT interval as an arrhythmia indicator is too sensitive and not selective, resulting in many potentially useful drugs eliminated early in the drug discovery process. We first set out to predict the fundamental mode of binding for the proarrhythmic drug dofetilide with the promiscuous cardiac drug target, the hERG potassium channel. In a novel linkage between the atomistic and functional scales, computed binding affinities and rates from atomistic simulation are utilized here to parameterize function scale kinetic models of dofetilide interactions with the hERG channel. The kinetic model components are then integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data from published studies were used to validate model framework and showed excellent agreement, demonstrating feasibility of the approach. The model predictions show that a clinically relevant dose of dofetilide increased arrhythmia vulnerability in all emergent TRIaD-linked parameters including Triangulation, Reverse use-dependence, beat-to-beat Instability and temporal and spatial action potential duration Dispersion. Application of machine learning demonstrated redundancy in the TRIaD linked parameters and suggested that changes in beat-to-beat instability were highly predictive of arrhythmia vulnerability in this setting. Here, we demonstrate the development and validation of a prototype multiscale model framework to predict electro-toxicity in the heart for the proarrhythmic drug dofetilide from the atom to the rhythm.SIGNIFICANCE STATEMENTCardiotoxicity in the form of deadly abnormal rhythms is one of the most common and dangerous risks for drugs in development and clinical use. There is an urgent need for new approaches to screen and predict the effects of chemically similar drugs on the cardiac rhythmandto move beyond the QT interval as a diagnostic indicator for arrhythmia. To this end, we present a computational pipeline to predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm. We utilize predicted quantitative estimates of ion channel-drug interactions from our companion paper to simulate cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.
The mineralization characteristics of organic carbon and particle composition analysis in reconstructed soil with different proportions of soft rock and sand
Authors: Guo Zhen , Han Jichang , Xu Yan , Tian Chang , Shi Chendi , Ge Lei , Li Juan , Cao Tingting 
Published: May 2019

AbstractThe organic carbon mineralization process can reflect the release intensity of soil CO2. Therefore, the study of organic carbon mineralization and particle composition analysis of soft rock and sand compound soil can provide technical support and theoretical basis for the theory of soil organic reconstruction. Based on the previous research, this paper mainly selected four typical treatments of 0:1 (CK), 1:5 (C1), 1:2 (C2) and 1:1 (C3), respectively, and analyzed the soil organic carbon mineralization process and particle composition by lye absorption method, laser particle size meter and scanning electron microscope. The results showed that there was no significant difference in organic carbon content between C1, C2 and C3 treatments, but they were significantly higher than CK treatment (P < 0.05). The organic carbon mineralization rate of each treatment accords with a logarithmic function throughout the culture period (P < 0.01), which can be divided into a rapid decline phase of 1-11 days and a steady decline phase of 11-30 days. The cumulative mineralization amount on the 11th day reached 54.96%-74.44% of the total mineralization amount. At the end of the culture, the cumulative mineralization and potential mineralizable organic carbon content of C1 and C2 treatments were significantly higher than those of CK treatment, and the cumulative mineralization rate was also the lowest with C1 and C2 treatment. The turnover rate constant of soil organic carbon in each treatment was significantly lower than that of CK treatment, and the residence time increased. With the increase of volume fraction of soft rock, the content of silt and clay particles increases gradually, the texture of soil changes from sandy soil to sandy loam, loam and silty loam, and because of the increase of small particles, the structure of soil appears to collapse when the volume ratio of soft rock was 50%. In summary, the ratio of soft rock to sand volume was 1:5-1: 2, which can effectively increased the accumulation of soil organic carbon. At this time, the distribution of soil particles was more uniform, the soil structure was stable, and the mineralization level of unit organic carbon was lower. The research results have practical significance for the large area popularization of soft rock and sand compound technology.
Patient experience: determinants and manifestations
Authors: Zakkar Moutasem 
Published: May 2019

Purpose
Patient experience is a complex multidimensional phenomenon that has been linked to constructs that are also complex to conceptualize, such as patient-centeredness, patient expectations and patient satisfaction. The purpose of this paper is to shed light on the different dimensions of patient experience, including those that receive inadequate attention from policymakers such as the patient’s lived experience of illness and the impact of healthcare politics. The paper proposes a simple classification for these dimensions, which differentiates between two types of dimensions: the determinants and the manifestations of patient experience.

Design/methodology/approach
This paper uses a narrative review of the literature to explore select constructs and initiatives developed for theorizing or operationalizing patient experience. Literature topics reviewed include healthcare quality, medical anthropology, health policy, healthcare system and public health.

Findings
The paper identifies five determinants for patient experience: the experience of illness, patient’s subjective influences, quality of healthcare services, health system responsiveness and the politics of healthcare. The paper identifies two manifestations of patient experience: patient satisfaction and patient engagement.

Originality/value
The paper proposes a classification scheme of the dimensions of patient experience and a concept map that links together heterogeneous constructs related to patient experience. The proposed classification and the concept map provide a holistic view of patient experience and help healthcare providers, quality managers and policymakers organize and focus their healthcare quality improvement endeavors on specific dimensions of patient experience while taking into consideration the other dimensions.
Privacy engineering for learning analytics in a global market
Authors: Hoel Tore , Chen Weiqin 
Published: May 2019

Purpose
Privacy is a culturally universal process; however, in the era of Big Data privacy is handled very differently in different parts of the world. This is a challenge when designing tools and approaches for the use of Educational Big Data (EBD) and learning analytics (LA) in a global market. The purpose of this paper is to explore the concept of information privacy in a cross-cultural setting to define a common point of reference for privacy engineering.

Design/methodology/approach
The paper follows a conceptual exploration approach. Conceptual work on privacy in EBD and LA in China and the west is contrasted with the general discussion of privacy in a large corpus of literature and recent research. As much of the discourse on privacy has an American or European bias, intimate knowledge of Chinese education is used to test the concept of privacy and to drive the exploration of how information privacy is perceived in different cultural and educational settings.

Findings
The findings indicate that there are problems using privacy concepts found in European and North-American theories to inform privacy engineering for a cross-cultural market in the era of Big Data. Theories based on individualism and ideas of control of private information do not capture current global digital practice. The paper discusses how a contextual and culture-aware understanding of privacy could be developed to inform privacy engineering without letting go of universally shared values. The paper concludes with questions that need further research to fully understand information privacy in education.

Originality/value
As far as the authors know, this paper is the first attempt to discuss – from a comparative and cross-cultural perspective – information privacy in an educational context in the era of Big Data. The paper presents initial explorations of a problem that needs urgent attention if good intentions of privacy supportive educational technologies are to be turned into more than political slogans.