bluuebunny/crossref_metadata_2025 huggingface dataset:
SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences
Authors: Zhang Jian , Kurgan Lukasz
Published: May 2019

Motivation

Accurate predictions of protein-binding residues (PBRs) enhances understanding of molecular-level rules governing protein–protein interactions, helps protein–protein docking and facilitates annotation of protein functions. Recent studies show that current sequence-based predictors of PBRs severely cross-predict residues that interact with other types of protein partners (e.g. RNA and DNA) as PBRs. Moreover, these methods are relatively slow, prohibiting genome-scale use.

Results

We propose a novel, accurate and fast sequence-based predictor of PBRs that minimizes the cross-predictions. Our SCRIBER (SeleCtive pRoteIn-Binding rEsidue pRedictor) method takes advantage of three innovations: comprehensive dataset that covers multiple types of binding residues, novel types of inputs that are relevant to the prediction of PBRs, and an architecture that is tailored to reduce the cross-predictions. The dataset includes complete protein chains and offers improved coverage of binding annotations that are transferred from multiple protein–protein complexes. We utilize innovative two-layer architecture where the first layer generates a prediction of protein-binding, RNA-binding, DNA-binding and small ligand-binding residues. The second layer re-predicts PBRs by reducing overlap between PBRs and the other types of binding residues produced in the first layer. Empirical tests on an independent test dataset reveal that SCRIBER significantly outperforms current predictors and that all three innovations contribute to its high predictive performance. SCRIBER reduces cross-predictions by between 41% and 69% and our conservative estimates show that it is at least 3 times faster. We provide putative PBRs produced by SCRIBER for the entire human proteome and use these results to hypothesize that about 14% of currently known human protein domains bind proteins.

Availability and implementation

SCRIBER webserver is available at http://biomine.cs.vcu.edu/servers/SCRIBER/.

Supplementary information

Supplementary data are available at Bioinformatics online.
Robust network inference using response logic
Authors: Gross Torsten , Wongchenko Matthew J , Yan Yibing , Blüthgen Nils
Published: May 2019

Motivation

A major challenge in molecular and cellular biology is to map out the regulatory networks of cells. As regulatory interactions can typically not be directly observed experimentally, various computational methods have been proposed to disentangling direct and indirect effects. Most of these rely on assumptions that are rarely met or cannot be adapted to a given context.

Results

We present a network inference method that is based on a simple response logic with minimal presumptions. It requires that we can experimentally observe whether or not some of the system’s components respond to perturbations of some other components, and then identifies the directed networks that most accurately account for the observed propagation of the signal. To cope with the intractable number of possible networks, we developed a logic programming approach that can infer networks of hundreds of nodes, while being robust to noisy, heterogeneous or missing data. This allows to directly integrate prior network knowledge and additional constraints such as sparsity. We systematically benchmark our method on KEGG pathways, and show that it outperforms existing approaches in DREAM3 and DREAM4 challenges. Applied to a novel perturbation dataset on PI3K and MAPK pathways in isogenic models of a colon cancer cell line, it generates plausible network hypotheses that explain distinct sensitivities toward various targeted inhibitors due to different PI3K mutants.

Availability and implementation

A Python/Answer Set Programming implementation can be accessed at github.com/GrossTor/response-logic. Data and analysis scripts are available at github.com/GrossTor/response-logic-projects.

Supplementary information

Supplementary data are available at Bioinformatics online.
Prediction of mRNA subcellular localization using deep recurrent neural networks
Authors: Yan Zichao , Lécuyer Eric , Blanchette Mathieu
Published: May 2019

Motivation

Messenger RNA subcellular localization mechanisms play a crucial role in post-transcriptional gene regulation. This trafficking is mediated by trans-acting RNA-binding proteins interacting with cis-regulatory elements called zipcodes. While new sequencing-based technologies allow the high-throughput identification of RNAs localized to specific subcellular compartments, the precise mechanisms at play, and their dependency on specific sequence elements, remain poorly understood.

Results

We introduce RNATracker, a novel deep neural network built to predict, from their sequence alone, the distributions of mRNA transcripts over a predefined set of subcellular compartments. RNATracker integrates several state-of-the-art deep learning techniques (e.g. CNN, LSTM and attention layers) and can make use of both sequence and secondary structure information. We report on a variety of evaluations showing RNATracker’s strong predictive power, which is significantly superior to a variety of baseline predictors. Despite its complexity, several aspects of the model can be isolated to yield valuable, testable mechanistic hypotheses, and to locate candidate zipcode sequences within transcripts.

Availability and implementation

Code and data can be accessed at https://www.github.com/HarveyYan/RNATracker.

Supplementary information

Supplementary data are available at Bioinformatics online.
Modeling clinical and molecular covariates of mutational process activity in cancer
Authors: Robinson Welles , Sharan Roded , Leiserson Mark D M
Published: May 2019

Motivation

Somatic mutations result from processes related to DNA replication or environmental/lifestyle exposures. Knowing the activity of mutational processes in a tumor can inform personalized therapies, early detection, and understanding of tumorigenesis. Computational methods have revealed 30 validated signatures of mutational processes active in human cancers, where each signature is a pattern of single base substitutions. However, half of these signatures have no known etiology, and some similar signatures have distinct etiologies, making patterns of mutation signature activity hard to interpret. Existing mutation signature detection methods do not consider tumor-level clinical/demographic (e.g. smoking history) or molecular features (e.g. inactivations to DNA damage repair genes).

Results

To begin to address these challenges, we present the Tumor Covariate Signature Model (TCSM), the first method to directly model the effect of observed tumor-level covariates on mutation signatures. To this end, our model uses methods from Bayesian topic modeling to change the prior distribution on signature exposure conditioned on a tumor’s observed covariates. We also introduce methods for imputing covariates in held-out data and for evaluating the statistical significance of signature-covariate associations. On simulated and real data, we find that TCSM outperforms both non-negative matrix factorization and topic modeling-based approaches, particularly in recovering the ground truth exposure to similar signatures. We then use TCSM to discover five mutation signatures in breast cancer and predict homologous recombination repair deficiency in held-out tumors. We also discover four signatures in a combined melanoma and lung cancer cohort—using cancer type as a covariate—and provide statistical evidence to support earlier claims that three lung cancers from The Cancer Genome Atlas are misdiagnosed metastatic melanomas.

Availability and implementation

TCSM is implemented in Python 3 and available at https://github.com/lrgr/tcsm, along with a data workflow for reproducing the experiments in the paper.

Supplementary information

Supplementary data are available at Bioinformatics online.
TreeMerge: a new method for improving the scalability of species tree estimation methods
Authors: Molloy Erin K , Warnow Tandy
Published: May 2019

Motivation

At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species.

Results

Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All.

Availability and implementation

TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge).

Supplementary information

Supplementary data are available at Bioinformatics online.
Locality-sensitive hashing for the edit distance
Authors: Marçais Guillaume , DeBlasio Dan , Pandey Prashant , Kingsford Carl
Published: May 2019

Motivation

Sequence alignment is a central operation in bioinformatics pipeline and, despite many improvements, remains a computationally challenging problem. Locality-sensitive hashing (LSH) is one method used to estimate the likelihood of two sequences to have a proper alignment. Using an LSH, it is possible to separate, with high probability and relatively low computation, the pairs of sequences that do not have high-quality alignment from those that may. Therefore, an LSH reduces the overall computational requirement while not introducing many false negatives (i.e. omitting to report a valid alignment). However, current LSH methods treat sequences as a bag of k-mers and do not take into account the relative ordering of k-mers in sequences. In addition, due to the lack of a practical LSH method for edit distance, in practice, LSH methods for Jaccard similarity or Hamming similarity are used as a proxy.

Results

We present an LSH method, called Order Min Hash (OMH), for the edit distance. This method is a refinement of the minHash LSH used to approximate the Jaccard similarity, in that OMH is sensitive not only to the k-mer contents of the sequences but also to the relative order of the k-mers in the sequences. We present theoretical guarantees of the OMH as a gapped LSH.

Availability and implementation

The code to generate the results is available at http://github.com/Kingsford-Group/omhismb2019.

Supplementary information

Supplementary data are available at Bioinformatics online.
A divide-and-conquer method for scalable phylogenetic network inference from multilocus data
Authors: Zhu Jiafan , Liu Xinhao , Ogilvie Huw A , Nakhleh Luay K
Published: May 2019

Motivation

Reticulate evolutionary histories, such as those arising in the presence of hybridization, are best modeled as phylogenetic networks. Recently developed methods allow for statistical inference of phylogenetic networks while also accounting for other processes, such as incomplete lineage sorting. However, these methods can only handle a small number of loci from a handful of genomes.

Results

In this article, we introduce a novel two-step method for scalable inference of phylogenetic networks from the sequence alignments of multiple, unlinked loci. The method infers networks on subproblems and then merges them into a network on the full set of taxa. To reduce the number of trinets to infer, we formulate a Hitting Set version of the problem of finding a small number of subsets, and implement a simple heuristic to solve it. We studied their performance, in terms of both running time and accuracy, on simulated as well as on biological datasets. The two-step method accurately infers phylogenetic networks at a scale that is infeasible with existing methods. The results are a significant and promising step towards accurate, large-scale phylogenetic network inference.

Availability and implementation

We implemented the algorithms in the publicly available software package PhyloNet (https://bioinfocs.rice.edu/PhyloNet).

Supplementary information

Supplementary data are available at Bioinformatics online.
DIFFUSE: predicting isoform functions from sequences and expression profiles via deep learning
Authors: Chen Hao , Shaw Dipan , Zeng Jianyang , Bu Dongbo , Jiang Tao
Published: May 2019

Motivation

Alternative splicing generates multiple isoforms from a single gene, greatly increasing the functional diversity of a genome. Although gene functions have been well studied, little is known about the specific functions of isoforms, making accurate prediction of isoform functions highly desirable. However, the existing approaches to predicting isoform functions are far from satisfactory due to at least two reasons: (i) unlike genes, isoform-level functional annotations are scarce. (ii) The information of isoform functions is concealed in various types of data including isoform sequences, co-expression relationship among isoforms, etc.

Results

In this study, we present a novel approach, DIFFUSE (Deep learning-based prediction of IsoForm FUnctions from Sequences and Expression), to predict isoform functions. To integrate various types of data, our approach adopts a hybrid framework by first using a deep neural network (DNN) to predict the functions of isoforms from their genomic sequences and then refining the prediction using a conditional random field (CRF) based on co-expression relationship. To overcome the lack of isoform-level ground truth labels, we further propose an iterative semi-supervised learning algorithm to train both the DNN and CRF together. Our extensive computational experiments demonstrate that DIFFUSE could effectively predict the functions of isoforms and genes. It achieves an average area under the receiver operating characteristics curve of 0.840 and area under the precision–recall curve of 0.581 over 4184 GO functional categories, which are significantly higher than the state-of-the-art methods. We further validate the prediction results by analyzing the correlation between functional similarity, sequence similarity, expression similarity and structural similarity, as well as the consistency between the predicted functions and some well-studied functional features of isoform sequences.

Availability and implementation

https://github.com/haochenucr/DIFFUSE.

Supplementary information

Supplementary data are available at Bioinformatics online.
LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search
Authors: Huang Liang , Zhang He , Deng Dezhong , Zhao Kai , Liu Kaibo , Hendrix David A , Mathews David H
Published: May 2019

Motivation

Predicting the secondary structure of an ribonucleic acid (RNA) sequence is useful in many applications. Existing algorithms [based on dynamic programming] suffer from a major limitation: their runtimes scale cubically with the RNA length, and this slowness limits their use in genome-wide applications.

Results

We present a novel alternative O(n3)-time dynamic programming algorithm for RNA folding that is amenable to heuristics that make it run in O(n) time and O(n) space, while producing a high-quality approximation to the optimal solution. Inspired by incremental parsing for context-free grammars in computational linguistics, our alternative dynamic programming algorithm scans the sequence in a left-to-right (5′-to-3′) direction rather than in a bottom-up fashion, which allows us to employ the effective beam pruning heuristic. Our work, though inexact, is the first RNA folding algorithm to achieve linear runtime (and linear space) without imposing constraints on the output structure. Surprisingly, our approximate search results in even higher overall accuracy on a diverse database of sequences with known structures. More interestingly, it leads to significantly more accurate predictions on the longest sequence families in that database (16S and 23S Ribosomal RNAs), as well as improved accuracies for long-range base pairs (500+ nucleotides apart), both of which are well known to be challenging for the current models.

Availability and implementation

Our source code is available at https://github.com/LinearFold/LinearFold, and our webserver is at http://linearfold.org (sequence limit: 100 000nt).

Supplementary information

Supplementary data are available at Bioinformatics online.
Inheritance and variability of kinetic gene expression parameters in microbial cells: modeling and inference from lineage tree data
Authors: Marguet Aline , Lavielle Marc , Cinquemani Eugenio
Published: May 2019

Motivation

Modern experimental technologies enable monitoring of gene expression dynamics in individual cells and quantification of its variability in isogenic microbial populations. Among the sources of this variability is the randomness that affects inheritance of gene expression factors at cell division. Known parental relationships among individually observed cells provide invaluable information for the characterization of this extrinsic source of gene expression noise. Despite this fact, most existing methods to infer stochastic gene expression models from single-cell data dedicate little attention to the reconstruction of mother–daughter inheritance dynamics.

Results

Starting from a transcription and translation model of gene expression, we propose a stochastic model for the evolution of gene expression dynamics in a population of dividing cells. Based on this model, we develop a method for the direct quantification of inheritance and variability of kinetic gene expression parameters from single-cell gene expression and lineage data. We demonstrate that our approach provides unbiased estimates of mother–daughter inheritance parameters, whereas indirect approaches using lineage information only in the post-processing of individual-cell parameters underestimate inheritance. Finally, we show on yeast osmotic shock response data that daughter cell parameters are largely determined by the mother, thus confirming the relevance of our method for the correct assessment of the onset of gene expression variability and the study of the transmission of regulatory factors.

Availability and implementation

Software code is available at https://github.com/almarguet/IdentificationWithARME. Lineage tree data is available upon request.

Supplementary information

Supplementary material is available at Bioinformatics online.
Inference of clonal selection in cancer populations using single-cell sequencing data
Authors: Skums Pavel , Tsyvina Viachaslau , Zelikovsky Alex
Published: May 2019

Intra-tumor heterogeneity is one of the major factors influencing cancer progression and treatment outcome. However, evolutionary dynamics of cancer clone populations remain poorly understood. Quantification of clonal selection and inference of fitness landscapes of tumors is a key step to understanding evolutionary mechanisms driving cancer. These problems could be addressed using single-cell sequencing (scSeq), which provides an unprecedented insight into intra-tumor heterogeneity allowing to study and quantify selective advantages of individual clones. Here, we present Single Cell Inference of FItness Landscape (SCIFIL), a computational tool for inference of fitness landscapes of heterogeneous cancer clone populations from scSeq data. SCIFIL allows to estimate maximum likelihood fitnesses of clone variants, measure their selective advantages and order of appearance by fitting an evolutionary model into the tumor phylogeny. We demonstrate the accuracy our approach, and show how it could be applied to experimental tumor data to study clonal selection and infer evolutionary history. SCIFIL can be used to provide new insight into the evolutionary dynamics of cancer.

Availability and implementation

Its source code is available at https://github.com/compbel/SCIFIL.
Integrating Governance and Quantitative Evaluation of Resource Management Strategies to Improve Social and Ecological Outcomes
Authors: Armitage Derek R , Okamoto Daniel K , Silver Jennifer J , Francis Tessa B , Levin Phillip S , Punt André E , Davies Ian P , Cleary Jaclyn S , Dressel Sherri C , Jones R Russ , Kitka Harvey , Lee Lynn Chi , MacCall Alec D , McIsaac Jim A , Poe Melissa R , Reifenstuhl Steve , Shelton Andrew O , Schmidt Jörn O , Thornton Thomas F , Voss Rudi , Woodruff John
Published: May 2019

In this article, we examine how governance can be more effectively integrated with quantitative evaluation methods in applied resource management. Governance refers to how societies organize to make decisions in ways that influence management choices (e.g., harvest allocation), such as levels of participation, the inclusion of different types of knowledge, and legitimacy of processes that lead to decisions. Using a fisheries example, we show that a failure to consider the governance context for quantitative evaluation of alternative management strategies may lead to unexpected consequences or break points in decision-making, bias estimates of risk and returns from management choices, and mask the potential for undesirable social and ecological outcomes.
Categorical Encoding of Vowels in Primary Auditory Cortex
Authors: Levy Deborah F , Wilson Stephen M
Published: May 2019

Speech perception involves mapping from a continuous and variable acoustic speech signal to discrete, linguistically meaningful units. However, it is unclear where in the auditory processing stream speech sound representations cease to be veridical (faithfully encoding precise acoustic properties) and become categorical (encoding sounds as linguistic categories). In this study, we used functional magnetic resonance imaging and multivariate pattern analysis to determine whether tonotopic primary auditory cortex (PAC), defined as tonotopic voxels falling within Heschl’s gyrus, represents one class of speech sounds—vowels—veridically or categorically. For each of 15 participants, 4 individualized synthetic vowel stimuli were generated such that the vowels were equidistant in acoustic space, yet straddled a categorical boundary (with the first 2 vowels perceived as [i] and the last 2 perceived as [i]). Each participant’s 4 vowels were then presented in a block design with an irrelevant but attention-demanding level change detection task. We found that in PAC bilaterally, neural discrimination between pairs of vowels that crossed the categorical boundary was more accurate than neural discrimination between equivalently spaced vowel pairs that fell within a category. These findings suggest that PAC does not represent vowel sounds veridically, but that encoding of vowels is shaped by linguistically relevant phonemic categories.
Epigenomic Convergence of Neural-Immune Risk Factors in Neurodevelopmental Disorder Cortex
Authors: Vogel Ciernia A , Laufer B I , Hwang H , Dunaway K W , Mordaunt C E , Coulson R L , Yasui D H , LaSalle J M
Published: May 2019

Neurodevelopmental disorders (NDDs) affect 7–14% of all children in developed countries and are one of the leading causes of lifelong disability. Epigenetic modifications are poised at the interface between genes and environment and are predicted to reveal insight into NDD etiology. Whole-genome bisulfite sequencing was used to examine DNA cytosine methylation in 49 human cortex samples from 3 different NDDs (autism spectrum disorder, Rett syndrome, and Dup15q syndrome) and matched controls. Integration of methylation changes across NDDs with relevant genomic and genetic datasets revealed differentially methylated regions (DMRs) unique to each type of NDD but with shared regulatory functions in neurons and microglia. NDD DMRs were enriched within promoter regions and for transcription factor binding sites with identified methylation sensitivity. DMRs from all 3 disorders were enriched for ontologies related to nervous system development and genes with disrupted expression in brain from neurodevelopmental or neuropsychiatric disorders. Genes associated with NDD DMRs showed expression patterns indicating an important role for altered microglial function during brain development. These findings demonstrate an NDD epigenomic signature in human cortex that will aid in defining therapeutic targets and early biomarkers at the interface of genetic and environmental NDD risk factors.
Direct and Indirect Costs of Inflammatory Bowel Disease: Ten Years of Follow-up in a Danish Population-based Inception Cohort
Authors: Lo Bobby , Vind Ida , Vester-Andersen Marianne Kajbaek , Bendtsen Flemming , Burisch Johan
Published: May 2019

Background

Inflammatory bowel disease [IBD], encompassing Crohn’s disease [CD] and ulcerative colitis [UC], places a high burden on health care resources. To date, no study has assessed the combined direct and indirect cost of IBD in a population-based setting. Our aim was to assess this in a population-based inception cohort with 10 years of follow-up.

Methods

All incident patients diagnosed with CD or UC, 2003–2004, in a well-defined area of Copenhagen, were followed prospectively until 2015. Direct and indirect costs were retrieved from Danish national registries. Data were compared with a control population [1:20]. Associations between the costs and multiple variables were assessed.

Results

A total of 513 (CD: 213 [42%], UC: 300 [58%]) IBD patients were included. No significant differences were found in indirect costs between CD, UC, and the control population. Costs for CD patients were significantly higher than those for UC regarding all direct expenditures (except for5-aminosalicylates [5-ASA] and diagnostic expenses). Biologics accounted for €1.6 and €0.3 million for CD and UC, respectively. The total costs amounted to €42.6 million. Only patients with extensive colitis had significantly higher direct costs (proctitis: €2273 [1341–4092], left-sided: €3606 [2354–5311], extensive: €4093 [2313–6057], p <0.001). No variables were significantly associated with increased total costs in CD or in UC patients.

Conclusions

In this prospective population-based cohort, direct costs for IBD remain high. However, indirect costs did not surpass the control population. Total costs were mainly driven by hospitalisation, but indirect costs accounted for a higher percentage overall, although these did decrease over time.

Podcast

This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast
Outcome of orthodontic treatment in subjects with periodontal disease. Part III: a CBCT study of external apical root resorption
Authors: Zasčiurinskienė Eglė , Lund Henrik , Lindsten Rune , Jansson Henrik , Bjerklin Krister
Published: May 2019

Background

No evidence is present on the risk for external apical root resorption (EARR) during orthodontic treatment (OT) of adult patients with periodontal disease.

Aim

To examine EARR after OT in subjects with periodontal disease and to analyse how intrusion and change in inclination of the most proclined maxillary incisors influence EARR.

Methods

The study included 50 patients with periodontal disease. Sub-gingival debridement by ultrasonic instrumentation supplemented with hand instruments was performed by experienced dental hygienist after baseline examination for all patients. For the control group, final periodontal treatment (PT) was performed before orthodontic tooth movement. For the test group patients, final PT was performed after levelling and alignment phases were finished, before the active space closure with elastic chain and/or inter-arch elastic traction for sagittal correction was started. OT was performed with a straight-wire appliance. Micro-implants or implants were used for posterior anchorage. Cone beam computed tomography examinations were performed before and after OT. EARR of all single-rooted teeth were measured. EARR of the most proclined maxillary incisor was related to intrusion and change in inclination angle.

Results

EARR after OT was observed in median 80.7 per cent (interquartile range 22.02) of single-rooted teeth [mean 1.2 (standard deviation 0.44) mm]. In 82.3 per cent of teeth, EARR was 2 mm or less. Severe EARR was found in 8 per cent of patients and five maxillary incisors (less than 1 per cent of all teeth). The amount of intrusion and change in inclination angle of the most proclined maxillary central incisor influenced the extent of EARR. Mean EARR was significantly higher when OT lasted more than 18 months (P = 0.02).

Conclusions

OT in conjunction with PT in periodontal patients resulted in EARR in 81 per cent of all single-rooted teeth. Intrusion and change in inclination angle of the most proclined maxillary central incisor influenced the extent of EARR, as did longer OT.
Physical illness leading to absence from work and the risk of subsequent suicide: a national register-based study
Authors: Tang Fang , Mehlum Lars , Mehlum Ingrid S , Qin Ping
Published: May 2019

Background

Studies have shown that people with physical illness are at increased risk of suicide, but knowledge on the association between absence from work due to specific physical health problems and suicide risk is limited. This study aimed to examine the relationship between suicide risk and physical illness requiring leave from work across a range of specific physical diagnoses, and to study the interactions of mental illness and socioeconomic factors on this relationship.

Methods

Using a nested case-control design, 9313 suicide cases and 169 235 matched controls were retrieved and interlinked from Norwegian national registries. Data on sick leave and related physical illness were derived from claims for sickness benefit and analyzed using conditional logistic regression.

Results

For males, the risk of suicide increased progressively with the number of previous physical illness-related absences and the duration of recent physical illness-related absences. Absences related to digestive, musculoskeletal and neurological disorders as well as cancer and accidents/injuries were associated with a significantly increased risk of suicide. In contrast, females with a history of physical illness-related absence and a diagnosis of most organ or system specific illnesses were at a relatively reduced risk of suicide. In both genders, the suicide risk associated with physical illness resulting in absence from work differentiated significantly by history of sickness absence due to mental illness, and by education and income levels.

Conclusions

The risk of suicide associated with physical illness requiring leave from work varied significantly by gender and by education and income status.
Comparative Effects of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers on Response to a Physical Activity Intervention in Older Adults: Results From the Lifestyle Interventions and Independence for Elders Study
Authors: Brown Joshua D , Smith Steven M , Strotmeyer Elsa S , Kritchevsky Stephen B , Gill Thomas M , Blair Steven N , Fielding Roger A , Buford Thomas W , Pahor Marco , Manini Todd M
Published: May 2019

Background

Angiotensin-converting enzyme inhibitors (ACEis) and angiotensin receptor blockers (ARBs) may protect against aging-related decline. This study directly compared ACEis and ARBs on associations with risk of mobility disability in older adults when combined with a physical activity intervention.

Methods

This was a secondary analysis of the Lifestyle Interventions and Independence for Elders (LIFE) trial. Participants aged 70–89 years were randomized to a physical activity or health education intervention. Outcomes included incident and persistent major mobility disability, injurious falls, short physical performance battery, and gait speed. For this analysis, only participants who reported ACEi or ARB use at baseline were included. Baseline differences between ACEi and ARB groups were adjusted for using inverse probability of treatment weights. Weighted Cox proportional hazard models and analysis of covariance models were used to evaluate the independent effects of medications and interaction effects with the intervention on each outcome.

Results

Of 1,635 participants in the Lifestyle Interventions and Independence for Elders study, 796 used either an ACEi (496, 62.3%) or ARB (300, 37.7%). Compared with ACEi users, ARB users had 28% lower risk (hazard ratio [HR] = 0.72 [0.60–0.85]) of incident major mobility disability and 35% (HR = 0.65 [0.52–0.82]) lower risk of persistent major mobility disability whereas no interaction between medication use and intervention was observed. Risk of injurious falls and changes in short physical performance battery or gait speed were not different between ARB and ACEi users.

Conclusions

These results suggest that ARBs may protect from major mobility disability by other mechanisms than improving physical performance.
Effects of Older Adult Driving Resumption on All-Cause Mortality
Authors: Ratnapradipa Kendra L , Wang Jing , Berg-Weger Marla , Schootman and Mario
Published: May 2019

Objectives

Driving cessation is associated with adverse social and health outcomes including increased mortality risk. Some former drivers resume driving. Do resumed drivers have a different mortality risk compared to former drivers or continued drivers?

Method

We analyzed National Health and Aging Trends Study (2011–2015) data of community-dwelling self-responding ever drivers (n = 6,189) with weighted stratified life tables and discrete time logistic regression models to characterize mortality risk by driving status (continued, resumed, former), adjusting for relevant sociodemographic and health variables.

Results

Overall, 14% (n = 844) of participants died and 52% (n = 3,209) completed Round 5. Former drivers had the highest mortality (25%), followed by resumed (9%) and continued (6%) drivers. Former drivers had 2.4 times the adjusted odds of mortality compared with resumed drivers (adjusted odds ratio [aOR] = 2.41; 95% confidence interval [CI] = 1.51, 3.83), with no difference between continued and resumed drivers (aOR = 1.22; 95% CI = 0.74, 1.99).

Discussion

Those who resumed driving had better survival than those who did not. Practice implications include driver rehabilitation and retraining to safely promote and prolong driving.
Looking back on 10 years of global road safety
Authors: Peden Margaret M , Puvanachandra Prasanthi
Published: May 2019

Every year more than 1.35 million people lose their lives on the road and tens of millions more are injured, some permanently. Since the early 2000s there has been renewed focus on the issue, with the United Nations, World Health Organization and the World Bank placing the issue higher on their agendas. Guided by the United Nations General Assembly, World Health Assembly resolutions and ministerial-level conferences on the global road safety crisis, multisectoral partnerships have synthesised the evidence, advocated for action (there are two Sustainable Development Goal targets with an ambitious goal of reducing deaths and injuries from road traffic crashes by 50%), raised public awareness, generated funding, piloted interventions and monitored progress. And yet the total number of deaths has plateaued despite some sporadic country-level successes. More needs to be done—more people need to be trained in countries to deliver, monitor and evaluate a systems approach to road safety, more solid evidence of what works in low-resource settings is needed (including sustainable transportation options) and there needs to be a greater focus on optimising care and support for those injured in crashes—if we are to begin to see numbers come down in the next decade.
On the concepts of legal standards and substantive standards (and how the latter influences the choice of the former)
Authors: Katsoulacos Yannis
Published: May 2019

The substantial literature on the optimal choice of legal standards (LSs) in Competition Law enforcement concentrates on the factors that influence this choice given the Substantive (or Liability) Standard adopted by courts and competition authorities (CAs). Generally, this literature assumes that the substantive standard (SS) is welfarist. However, in reality, courts and CAs in different countries and over time use different criteria for establishing liability and, very often, these criteria are not welfarist. This article’s main objective is to clarify the relationship between legal and SSs and show the important influence of the latter on the choice of the former: our analysis shows that while efects-based LSs are compatible with non-welfarist SSs, under the latter courts and CAs will be much more likely to use Per Se LSs. This occurs as under non-welfarist SSs the strength of the presumption of illegality will be higher. This influence may be considered as being mainly responsible for differences in the LSs adopted in European Union and in North America (USA and Canada) or UK, especially in relation to abuse of dominance cases.
The extent of market concentration in South Africa’s product markets
Authors: Buthelezi Thembalethu , Mtani Thando , Mncube Liberty
Published: May 2019

Competitive markets can benefit consumers, workers, entrepreneurs, small businesses, and the economy more generally but several indicators suggest the persistence of high levels of market concentration in many of South Africa’s economic sectors. The causes underlying the high levels of concentration and corresponding market power are not clear. This article uses recent data from notified mergers to show the extent of the static level of market concentration (measured using the Herfindahl–Hirschman index). This article argues that consumers and workers would benefit from additional actions to promote effective competition and inclusion in markets.
Monophyletic status of European morphogenera of the subfamily Candoninae Kaufmann, 1900 (Ostracoda: Candonidae) in relation to their mtDNA phylogenies
Authors: Wysocka Anna , Kilikowska Adrianna , Mori Nataša , Iepure Sanda , Kijowska Michalina , Namiotko Tadeusz
Published: May 2019

The subfamily Candoninae Kaufmann, 1900a is one of the most taxonomically difficult and species-rich lineages of non-marine Ostracoda. It is widely distributed, inhabiting all kinds of surface and subterranean waters, but its taxonomy remains unclear and generic relationships ambiguous due to a number of homoplasies. To verify the morphology-based taxonomy and monophyly of the European morphogenera of Candoninae we propose the analysis of the mitochondrial fragment encoding cytochrome c oxidase subunit I (COI). We investigated 75 individuals of 25 species representing eight of 13 extant genera of Candoninae known from Europe. The phylogenetic analyses revealed a complex pattern of relationships and a noteworthy incongruence with the currently used taxonomic system. The monophyletic status of the morphogenera CandonaBaird, 1845, FabaeformiscandonaKrstić, 1972, and PseudocandonaKaufmann, 1900a appeared questionable, but instead monophyly of some species groups distinguished morphologically within these genera seemed to be confirmed in our study. The phylogenetic position of some other morphogenera remained unresolved. Our analysis, focusing on well-supported nodes, nevertheless revealed a handful of salient points on the evolution of Candoninae that deserve further investigation.
Vegetation classification at the association level under the China Vegetation Classification System: an example of six Stipa steppe formations in China
Authors: Liu Changcheng , Wentworth Thomas R , Qiao Xianguo , Guo Ke , Hou Dongjie
Published: May 2019

Aims

The latest China Vegetation Classification System (China-VCS) for natural/semi-natural vegetation has eight hierarchical levels: Association < Association-group < Subformation < Formation < Formation-group < Vegetation-subtype < Vegetation-type < Vegetation-type-group. The classification is based on dominant species and their growth forms and has been completed at the formation level. The principal challenge today in Chinese vegetation classification is to develop the China-VCS at levels below the formation in a way that is consistent with current international standards. We explored the following question: how can existing vegetation plot data help develop the China-VCS and improve its compatibility with other international classification systems?

Methods

We compiled 401 plots having plant cover and/or aboveground biomass measurements collected in six Stipa steppe formations and divided them into those with cover data (299 plots) and/or biomass data (283 plots). We applied a combination of hierarchical clustering and ordination to partition the cover and biomass data sets into formations and constituent associations. We then used supervised noise clustering to improve the classification and to identify the core plots representing each association. Diagnostic species were also identified at both association and formation levels. Finally, we compared the classification results based on cover and biomass data sets and combined these results into a comprehensive classification framework for the six formations.

Important Findings

Our results using cover data were comparable with those using biomass data at both formation and association levels. Three Stipa formations were classified into associations based on cover data, two based on biomass data and one based on both biomass and cover data. Twenty-seven associations were defined and proposed within the six formations, using cover or biomass data as consistent classification sections (CCSs). Both dominant species in the dominant stratum and diagnostic species from multiple strata of the core plots were used to characterize vegetation types at both formation and association levels, improving the compatibility of our classification with the International Vegetation Classification. Temperature and precipitation were found to be important climatic factors determining the distribution pattern and species composition of Stipa-dominated vegetation. We propose a framework for plot-based vegetation classification in the China-VCS, using our work with Stipa-dominated steppe vegetation as an example. We applied the concept of CCS to make optimal use of available data representing both plant cover and biomass. This study offers a model for developing the China-VCS to the association level in a way that is consistent with current international standards.
Eukaryotic initiation factor (eIF) 3 mediates Barley Yellow Dwarf Viral mRNA 3′–5′ UTR interactions and 40S ribosomal subunit binding to facilitate cap-independent translation
Authors: Bhardwaj Usha , Powell Paul , Goss Dixie J
Published: May 2019

Barley Yellow Dwarf Virus (BYDV) is a positive strand RNA virus that lacks the canonical 5′ 7-methylguanosine cap and a 3′ poly-A tail. Instead, BYDV utilizes a cruciform cap independent translation element (CITE) in its 3′UTR RNA (BYDV-like CITE or BTE) that binds eukaryotic translation initiation factor (eIF) 4F and recruits 40S ribosomal subunits in the presence of active helicase factors (eIF4A, eIF4B, eIF4F and ATP). A long-range, 5-nucleotide, base-pairing kissing loop interaction between the 3′BTE and a 5′UTR stem-loop is necessary for translation to initiate. The 40S–eIF complex does not bind to the BYDV 5′UTR, suggesting the involvement of additional factors. We identified eIF3 as a component of the 3′BTE recruited complex using affinity-tagged 3′BTE RNA pull-down assays. Fluorescence anisotropy binding and gel shift assays showed that the 3′BTE and 5′UTR RNAs can simultaneously and non-competitively bind eIF3 in the presence of active helicase factors forming a single, macromolecular complex. Further, quantitative studies showed eIF3 increased recruitment of the 40S subunit by more than 25-fold. We propose a new role for eIF3, where eIF3 bridges BYDV’s UTRs, stabilizes the long-range 5′-3′ interaction, and facilitates recruitment of the 40S–eIF complex to the 5′UTR, leading to translation initiation.
ImmuneRegulation: a web-based tool for identifying human immune regulatory elements
Authors: Kalayci Selim , Selvan Myvizhi Esai , Ramos Irene , Cotsapas Chris , Harris Eva , Kim Eun-Young , Montgomery Ruth R , Poland Gregory , Pulendran Bali , Tsang John S , Klein Robert J , Gümüş Zeynep H
Published: May 2019

Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at https://immuneregulation.mssm.edu.
Talk About Intimate Subjects
Authors: Gaudio Rudolf P.
Published: May 2019

Ethnographic research is to a great extent a process of language socialization. Like children and other neophytes, ethnographers learn how to use language to participate in the social worlds they are studying. For scholars of language, gender, and sexuality, this ideally entails developing communicative competence as gendered and sexual subjects: we learn how people talk, and don’t talk, about gender and sex. This chapter describes how long-term participant-observation, the core ethnographic research method, allowed the author to come to a (partial) appreciation of the language and subjectivities articulated by Hausa-speaking men in northern Nigeria, who saw themselves as “feminine” and/or enjoyed sex with other men. Using examples of miscommunication that occurred at different stages of fieldwork, the chapter illustrates how the time and attention required for ethnographic research can contribute to nuanced understandings of language, gender, and sexuality in particular cultural contexts.
The Ethics of Digital Research
Authors: Hancock Jeffrey T.
Published: May 2019

With all the important changes to methodology that research on networked communication brings, a key dimension that must be addressed is how to conduct research ethically. This chapter introduces section VI of the Handbook and reviews some of the key challenges that arise when doing digital research. This introduction draws from the many conversations the author had with various stakeholders about the the key issues surrounding the Facebook Emotional Contagion study, and it uses that discussion to highlight the main contributions of the chapters in this section. Some of the challenges considered include the evolving research ecosystem, changes in privacy practices, informed consent, heterogeneous populations and cultures, and technical and legal issues.