bluuebunny/crossref_metadata_2025_split huggingface dataset:
Landscape of cancer diagnostic biomarkers from specifically expressed genes
Authors: Lv Yao , Lin Sheng-Yan , Hu Fei-Fei , Ye Zheng , Zhang Qiong , Wang Yan , Guo An-Yuan 
Published: October 2019

Abstract
Although there has been great progress in cancer treatment, cancer remains a serious health threat to humans because of the lack of biomarkers for diagnosis, especially for early-stage diagnosis. In this study, we comprehensively surveyed the specifically expressed genes (SEGs) using the SEGtool based on the big data of gene expression from the The Cancer Genome Atlas (TCGA) and the Genotype–Tissue Expression (GTEx) projects. In 15 solid tumors, we identified 233 cancer-specific SEGs (cSEGs), which were specifically expressed in only one cancer and showed great potential to be diagnostic biomarkers. Among them, three cSEGs (OGDH, MUDENG and ACO2) had a sample frequency &gt;80% in kidney cancer, suggesting their high sensitivity. Furthermore, we identified 254 cSEGs as early-stage diagnostic biomarkers across 17 cancers. A two-gene combination strategy was applied to improve the sensitivity of diagnostic biomarkers, and hundreds of two-gene combinations were identified with high frequency. We also observed that 13 SEGs were targets of various drugs and nearly half of these drugs may be repurposed to treat cancers with SEGs as their targets. Several SEGs were regulated by specific transcription factors in the corresponding cancer, and 39 cSEGs were prognosis-related genes in 7 cancers. This work provides a survey of cancer biomarkers for diagnosis and early diagnosis and new insights to drug repurposing. These biomarkers may have great potential in cancer research and application.
Bioinformatics-assisted, integrated omics studies on medicinal plants
Authors: Ma Xiaoxia , Meng Yijun , Wang Pu , Tang Zhonghai , Wang Huizhong , Xie Tian 
Published: October 2019

AbstractThe immense therapeutic and economic values of medicinal plants have attracted increasing attention from the worldwide researchers. It has been recognized that production of the authentic and high-quality herbal drugs became the prerequisite for maintaining the healthy development of the traditional medicine industry. To this end, intensive research efforts have been devoted to the basic studies, in order to pave a way for standardized authentication of the plant materials, and bioengineering of the metabolic pathways in the medicinal plants. In this paper, the recent advances of omics studies on the medicinal plants were summarized from several aspects, including phenomics and taxonomics, genomics, transcriptomics, proteomics and metabolomics. We proposed a multi-omics data-based workflow for medicinal plant research. It was emphasized that integration of the omics data was important for plant authentication and mechanistic studies on plant metabolism. Additionally, the computational tools for proper storage, efficient processing and high-throughput analyses of the omics data have been introduced into the workflow. According to the workflow, authentication of the medicinal plant materials should not only be performed at the phenomics level but also be implemented by genomic and metabolomic marker-based examination. On the other hand, functional genomics studies, transcriptional regulatory networks and protein–protein interactions will contribute greatly for deciphering the secondary metabolic pathways. Finally, we hope that our work could inspire further efforts on the bioinformatics-assisted, integrated omics studies on the medicinal plants.
CpG-island-based annotation and analysis of human housekeeping genes
Authors: Zhang Le , Dai Zichun , Yu Jun , Xiao Ming 
Published: October 2019

Abstract
By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CpG islands (CGIs), their methylation states, CpG spacing and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be explained at individual gene and gene-family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI) and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA box on HK genes, remains to be elucidated. First, this study introduces such a problem-solving protocol for human-genome annotation, which is based on a combination of GTEx, JBLA and Gene Ontology (GO) analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; the HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic based on GO enrichment analysis. Finally, we demonstrate that Hadoop MapReduce-based MR-JBLA algorithm is more efficient than the original JBLA in k-mer counting and CGI-associated gene analysis.
Computationally predicted gene regulatory networks in molluscan biomineralization identify extracellular matrix production and ion transportation pathways
Authors: Sleight Victoria A , Antczak Philipp , Falciani Francesco , Clark Melody S 
Published: October 2019

AbstractMotivationThe molecular processes regulating molluscan shell production remain relatively uncharacterized, despite the clear evolutionary and societal importance of biomineralization.ResultsHere we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineralization using Antarctic clam (Laternula elliptica) mantle gene expression data produced over an age-categorized shell damage-repair time-course. We used previously published in vivo in situ hybridization expression data to ground truth gene interactions predicted by the GRN and show that candidate biomineralization genes from different shell layers, and hence microstructures, were connected in unique modules. We characterized two biomineralization modules of the GRN and hypothesize that one module is responsible for translating the extracellular proteins required for growing, repairing or remodelling the nacreous shell layer, whereas the second module orchestrates the transport of both ions and proteins to the shell secretion site, which are required during normal shell growth, and repair. Our findings demonstrate that unbiased computational methods are particularly valuable for studying fundamental biological processes and gene interactions in non-model species where rich sources of gene expression data exist, but annotation rates are poor and the ability to carry out true functional tests are still lacking.Availability and implementationThe raw RNA-Seq data is freely available for download from NCBI SRA (Accession: PRJNA398984), the assembled and annotated transcriptome can be viewed and downloaded from molluscDB (ensembl.molluscdb.org) and in addition, the assembled transcripts, reconstructed GRN, modules and detailed annotations are all available as Supplementary Files.Supplementary informationSupplementary data are available at Bioinformatics online.
Expectation pooling: an effective and interpretable pooling method for predicting DNA–protein binding
Authors: Luo Xiao , Tu Xinming , Ding Yang , Gao Ge , Deng Minghua 
Published: October 2019

AbstractMotivationConvolutional neural networks (CNNs) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. While previous studies have built a connection between CNNs and probabilistic models, simple models of CNNs cannot achieve sufficient accuracy on this problem. Recently, some methods of neural networks have increased performance using complex neural networks whose results cannot be directly interpreted. However, it is difficult to combine probabilistic models and CNNs effectively to improve DNA–protein binding predictions.ResultsIn this article, we present a novel global pooling method: expectation pooling for predicting DNA–protein binding. Our pooling method stems naturally from the expectation maximization algorithm, and its benefits can be interpreted both statistically and via deep learning theory. Through experiments, we demonstrate that our pooling method improves the prediction performance DNA–protein binding. Our interpretable pooling method combines probabilistic ideas with global pooling by taking the expectations of inputs without increasing the number of parameters. We also analyze the hyperparameters in our method and propose optional structures to help fit different datasets. We explore how to effectively utilize these novel pooling methods and show that combining statistical methods with deep learning is highly beneficial, which is promising and meaningful for future studies in this field.Availability and implementationAll code is public in https://github.com/gao-lab/ePooling.Supplementary informationSupplementary data are available at Bioinformatics online.
MIRUReader: MIRU-VNTR typing directly from long sequencing reads
Authors: Tang Cheng Yee , Ong Rick Twee-Hee 
Published: October 2019

Abstract

Summary
Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing is widely used to genotype Mycobacterium tuberculosis complex in epidemiological studies for tracking tuberculosis transmission. Recent long-read sequencing technologies from Pacific Biosciences and Oxford Nanopore Technologies can produce reads that are long enough to cover the entire repeat regions in each MIRU-VNTR locus which was previously not possible using the short reads from Illumina high-throughput sequencing technologies. We thus developed MIRUReader for MIRU-VNTR typing directly from long sequence reads.

Availability and implementation
Source code and documentation for MIRUReader program is freely available at https://github.com/phglab/MIRUReader.

Supplementary information
Supplementary data are available at Bioinformatics online.
Domain-invariant features for mechanism of action prediction in a multi-cell-line drug screen
Authors: Boyd Joseph C , Pinheiro Alice , Del Nery Elaine , Reyal Fabien , Walter Thomas 
Published: October 2019

Abstract

Motivation
High-content screening is an important tool in drug discovery and characterization. Often, high-content drug screens are performed on one single-cell line. Yet, a single-cell line cannot be thought of as a perfect disease model. Many diseases feature an important molecular heterogeneity. Consequently, a drug may be effective against one molecular subtype of a disease, but less so against another. To characterize drugs with respect to their effect not only on one cell line but on a panel of cell lines is therefore a promising strategy to streamline the drug discovery process.

Results
The contribution of this article is 2-fold. First, we investigate whether we can predict drug mechanism of action (MOA) at the molecular level without optimization of the MOA classes to the screen specificities. To this end, we benchmark a set of algorithms within a conventional pipeline, and evaluate their MOA prediction performance according to a statistically rigorous framework. Second, we extend this conventional pipeline to the simultaneous analysis of multiple cell lines, each manifesting potentially different morphological baselines. For this, we propose multi-task autoencoders, including a domain-adaptive model used to construct domain-invariant feature representations across cell lines. We apply these methods to a pilot screen of two triple negative breast cancer cell lines as models for two different molecular subtypes of the disease.

Availability and implementation
https://github.com/jcboyd/multi-cell-line or https://zenodo.org/record/2677923.

Supplementary information
Supplementary data are available at Bioinformatics online.
Revision and Update of the Consensus Definitions of Invasive Fungal Disease From the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium
Authors: Donnelly J Peter , Chen Sharon C , Kauffman Carol A , Steinbach William J , Baddley John W , Verweij Paul E , Clancy Cornelius J , Wingard John R , Lockhart Shawn R , Groll Andreas H , Sorrell Tania C , Bassetti Matteo , Akan Hamdi , Alexander Barbara D , Andes David , Azoulay Elie , Bialek Ralf , Bradsher Robert W , Bretagne Stephane , Calandra Thierry , Caliendo Angela M , Castagnola Elio , Cruciani Mario , Cuenca-Estrella Manuel , Decker Catherine F , Desai Sujal R , Fisher Brian , Harrison Thomas , Heussel Claus Peter , Jensen Henrik E , Kibbler Christopher C , Kontoyiannis Dimitrios P , Kullberg Bart-Jan , Lagrou Katrien , Lamoth Frédéric , Lehrnbecher Thomas , Loeffler Jurgen , Lortholary Olivier , Maertens Johan , Marchetti Oscar , Marr Kieren A , Masur Henry , Meis Jacques F , Morrisey C Orla , Nucci Marcio , Ostrosky-Zeichner Luis , Pagano Livio , Patterson Thomas F , Perfect John R , Racil Zdenek , Roilides Emmanuel , Ruhnke Marcus , Prokop Cornelia Schaefer , Shoham Shmuel , Slavin Monica A , Stevens David A , Thompson George R , Vazquez Jose A , Viscoli Claudio , Walsh Thomas J , Warris Adilia , Wheat L Joseph , White P Lewis , Zaoutis Theoklis E , Pappas Peter G 
Published: October 2019

Abstract

Background
Invasive fungal diseases (IFDs) remain important causes of morbidity and mortality. The consensus definitions of the Infectious Diseases Group of the European Organization for Research and Treatment of Cancer and the Mycoses Study Group have been of immense value to researchers who conduct clinical trials of antifungals, assess diagnostic tests, and undertake epidemiologic studies. However, their utility has not extended beyond patients with cancer or recipients of stem cell or solid organ transplants. With newer diagnostic techniques available, it was clear that an update of these definitions was essential.

Methods
To achieve this, 10 working groups looked closely at imaging, laboratory diagnosis, and special populations at risk of IFD. A final version of the manuscript was agreed upon after the groups’ findings were presented at a scientific symposium and after a 3-month period for public comment. There were several rounds of discussion before a final version of the manuscript was approved.

Results
There is no change in the classifications of “proven,” “probable,” and “possible” IFD, although the definition of “probable” has been expanded and the scope of the category “possible” has been diminished. The category of proven IFD can apply to any patient, regardless of whether the patient is immunocompromised. The probable and possible categories are proposed for immunocompromised patients only, except for endemic mycoses.

Conclusions
These updated definitions of IFDs should prove applicable in clinical, diagnostic, and epidemiologic research of a broader range of patients at high-risk.
Occult Adenocarcinoma Arising in Crohn’s-Related Strictures: A Case Series
Authors: Singh Kevin , Singh Amandeep , Philpott Jessica , Liska David , Lai Keith 
Published: October 2019

Abstract
Strictures are frequent complications of Crohn’s disease, but malignant small bowel strictures are uncommon and their diagnosis is often challenging. In this case series, we present 3 patients with underlying Crohn’s disease and symptomatic strictures who were found to have adenocarcinomas arising within the strictures at time of operation or after histopathological examination. Given the critical need to identify such malignancies early and the diagnostic difficulty, we use this opportunity to review the presentation, diagnosis, and management of strictures and adenocarcinomas arising in the ileum to raise awareness of this entity so that optimal outcomes can be achieved, if identified early in the disease course.
PCIR: a database of Plant Chloroplast Inverted Repeats
Authors: Zhang Rui , Ge Fangfang , Li Huayang , Chen Yudong , Zhao Ying , Gao Ying , Liu Zhiguo , Yang Long 
Published: October 2019

Abstract
Inverted repeats (IRs) serve as potential biomarkers for genomic instability, DNA replication and other genetic processes. However, little information can be found in databases to help researchers recognize potential IR nucleotides, explore junction sites and annotate related functional genes. Plant Chloroplast Inverted Repeats (PCIR) is an interactive, web-based platform containing various sequenced chloroplast genomes that enables detection, searching and visualization of large-scale detailed information on IRs. PCIR contains many datasets, including 21 433 IRs, 113 plants chloroplast genomes, 16 948 functional genes and 21 659 visual maps. This database offers an online prediction tool for detecting IRs based on DNA sequences. PCIR can also analyze phylogenetic relationships using IR information among different species and provide users with high-quality marker maps. This database will be a valuable resource for IR distribution patterns, related genes and architectural features.
Wolbachia Infection in Two Species: Novel Views on the Colonization Ability of Wolbachia in Aphids
Authors: Chen Rui , Su Xiaomin , Chen Jing , Jiang Liyun , Qiao Ge-Xia 
Published: October 2019

Abstract
Wolbachia pipientis (Rickettsiales: Anaplasmataceae) is an intracellular symbiont residing in arthropods and filarial nematodes. Sixteen supergroups have been described from different host taxa. Four supergroups A, B, M, and N were found in aphids according to prior studies. The cotton aphid, Aphis gossypii, and the green peach aphid, Myzus persicae, are typical polyphagous species with global distributions. We conducted an extensive and systematic survey of Wolbachia infections in these aphids from China. High incidences of Wolbachia infection were detected. The total infection incidence was 60% in A. gossypii and 88% in M. persicae. Both aphid species were infected with supergroups A, B and M. Different incidences of infection were observed among the seven geographical regions in China, which suggested a positive relationship between Wolbachia infections and the geographical distribution of aphid species. Furthermore, multiple infection patterns (M, B, A&M, B&M, and A&B&M) were observed. Infection patterns M and B&M were detected in almost all populations. Patterns A&B&M and B showed geographical restriction in North China. Three factors can possibly influence the Wolbachia infection incidences and patterns: the geographical distribution, aphid species, and different supergroup types.
Associations of recreational and non-recreational physical activity with coronary artery calcium density vs. volume and cardiovascular disease events: the Multi-Ethnic Study of Atherosclerosis
Authors: Thomas Isac C , Takemoto Michelle L , Forbang Nketi I , Larsen Britta A , Michos Erin D , McClelland Robyn L , Allison Matthew A , Budoff Matthew J , Criqui Michael H 
Published: October 2019

Abstract

Aims
The benefits of physical activity (PA) on cardiovascular disease (CVD) are well known. However, studies suggest PA is associated with coronary artery calcium (CAC), a subclinical marker of CVD. In this study, we evaluated the associations of self-reported recreational and non-recreational PA with CAC composition and incident CVD events. Prior studies suggest high CAC density may be protective for CVD events.

Methods and results
We evaluated 3393 participants of the Multi-Ethnic Study of Atherosclerosis with prevalent CAC. After adjusting for demographics, the highest quintile of recreational PA was associated with 0.07 (95% confidence interval 0.01–0.13) units greater CAC density but was not associated with CAC volume. In contrast, the highest quintile of non-recreational PA was associated with 0.08 (0.02–0.14) units lower CAC density and a trend toward 0.13 (−0.01 to 0.27) log-units higher CAC volume. There were 520 CVD events over a 13.7-year median follow-up. Recreational PA was associated with lower CVD risk (hazard ratio 0.88, 0.79–0.98, per standard deviation), with an effect size that was not changed with adjustment for CAC composition or across levels of prevalent CAC.

Conclusion
Recreational PA may be associated with a higher density but not a higher volume of CAC. Non-recreational PA may be associated with lower CAC density, suggesting these forms of PA may not have equivalent associations with this subclinical marker of CVD. While PA may affect the composition of CAC, the associations of PA with CVD risk appear to be independent of CAC.
Personalized antiplatelet therapy guided by a novel detection of platelet aggregation function in stable coronary artery disease patients undergoing percutaneous coronary intervention: a randomized controlled clinical trial
Authors: Zheng Ying-Ying , Wu Ting-Ting , Yang Yi , Hou Xian-Geng , Gao Ying , Chen You , Yang Yi-Ning , Li Xiao-Mei , Ma Xiang , Ma Yi-Tong , Xie Xiang 
Published: October 2019

Abstract

Aims
A number of studies have attempted to demonstrate the benefits associated with personalized antiplatelet therapy guided by platelet function testing, which has led to disappointing findings. In this study, we used a new platelet function test to guide antiplatelet therapy in stable coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI).

Methods and results
In the present randomized controlled trial, a total of 2237 patients with stable CAD undergoing PCI were randomly chosen to be administered personalized antiplatelet therapy (personalized group; n = 1123) or standard antiplatelet treatment (standard group; n = 1114). The patients in the standard therapy group, without detecting the platelet aggregation rate, were administered a 75 mg/day clopidogrel maintenance dosage plus 100 mg/day of aspirin for at least 6 months after the procedure. For the patients in the personalized therapy group, the antiplatelet strategy was performed according to the maximum aggregation rate (MAR), determined using a novel platelet analyser, PL-12. If MAR &gt; 55%, 90 mg ticagrelor was administered twice daily plus 100 mg/day of aspirin after PCI. If MAR ≤55%, 75 mg/day clopidogrel plus 100 mg/day of aspirin was administered after PCI. The primary endpoint was net clinical adverse events, which were a composite of cardiac death, myocardial infarction, stroke, stent thrombosis, urgent revascularization, and bleeding [Bleeding Academic Research Consortium (BARC) definitions, Type 2, 3, or 5], in the 180-day period after randomization. The primary endpoint was reached in 58 patients in the personalized group, compared with 85 patients in the standard group [5.1% vs. 7.5%, hazard ratio (HR) 0.678, 95% confidence interval (CI) 0.486–0.947, P = 0.023], on intention-to-treat analysis. We also found that the net clinical adverse events (including ischaemic and bleeding events) were significantly reduced in the personalized group at 30 days after PCI compared to the standard group (1.5% vs. 3.0%, HR 0.510, 95% CI 0.284–0.915, P = 0.020). We did not find a significant difference in major bleeding events at either the 30-day (0.5% vs. 0.3%, P = 0.322) or the 180-day follow-up (2.1% vs. 1.6%, P = 0.364) between the two groups.

Conclusion
The present study suggests that personalized antiplatelet therapy according to MAR can significantly improve the net clinical benefit 180 days after PCI.