bluuebunny/crossref_metadata_2025_split huggingface dataset:
An efficient gene selection method for microarray data based on LASSO and BPSO
Authors: Xiong Ying , Ling Qing-Hua , Han Fei , Liu Qing-Hua 
Published: December 2019

AbstractBackgroundThe main goal of successful gene selection for microarray data is to find compact and predictive gene subsets which could improve the accuracy. Though a large pool of available methods exists, selecting the optimal gene subset for accurate classification is still very challenging for the diagnosis and treatment of cancer.ResultsTo obtain the most predictive genes subsets without filtering out critical genes, a gene selection method based on least absolute shrinkage and selection operator (LASSO) and an improved binary particle swarm optimization (BPSO) is proposed in this paper. To avoid overfitting of LASSO, the initial gene pool is divided into clusters based on their structure. LASSO is then employed to select high predictive genes and further calculate the contribution value which indicates the genes’ sensitivity to samples’ classes. With the second-level gene pool established by double filter strategy, the BPSO encoding the contribution information obtained from LASSO is improved to perform gene selection. Moreover, from the perspective of the bit change probability, a new mapping function is defined to guide the updating of the particle to select the more predictive genes in the improved BPSO.ConclusionsWith the compact gene pool obtained by double filter strategies, the improved BPSO could select the optimal gene subsets with high probability. The experimental results on several public microarray data with extreme learning machine verify the effectiveness of the proposed method compared to the relevant methods.
DynaVenn: web-based computation of the most significant overlap between ordered sets
Authors: Amand Jérémy , Fehlmann Tobias , Backes Christina , Keller Andreas 
Published: December 2019

Abstract
Background
In many research disciplines, ordered lists are compared. One example is to compare a subset of all significant genes or proteins in a primary study to those in a replication study. Often, the top of the lists are compared using Venn diagrams, ore more precisely Euler diagrams (set diagrams showing logical relations between a finite collection of different sets). If different cohort sizes, different techniques or algorithms for evaluation were applied, a direct comparison of significant genes with a fixed threshold can however be misleading and approaches comparing lists would be more appropriate.

Results
We developed DynaVenn, a web-based tool that incrementally creates all possible subsets from two or three ordered lists and computes for each combination a p-value for the overlap. Respectively, dynamic Venn diagrams are generated as graphical representations. Additionally an animation is generated showing how the most significant overlap is reached by backtracking. We demonstrate the improved performance of DynaVenn over an arbitrary cut-off approach on an Alzheimer’s Disease biomarker set.

Conclusion
DynaVenn combines the calculation of the most significant overlap of different cohorts with an intuitive visualization of the results. It is freely available as a web service at http://www.ccb.uni-saarland.de/dynavenn.
The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): conference summary and innovations in genomics
Authors: Mathé Ewy , Zhang Chi , Wang Kai , Ning Xia , Guo Yan , Zhao Zhongming 
Published: December 2019

AbstractThe goal of this editorial is to summarize the 2019 International Conference on Intelligent Biology and Medicine (ICIBM 2019) conference that took place on June 9–11, 2019 in The Ohio State University, Columbus, OH, and to provide an introductory summary of the seven articles presented in this supplement issue. ICIBM 2019 hosted four keynote speakers, four eminent scholar speakers, five tutorials and workshops, twelve concurrent sessions and a poster session, totaling 23 posters, spanning state-of-the-art developments in bioinformatics, genomics, next-generation sequencing (NGS) analysis, scientific databases, cancer and medical genomics, and computational drug discovery. A total of 105 original manuscripts were submitted to ICIBM 2019, and after careful review, seven were selected for this supplement issue. These articles cover methods and applications for functional annotations of miRNA targeting, clonal evolution of bacterial cells, gene co-expression networks that describe a given phenotype, functional binding site analysis of RNA-binding proteins, normalization of genome architecture mapping data, sample predictions based on multiple NGS data types, and prediction of an individual’s genetic admixture given exonic single nucleotide polymorphisms data.
normGAM: an R package to remove systematic biases in genome architecture mapping data
Authors: Liu Tong , Wang Zheng 
Published: December 2019

Abstract
Background
The genome architecture mapping (GAM) technique can capture genome-wide chromatin interactions. However, besides the known systematic biases in the raw GAM data, we have found a new type of systematic bias. It is necessary to develop and evaluate effective normalization methods to remove all systematic biases in the raw GAM data.

Results
We have detected a new type of systematic bias, the fragment length bias, in the genome architecture mapping (GAM) data, which is significantly different from the bias of window detection frequency previously mentioned in the paper introducing the GAM method but is similar to the bias of distances between restriction sites existing in raw Hi-C data. We have found that the normalization method (a normalized variant of the linkage disequilibrium) used in the GAM paper is not able to effectively eliminate the new fragment length bias at 1 Mb resolution (slightly better at 30 kb resolution). We have developed an R package named normGAM for eliminating the new fragment length bias together with the other three biases existing in raw GAM data, which are the biases related to window detection frequency, mappability, and GC content. Five normalization methods have been implemented and included in the R package including Knight-Ruiz 2-norm (KR2, newly designed by us), normalized linkage disequilibrium (NLD), vanilla coverage (VC), sequential component normalization (SCN), and iterative correction and eigenvector decomposition (ICE).

Conclusions
Based on our evaluations, the five normalization methods can eliminate the four biases existing in raw GAM data, with VC and KR2 performing better than the others. We have observed that the KR2-normalized GAM data have a higher correlation with the KR-normalized Hi-C data on the same cell samples indicating that the KR-related methods are better than the others for keeping the consistency between the GAM and Hi-C experiments. Compared with the raw GAM data, the normalized GAM data are more consistent with the normalized distances from the fluorescence in situ hybridization (FISH) experiments. The source code of normGAM can be freely downloaded from http://dna.cs.miami.edu/normGAM/.
Hydrogen cyanamide induces grape bud endodormancy release through carbohydrate metabolism and plant hormone signaling
Authors: Liang Dong , Huang Xiaojing , Shen Yanqiu , Shen Tian , Zhang Huifen , Lin Lijin , Wang Jin , Deng Qunxian , Lyu Xiulan , Xia Hui 
Published: December 2019

Abstract
Background
Grape buds exhibit non-uniform, or delayed, break in early spring in subtropical regions because the accumulation of chilling is insufficient. Hydrogen cyanamide (H2CN2, HC) can partially replace chilling to effectively promote bud sprouting and is used widely in warm winter areas. However, the exact underlying mechanism of grape bud release from endodormancy induced by HC remains elusive.

Results
In this study, the transcriptome of grape winter buds under in vitro conditions following HC and water treatment (control) was analyzed using RNA-seq technology. A total of 6772 differentially expressed genes (DEGs) were identified. Furthermore, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that starch and sucrose metabolism and plant hormone signaling transduction were most enriched out of the 50 total pathways. HC treatment induced the upregulated expression of sucrose synthase (SUS), sucrose phosphate synthase (SPS), α-amylase (AM), and β-amylase (BM) and downregulated expression of sucrose invertase (INV), hexokinase (HK), fructokinase (FK), soluble starch synthase (SS), and granule-bound starch synthase (GBSS). Hence, the starch concentration in the HC-treated group was significantly lower than that in control, whereas soluble sugar content in the HC-treated group increased quickly and was higher than that in control between 0 and 8 d. The concentration of indoleacetic acid (IAA) and zeatin (ZT) increased, whereas that of abscisic acid (ABA) and gibberellin (GA) decreased in HC treated group, which coincided with the expression level of genes involved in above hormone signals. The content of hydrogen peroxide (H2O2) and enzyme activity of superoxide dismutase (SOD) and peroxidase (POD) were increased in grape buds with HC treatment, whereas catalase (CAT) activity was decreased. HC treatment increased the expression of POD, SOD, primary amine oxidase (PAO), polyamine oxidase (PAOX), and glutathione peroxidase (GSH-Px).

Conclusion
Based on these results, it is possible to propose a mechanistic model that underlies the regulation of endodormancy release in grapevine buds by exogenous HC application.
De novo sequencing of the transcriptome reveals regulators of the floral transition in Fargesia macclureana (Poaceae)
Authors: Li Ying , Zhang Chunxia , Yang Kebin , Shi Jingjing , Ding Yulong , Gao Zhimin 
Published: December 2019

AbstractBackgroundFargesia macclureana(Poaceae) is a woody bamboo species found on the Qinghai–Tibet Plateau (QTP) approximately 2000 ~ 3800 m above sea level. It rarely blossoms in the QTP, but it flowered 20 days after growing in our lab, which is in a low-altitude area outside the QTP. To date, little is known regarding the molecular mechanism of bamboo flowering, and no studies of flowering have been conducted on wild bamboo plants growing in extreme environments. Here, we report the first de novo transcriptome sequence forF. macclureanato investigate the putative mechanisms underlying the flowering time control used byF. macclureanato adapt to its environment.ResultsIllumina deep sequencing of theF. macclureanatranscriptome generated 140.94 Gb of data, assembled into 99,056 unigenes. A comprehensive analysis of the broadly, specifically and differentially expressed unigenes (BEUs, SEUs and DEUs) indicated that they were mostly involved in metabolism and signal transduction, as well as DNA repair and plant-pathogen interactions, which may be of adaptive importance. In addition, comparison analysis between non-flowering and flowering tissues revealed that expressions ofFmFTandFmHd3a, two putativeF. macclureanaorthologs, were differently regulated in NF- vs F- leaves, and carbohydrate metabolism and signal transduction were two major KEGG pathways that DEUs were enriched in. Finally, we detected 9296 simple sequence repeats (SSRs) that may be useful for further molecular marker-assisted breeding.ConclusionsF. macclureanamay have evolved specific reproductive strategies for flowering-related pathways in response to photoperiodic cues to ensure long vegetation growing period. Our findings will provide new insights to future investigations into the mechanisms of flowering time control and adaptive evolution in plants growing at high altitudes.
Application of LpxC enzyme inhibitor to inhibit some fast-growing bacteria in human gut bacterial culturomics
Authors: Hou Fengyi , Chang Yuxiao , Huang Zongyu , Han Ni , Bin Lei , Deng Huimin , Li Zhengchao , Pan Zhiyuan , Ding Lei , Gao Hong , Yang Ruifu , Zhi Fachao , Bi Yujing 
Published: December 2019

Abstract
Background
Culturomics can ascertain traces of microorganisms to be cultivated using different strategies and identified by matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry or 16S rDNA sequencing. However, to cater to all requirements of microorganisms and isolate as many species as possible, multiple culture conditions must be used, imposing a heavy workload. In addition, the fast-growing bacteria (e.g., Escherichia) surpass the slow-growing bacteria in culture by occupying space and using up nutrients. Besides, some bacteria (e.g., Pseudomonas) suppress others by secreting antibacterial metabolites, making it difficult to isolate bacteria with lower competence. Applying inhibitors to restrain fast-growing bacteria is one method to cultivate more bacterial species from human feces.

Results
We applied CHIR-090, an LpxC enzyme inhibitor that has antibacterial activity against most Gram-negative bacteria, to culturomics of human fresh feces. The antibacterial activity of CHIR-090 was first assessed on five Gram-negative species of bacteria (Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Proteus vulgaris, and Bacteroides vulgatus), all of which are commonly isolated from the human gut. Then, we assessed suitable concentrations of the inhibitor. Finally, CHIR-090 was applied in blood culture bottles for bacterial cultivation. In total, 102 species from five samples were identified. Of these, we found one new species, two species not reported previously in the human gut, and 11 species not previously isolated from humans.

Conclusions
CHIR-090 can suppress E. coli, P. aeruginosa, K. pneumoniae, Pro. vulgaris, but not B. vulgatus. Compared with the non-inhibitor group, CHIR-090 increased bacteria isolation by 23.50%, including four species not reported in humans and one new species. Application of LpxC enzyme inhibitor in culturomics increased the number of species isolated from the human gut.
Metabolite profiling during graft union formation reveals the reprogramming of primary metabolism and the induction of stilbene synthesis at the graft interface in grapevine
Authors: Prodhomme Duyên , Valls Fonayet Josep , Hévin Cyril , Franc Céline , Hilbert Ghislaine , de Revel Gilles , Richard Tristan , Ollat Nathalie , Cookson Sarah Jane 
Published: December 2019

Abstract
Background
Grafting with rootstocks is essential for the culture of many perennial fruit crops and is increasing being used in the production of annual fruits and vegetables. Our previous work based on microarrays showed that transcripts encoding enzymes of both primary and secondary metabolism were differentially expressed during graft union formation in both homo-grafts (a genotype grafted with itself) and hetero-grafts (two different genotypes grafted together). The aim of this study was to profile primary and secondary metabolites, and quantify the activity of phenylalanine ammonia lyase (PAL) and neutral invertase (NI) in the scion and rootstock tissues and the graft interface of homo and hetero-grafts of grapevine 1 month after grafting. Table-top grafting was done on over-wintering stems (canes) of grapevine and the graft interface tissues (containing some woody stem tissues and callus) were compared to the surrounding rootstock and scion tissues. The objective was to identify compounds involved in graft union formation and hetero-grafting responses.

Results
A total of 54 compounds from primary and secondary metabolism (19 amino acids, five primary and 30 secondary compounds metabolites) and the activity of two enzymes were measured. The graft interface was associated with an increase in the accumulation of the branched-chain amino acids, basic amino acids, certain stilbene compounds and higher PAL and NI activity in comparison to the surrounding woody stem tissues. Some amino acids and stilbenes were identified as being accumulated differently between the graft interfaces of the scion/rootstock combinations in a manner which was unrelated to their concentrations in the surrounding woody stem tissues.

Conclusions
This study revealed the modification of primary metabolism to support callus cell formation and the stimulation of stilbene synthesis at the graft interface, and how these processes are modified by hetero-grafting. Knowledge of the metabolites and/or enzymes required for successful graft union formation offer us the potential to identify markers that could be used by nurseries and researchers for selection and breeding purposes.
Construction of a high-density genetic map and QTL mapping of leaf traits and plant growth in an interspecific F1 population of Catalpa bungei × Catalpa duclouxii Dode
Authors: Lu Nan , Zhang Miaomiao , Xiao Yao , Han Donghua , Liu Ying , Zhang Yu , Yi Fei , Zhu Tianqing , Ma Wenjun , Fan Erqin , Qu Guanzheng , Wang Junhui 
Published: December 2019

Abstract
Background
Catalpa bungei is an important tree species used for timber in China and widely cultivated for economic and ornamental purposes. A high-density linkage map of C. bungei would be an efficient tool not only for identifying key quantitative trait loci (QTLs) that affect important traits, such as plant growth and leaf traits, but also for other genetic studies.

Results
Restriction site-associated DNA sequencing (RAD-seq) was used to identify molecular markers and construct a genetic map. Approximately 280.77 Gb of clean data were obtained after sequencing, and in total, 25,614,295 single nucleotide polymorphisms (SNPs) and 2,871,647 insertions-deletions (InDels) were initially identified in the genomes of 200 individuals of a C. bungei (7080) × Catalpa duclouxii (16-PJ-3) F1 population and their parents. Finally, 9072 SNP and 521 InDel markers that satisfied the requirements for constructing a genetic map were obtained. The integrated genetic map contained 9593 pleomorphic markers in 20 linkage groups and spanned 3151.63 cM, with an average distance between adjacent markers of 0.32 cM. Twenty QTLs for seven leaf traits and 13 QTLs for plant height at five successive time points were identified using our genetic map by inclusive composite interval mapping (ICIM). Q16–60 was identified as a QTL for five leaf traits, and three significant QTLs (Q9–1, Q18–66 and Q18–73) associated with plant growth were detected at least twice. Genome annotation suggested that a cyclin gene participates in leaf trait development, while the growth of C. bungei may be influenced by CDC48C and genes associated with phytohormone synthesis.

Conclusions
This is the first genetic map constructed in C. bungei and will be a useful tool for further genetic study, molecular marker-assisted breeding and genome assembly.
Nitric oxide- induced AtAO3 differentially regulates plant defense and drought tolerance in Arabidopsis thaliana
Authors: Khan Murtaza , Imran Qari Muhammad , Shahid Muhammad , Mun Bong-Gyu , Lee Sang-Uk , Khan Muhammad Aaqil , Hussain Adil , Lee In-Jung , Yun Byung-Wook 
Published: December 2019

AbstractBackgroundExposure of plants to different environmental insults instigates significant changes in the cellular redox tone driven in part by promoting the production of reactive nitrogen species. The key player, nitric oxide (NO) is a small gaseous diatomic molecule, well-known for its signaling role during stress. In this study, we focused on abscisic acid (ABA) metabolism-related genes that showed differential expression in response to the NO donorS-nitroso-l-cysteine (CySNO) by conducting RNA-seq-based transcriptomic analysis.ResultsCySNO-induced ABA-related genes were identified and further characterized. Gene ontology terms for biological processes showed most of the genes were associated with protein phosphorylation. Promoter analysis suggested that severalcis-regulatory elements were activated under biotic and/or abiotic stress conditions. The ABA biosynthetic geneAtAO3was selected for validation using functional genomics. The loss of function mutantatao3was found to differentially regulate oxidative and nitrosative stress. Further investigations for determining the role ofAtAO3in plant defense suggested a negative regulation of plant basal defense andR-gene-mediated resistance. Theatao3plants showed resistance to virulentPseudomonas syringaepv.tomatostrain DC3000 (PstDC3000) with gradual increase inPR1gene expression. Similarly,atao3plants showed increased hypersensitive response (HR) when challenged withPstDC3000 (avrB). Theatgsnor1–3andatsid2mutants showed a susceptible phenotype with reducedPR1transcript accumulation. Drought tolerance assay indicated thatatao3andatnced3ABA-deficient mutants showed early wilting, followed by plant death. The study of stomatal structure showed thatatao3andatnced3were unable to close stomata even at 7 days after drought stress. Further, they showed reduced ABA content and increased electrolyte leakage than the wild-type (WT) plants. The quantitative polymerase chain reaction analysis suggested that ABA biosynthesis genes were down-regulated, whereas expression of most of the drought-related genes were up-regulated inatao3than in WT.ConclusionsAtAO3negatively regulates pathogen-induced salicylic acid pathway, although it is required for drought tolerance, despite the fact that ABA production is not totally dependent onAtAO3, and that drought-related genes likeDREB2andABI2show response to drought irrespective of ABA content.
Evaluation of alterations in serum immunoglobulin concentrations in components of metabolic syndrome, obesity, diabetes, and dyslipidemia
Authors: Lin Dee , Bridgeman Mary Barna , Brunetti Luigi 
Published: December 2019

Abstract
Purpose
Serum immunoglobulins (Igs) play a critical role in modulating the immune response by neutralizing pathogens, although little is known about the effect of Igs in development of atherosclerotic cardiovascular disease (ASCVD). Elevated serum Immunoglobulin A (IgA) concentrations have been identified in previous studies in populations with obesity and hypertriglyceridemia, whereas variable concentrations of Immunoglobulin M (IgM) have been observed in the setting of dyslipidemia.

Methods
In this cross-sectional study, investigators examined the association of serum Ig concentrations with components of metabolic syndrome, including obesity, diabetes, and dyslipidemia. All consecutive adult patients aged 18 years or older discharged from two academic teaching hospitals with serum Immunoglobulin G (IgG) concentration measured during their admission were evaluated, with a total of 1809 individuals included and stratified into two groups: those with and those without dyslipidemia.

Results
Mean IgG concentration in individuals with and without dyslipidemia was 997 ± 485 mg/dL and 1144 ± 677 mg/dL, respectively (P <  0.0001). After controlling for confounders in the generalized linear model (GLM), the least square mean IgG concentration in individuals with and without dyslipidemia was 1095 and 1239 mg/dL, respectively (P <  0.0001). The mean IgA and IgM concentrations were not significantly different in individuals with and without dyslipidemia both before and after adjusting covariates. After controlling for confounding variables, all three serum Ig concentrations were not significantly different in individuals with and without diabetes.

Conclusion
Dyslipidemia was associated with a lower mean serum IgG concentration. No association with any serum Ig was indentified in individuals with diabetes. Exploration of the association between alterations in serum Igs and metabolic syndrome and the role of alterations of Ig concentrations in disease progression represents an important step in identification of appropriate targeted treatment options for reducing cardiovascular risk.