cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1568389
title: Constructing comprehensive venom proteome reference maps for integrative venomics

description: Objective: Understanding the molecular basis of complex adaptive traits, such as snake venom, demands qualitative and quantitative comparisons of the temporal and spatial patterns of venom variation. Here, we assessed the proof–of-concept that locus-resolved reference venom proteome maps can be achieved through efficient pre-MS venom proteome decomplexation, peptide-centric MS/MS analysis and species-specific database searching. Methods: Venom proteome components were fractionated and quantified by RP-HPLC, SDS-PAGE and 2DE prior to LC-MS/MS matching against a species-specific transcriptomic dataset. Results: Combination of RP-HPLC/SDS-PAGE and 2DE followed by LC-MS/MS showed the existence of ∼178–180 venom protein species generated from ∼48 unique transcripts. Conclusions: Our results underscore that if sufficient pre-MS and MS efforts are applied, comprehensive venom maps can be achieved. And – equally important – dissociating the venom decomplexing steps from the protein identification process represents the key to achieving a quantitative and locus-resolved insight of the venom proteome.
DOI: 10.6084/m9.figshare.1568389.v1
title: Constructing comprehensive venom proteome reference maps for integrative venomics

description: Objective: Understanding the molecular basis of complex adaptive traits, such as snake venom, demands qualitative and quantitative comparisons of the temporal and spatial patterns of venom variation. Here, we assessed the proof–of-concept that locus-resolved reference venom proteome maps can be achieved through efficient pre-MS venom proteome decomplexation, peptide-centric MS/MS analysis and species-specific database searching. Methods: Venom proteome components were fractionated and quantified by RP-HPLC, SDS-PAGE and 2DE prior to LC-MS/MS matching against a species-specific transcriptomic dataset. Results: Combination of RP-HPLC/SDS-PAGE and 2DE followed by LC-MS/MS showed the existence of ∼178–180 venom protein species generated from ∼48 unique transcripts. Conclusions: Our results underscore that if sufficient pre-MS and MS efforts are applied, comprehensive venom maps can be achieved. And – equally important – dissociating the venom decomplexing steps from the protein identification process represents the key to achieving a quantitative and locus-resolved insight of the venom proteome.
DOI: 10.6084/m9.figshare.1568385
title: Follicular fluid alterations in endometriosis: label-free proteomics by MS<sup>E</sup> as a functional tool for endometriosis

description: Endometriosis is a chronic gynecological condition that affects 10-32% of women of reproductive age and may lead to infertility. The study of protein profiles in follicular fluid may assist in elucidating possible biomarkers related to this disease. For this, follicular fluid samples were obtained from women with tubal factor or minimal male factor infertility who had pregnancy outcomes after <i>in vitro</i> fertilization (IVF) treatment (control group, <i>n</i> = 10), women with endometriosis (endometriosis group, <i>n</i> = 10), along with the endometrioma from these same patients were included (endometrioma group, <i>n</i> = 10). For proteomic analysis, samples were pooled according to their respective groups and normalized to protein content. Proteins were analyzed by in tandem mass spectrometry (MS<sup>E</sup>) Spectra processing and the ProteinLynx Global Server v.2.5. was used for database searching. Data was submitted to the biological network analysis using Cytoscape 2.8.2 with ClueGO plugin. As a result, 535 proteins were identified among all groups. The control group differentially or uniquely expressed 33 (6%) proteins and equal expression of 98 (18%) proteins was observed in the control and endometriosis groups of which 41 (7%) proteins were further identified and/or quantified. Six (1%) proteins were observed in both the endometriosis and endometrioma groups, but 212 (39%) proteins were exclusively identified and/or quantified in the endometrioma group. There were 9 (1%) proteins observed in both the control and endometrioma groups and there were 139 (25%) proteins common among all three groups. Distinct differences among the protein profiles in the follicular fluid of patients included in this study were found, identifying proteins related to the disease progression and IVF success. Thus, some pathways related to endometriosis are associated with the presence of specific proteins, as well as the absence of others. This study provides a first step to the development of more sensitive diagnostic tests and treatment.
DOI: 10.6084/m9.figshare.1568385.v3
title: Follicular fluid alterations in endometriosis: label-free proteomics by MS<sup>E</sup> as a functional tool for endometriosis

description: Endometriosis is a chronic gynecological condition that affects 10-32% of women of reproductive age and may lead to infertility. The study of protein profiles in follicular fluid may assist in elucidating possible biomarkers related to this disease. For this, follicular fluid samples were obtained from women with tubal factor or minimal male factor infertility who had pregnancy outcomes after <i>in vitro</i> fertilization (IVF) treatment (control group, <i>n</i> = 10), women with endometriosis (endometriosis group, <i>n</i> = 10), along with the endometrioma from these same patients were included (endometrioma group, <i>n</i> = 10). For proteomic analysis, samples were pooled according to their respective groups and normalized to protein content. Proteins were analyzed by in tandem mass spectrometry (MS<sup>E</sup>) Spectra processing and the ProteinLynx Global Server v.2.5. was used for database searching. Data was submitted to the biological network analysis using Cytoscape 2.8.2 with ClueGO plugin. As a result, 535 proteins were identified among all groups. The control group differentially or uniquely expressed 33 (6%) proteins and equal expression of 98 (18%) proteins was observed in the control and endometriosis groups of which 41 (7%) proteins were further identified and/or quantified. Six (1%) proteins were observed in both the endometriosis and endometrioma groups, but 212 (39%) proteins were exclusively identified and/or quantified in the endometrioma group. There were 9 (1%) proteins observed in both the control and endometrioma groups and there were 139 (25%) proteins common among all three groups. Distinct differences among the protein profiles in the follicular fluid of patients included in this study were found, identifying proteins related to the disease progression and IVF success. Thus, some pathways related to endometriosis are associated with the presence of specific proteins, as well as the absence of others. This study provides a first step to the development of more sensitive diagnostic tests and treatment.
DOI: 10.6084/m9.figshare.1568372
title: A Data Science Course for Undergraduates: Thinking With Data

description: Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be nontraditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students to a variety of techniques to analyze small, neat, and clean datasets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that are considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms. Supplementary materials for this article are available online. [Received June 2014. Revised July 2015.]
DOI: 10.6084/m9.figshare.1568370
title: Domain movements during CCA-addition: A new function for motif C in the catalytic core of the human tRNA nucleotidyltransferases

description: CCA-adding enzymes are highly specific RNA polymerases that synthesize and maintain the sequence CCA at the tRNA 3′-end. This nucleotide triplet is a prerequisite for tRNAs to be aminoacylated and to participate in protein biosynthesis. During CCA-addition, a set of highly conserved motifs in the catalytic core of these enzymes is responsible for accurate sequential nucleotide incorporation. In the nucleotide binding pocket, three amino acid residues form Watson-Crick-like base pairs to the incoming CTP and ATP. A reorientation of these templating amino acids switches the enzyme's specificity from CTP to ATP recognition. However, the mechanism underlying this essential structural rearrangement is not understood. Here, we show that motif C, whose actual function has not been identified yet, contributes to the switch in nucleotide specificity during polymerization. Biochemical characterization as well as EPR spectroscopy measurements of the human enzyme reveal that mutating the highly conserved amino acid position D139 in this motif interferes with AMP incorporation and affects interdomain movements in the enzyme. We propose a model of action, where motif C forms a flexible spring element modulating the relative orientation of the enzyme's head and body domains to accommodate the growing 3′-end of the tRNA. Furthermore, these conformational transitions initiate the rearranging of the templating amino acids to switch the specificity of the nucleotide binding pocket from CTP to ATP during CCA-synthesis.
DOI: 10.6084/m9.figshare.1568372.v2
title: A Data Science Course for Undergraduates: Thinking With Data

description: Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be nontraditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students to a variety of techniques to analyze small, neat, and clean datasets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that are considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms. Supplementary materials for this article are available online. [Received June 2014. Revised July 2015.]
DOI: 10.6084/m9.figshare.1568373.v1
title: ncRDeathDB: a comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system

description: Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypothesis.
DOI: 10.6084/m9.figshare.1568372.v1
title: A Data Science Course for Undergraduates: Thinking with Data

description: Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be non-traditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students to a variety of techniques to analyze small, neat, and clean data sets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that are considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms.
DOI: 10.6084/m9.figshare.1568373.v3
title: ncRDeathDB: A comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system

description: Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypotheses.
DOI: 10.6084/m9.figshare.1568370.v2
title: Domain movements during CCA-addition: A new function for motif C in the catalytic core of the human tRNA nucleotidyltransferases

description: CCA-adding enzymes are highly specific RNA polymerases that synthesize and maintain the sequence CCA at the tRNA 3′-end. This nucleotide triplet is a prerequisite for tRNAs to be aminoacylated and to participate in protein biosynthesis. During CCA-addition, a set of highly conserved motifs in the catalytic core of these enzymes is responsible for accurate sequential nucleotide incorporation. In the nucleotide binding pocket, three amino acid residues form Watson-Crick-like base pairs to the incoming CTP and ATP. A reorientation of these templating amino acids switches the enzyme's specificity from CTP to ATP recognition. However, the mechanism underlying this essential structural rearrangement is not understood. Here, we show that motif C, whose actual function has not been identified yet, contributes to the switch in nucleotide specificity during polymerization. Biochemical characterization as well as EPR spectroscopy measurements of the human enzyme reveal that mutating the highly conserved amino acid position D139 in this motif interferes with AMP incorporation and affects interdomain movements in the enzyme. We propose a model of action, where motif C forms a flexible spring element modulating the relative orientation of the enzyme's head and body domains to accommodate the growing 3′-end of the tRNA. Furthermore, these conformational transitions initiate the rearranging of the templating amino acids to switch the specificity of the nucleotide binding pocket from CTP to ATP during CCA-synthesis.
DOI: 10.6084/m9.figshare.1568373.v2
title: ncRDeathDB: A comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system

description: Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypotheses.
DOI: 10.6084/m9.figshare.1568364
title: ADAM10 gene expression in the blood cells of Alzheimer's disease patients and mild cognitive impairment subjects

description: ADAM10 is a potential biomarker for Alzheimer's disease (AD). ADAM10 protein levels are reduced in platelets of AD patients. The aim was to verify the total blood and platelet ADAM10 gene expression in AD patients and to compare with mild cognitive impairment (MCI) and healthy subjects. No significant differences in ADAM10 gene expression were observed. Therefore, the decrease of ADAM10 protein in platelets of AD patients is not caused by a reduction in ADAM10 mRNA. Further studies must be performed to investigate other pathways in the down regulation of ADAM10 protein.
DOI: 10.6084/m9.figshare.1568364.v1
title: ADAM10 gene expression in the blood cells of Alzheimer's disease patients and mild cognitive impairment subjects

description: ADAM10 is a potential biomarker for Alzheimer's disease (AD). ADAM10 protein levels are reduced in platelets of AD patients. The aim was to verify the total blood and platelet ADAM10 gene expression in AD patients and to compare with mild cognitive impairment (MCI) and healthy subjects. No significant differences in ADAM10 gene expression were observed. Therefore, the decrease of ADAM10 protein in platelets of AD patients is not caused by a reduction in ADAM10 mRNA. Further studies must be performed to investigate other pathways in the down regulation of ADAM10 protein.
DOI: 10.6084/m9.figshare.1568370.v1
title: Domain movements during CCA-addition: A new function for motif C in the catalytic core of the human tRNA nucleotidyltransferases

description: CCA-adding enzymes are highly specific RNA polymerases that synthesize and maintain the sequence CCA at the tRNA 3′-end. This nucleotide triplet is a prerequisite for tRNAs to be aminoacylated and to participate in protein biosynthesis. During CCA-addition, a set of highly conserved motifs in the catalytic core of these enzymes is responsible for accurate sequential nucleotide incorporation. In the nucleotide binding pocket, three amino acid residues form Watson-Crick-like base pairs to the incoming CTP and ATP. A reorientation of these templating amino acids switches the enzyme's specificity from CTP to ATP recognition. However, the mechanism underlying this essential structural rearrangement is not understood. Here, we show that motif C, whose actual function has not been identified yet, contributes to the switch in nucleotide specificity during polymerization. Biochemical characterization as well as EPR spectroscopy measurements of the human enzyme reveal that mutating the highly conserved amino acid position D139 in this motif interferes with AMP incorporation and affects interdomain movements in the enzyme. We propose a model of action, where motif C forms a flexible spring element modulating the relative orientation of the enzyme's head and body domains to accommodate the growing 3′-end of the tRNA. Furthermore, these conformational transitions initiate the rearranging of the templating amino acids to switch the specificity of the nucleotide binding pocket from CTP to ATP during CCA-synthesis.
DOI: 10.17632/v2p3th8pb5.3
title: Data for: Failure Analysis of Feed Water Pump Shaft in HRSG of 9F Gas Turbine Generator Unit

description: macrophotograph，fracture morphology，microstructure，mechanical property
DOI: 10.6084/m9.figshare.1568358
title: The elicitor-responsive gene for a GRAS family protein, <i>CIGR2</i>, suppresses cell death in rice inoculated with rice blast fungus via activation of a heat shock transcription factor, <i>OsHsf23</i>

description: We show that a rice GRAS family protein, CIGR2, is a <i>bonafide</i> transcriptional activator, and through this function, targets the B-type heat shock protein-encoding gene <i>OsHsf23</i> (Os09g0456800). <i>CIGR2</i> (Os07g0583600) is an <i>N</i>-acetylchitooligosaccharide elicitor-responsive gene whose activity, through the direct transcriptional control of <i>OsHsf23</i>, is required for mediating hypersensitive cell death activation during pathogen infection. RNAi lines of <i>CIGR2</i> and <i>OsHsf23</i> similarly exhibited the higher level of granulation in the epidermal cells of leaf sheath inoculated with an avirulent isolate of rice blast fungus. Interestingly, we did not observe altered levels of resistance, suggesting that CIGR2 suppresses excessive cell death in the incompatible interaction with blast fungus via activation of <i>OsHsf23</i>. <i>N</i>-Acetylchitooligosaccharides-responsive <i>CIGR2</i> suppresses cell death of rice in cooperation with <i>OsHsf23</i>.