cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6646895
title: Theoretical ribosomal protein mass fingerprint of Photobacterium phosphoreum

description: This is a dataset containing the theoretical molecular mass of various ribosomal proteins in the large and small ribosome subunit of <i>Photobacterium phosphoreum.</i>
DOI: 10.6084/m9.figshare.6646895.v1
title: Theoretical ribosomal protein mass fingerprint of Photobacterium phosphoreum

description: This is a dataset containing the theoretical molecular mass of various ribosomal proteins in the large and small ribosome subunit of <i>Photobacterium phosphoreum.</i>
DOI: 10.4225/03/5b2c64f668b73
title: Menelik head mesh model (STL files)

description: The folder contains the 33 anatomical structures of the Menelik surface mesh head model in STL files. A pdf file containing the information of each STL file was also included.<br>All surface mesh models have water-tight faces (no holes), 2-manifold mesh, and no self-intersecting faces that make them suitable for numerical computations.<br><br>The quality of faces was measured using the ratio of the radii of the incenter and circumcenter of faces.<br>
DOI: 10.6084/m9.figshare.6646595
title: Theoretical ribosomal protein mass fingerprint of Photobacterium damselae

description: This is a dataset containing the theoretical molecular mass of various ribosomal proteins in the large and small ribosome subunit of <i>Photobacterium damselae</i>.<br><br>
DOI: 10.6084/m9.figshare.6646595.v1
title: Theoretical ribosomal protein mass fingerprint of Photobacterium damselae

description: This is a dataset containing the theoretical molecular mass of various ribosomal proteins in the large and small ribosome subunit of <i>Photobacterium damselae</i>.<br><br>
DOI: 10.4225/03/5b2c7e150fd92
title: Menelik head mesh model images

description: Some anatomical structures in the Menelik head mesh model
DOI: 10.6084/m9.figshare.6643292
title: Non-exclusive α-helices in (α+β)+(α/β) proteins

description: Dataset containing physical-chemical and strucutural descriptors for non-exclusive α-helices and its flanking regions.<br>Only α-helices from <b>(α+β)+(α/β) proteins</b> are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter]</b>.<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix(<b>&lt;</b>); α-helix(<b>=</b>); flanking region after the α-helix (<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6641744
title: Exclusive α-helices in (α+β)+(α/β) proteins

description: Dataset containing physical-chemical and strucutural descriptors for exclusive α-helices and its flanking regions.<br>Only α-helices from (α+β)+(α/β) proteins are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter]</b>.<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix ().<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6639209
title: Marchantia inflexa mitochondrion and chloroplast genomes

description: Assemblies of the mitochondrion and chloroplast sequences of the tropical liverwort Marchantia inflexa. Details provided in:<br>Marks RA, Smith JJ, Cronk Q, Grassa CJ, McLetchie DN Genome of the tropical plant Marchantia inflexa: implications for sex chromosome evolution and dehydration tolerance. Submitted at Scientific Reports
DOI: 10.6084/m9.figshare.6639191
title: Network Analysis Data.zip

description: Initial coding from individual networks (photographed) into excel (see combined data entry). Nodes assigned weights based on position in network. Edges assigned ranks by participants. Networks imported to Gephi for visualisation of networks.
DOI: 10.6084/m9.figshare.6639023
title: α-helices in all-α proteins

description: Dataset containing physical-chemical and strucutural descriptors for α-helices and its flanking regions.<br>Only α-helices from <b>all-α proteins </b>are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter]</b>.<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix(<b>&lt;</b>); α-helix(<b>=</b>); flanking region after the α-helix(<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6639023.v2
title: α-helices in all-α proteins

description: Dataset containing physical-chemical and strucutural descriptors for α-helices and its flanking regions.<br>Only α-helices from <b>all-α proteins </b>are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter]</b>.<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix(<b>&lt;</b>); α-helix(<b>=</b>); flanking region after the α-helix(<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6639023.v1
title: alpha-helices-all-alpha-proteins

description: Dataset containing physical-chemical and strucutural descriptors for alpha helices and its flanking regions.<br>Only alpha helices from <b>all-alpha proteins </b>are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter]</b>.<br><b>length </b>is the number of amino acid residues comprising the aplha helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the alpha helix ().<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.<br><b>Example:</b><b>Solvent-accessible surface area for all amino acid residues forming an alpha helix of length 6</b><br>length, pdb_name, chain_id, flag, position, Accessible_Surface_in_Isolation6,1not,A,=,1,136.5856,1not,A,=,2,106.0686,1not,A,=,3,11.3226,1not,A,=,4,49.5176,1not,A,=,5,227.676,1not,A,"=",6,110.9
DOI: 10.6084/m9.figshare.6638972
title: Dataset & Codebook

description: Anonymized dataset for the Why We Retweet Scale. Data was collected during the year 2016. Current dataset is deidentified. Please refer to codebook for descriptions of the variables in the dataset.<br>Codebook describes columns in the dataset.
DOI: 10.6084/m9.figshare.6638972.v1
title: Dataset & Codebook

description: Anonymized dataset for the Why We Retweet Scale. Data was collected during the year 2016. Current dataset is deidentified. Please refer to codebook for descriptions of the variables in the dataset.<br>Codebook describes columns in the dataset.
DOI: 10.6084/m9.figshare.6638945
title: Non-exclusive α-helices in all-α proteins

description: Dataset containing physical-chemical and strucutural descriptors for non-exclusive α-helices and its flanking regions. <br>Only α-helices from <b>all-α proteins</b> are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter</b>].<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix(<b>&lt;</b>); α-helix (<b>=</b>); flanking region after the α-helix (<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6638945.v1
title: non-exclusive-alpha-helices-all-alpha-proteins

description: <b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6638945.v3
title: Non-exclusive α-helices in all-α proteins

description: Dataset containing physical-chemical and strucutural descriptors for non-exclusive α-helices and its flanking regions. <br>Only α-helices from <b>all-α proteins</b> are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter</b>].<br><b>length </b>is the number of amino acid residues comprising the α-helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the α-helix(<b>&lt;</b>); α-helix (<b>=</b>); flanking region after the α-helix (<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.
DOI: 10.6084/m9.figshare.6638945.v2
title: non-exclusive-alpha-helices-all-alpha-proteins

description: Dataset containing physical-chemical and strucutural descriptors for non-exclusive alpha helices and its flanking regions. <br>Only alpha helices from <b>all-alpha proteins</b> are eligible for this dataset.<br>Data is organized into sections. Each section begins with the following header: <b>length, pdb_name, chain_id, flag, position, [parameter</b>].<br><b>length </b>is the number of amino acid residues comprising the alpha helix.<br><b>flag </b>indicates the amino acid residue underlying region, namely: flanking region before the alpha helix (<b>&lt;</b>); alpha helix (<b>=</b>); flanking region after the alpha helix (<b>&gt;</b>).<br><b>[parameter]</b>: paramater's value for the given amino acid residue. All parameters are extracted from the STING Database.<br><b>Example:</b><b>Solvent-accessible surface area for all amino acid residues forming an alpha helix of length 5</b><br>length, pdb_name, chain_id, flag, position, Acessible_Surface_in_Isolation5,1all,A,=,1,66.1625,1all,A,=,2,81.3985,1all,A,=,3,11.9495,1all,A,=,4,22.165,1all,A,=,5,77.672
DOI: 10.6084/m9.figshare.6638891
title: Loci-specific differences in blood DNA methylation in HBV-negative populations at risk for hepatocellular carcinoma development

description: Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed. We used the Illumina HumanMethylation450 BeadChip microarray to test whether white blood cell DNA, an easily accessible source of DNA, exhibits site-specific changes in DNA methylation in blood of diagnosed HCC patients (post-diagnostic, 24 cases, 24 controls) and in prospectively collected blood specimens of HCC patients who were cancer-free at blood collection (pre-diagnostic, 21 cases, 21 controls). Out of 22 differentially methylated loci selected for validation by pyrosequencing, 19 loci with neighbouring CpG sites (probes) were confirmed in the pre-diagnostic study group and subjected to verification in a prospective cirrhotic cohort (13 cases, 23 controls). We established for the first time 9 probes that could distinguish HBV-negative cirrhotic patients who subsequently developed HCC from those who stayed cancer-free. These probes were identified within regulatory regions of <i>BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210</i>, and <i>LSP1</i>. Methylation levels within <i>DPPA5, KIAA1210</i>, and <i>LSP1</i> were higher in prospective samples from HCC cases vs. cirrhotic controls. The remaining probes were hypomethylated in cases compared with controls. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established probes have potential to be developed into a routine clinical test after validation in larger cohorts.
DOI: 10.6084/m9.figshare.6638891.v1
title: Loci-specific differences in blood DNA methylation in HBV-negative populations at risk for hepatocellular carcinoma development

description: Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed. We used the Illumina HumanMethylation450 BeadChip microarray to test whether white blood cell DNA, an easily accessible source of DNA, exhibits site-specific changes in DNA methylation in blood of diagnosed HCC patients (post-diagnostic, 24 cases, 24 controls) and in prospectively collected blood specimens of HCC patients who were cancer-free at blood collection (pre-diagnostic, 21 cases, 21 controls). Out of 22 differentially methylated loci selected for validation by pyrosequencing, 19 loci with neighbouring CpG sites (probes) were confirmed in the pre-diagnostic study group and subjected to verification in a prospective cirrhotic cohort (13 cases, 23 controls). We established for the first time 9 probes that could distinguish HBV-negative cirrhotic patients who subsequently developed HCC from those who stayed cancer-free. These probes were identified within regulatory regions of <i>BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210</i>, and <i>LSP1</i>. Methylation levels within <i>DPPA5, KIAA1210</i>, and <i>LSP1</i> were higher in prospective samples from HCC cases vs. cirrhotic controls. The remaining probes were hypomethylated in cases compared with controls. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established probes have potential to be developed into a routine clinical test after validation in larger cohorts.
DOI: 10.6084/m9.figshare.6638888
title: Inhibition of the histone demethylase KDM4B leads to activation of KDM1A, attenuates bacterial-induced pro-inflammatory cytokine release, and reduces osteoclastogenesis

description: Periodontal disease (PD) afflicts 46% of Americans with no effective adjunctive therapies available. While most pharmacotherapy for PD targets bacteria, the host immune response is responsible for driving tissue damage and bone loss in severe disease. Herein, we establish that the histone demethylase KDM4B is a potential drug target for the treatment of PD. Immunohistochemical staining of diseased periodontal epithelium revealed an increased abundance of KDM4B that correlates with inflammation. In murine calvarial sections exposed to Aggregatibacter actinomycetemcomitans lipopolysaccharide (Aa-LPS), immunohistochemical staining revealed a significant increase in KDM4B protein expression. The 8-hydroxyquinoline ML324 is known to inhibit the related demethylase KDM4E in vitro, but has not been evaluated against any other targets. Our studies indicate that ML324 also inhibits KDM4B (IC50: 4.9 μM), and decreases the pro-inflammatory cytokine response to an Aa-LPS challenge in vitro. Our results suggest that KDM4B inhibition-induced immunosuppression works indirectly, requiring new protein synthesis. In addition, fluorescence-stained macrophages exhibited a significant decrease in global monomethyl histone 3 lysine 4 (H3K4me) levels following an Aa-LPS challenge that was prevented by KDM4B inhibition, suggesting this effect is produced through KDM1A-mediated demethylation of H3K4. Finally, ML324 inhibition of KDM4B in osteoclast progenitors produced a significant reduction in Aa-LPS-induced osteoclastogenesis. These data link histone methylation with host immune response to bacterial pathogens in PD, and suggest a previously unreported, alternative mechanism for epigenetic control of the host inflammatory environment. As such, KDM4B represents a new therapeutic target for treating hyper-inflammatory diseases that result in bone destruction.
DOI: 10.6084/m9.figshare.6638888.v2
title: Inhibition of the histone demethylase KDM4B leads to activation of KDM1A, attenuates bacterial-induced pro-inflammatory cytokine release, and reduces osteoclastogenesis

description: Periodontal disease (PD) afflicts 46% of Americans with no effective adjunctive therapies available. While most pharmacotherapy for PD targets bacteria, the host immune response is responsible for driving tissue damage and bone loss in severe disease. Herein, we establish that the histone demethylase KDM4B is a potential drug target for the treatment of PD. Immunohistochemical staining of diseased periodontal epithelium revealed an increased abundance of KDM4B that correlates with inflammation. In murine calvarial sections exposed to Aggregatibacter actinomycetemcomitans lipopolysaccharide (Aa-LPS), immunohistochemical staining revealed a significant increase in KDM4B protein expression. The 8-hydroxyquinoline ML324 is known to inhibit the related demethylase KDM4E in vitro, but has not been evaluated against any other targets. Our studies indicate that ML324 also inhibits KDM4B (IC50: 4.9 μM), and decreases the pro-inflammatory cytokine response to an Aa-LPS challenge in vitro. Our results suggest that KDM4B inhibition-induced immunosuppression works indirectly, requiring new protein synthesis. In addition, fluorescence-stained macrophages exhibited a significant decrease in global monomethyl histone 3 lysine 4 (H3K4me) levels following an Aa-LPS challenge that was prevented by KDM4B inhibition, suggesting this effect is produced through KDM1A-mediated demethylation of H3K4. Finally, ML324 inhibition of KDM4B in osteoclast progenitors produced a significant reduction in Aa-LPS-induced osteoclastogenesis. These data link histone methylation with host immune response to bacterial pathogens in PD, and suggest a previously unreported, alternative mechanism for epigenetic control of the host inflammatory environment. As such, KDM4B represents a new therapeutic target for treating hyper-inflammatory diseases that result in bone destruction.
DOI: 10.6084/m9.figshare.6638888.v1
title: Inhibition of the Histone Demethylase KDM4B Leads to Activation of KDM1A, Attenuates Bacterial-Induced Pro-Inflammatory Cytokine Release, and Reduces Osteoclastogenesis

description: Periodontal disease (PD) afflicts 46% of Americans with no effective adjunctive therapies available. While most pharmacotherapy for PD targets bacteria, the host immune response is responsible for driving tissue damage and bone loss in severe disease. Herein, we establish that the histone demethylase KDM4B is a potential drug target for the treatment of PD. Immunohistochemical staining of diseased periodontal epithelium revealed an increased abundance of KDM4B that correlates with inflammation. In murine calvarial sections exposed to <i>Aggregatibacter actinomycetemcomitans</i> lipopolysaccharide <i>(Aa</i>-LPS), immunohistochemical staining revealed a significant increase in KDM4B protein expression. The 8-hydroxyquinoline ML324 is known to inhibit the related demethylase KDM4E <i>in vitro</i>, but has not been evaluated against any other targets. Our studies indicate that ML324 also inhibits KDM4B (IC<sub>50</sub>: 4.9 μM), and decreases the pro-inflammatory cytokine response to an <i>Aa</i>-LPS challenge <i>in vitro</i>. Our results suggest that KDM4B inhibition-induced immunosuppression works indirectly, requiring new protein synthesis. In addition, fluorescence-stained macrophages exhibited a significant decrease in global monomethyl histone 3 lysine 4 (H3K4me) levels following an <i>Aa</i>-LPS challenge that was prevented by KDM4B inhibition, suggesting this effect is produced through KDM1A-mediated demethylation of H3K4. Finally, ML324 inhibition of KDM4B in osteoclast progenitors produced a significant reduction in <i>Aa</i>-LPS-induced osteoclastogenesis. These data link histone methylation with host immune response to bacterial pathogens in PD, and suggest an alternative mechanism for epigenetic control of the host inflammatory environment that has not previously been reported. As such, KDM4B represents a new therapeutic target for treating hyper-inflammatory diseases that result in bone destruction.
DOI: 10.6084/m9.figshare.6637871
title: The Effectiveness of an On-Bicycle Curriculum on Children

description: <b>Objective:</b> The objective of this study was to determine whether the BikeSafe on-bicycle curriculum affects children’s bicycle safety knowledge and collect cross-sectional data on cycling beliefs and attitudes. <b>Methods:</b> The University of Miami’s BikeSafe program collected surveys from 286 participants, aged 7–15, in 10 Miami–Dade County Parks, Recreation, and Open Spaces summer camps from June to August 2015. Pre and post knowledge assessments were analyzed for 83 intervention group and 57 control group participants. Posttesting occurred immediately following program implementation and 2–4 weeks postimplementation. <b>Results:</b> Intervention group participants demonstrated significant differences (<i>P</i> n = 286) were more likely to be encouraged to ride a bicycle by parents/guardians (61.2%) than by friends (38.1%) or schools (19.6%). Older respondents reported lower intentions of helmet use compared to the younger age group, χ<sup>2</sup>(4) = 27.96, <i>P</i> <b>Conclusions:</b> Children’s bicycle safety knowledge increased following implementation of the BikeSafe on-bicycle curriculum. This study confirmed previous research on the decrease in helmet use as children get older and provided insight into how children view their parents’ beliefs and attitudes relating to cycling. The findings of this study can be used to effectively target future educational and encouragement initiatives.
DOI: 10.6084/m9.figshare.6637871.v2
title: The Effectiveness of an On-Bicycle Curriculum on Children

description: <b>Objective:</b> The objective of this study was to determine whether the BikeSafe on-bicycle curriculum affects children’s bicycle safety knowledge and collect cross-sectional data on cycling beliefs and attitudes. <b>Methods:</b> The University of Miami’s BikeSafe program collected surveys from 286 participants, aged 7–15, in 10 Miami–Dade County Parks, Recreation, and Open Spaces summer camps from June to August 2015. Pre and post knowledge assessments were analyzed for 83 intervention group and 57 control group participants. Posttesting occurred immediately following program implementation and 2–4 weeks postimplementation. <b>Results:</b> Intervention group participants demonstrated significant differences (<i>P</i> n = 286) were more likely to be encouraged to ride a bicycle by parents/guardians (61.2%) than by friends (38.1%) or schools (19.6%). Older respondents reported lower intentions of helmet use compared to the younger age group, χ<sup>2</sup>(4) = 27.96, <i>P</i> <b>Conclusions:</b> Children’s bicycle safety knowledge increased following implementation of the BikeSafe on-bicycle curriculum. This study confirmed previous research on the decrease in helmet use as children get older and provided insight into how children view their parents’ beliefs and attitudes relating to cycling. The findings of this study can be used to effectively target future educational and encouragement initiatives.