cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6075737
title: Experimental Setup for Co-Cultivation of Model Cyanobacteria with Rice Roots

description: <b>Co-Inoculation of Rice roots with cyanobacteria</b><b><br></b>Glass cultivation tubes (Photosystem Instruments, PSI) containing 100 mL BG11 liquid medium were inoculated with <i>Synechocystis</i> sp. PCC 6803 (PCC-M) to an optical density (OD<sub>750</sub>) of 0.15. Roots of young rice seedlings (variety Kitaake; ~ 1 week after germination) were pulled through the outflow holes of the silicone plugs (PSI) and submerged into the BG11 medium.Co-cultivation took place at ~30 °C, either in a rooftop greenhouse (HHU Düsseldorf, Germany), or in a growth chamber (Versatile environmental test chamber, Sanyo).Note that growth of rice plants is compromised in the latter without humidifier. Leafs were manually humidified with an aerosol. However, cultivation in non-humid environments is not recommended. The co-cultures were supplemented with a continuous stream of air using simple aquarium air pumps. The mass flow was not precisely controlled in these experiment. However, the usage of mass flow control (MFC) devices is recommended. In the growth chamber, co-cultures were constantly illuminated (&gt; 100 µmol m<sup>-2</sup> s<sup>-1</sup>), while greenhouse cultures were subjected to natural day-night cycles (Nov-Jan, Germany, daylight int.: (&gt; 100 µmol m<sup>-2</sup> s<sup>-1</sup>). While the rice seedlings thrived in BG11 medium (buffered to pH 8.0, see link to protocols.io), the tested <i>Synechocystis</i> strains did not proliferate in more acidic medium for rice growth (buffered to pH &lt; 6.0). <br><br><br><br><br><br><br>
DOI: 10.6084/m9.figshare.6075737.v1
title: Experimental Setup for Co-Cultivation of Model Cyanobacteria with Rice Roots

description: <b>Co-Inoculation of Rice roots with cyanobacteria</b><b><br></b>Glass cultivation tubes (Photosystem Instruments, PSI) containing 100 mL BG11 liquid medium were inoculated with <i>Synechocystis</i> sp. PCC 6803 (PCC-M) to an optical density (OD<sub>750</sub>) of 0.15. Roots of young rice seedlings (variety Kitaake; ~ 1 week after germination) were pulled through the outflow holes of the silicone plugs (PSI) and submerged into the BG11 medium.Co-cultivation took place at ~30 °C, either in a rooftop greenhouse (HHU Düsseldorf, Germany), or in a growth chamber (Versatile environmental test chamber, Sanyo).Note that growth of rice plants is compromised in the latter without humidifier. Leafs were manually humidified with an aerosol. However, cultivation in non-humid environments is not recommended. The co-cultures were supplemented with a continuous stream of air using simple aquarium air pumps. The mass flow was not precisely controlled in these experiment. However, the usage of mass flow control (MFC) devices is recommended. In the growth chamber, co-cultures were constantly illuminated (&gt; 100 µmol m<sup>-2</sup> s<sup>-1</sup>), while greenhouse cultures were subjected to natural day-night cycles (Nov-Jan, Germany, daylight int.: (&gt; 100 µmol m<sup>-2</sup> s<sup>-1</sup>). While the rice seedlings thrived in BG11 medium (buffered to pH 8.0, see link to protocols.io), the tested <i>Synechocystis</i> strains did not proliferate in more acidic medium for rice growth (buffered to pH &lt; 6.0). <br><br><br><br><br><br><br>
DOI: 10.6084/m9.figshare.6075614
title: Muscles provide an internal water reserve for reproduction

description: Publicly available data for Title: Muscles provide an internal water reserve for reproduction Authors: George A Brusch IV*<sup>1</sup>, Olivier Lourdais<sup>2</sup>, Brittany Kaminsky<sup>1</sup>, Dale F DeNardo<sup>1</sup> *Corresponding author [bruschg@gmail.com] 1 - School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA 2 - Centre d’Etudes Biologiques de Chizé, CNRS, 79360 Villiers en Bois, FR Running title: Muscle as a water reserve Keywords: Reproductive costs. Capital breeder. Water constraints. Protein catabolism. Bound water. Manuscript type: Research article<br>
DOI: 10.6084/m9.figshare.6075614.v1
title: Muscles provide an internal water reserve for reproduction

description: Publicly available data for Title: Muscles provide an internal water reserve for reproduction Authors: George A Brusch IV*<sup>1</sup>, Olivier Lourdais<sup>2</sup>, Brittany Kaminsky<sup>1</sup>, Dale F DeNardo<sup>1</sup> *Corresponding author [bruschg@gmail.com] 1 - School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA 2 - Centre d’Etudes Biologiques de Chizé, CNRS, 79360 Villiers en Bois, FR Running title: Muscle as a water reserve Keywords: Reproductive costs. Capital breeder. Water constraints. Protein catabolism. Bound water. Manuscript type: Research article<br>
DOI: 10.6084/m9.figshare.6075608.v1
title: 15scene.rar

description: Dataset Source: http://www-cvr.ai.uiuc.edu/ponce_grp/data/
DOI: 10.6084/m9.figshare.6074129
title: Enriched_protein_clusters

description: This file contains the protein clusters identified as enriched in either epipelagic or mesopelagic Marinimicrobia. <br>
DOI: 10.6084/m9.figshare.6074129.v1
title: enriched_clusters_epi_vs_deep.tsv

description: This file contains the protein clusters identified as enriched in either epipelagic or mesopelagic Marinimicrobia. <br>
DOI: 10.6084/m9.figshare.6073991
title: Perturbation allowed transitions in the infrared spectrum of <sup>14</sup>ND<sub>3</sub>: determination of the <i>K</i>-dependent parameters in the ground state

description: Accurate values of the <i>K</i>-dependent constants <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>C</i>, <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>D<sub>K</sub> </i> and <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>H<sub>K</sub> </i> in the ground state of <sup>14</sup>ND<sub>3</sub>, with <i>i</i> = <i>s</i>, <i>a</i>, have been determined for the first time thanks to the detections of ‘perturbation allowed’ transitions in the ν<sub>1</sub>, ν<sub>2</sub>, ν<sub>3</sub>, ν<sub>4</sub> and 2ν<sub>4</sub> infrared bands. The rotation–inversion and inversion transitions from the literature, together with 7289 ground state combination differences from the infrared vibration–rotation–inversion transitions have been simultaneously analysed. The adopted rotation–inversion Hamiltonian includes distortion constants up to the eighth power and the Δ<i>k</i> = ±3 and Δ<i>k</i> = ±6 interaction terms. Precise values of the diagonal constants and of the Δ<i>k</i> = ±3 interaction coefficients have been obtained. Accurate values of the ground state term values have been calculated for both <i>s</i> and <i>a</i> levels up to <i>J</i> = 21.
DOI: 10.6084/m9.figshare.6073991.v1
title: Perturbation allowed transitions in the infrared spectrum of <sup>14</sup>ND<sub>3</sub>: determination of the <i>K</i>-dependent parameters in the ground state

description: Accurate values of the <i>K</i>-dependent constants <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>C</i>, <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>D<sub>K</sub> </i> and <sup>(</sup> <i><sup>i</sup></i> <sup>)</sup> <i>H<sub>K</sub> </i> in the ground state of <sup>14</sup>ND<sub>3</sub>, with <i>i</i> = <i>s</i>, <i>a</i>, have been determined for the first time thanks to the detections of ‘perturbation allowed’ transitions in the ν<sub>1</sub>, ν<sub>2</sub>, ν<sub>3</sub>, ν<sub>4</sub> and 2ν<sub>4</sub> infrared bands. The rotation–inversion and inversion transitions from the literature, together with 7289 ground state combination differences from the infrared vibration–rotation–inversion transitions have been simultaneously analysed. The adopted rotation–inversion Hamiltonian includes distortion constants up to the eighth power and the Δ<i>k</i> = ±3 and Δ<i>k</i> = ±6 interaction terms. Precise values of the diagonal constants and of the Δ<i>k</i> = ±3 interaction coefficients have been obtained. Accurate values of the ground state term values have been calculated for both <i>s</i> and <i>a</i> levels up to <i>J</i> = 21.
DOI: 10.6084/m9.figshare.6073961
title: An epigenomic approach to identifying differential overlapping and <i>cis</i>-acting lncRNAs in cisplatin-resistant cancer cells

description: Long noncoding RNAs (lncRNAs) are critical regulators of cell biology whose alteration can lead to the development of diseases such as cancer. The potential role of lncRNAs and their epigenetic regulation in response to platinum treatment are largely unknown. We analyzed four paired cisplatin-sensitive/resistant non-small cell lung cancer and ovarian cancer cell lines. The epigenetic landscape of overlapping and <i>cis</i>-acting lncRNAs was determined by combining human microarray data on 30,586 lncRNAs and 20,109 protein coding mRNAs with whole-genome bisulfite sequencing. Selected candidate lncRNAs were further characterized by PCR, gene-ontology analysis, and targeted bisulfite sequencing. Differential expression in response to therapy was observed more frequently in <i>cis</i>-acting than in overlapping lncRNAs (78% vs. 22%, fold change ≥1.5), while significantly altered methylation profiles were more commonly associated with overlapping lncRNAs (29% vs. 8%; <i>P</i> value &lt;0.001). Moreover, overlapping lncRNAs contain more CpG islands (CGIs) (25% vs. 17%) and the majority of CGI-containing overlapping lncRNAs share these CGIs with their associated coding genes (84%). The differences in expression between sensitive and resistant cell lines were replicated in 87% of the selected candidates (<i>P</i>&lt;0.05), while our bioinformatics approach identifying differential methylation was confirmed in all of the selected lncRNAs (100%). Five lncRNAs under epigenetic regulation appear to be involved in cisplatin resistance (AC091814.2, AC141928.1, RP11-65J3.1-002, BX641110, and AF198444). These novel findings provide new insights into epigenetic mechanisms and acquired resistance to cisplatin that highlight specific lncRNAs, some with unknown function, that may signal strategies in epigenetic therapies.
DOI: 10.6084/m9.figshare.6073961.v2
title: An epigenomic approach to identifying differential overlapping and <i>cis</i>-acting lncRNAs in cisplatin-resistant cancer cells

description: Long noncoding RNAs (lncRNAs) are critical regulators of cell biology whose alteration can lead to the development of diseases such as cancer. The potential role of lncRNAs and their epigenetic regulation in response to platinum treatment are largely unknown. We analyzed four paired cisplatin-sensitive/resistant non-small cell lung cancer and ovarian cancer cell lines. The epigenetic landscape of overlapping and <i>cis</i>-acting lncRNAs was determined by combining human microarray data on 30,586 lncRNAs and 20,109 protein coding mRNAs with whole-genome bisulfite sequencing. Selected candidate lncRNAs were further characterized by PCR, gene-ontology analysis, and targeted bisulfite sequencing. Differential expression in response to therapy was observed more frequently in <i>cis</i>-acting than in overlapping lncRNAs (78% vs. 22%, fold change ≥1.5), while significantly altered methylation profiles were more commonly associated with overlapping lncRNAs (29% vs. 8%; <i>P</i> value &lt;0.001). Moreover, overlapping lncRNAs contain more CpG islands (CGIs) (25% vs. 17%) and the majority of CGI-containing overlapping lncRNAs share these CGIs with their associated coding genes (84%). The differences in expression between sensitive and resistant cell lines were replicated in 87% of the selected candidates (<i>P</i>&lt;0.05), while our bioinformatics approach identifying differential methylation was confirmed in all of the selected lncRNAs (100%). Five lncRNAs under epigenetic regulation appear to be involved in cisplatin resistance (AC091814.2, AC141928.1, RP11-65J3.1-002, BX641110, and AF198444). These novel findings provide new insights into epigenetic mechanisms and acquired resistance to cisplatin that highlight specific lncRNAs, some with unknown function, that may signal strategies in epigenetic therapies.
DOI: 10.6084/m9.figshare.6073961.v1
title: An epigenomic approach to identifying differential overlapping and <i>cis</i>-acting lncRNAs in cisplatin-resistant cancer cells

description: Long noncoding RNAs (lncRNAs) are critical regulators of cell biology whose alteration can lead to the development of diseases such as cancer. The potential role of lncRNAs and their epigenetic regulation in response to platinum treatment are largely unknown. We analyzed four paired cisplatin-sensitive/resistant non-small cell lung cancer and ovarian cancer cell lines. The epigenetic landscape of overlapping and <i>cis</i>-acting lncRNAs was determined by combining human microarray data on 30,586 lncRNAs and 20,109 protein coding mRNAs with whole-genome bisulfite sequencing. Selected candidate lncRNAs were further characterized by PCR, gene-ontology analysis, and targeted bisulfite sequencing. Differential expression in response to therapy was observed more frequently in <i>cis</i>-acting than in overlapping lncRNAs (78% vs. 22%, fold change ≥1.5), while significantly altered methylation profiles were more commonly associated with overlapping lncRNAs (29% vs. 8%; <i>P</i> value &lt;0.001). Moreover, overlapping lncRNAs contain more CpG islands (CGIs) (25% vs. 17%) and the majority of CGI-containing overlapping lncRNAs share these CGIs with their associated coding genes (84%). The differences in expression between sensitive and resistant cell lines were replicated in 87% of the selected candidates (<i>P</i>&lt;0.05), while our bioinformatics approach identifying differential methylation was confirmed in all of the selected lncRNAs (100%). Five lncRNAs under epigenetic regulation appear to be involved in cisplatin resistance (AC091814.2, AC141928.1, RP11-65J3.1-002, BX641110, and AF198444). These novel findings provide new insights into epigenetic mechanisms and acquired resistance to cisplatin that highlight specific lncRNAs, some with unknown function, that may signal strategies in epigenetic therapies.
DOI: 10.6084/m9.figshare.6073955
title: Breast cancer family history and allele-specific DNA methylation in the legacy girls study

description: Family history, a well-established risk factor for breast cancer, can have both genetic and environmental contributions. Shared environment in families as well as epigenetic changes that also may be influenced by shared genetics and environment may also explain familial clustering of cancers. Epigenetic regulation, such as DNA methylation, can change the activity of a DNA segment without a change in the sequence; environmental exposures experienced across the life course can induce such changes. However, genetic-epigenetic interactions, detected as methylation quantitative trait loci (mQTLs; a.k.a. meQTLs) and haplotype-dependent allele-specific methylation (hap-ASM), can also contribute to inter-individual differences in DNA methylation patterns. To identify differentially methylated regions (DMRs) associated with breast cancer susceptibility, we examined differences in white blood cell DNA methylation in 29 candidate genes in 426 girls (ages 6–13 years) from the LEGACY Girls Study, 239 with and 187 without a breast cancer family history (BCFH). We measured methylation by targeted massively parallel bisulfite sequencing (bis-seq) and observed BCFH DMRs in two genes: <i>ESR1</i> (Δ4.9%, <i>P</i> = 0.003) and <i>SEC16B</i> (Δ3.6%, <i>P</i> = 0.026), each of which has been previously implicated in breast cancer susceptibility and pubertal development. These DMRs showed high inter-individual variability in methylation, suggesting the presence of mQTLs/hap-ASM. Using single nucleotide polymorphisms data in the bis-seq amplicon, we found strong hap-ASM in <i>SEC16B</i> <b>(</b>with allele specific-differences ranging from 42% to 74%). These findings suggest that differential methylation in genes relevant to breast cancer susceptibility may be present early in life, and that inherited genetic factors underlie some of these epigenetic differences.
DOI: 10.6084/m9.figshare.6073955.v2
title: Breast cancer family history and allele-specific DNA methylation in the legacy girls study

description: Family history, a well-established risk factor for breast cancer, can have both genetic and environmental contributions. Shared environment in families as well as epigenetic changes that also may be influenced by shared genetics and environment may also explain familial clustering of cancers. Epigenetic regulation, such as DNA methylation, can change the activity of a DNA segment without a change in the sequence; environmental exposures experienced across the life course can induce such changes. However, genetic-epigenetic interactions, detected as methylation quantitative trait loci (mQTLs; a.k.a. meQTLs) and haplotype-dependent allele-specific methylation (hap-ASM), can also contribute to inter-individual differences in DNA methylation patterns. To identify differentially methylated regions (DMRs) associated with breast cancer susceptibility, we examined differences in white blood cell DNA methylation in 29 candidate genes in 426 girls (ages 6–13 years) from the LEGACY Girls Study, 239 with and 187 without a breast cancer family history (BCFH). We measured methylation by targeted massively parallel bisulfite sequencing (bis-seq) and observed BCFH DMRs in two genes: <i>ESR1</i> (Δ4.9%, <i>P</i> = 0.003) and <i>SEC16B</i> (Δ3.6%, <i>P</i> = 0.026), each of which has been previously implicated in breast cancer susceptibility and pubertal development. These DMRs showed high inter-individual variability in methylation, suggesting the presence of mQTLs/hap-ASM. Using single nucleotide polymorphisms data in the bis-seq amplicon, we found strong hap-ASM in <i>SEC16B</i> <b>(</b>with allele specific-differences ranging from 42% to 74%). These findings suggest that differential methylation in genes relevant to breast cancer susceptibility may be present early in life, and that inherited genetic factors underlie some of these epigenetic differences.
DOI: 10.6084/m9.figshare.6073955.v1
title: Breast cancer family history and allele-specific DNA methylation in the legacy girls study

description: Family history, a well-established risk factor for breast cancer, can have both genetic and environmental contributions. Shared environment in families as well as epigenetic changes that also may be influenced by shared genetics and environment may also explain familial clustering of cancers. Epigenetic regulation, such as DNA methylation, can change the activity of a DNA segment without a change in the sequence; environmental exposures experienced across the life course can induce such changes. However, genetic-epigenetic interactions, detected as methylation quantitative trait loci (mQTLs; a.k.a. meQTLs) and haplotype-dependent allele-specific methylation (hap-ASM), can also contribute to inter-individual differences in DNA methylation patterns. To identify differentially methylated regions (DMRs) associated with breast cancer susceptibility, we examined differences in white blood cell DNA methylation in 29 candidate genes in 426 girls (ages 6–13 years) from the LEGACY Girls Study, 239 with and 187 without a breast cancer family history (BCFH). We measured methylation by targeted massively parallel bisulfite sequencing (bis-seq) and observed BCFH DMRs in two genes: <i>ESR1</i> (Δ4.9%, <i>P</i> = 0.003) and <i>SEC16B</i> (Δ3.6%, <i>P</i> = 0.026), each of which has been previously implicated in breast cancer susceptibility and pubertal development. These DMRs showed high inter-individual variability in methylation, suggesting the presence of mQTLs/hap-ASM. Using single nucleotide polymorphisms data in the bis-seq amplicon, we found strong hap-ASM in <i>SEC16B</i> <b>(</b>with allele specific-differences ranging from 42% to 74%). These findings suggest that differential methylation in genes relevant to breast cancer susceptibility may be present early in life, and that inherited genetic factors underlie some of these epigenetic differences.
DOI: 10.6084/m9.figshare.6073910
title: Souce Code

description: Source Code
DOI: 10.6084/m9.figshare.6073886
title: Infant Bayley Scores and Full Day Arm Movement Data

description: Please see "Relationships between full-day arm movement characteristics and developmental status in infants with typical development as they learn to reach: An observational study" in Gates Open Research. Authors are Joanne Shida-Tokeshi, Christianne J. Lane, Ivan A. Trujillo-Priego, Weiyang Deng, Douglas L. Vanderbilt, Gerald E. Loeb, and Beth A. Smith. Beth A. Smith is the corresponding author.
DOI: 10.6084/m9.figshare.6073838
title: Jerash Aerial Photos

description: Orthophotos of Jerash and it's environs purchased by the Danish-German Jerash Northwest Quarter Project from the Royal Geographic Center of the Hashemite Kingdom of Jordan<br>Used in the following article:<br>Stott, D., Kristiansen, S.M., Lichtenberger, A. and Raja, R., 2018. Mapping an ancient city with a century of remotely sensed data. <i>Proceedings of the National Academy of Sciences</i>, <i>115</i>(24), pp.E5450-E5458.<br><br>https://www.pnas.org/content/115/24/E5450<br>
DOI: 10.6084/m9.figshare.6073838.v1
title: Jerash Aerial Photos

description: Orthophotos of Jerash and it's environs purchased by Aarhus University from the Royal Geographic Cernter of the Hashemite Kingdom of Jordan
DOI: 10.6084/m9.figshare.6073799
title: G3/2018/200287R1

description: Figure S1 shows the length and quality distributions of PacBio reads. Figure S2 shows the BUSCO analysis of the completeness of the assembly results. Figure S3 shows the distribution of gene length predicted in the <i>C. guangdongensis</i> genome. Table S1 shows the genome sequences used to analyze the chromosome. Table S2 shows the genome annotation of proteins in <i>C. guangdongensis</i> genome. Table S3 shows the transposable elements classification in <i>C. guangdongensis</i>.
DOI: 10.6084/m9.figshare.6073799.v1
title: G3/2018/200287R1

description: Figure S1 shows the length and quality distributions of PacBio reads. Figure S2 shows the BUSCO analysis of the completeness of the assembly results. Figure S3 shows the distribution of gene length predicted in the <i>C. guangdongensis</i> genome. Table S1 shows the genome sequences used to analyze the chromosome. Table S2 shows the genome annotation of proteins in <i>C. guangdongensis</i> genome. Table S3 shows the transposable elements classification in <i>C. guangdongensis</i>.
DOI: 10.6084/m9.figshare.6073778.v1
title: fig.1.2.3.data.zip

description: Google Trends, the prioritized diseases
DOI: 10.6084/m9.figshare.6073664
title: SharingEconomy_rawdata.ods

description: List of peer-reviewed articles on sharing paradigm and categorization of sharing types<br>
DOI: 10.6084/m9.figshare.6073664.v1
title: SharingEconomy_rawdata.ods

description: List of peer-reviewed articles on sharing paradigm and categorization of sharing types<br>
DOI: 10.6084/m9.figshare.6073598
title: Flowers with poricidal anthers and their complex interaction networks—Disentangling legitimate pollinators and illegitimate visitors

description: Interaction network database between plants with poricidal anthers and their visitors/pollinators in the “Parque Estadual do Rio Preto” nature reserve in the municipality of São Gonçalo do Rio Preto, Minas Gerais State, Brazil (18°05'28.3"S, 43°20'29.2"W), from September to December 2014 and 2015.<br>
DOI: 10.6084/m9.figshare.6073598.v1
title: Plants with poricidal anthers and their pollinators – an assembly characterized by modular interactions

description: Interaction network database between plants with poricidal anthers and their visitors/pollinators in the “Parque Estadual do Rio Preto” nature reserve in the municipality of São Gonçalo do Rio Preto, Minas Gerais State, Brazil (18°05'28.3"S, 43°20'29.2"W), from September to December 2014 and 2015.<br>