cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7037528.v1
title: New monoclonal antibodies specific for mammalian protamines P1 and P2

description: The expression of protamines and the binding of these small arginine-rich proteins to DNA complete the process of spermatid chromatin reorganization and the global inactivation of the male’s haploid genome that occurs during the final stages of sperm development in mammals. While a number of anti-protamine antibodies have been created during the last 40 years, only a few have proven useful for detecting the presence of the protamines, determining the timing of their expression and deposition in chromatin, and investigating their structure and function in both maturing spermatids and sperm. The aim of this effort was to develop an additional set of monoclonal antibodies (MAbs) that not only recognize new P1 and P2 protamine epitopes but also work well as IHC reagents for detecting and identifying mammalian protamines in testicular tissue and ejaculated sperm. Using a combination of native and synthetic human protamines as antigens, 38 hybridoma clones recognizing human protamine P1 or P2 were generated. Antibodies produced by the 12 best clones were screened for selectivity by enzyme-linked immunosorbent assay, and two were found to recognize only human protamine P1 or P2, while a number of the others bound to both the human and mouse proteins. One MAb recognized every protamine tested. All the antibodies, including one recognizing stallion P1 and another recognizing stallion P2, bound to the native protamines in the chromatin of spermatids or sperm. While the majority labeled only elongating spermatids or sperm, several of the antibodies were found to also bind to the cytoplasm or nuclei of cells that lack protamine, which indicates these MAbs must recognize epitopes present in the protamines that are also found in other proteins. Thirteen overlapping human protamine P1 peptides were synthesized and subsequently used to identify the epitopes recognized by the six best antibodies. <b>Abbreviations</b>: BSA: bovine serum albumin; ELISA: enzyme-linked immunosorbent assay; HCl: hydrochloric acid; IHC: immunohistochemistry; i.p: intraperitoneal; LIS: lithium diiodosalicylate; MAb: monoclonal antibody; PBS: phosphate buffered saline
DOI: 10.6084/m9.figshare.7037489
title: A large-scale analysis of autophagy-related gene expression identifies new regulators of autophagy

description: Autophagy is a pathway mediating vacuolar degradation and recycling of proteins and organelles, which plays crucial roles in cellular physiology. To ensure its proper cytoprotective function, the induction and amplitude of autophagy are tightly regulated, and defects in its regulation are associated with various diseases. Transcriptional control of autophagy is a critical aspect of autophagy regulation, which remains largely unexplored. In particular, very few transcription factors involved in the activation or repression of autophagy-related gene expression have been characterized. To identify such regulators, we analyzed the expression of representative <i>ATG</i> genes in a large collection of DNA-binding mutant deletion strains in growing conditions as well as after nitrogen or glucose starvation. This analysis identified several proteins involved in the transcriptional control of <i>ATG</i> genes. Further analyses showed a correlation between variations in expression and autophagy magnitude, thus identifying new positive and negative regulators of the autophagy pathway. By providing a detailed analysis of the regulatory network of the <i>ATG</i> genes our study paves the way for future research on autophagy regulation and signaling.
DOI: 10.6084/m9.figshare.7037489.v1
title: A large-scale analysis of autophagy-related gene expression identifies new regulators of autophagy

description: Autophagy is a pathway mediating vacuolar degradation and recycling of proteins and organelles, which plays crucial roles in cellular physiology. To ensure its proper cytoprotective function, the induction and amplitude of autophagy are tightly regulated, and defects in its regulation are associated with various diseases. Transcriptional control of autophagy is a critical aspect of autophagy regulation, which remains largely unexplored. In particular, very few transcription factors involved in the activation or repression of autophagy-related gene expression have been characterized. To identify such regulators, we analyzed the expression of representative <i>ATG</i> genes in a large collection of DNA-binding mutant deletion strains in growing conditions as well as after nitrogen or glucose starvation. This analysis identified several proteins involved in the transcriptional control of <i>ATG</i> genes. Further analyses showed a correlation between variations in expression and autophagy magnitude, thus identifying new positive and negative regulators of the autophagy pathway. By providing a detailed analysis of the regulatory network of the <i>ATG</i> genes our study paves the way for future research on autophagy regulation and signaling.
DOI: 10.6084/m9.figshare.7037480
title: parallel uniform density kelvin helmholtz 256

description: parallel uniform density kelvin helmholtz
DOI: 10.6084/m9.figshare.7037480.v1
title: parallel uniform density kelvin helmholtz 256

description: parallel uniform density kelvin helmholtz
DOI: 10.6084/m9.figshare.7037456
title: ANCIENT FICTIONALITY YHWH'S MORALS.docx

description: The morals' of god. A study of supernatural character.Child sacrifice, prevalent in Hebrew culture.
DOI: 10.6084/m9.figshare.7037456.v1
title: ANCIENT FICTIONALITY YHWH'S MORALS.docx

description: The morals' of god. A study of supernatural character.Child sacrifice, prevalent in Hebrew culture.
DOI: 10.6084/m9.figshare.7037411
title: A new role for PGRP-S (Tag7) in immune defense: lymphocyte migration is induced by a chemoattractant complex of Tag7 with Mts1

description: PGRP-S (Tag7) is an innate immunity protein involved in the antimicrobial defense systems, both in insects and in mammals. We have previously shown that Tag7 specifically interacts with several proteins, including Hsp70 and the calcium binding protein S100A4 (Mts1), providing a number of novel cellular functions. Here we show that Tag7–Mts1 complex causes chemotactic migration of lymphocytes, with NK cells being a preferred target. Cells of either innate immunity (neutrophils and monocytes) or acquired immunity (CD4<sup>+</sup> and CD8<sup>+</sup> lymphocytes) can produce this complex, which confirms the close connection between components of the 2 branches of immune response.
DOI: 10.6084/m9.figshare.7037411.v1
title: A new role for PGRP-S (Tag7) in immune defense: lymphocyte migration is induced by a chemoattractant complex of Tag7 with Mts1

description: PGRP-S (Tag7) is an innate immunity protein involved in the antimicrobial defense systems, both in insects and in mammals. We have previously shown that Tag7 specifically interacts with several proteins, including Hsp70 and the calcium binding protein S100A4 (Mts1), providing a number of novel cellular functions. Here we show that Tag7–Mts1 complex causes chemotactic migration of lymphocytes, with NK cells being a preferred target. Cells of either innate immunity (neutrophils and monocytes) or acquired immunity (CD4<sup>+</sup> and CD8<sup>+</sup> lymphocytes) can produce this complex, which confirms the close connection between components of the 2 branches of immune response.
DOI: 10.6084/m9.figshare.7037297
title: Mean Seasonal Cycle of Leaf Area Index Data for the HighResMIP of CMIP6

description: Value of this dataset:<i></i>The High Resolution Model Intercomparison Project (HighResMIP) is one of the major projects for the Coupled Model Intercomparison Project 6 (CMIP6) (Haarsma et al., 2016). It, for the first time, adopts a multi-model approach to systematicly investigate the impacts of model horizonal resolution on historical and future climate variabilities and changing trends. Functioning as one of the required drivers for the HighResMIP, this mean seasonal cycle of leaf area index (LAI) product will be adopted by different modeling groups to quantify the sensitivity of land-atmosphere feedbacks to the high resolution LAI datasets. Moreover, through the comprehensive evaluation of LAI-related simulaitons against multi-source observations, the CMIP6 community will better understand the sources of their model uncertainties. <br>Data Description: This mean seasonal cycle of LAI version 1 (LAI_V1_for_HighResMIP.nc) was reprocessed from the monthly AVHRR GIMMS LAI3g version 2 (1981/08 to 2015/09, Mao et al., 2013; Zhu et al., 2013). It is a gridded mean product (0.25 degree by 0.25 degree) specially designed for the abovementioned HighResMIP of CMIP6. <br>Data Collection Methods: We downloaded the raw monthly LAI3g time series from http://pan.baidu.com/s/1kUXTQp5. We then made necessary processes including the remapping to produce multi-year LAI means. More detailed information can be found in the “Data Processing Steps” below. <br><br>Data Processing Steps: All missing values (e.g., 25000) and unreasonable values higher than 7000 in the raw LAI3g data were first replaced by 0, and a scaling factor of 0.001 was adopted to obtain the actual LAI. The raw 1/12 degree by 1/12 degree LAI3g data were then regridded to 0.25 degree by 0.25 degree using the bilinear interpolation. Since the raw LAI3g data provide bi-weekly LAI, i.e., two LAI values for a certain grid every month, monthly mean LAI for the new product was calculated as the average of the two values for the remapped data. The 34-year or 35-year mean monthly LAI was then calculated for each 12-month based on the data availability. For example, the LAI climatology for January was calculated as the average of 1982 to 2015, but the LAI climatology for August was computed as the average of 1981 to 2015.<br>Data Set Coverage:<br>Temporal Coverage: Start Date: January<br>Temporal Coverage: End Date: December<br>Temporal Resolution: Monthly<br>Spatial Coverage: GlobeSpatial Resolution: 0.25 degree by 0.25 degree<br><br>Parameters: time, lat, lon and LAI<br><br>PI Contact Information: <br>Title: R&D Staff Scientist<br>First Name: Jiafu<br>Last Name: Mao <br>Organization: Oak Ridge National Laboratory<br>E-mail: maoj@ornl.gov<br>Country: USA<br>Phone: 865-576-7815<br> Technical Contact Information:First Name: BinyanLast Name: YanOrganization: the University of Texas at Austin<br>E-mail: byan@utexas.edu<br>Country: USA<br>Phone: 512-994-9968<br>
DOI: 10.6084/m9.figshare.7037288
title: Fungal connections between plants and biocrusts

description: Treatments_180914 file:<br>2x2 experimental design with mesocosms with field-collected Bouteloua gracilis and associated rhizosphere soil and biocrusts. <br><br>Fungal connection treatment: For the intact fungal connections treatment, we used mesh with 50μm pores (Small Parts, Fort Meade, FL) to inhibit fine roots but allow fungal hyphae to pass through. For the impeded treatment, we used mesh with 0.45μm pores (GE Healthcare Life Science, Pittsburg, PA) to inhibit both roots and fungi. The mesh was placed horizontally under the biocrust (~0.5 – 1cm depth) with a small hole (~5 cm diameter) in the center to allow bunchgrass shoots to pass through. <br><br><br> Precipitation regime: We applied small,<b> </b>frequent events (100mL/pot once per week, a 2.5mm event) or large,<b> </b>infrequent<b> </b>events<b> </b>(400mL/pot once per month, a 10mm event) during August through October in 2013 and May through October in 2014 and 2015. <br><br>Response variables for each pot:- CN_r_ecol_180914 file: Percentage C and N by mass for crust and leaf from elemental analyzer.<br>- EEA_ecol_180914 file: Extracellular enzyme activity (nmol h^-1 g^-1) and organic matter percentage (Loss on ignition). β-1,4-glucosidase (BG), β-1,4- <i>N </i>-acetylglucosaminidase (NAG), and leucine aminopeptidase (LAP)<br>-PChSc_r_ecol_180914 file: Chlorophyll content for biocrust samples ("CHAugperg") and plant root crown dimensions ("shoot_largest_diameter_cm" and "shoot_perpendicular_diameter_cm") for each sampling period 2013-2015.<br>root_ecol_180914 file: Roots in 1.9cm diameter x 5cm deep soil core (g_root_intop5cm), in 19.cm diameter x .5cm deep crust sample, colonization of septate and aseptate hyphae in roots, and ergosterol content (ug g^-1) in bulk soil and crust.<br><br> seeds_ecol_180914 file: total mass of seed heads (g) at end of growing season (Oct) of 2014 and 2015. <br><br><br><br> 15N tracer experiment: To investigate N transfer from biocrust to plants, we added a total of 800μL of 0.86M <sup>15</sup>N-NaNO<sub>3</sub> (8 mg N) to two points of biocrust on opposite sides of the plant (~6cm from root crown) during October 2015. <br><br>mass_balance_180914 file: sample type (crust, root, or leaf), time (h) since 15N tracer added (0=before label added), whether the pot had tracer added ("labeled15N"), the delta 15N value, the average mass percentage N, and the destructive harvest shoot and root values.<br><br>
DOI: 10.6084/m9.figshare.7037288.v1
title: Fungal connections between plants and biocrusts

description: Treatments_180914 file:<br>2x2 experimental design with mesocosms with field-collected Bouteloua gracilis and associated rhizosphere soil and biocrusts. <br><br>Fungal connection treatment: For the intact fungal connections treatment, we used mesh with 50μm pores (Small Parts, Fort Meade, FL) to inhibit fine roots but allow fungal hyphae to pass through. For the impeded treatment, we used mesh with 0.45μm pores (GE Healthcare Life Science, Pittsburg, PA) to inhibit both roots and fungi. The mesh was placed horizontally under the biocrust (~0.5 – 1cm depth) with a small hole (~5 cm diameter) in the center to allow bunchgrass shoots to pass through. <br><br><br> Precipitation regime: We applied small,<b> </b>frequent events (100mL/pot once per week, a 2.5mm event) or large,<b> </b>infrequent<b> </b>events<b> </b>(400mL/pot once per month, a 10mm event) during August through October in 2013 and May through October in 2014 and 2015. <br><br>Response variables for each pot:- CN_r_ecol_180914 file: Percentage C and N by mass for crust and leaf from elemental analyzer.<br>- EEA_ecol_180914 file: Extracellular enzyme activity (nmol h^-1 g^-1) and organic matter percentage (Loss on ignition). β-1,4-glucosidase (BG), β-1,4- <i>N </i>-acetylglucosaminidase (NAG), and leucine aminopeptidase (LAP)<br>-PChSc_r_ecol_180914 file: Chlorophyll content for biocrust samples ("CHAugperg") and plant root crown dimensions ("shoot_largest_diameter_cm" and "shoot_perpendicular_diameter_cm") for each sampling period 2013-2015.<br>root_ecol_180914 file: Roots in 1.9cm diameter x 5cm deep soil core (g_root_intop5cm), in 19.cm diameter x .5cm deep crust sample, colonization of septate and aseptate hyphae in roots, and ergosterol content (ug g^-1) in bulk soil and crust.<br><br> seeds_ecol_180914 file: total mass of seed heads (g) at end of growing season (Oct) of 2014 and 2015. <br><br><br><br> 15N tracer experiment: To investigate N transfer from biocrust to plants, we added a total of 800μL of 0.86M <sup>15</sup>N-NaNO<sub>3</sub> (8 mg N) to two points of biocrust on opposite sides of the plant (~6cm from root crown) during October 2015. <br><br>mass_balance_180914 file: sample type (crust, root, or leaf), time (h) since 15N tracer added (0=before label added), whether the pot had tracer added ("labeled15N"), the delta 15N value, the average mass percentage N, and the destructive harvest shoot and root values.<br><br>
DOI: 10.6084/m9.figshare.7037297.v2
title: Mean Seasonal Cycle of Leaf Area Index Data for the HighResMIP of CMIP6

description: Value of this dataset:<i></i>The High Resolution Model Intercomparison Project (HighResMIP) is one of the major projects for the Coupled Model Intercomparison Project 6 (CMIP6) (Haarsma et al., 2016). It, for the first time, adopts a multi-model approach to systematicly investigate the impacts of model horizonal resolution on historical and future climate variabilities and changing trends. Functioning as one of the required drivers for the HighResMIP, this mean seasonal cycle of leaf area index (LAI) product will be adopted by different modeling groups to quantify the sensitivity of land-atmosphere feedbacks to the high resolution LAI datasets. Moreover, through the comprehensive evaluation of LAI-related simulaitons against multi-source observations, the CMIP6 community will better understand the sources of their model uncertainties. <br>Data Description: This mean seasonal cycle of LAI version 1 (LAI_V1_for_HighResMIP.nc) was reprocessed from the monthly AVHRR GIMMS LAI3g version 2 (1981/08 to 2015/09, Mao et al., 2013; Zhu et al., 2013). It is a gridded mean product (0.25 degree by 0.25 degree) specially designed for the abovementioned HighResMIP of CMIP6. <br>Data Collection Methods: We downloaded the raw monthly LAI3g time series from http://pan.baidu.com/s/1kUXTQp5. We then made necessary processes including the remapping to produce multi-year LAI means. More detailed information can be found in the “Data Processing Steps” below. <br><br>Data Processing Steps: All missing values (e.g., 25000) and unreasonable values higher than 7000 in the raw LAI3g data were first replaced by 0, and a scaling factor of 0.001 was adopted to obtain the actual LAI. The raw 1/12 degree by 1/12 degree LAI3g data were then regridded to 0.25 degree by 0.25 degree using the bilinear interpolation. Since the raw LAI3g data provide bi-weekly LAI, i.e., two LAI values for a certain grid every month, monthly mean LAI for the new product was calculated as the average of the two values for the remapped data. The 34-year or 35-year mean monthly LAI was then calculated for each 12-month based on the data availability. For example, the LAI climatology for January was calculated as the average of 1982 to 2015, but the LAI climatology for August was computed as the average of 1981 to 2015.<br>Data Set Coverage:<br>Temporal Coverage: Start Date: January<br>Temporal Coverage: End Date: December<br>Temporal Resolution: Monthly<br>Spatial Coverage: GlobeSpatial Resolution: 0.25 degree by 0.25 degree<br><br>Parameters: time, lat, lon and LAI<br><br>PI Contact Information: <br>Title: R&D Staff Scientist<br>First Name: Jiafu<br>Last Name: Mao <br>Organization: Oak Ridge National Laboratory<br>E-mail: maoj@ornl.gov<br>Country: USA<br>Phone: 865-576-7815<br> Technical Contact Information:First Name: BinyanLast Name: YanOrganization: the University of Texas at Austin<br>E-mail: byan@utexas.edu<br>Country: USA<br>Phone: 512-994-9968<br>
DOI: 10.6084/m9.figshare.7037228
title: Figure_4_Sulfite_Reductase_Phylogeny

description: Figure 4 of manuscript "Comparative genomics and proteomic analysis of assimilatory sulfate reduction pathways in anaerobic methanotrophic archaea"<br>Files included:Fig4_sulfite_reductase_clustalo_alignment.faa - ClustalO alignment of protein sequencesFig4_sulfite_reductase_clustalo_alignment_filtered_for_tree.faa - Filtered protein sequences (224 amino acids) used for phylogeneticsFig2_cysN_ef_clustalo_tree.png - Bayesian phylogeny of sulfite reductases with collapsed groups<br>Figure 4. Bayesian phylogeny of sulfite reductases. Two well-supported groups of Fsr were identified in exclusion of alSir and other sulfite reductases. ANME proteins are bolded and in red. The phylogenetic tree was constructed based on 224 amino acid residues of the shared catalytic and siroheme-binding region. Asterisks (*) indicate proteins that have been studied biochemically (Huynh et al., 1984; Johnson and Mukhopadhyay, 2005; Moura et al., 1986). Protein accession numbers from the NCBI database or gene IDs from the IMG database are shown in parentheses. Black dots on the branches represent Bayesian posterior probability values greater than 90%, and scale bar indicates the number of amino acid substitutions per site. The fully expanded tree can be found be found in Supplementary Figure 1.<br><br>
DOI: 10.6084/m9.figshare.7037297.v1
title: Mean Seasonal Cycle of Leaf Area Index

description: Value of this dataset:<i></i>The High Resolution Model Intercomparison Project (HighResMIP) is one of the major projects for the Coupled Model Intercomparison Project 6 (CMIP6) (Haarsma et al., 2016). It, for the first time, adopts a multi-model approach to systematicly investigate the impacts of model horizonal resolution on historical and future climate variabilities and changing trends. Functioning as one of the required drivers for the HighResMIP, this mean seasonal cycle of leaf area index (LAI) product will be adopted by different modeling groups to quantify the sensitivity of land-atmosphere feedbacks to the high resolution LAI datasets. Moreover, through the comprehensive evaluation of LAI-related simulaitons against multi-source observations, the CMIP6 community will better understand the sources of their model uncertainties. <br>Data Description: This mean seasonal cycle of LAI version 1 (LAI_V1_for_HighResMIP.nc) was reprocessed from the monthly AVHRR GIMMS LAI3g version 2 (1981/08 to 2015/09, Mao et al., 2013; Zhu et al., 2013). It is a gridded mean product (0.25 degree by 0.25 degree) specially designed for the abovementioned HighResMIP of CMIP6. <br>Data Collection Methods: We downloaded the raw monthly LAI3g time series from http://pan.baidu.com/s/1kUXTQp5. We then made necessary processes including the remapping to produce multi-year LAI means. More detailed information can be found in the “Data Processing Steps” below. <br><br>Data Processing Steps: All missing values (e.g., 25000) and unreasonable values higher than 7000 in the raw LAI3g data were first replaced by 0, and a scaling factor of 0.001 was adopted to obtain the actual LAI. The raw 1/12 degree by 1/12 degree LAI3g data were then regridded to 0.25 degree by 0.25 degree using the bilinear interpolation. Since the raw LAI3g data provide bi-weekly LAI, i.e., two LAI values for a certain grid every month, monthly mean LAI for the new product was calculated as the average of the two values for the remapped data. The 34-year or 35-year mean monthly LAI was then calculated for each 12-month based on the data availability. For example, the LAI climatology for January was calculated as the average of 1982 to 2015, but the LAI climatology for August was computed as the average of 1981 to 2015.<br>