cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25442/hku.23667204.v1
title: Supporting Data for "The Mediating Roles of Emotional Reactivity and Regulation in the Relationship Between Insomnia, Depression, and Anxiety"

description: This dataset contain data from the student's thesis titled "The Mediating Roles of Emotional Reactivity and Regulation in the Relationship Between Insomnia, Depression, and Anxiety". It consists of two sub-datasets: the first one is a daily study of two weeks with 60 participants. The second one is a longitudinal study of 924 participants and the data was collected over three months, once per month. Both datasets contained the data of the sleep and mood disturbances, and emotional reactivity and regulation of the participants. <br>
DOI: 10.57841/casdc.0001781
title: 1种双配副摩擦试验机及其在多孔聚酰亚胺摩擦磨损测试方面的应用
DOI: 10.25442/hku.23674659
title: <em>Supporting data for </em> “Gut Microbiome Regulates Immunotherapy Response through Systemic Immune Environment in Patients with Hepatocellular Carcinoma”

description: This dataset was originated from the thesis entitled "Gut Microbiome Regulates Immunotherapy Response through Systemic Immune Environment in Patients with Hepatocellular Carcinoma", including metagenomic sequencing and flow cytometry data. Immune checkpoint inhibitors (ICIs) have emerged as the pillars of anticancer treatment for hepatocellular carcinoma (HCC). Nevertheless, only few patients could benefit from ICIs. Most efforts have been directed toward identifying biomarkers of ICIs response more than 6 months, while biomarkers to predict long-term benefits are scarce. Gut microbiota is related with the incidence, progression of several cancer types. There is also a crosstalk between gut microbiota and immune systems, which has the potential of predicting immunotherapy response. In this study, we performed an integrative analysis of gut commensal bacteria and systemic immune, to assess their prospective role on outcomes of HCC patients treated with immunotherapy and establish their causal links. <br>
DOI: 10.25442/hku.23674659.v1
title: <em>Supporting data for </em> “Gut Microbiome Regulates Immunotherapy Response through Systemic Immune Environment in Patients with Hepatocellular Carcinoma”

description: This dataset was originated from the thesis entitled "Gut Microbiome Regulates Immunotherapy Response through Systemic Immune Environment in Patients with Hepatocellular Carcinoma", including metagenomic sequencing and flow cytometry data. Immune checkpoint inhibitors (ICIs) have emerged as the pillars of anticancer treatment for hepatocellular carcinoma (HCC). Nevertheless, only few patients could benefit from ICIs. Most efforts have been directed toward identifying biomarkers of ICIs response more than 6 months, while biomarkers to predict long-term benefits are scarce. Gut microbiota is related with the incidence, progression of several cancer types. There is also a crosstalk between gut microbiota and immune systems, which has the potential of predicting immunotherapy response. In this study, we performed an integrative analysis of gut commensal bacteria and systemic immune, to assess their prospective role on outcomes of HCC patients treated with immunotherapy and establish their causal links. <br>
DOI: 10.5281/zenodo.7123623
title: Genomic insight into domestication of rubber tree

description: we upgraded H. brasiliensis genome assembly (contig N50 of 11.21 megabases), presented a map of genome variations by resequencing 335 accessions and revealed domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), was a key domestication gene. It was closely associated with the major domestication trait by positively controlling laticifer differentiation from vascular cambia. The transcriptional activation of HbPSK5 by MYC members linked JA signaling to PSK signaling in enhancing laticifer formation
DOI: 10.5281/zenodo.7672530
title: Genomic insight into domestication of rubber tree

description: we upgraded H. brasiliensis genome assembly (contig N50 of 11.21 megabases), presented a map of genome variations by resequencing 335 accessions and revealed domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), was a key domestication gene. It was closely associated with the major domestication trait by positively controlling laticifer differentiation from vascular cambia. The transcriptional activation of HbPSK5 by MYC members linked JA signaling to PSK signaling in enhancing laticifer formation
DOI: 10.5281/zenodo.7123622
title: Genomic insight into domestication of rubber tree

description: we upgraded H. brasiliensis genome assembly (contig N50 of 11.21 megabases), presented a map of genome variations by resequencing 335 accessions and revealed domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), was a key domestication gene. It was closely associated with the major domestication trait by positively controlling laticifer differentiation from vascular cambia. The transcriptional activation of HbPSK5 by MYC members linked JA signaling to PSK signaling in enhancing laticifer formation. cite:https://www.nature.com/articles/s41467-023-40304-y
description: We updated the name of the gene to make it the same as the name number shown in the article, which is easy to use .cite:https://www.nature.com/articles/s41467-023-40304-y
DOI: 10.5281/zenodo.8002771
title: Genomic insight into domestication of rubber tree

description: we upgraded H. brasiliensis genome assembly (contig N50 of 11.21 megabases), presented a map of genome variations by resequencing 335 accessions and revealed domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), was a key domestication gene. It was closely associated with the major domestication trait by positively controlling laticifer differentiation from vascular cambia. The transcriptional activation of HbPSK5 by MYC members linked JA signaling to PSK signaling in enhancing laticifer formation
DOI: 10.5281/zenodo.8226747
title: Genomic insight into domestication of rubber tree

description: we upgraded H. brasiliensis genome assembly (contig N50 of 11.21 megabases), presented a map of genome variations by resequencing 335 accessions and revealed domestication-related molecular signals and a major domestication trait, the higher number of laticifer rings. HbPSK5, encoding the small-peptide hormone phytosulfokine (PSK), was a key domestication gene. It was closely associated with the major domestication trait by positively controlling laticifer differentiation from vascular cambia. The transcriptional activation of HbPSK5 by MYC members linked JA signaling to PSK signaling in enhancing laticifer formation. cite:https://www.nature.com/articles/s41467-023-40304-y
description: We updated the name of the gene to make it the same as the name number shown in the article, which is easy to use .cite:https://www.nature.com/articles/s41467-023-40304-y
DOI: 10.34740/kaggle/dsv/6272506
title: ScholarTeamFinder - NSF dataset
DOI: 10.25442/hku.23681418
title: Supporting data for "Reversing neutrophil exhaustion in hepatocellular carcinoma via RARA and GMCSF signaling enhances their anti-tumor ability"

description: This dataset contains files of multiplexed immunohistochemistry images of patient's staining in HCC. Patient demographics of the cohorts to analysis N1 and N2 clinical significance were included. Their expression levels, associations with clinopathological parameters, and survival curve analysis were included. This dataset also contains files of murine HCC gross images, multuiplexed immunohistochemistry images and analysis of differential expressed genes expression in treated and non-treated mice.
DOI: 10.25442/hku.23681418.v1
title: Supporting data for "Reversing neutrophil exhaustion in hepatocellular carcinoma via RARA and GMCSF signaling enhances their anti-tumor ability"

description: This dataset contains files of multiplexed immunohistochemistry images of patient's staining in HCC. Patient demographics of the cohorts to analysis N1 and N2 clinical significance were included. Their expression levels, associations with clinopathological parameters, and survival curve analysis were included. This dataset also contains files of murine HCC gross images, multuiplexed immunohistochemistry images and analysis of differential expressed genes expression in treated and non-treated mice.
DOI: 10.25442/hku.23674593
title: Supporting data for "Quantitative Multiparametric MRI and its application on endometrial cancer"

description: This dataset included raw data acquired from MRI scanners and EPR system, and my developed program related to my PhD thesis. <br> The first study (chapter 2) investigated the association of T1, T2, proton density (PD) and the apparent diffusion coefficient (ADC) with histopathologic features of endometrial carcinoma (EC). Quantitative maps and contrast-weighted images were saved in DICOM format, while ROIs were saved in NIFTI format. Histopathologlical information was recorded in an excel file. <br> The second study (chapter 3) investigated the diagnostic performance of radiomics models based on features extracted from T1, T2 and PD maps. The identical image dataset was used in these two studies. Radiomics features were recorded in excel files. <br> The third study (chapter 4) developed a novel sequence for the simultanious quantification of T1, T2, PD and ADC. Raw data acquired from an MRI scanner was saved in a binary format.
DOI: 10.25442/hku.23674593.v1
title: Supporting data for "Quantitative Multiparametric MRI and its application on endometrial cancer"

description: This dataset included raw data acquired from MRI scanners and EPR system, and my developed program related to my PhD thesis. <br> The first study (chapter 2) investigated the association of T1, T2, proton density (PD) and the apparent diffusion coefficient (ADC) with histopathologic features of endometrial carcinoma (EC). Quantitative maps and contrast-weighted images were saved in DICOM format, while ROIs were saved in NIFTI format. Histopathologlical information was recorded in an excel file. <br> The second study (chapter 3) investigated the diagnostic performance of radiomics models based on features extracted from T1, T2 and PD maps. The identical image dataset was used in these two studies. Radiomics features were recorded in excel files. <br> The third study (chapter 4) developed a novel sequence for the simultanious quantification of T1, T2, PD and ADC. Raw data acquired from an MRI scanner was saved in a binary format.
DOI: 10.25442/hku.23665479
title: <em>Supporting data for</em> "Characterization of early metastatic microenvironment in esophageal squamous cell carcinoma by single-cell transcriptome sequencing."

description: Data of the project "Characterization of early metastatic microenvironment in esophageal squamous cell carcinoma by single-cell transcriptome sequencing", including scRNA-seq data, bulk RNA-seq data, staining images of IF, IHC, and multiplex IHC, in vivo imaging, in vitro functional assay results.
DOI: 10.25442/hku.23665479.v1
title: <em>Supporting data for</em> "Characterization of early metastatic microenvironment in esophageal squamous cell carcinoma by single-cell transcriptome sequencing."

description: Data of the project "Characterization of early metastatic microenvironment in esophageal squamous cell carcinoma by single-cell transcriptome sequencing", including scRNA-seq data, bulk RNA-seq data, staining images of IF, IHC, and multiplex IHC, in vivo imaging, in vitro functional assay results.
DOI: 10.6084/m9.figshare.23908500
title: Posture_4520_my_yolo_dataset——test

description: The data set contains three postures of live pigs (standing, lying on their side, and lying on their stomach).The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.6084/m9.figshare.23908500.v1
title: Posture_4520_my_yolo_dataset——test

description: The data set contains three postures of live pigs (standing, lying on their side, and lying on their stomach).The Posture_4520_my_yolo_dataset contains 4520 images. According to the ratio of 8:1:1, the training set (3616), the verification set (452), the test set (452).
DOI: 10.5281/zenodo.8226772
title: Cleveland Shale geochemical data

description: Supplementary data for Geochemistry, Geophysics, Geosystems publication "<strong>Geochemical and hydrographic evolution of the Late Devonian Appalachian Seaway: Linking sedimentation, redox, and salinity across time and space"</strong>.
DOI: 10.5281/zenodo.8226771
title: Cleveland Shale geochemical data

description: Supplementary data for Geochemistry, Geophysics, Geosystems publication "<strong>Geochemical and hydrographic evolution of the Late Devonian Appalachian Seaway: Linking sedimentation, redox, and salinity across time and space"</strong>.
DOI: 10.15485/1828589
title: Fungal and bacterial growth variation due to drought and nitrogen addition experimental treatments. Loma Ridge Experimental Project. 2010-2012

description: Terrestrial ecosystem models assume that microbial communities respond instantaneously, or are immediately resilient, to environmental change. Here we tested this assumption by quantifying the resilience of a leaf litter community to changes in precipitation or nitrogen availability. By manipulating composition within a global change experiment, we decoupled the legacies of abiotic parameters versus that of the microbial community itself. After one rainy season, more variation in fungal composition could be explained by the original microbial inoculum than the litterbag environment (18% versus 5.5% of total variation). This compositional legacy persisted for 3 years, when 6% of the variability in fungal composition was still explained by the microbial origin. In contrast, bacterial composition was generally more resilient than fungal composition. Microbial functioning (measured as decomposition rate) was not immediately resilient to the global change manipulations; decomposition depended on both the contemporary environment and rainfall the year prior. Finally, using metagenomic sequencing, we showed that changes in precipitation, but not nitrogen availability, altered the potential for bacterial carbohydrate degradation, suggesting why the functional consequences of the two experiments may have differed. Predictions of how terrestrial ecosystem processes respond to environmental change may thus be improved by considering the legacies of microbial communities. This data package includes ten csv files (five data files and their corresponding data dictionaries) and one file-level metadata excel file. Data files contains information about which plots were exposed to treatments related to drought and nitrogen, information about litter bags reciprocal transplants manipulation for water input and nitrogen, detail information about water addition, precipitation records, and litter variables collected. Data dictionary files include detail explanation for each column in the data files. The file-level metadata file describes each file mentioned above. All the analyses were done using the R software.
DOI: 10.15485/1830417
title: Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

description: This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots.Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models.The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.
DOI: 10.15485/1840779
title: Perceived Costs and Benefits of ICON Science and Foundational Documents associated with “Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles"

description: This data package is associated with the publication "Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles" in Earth and Space Science (Goldman et al. 2022; https://doi.org/10.1029/2021EA002099). The manuscript is an introductory article for a special collection of commentary articles across 19 geoscience disciplines that explore the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes.This data package contains data, figures, and R scripts associated with the cost/benefit analysis presented in the manuscript. The writing teams involved in the special collection placed each letter of ICON on a plot with perceived cost on one axis and perceived benefit on the other to summarize their perceptions of pursuing each principle of ICON science. These data were subsequently quantified and analyzed. Files are saved as .csv, .R, and .pdf.This data package also contains (1) the public foundational and instructional documents that enabled the crowdsourced creation of the special collection; (2) file-level metadata (flmd) that lists each file in the data package with a description; (3) data dictionary (dd) that defines column headers that appear in csv files. Files are saved as .pdf and .csv.
DOI: 10.15485/1854257
title: Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

description: This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.
DOI: 10.15485/1866269
title: Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

description: This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.