cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25339441
title: Data for the study entitled "A method for calculating denudation from the big global thermochronologic data: Example applications to the Dabie orogen, eastern China"

description: This data set contains the supporting information and the data for the paper entitled "A method for calculating denudation from the big global thermochronologic data: Example applications to the Dabie orogen, eastern China". The supporting information file includes 7 figures (Figures S1 to S7), 2 data tables (Tables S1 to S2), and a text (Text S1). The other file compiles 158 temperature histories from previous publications (n = 151) [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Reiners et al.</i>, 2003; <i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ji et al.</i>, 2017; <i>Ding et al.</i>, 2021] and our new study (n = 7). Below is a brief introduction of the temperature histories.The temperature histories compiled in this work can be divided into the following four categories, based on the corresponding methodologies for data collection and numerical modelling. (1) Most of them were derived from inverse modeling of continuous temperature history from multiple thermochronologic data of individual samples till the present [<i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ding et al.</i>, 2021]. (2) Ten histories out of the total, derived from multi-domain diffusion modelling of Ar in K-feldspar, cover temperature and time period of the early exhumation stage, not lasting to the present-day [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Wang et al.</i>, 2014; <i>Ji et al.</i>, 2017]. (3) Nearly 50% of temperature paths were reconstructed by joint modelling of multiple samples collected from vertical profiles [<i>Reiners et al.</i>, 2003; <i>Ding et al.</i>, 2021]. (4) A number of temperature histories were restored by plotting the thermochronologic age versus their corresponding closure temperatures [<i>Chen et al.</i>, 1995; <i>Wang and Yang</i>, 1998; <i>Grimmer et al.</i>, 2002].Those cooling histories mostly cover the time between 130-0 Ma, with a few up to 270 Ma. The compilation of the temperature histories shows three phases of relatively rapid cooling during the Cretaceous, early Cenozoic, and Late Miocene-present. Given that all host rocks are Cretaceous or older, the cooling histories have been interpreted as rock exhumation in response to tectonic deformation or denudation [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Reiners et al.</i>, 2003; <i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ji et al.</i>, 2017; <i>Ding et al.</i>, 2021].
DOI: 10.6084/m9.figshare.25339441.v2
title: Data for the study entitled "A method for calculating denudation from the big global thermochronologic data: Example applications to the Dabie orogen, eastern China"

description: This data set contains the supporting information and the data for the paper entitled "A method for calculating denudation from the big global thermochronologic data: Example applications to the Dabie orogen, eastern China". The supporting information file includes 7 figures (Figures S1 to S7), 2 data tables (Tables S1 to S2), and a text (Text S1). The other file compiles 158 temperature histories from previous publications (n = 151) [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Reiners et al.</i>, 2003; <i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ji et al.</i>, 2017; <i>Ding et al.</i>, 2021] and our new study (n = 7). Below is a brief introduction of the temperature histories.The temperature histories compiled in this work can be divided into the following four categories, based on the corresponding methodologies for data collection and numerical modelling. (1) Most of them were derived from inverse modeling of continuous temperature history from multiple thermochronologic data of individual samples till the present [<i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ding et al.</i>, 2021]. (2) Ten histories out of the total, derived from multi-domain diffusion modelling of Ar in K-feldspar, cover temperature and time period of the early exhumation stage, not lasting to the present-day [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Wang et al.</i>, 2014; <i>Ji et al.</i>, 2017]. (3) Nearly 50% of temperature paths were reconstructed by joint modelling of multiple samples collected from vertical profiles [<i>Reiners et al.</i>, 2003; <i>Ding et al.</i>, 2021]. (4) A number of temperature histories were restored by plotting the thermochronologic age versus their corresponding closure temperatures [<i>Chen et al.</i>, 1995; <i>Wang and Yang</i>, 1998; <i>Grimmer et al.</i>, 2002].Those cooling histories mostly cover the time between 130-0 Ma, with a few up to 270 Ma. The compilation of the temperature histories shows three phases of relatively rapid cooling during the Cretaceous, early Cenozoic, and Late Miocene-present. Given that all host rocks are Cretaceous or older, the cooling histories have been interpreted as rock exhumation in response to tectonic deformation or denudation [<i>Hacker et al.</i>, 2000; <i>Ratschbacher et al.</i>, 2000; <i>Reiners et al.</i>, 2003; <i>Zhou et al.</i>, 2003; <i>Xu et al.</i>, 2005; <i>Hu et al.</i>, 2006; <i>Ji et al.</i>, 2017; <i>Ding et al.</i>, 2021].
DOI: 10.25345/c51834f25
title: MassIVE MSV000097095 - Elodie Mailler_Carlos Guardia_ATG9A_12LFQ
title: Proteomics analysis in whole-liver lysates to assess differences between the Atg9a-cKO and control mice.
DOI: 10.6084/m9.figshare.25879236
title: When and How to Use AI in the Design Process? Implications for Human-AI Design Collaboration

description: As the potential for human-AI design collaboration increases, understanding the role of artificial intelligence (AI) in the design process becomes more important. <i>How does AI currently support the design process and how could it do so in the future?</i> To answer this question, we categorized existing AI design support systems (DSS) according to the Double-Diamond design process model, and found that they are mostly used in the later stages of the design process, focusing on generating design solutions. In contrast, very few systems focus on the early stages of the process, which include discovering and defining design problems. To explore this finding’s alignment with designers’ expectations in real-world design, we present a case study involving emerging AI technologies such as ChatGPT and robots. This study proposes that AI agents can potentially assist designers by providing inspirations, defining design problems with constraints, offering grounded metaphors, and exploring design materials.
DOI: 10.6084/m9.figshare.25879236.v1
title: When and How to Use AI in the Design Process? Implications for Human-AI Design Collaboration

description: As the potential for human-AI design collaboration increases, understanding the role of artificial intelligence (AI) in the design process becomes more important. <i>How does AI currently support the design process and how could it do so in the future?</i> To answer this question, we categorized existing AI design support systems (DSS) according to the Double-Diamond design process model, and found that they are mostly used in the later stages of the design process, focusing on generating design solutions. In contrast, very few systems focus on the early stages of the process, which include discovering and defining design problems. To explore this finding’s alignment with designers’ expectations in real-world design, we present a case study involving emerging AI technologies such as ChatGPT and robots. This study proposes that AI agents can potentially assist designers by providing inspirations, defining design problems with constraints, offering grounded metaphors, and exploring design materials.
DOI: 10.6084/m9.figshare.28386476
title: Data for “<b>Afforestation </b><b>on</b><b> </b><b>Abandoned Croplands in China Has the Potential to Increase Carbon Sequestration by </b><b>half</b>”

description: This database includes 30m resolution <b>abandoned cropland raster data</b> for China, provincial-scale data on <b>afforestation areas and investment</b> (including both national and local investments) in China from 2003 to 2020, the <b>daily transaction records from China's nine carbon emission trading</b> exchanges, the <b>raw carbon datasets</b> for abandoned cropland, and the <b>main code</b> used in this work.
DOI: 10.5281/zenodo.14847170
title: ApoE gene sequencing

description: APOE gene sequencing
DOI: 10.5281/zenodo.14847171
title: ApoE gene sequencing

description: APOE gene sequencing
DOI: 10.5281/zenodo.14839835
title: unimpeded: nrunlcdm planck_2018_plik+sn.pantheon

description: cosmological model:nrunlcdm, dataset:planck_2018_plik+sn.pantheon
DOI: 10.5281/zenodo.14839836
title: unimpeded: nrunlcdm planck_2018_plik+sn.pantheon

description: cosmological model:nrunlcdm, dataset:planck_2018_plik+sn.pantheon
DOI: 10.5281/zenodo.14839620
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839621
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.6084/m9.figshare.28386470
title: 生物硅化模拟手性纳米结构靶向治疗炎症性肠病

description: 生物硅化模拟手性纳米结构靶向治疗炎症性肠病
DOI: 10.5281/zenodo.12664852
title: Data
DOI: 10.5281/zenodo.12696785
title: Data
DOI: 10.5281/zenodo.12697372
title: Data
DOI: 10.5281/zenodo.14839622
title: unimpeded: klcdm planck_2018_CamSpec+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_CamSpec+sn.pantheon
DOI: 10.5281/zenodo.14839623
title: unimpeded: klcdm planck_2018_CamSpec+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_CamSpec+sn.pantheon
DOI: 10.5281/zenodo.12664851
title: Data
DOI: 10.5281/zenodo.14839611
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_CamSpec_nolens

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_CamSpec_nolens
DOI: 10.5281/zenodo.14839612
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_CamSpec_nolens

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_CamSpec_nolens
DOI: 10.5281/zenodo.14847923
title: Data
DOI: 10.5281/zenodo.14839636
title: unimpeded: klcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.5281/zenodo.14839637
title: unimpeded: klcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:klcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.5281/zenodo.14839713
title: unimpeded: nrunlcdm bicep_keck_2018+sn.pantheon

description: cosmological model:nrunlcdm, dataset:bicep_keck_2018+sn.pantheon
DOI: 10.5281/zenodo.14839714
title: unimpeded: nrunlcdm bicep_keck_2018+sn.pantheon

description: cosmological model:nrunlcdm, dataset:bicep_keck_2018+sn.pantheon
DOI: 10.5281/zenodo.14839725
title: unimpeded: mlcdm des_y1.joint

description: cosmological model:mlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839726
title: unimpeded: mlcdm des_y1.joint

description: cosmological model:mlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14847731
title: DECODE: Deep learning-based common deconvolution framework for various omics data
DOI: 10.5281/zenodo.14847732
title: DECODE: Deep learning-based common deconvolution framework for various omics data
DOI: 10.5281/zenodo.14839538
title: unimpeded: klcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:klcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.5281/zenodo.14839539
title: unimpeded: klcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:klcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.25345/c5wh2ds75
title: MassIVE MSV000097096 - Data for "Different tools for different trades: Contrasts in specialized metabolite chemodiversity and phylogenetic dispersion in fruit, leaves, and roots of the Neotropical shrubs Psychotria and Palicourea (Rubiaceae)"
title: Data for "Different tools for different trades: Contrasts in specialized metabolite chemodiversity and phylogenetic dispersion in fruit, leaves, and roots of the Neotropical shrubs Psychotria and Palicourea (Rubiaceae)", accepted at Plant Biology Feb. 2025
DOI: 10.3886/e218961
title: Survey on Perceived Organizational Identities (POI)

description: This
dataset consists of survey responses from 420 taxation officials across two
major Chinese cities, capturing their Perceived Organizational Identities (POI)—categorized
into State Representative Identity and Market Provider Identity—as well as their
perceptions of Public Service Motivation (PSM) and Leadership Orientation on
Customer Service. Each construct is measured using a five-point Likert scale (1
= Strongly Disagree to 5 = Strongly Agree). This dataset aims to examine how
the two identities influence public service motivation and how leadership
orientation moderates this relationship.<br>
description: Taxation officials from two Chinese cities in 2020.
DOI: 10.3886/e218961v1
title: Survey on Perceived Organizational Identities (POI)

description: This
dataset consists of survey responses from 420 taxation officials across two
major Chinese cities, capturing their Perceived Organizational Identities (POI)—categorized
into State Representative Identity and Market Provider Identity—as well as their
perceptions of Public Service Motivation (PSM) and Leadership Orientation on
Customer Service. Each construct is measured using a five-point Likert scale (1
= Strongly Disagree to 5 = Strongly Agree). This dataset aims to examine how
the two identities influence public service motivation and how leadership
orientation moderates this relationship.<br>
description: Taxation officials from two Chinese cities in 2020.
DOI: 10.5281/zenodo.14839540
title: unimpeded: wlcdm des_y1.joint

description: cosmological model:wlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839541
title: unimpeded: wlcdm des_y1.joint

description: cosmological model:wlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839572
title: unimpeded: klcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:klcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839573
title: unimpeded: klcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:klcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839578
title: unimpeded: klcdm bicep_keck_2018+planck_2018_CamSpec

description: cosmological model:klcdm, dataset:bicep_keck_2018+planck_2018_CamSpec
DOI: 10.5281/zenodo.14839579
title: unimpeded: klcdm bicep_keck_2018+planck_2018_CamSpec

description: cosmological model:klcdm, dataset:bicep_keck_2018+planck_2018_CamSpec
DOI: 10.6084/m9.figshare.28386518
title: Developmental air pollution exposure augments airway hyperreactivity, alters transcriptome, and DNA methylation in female adult progeny

description: Allergic airways disease model used to show developmental exposure to pm2.5 air pollution particulates causes worsened airway hyperreactivity in offspring, and associated changes in lung transcriptome and DNAm.
DOI: 10.6084/m9.figshare.28386518.v1
title: Developmental air pollution exposure augments airway hyperreactivity, alters transcriptome, and DNA methylation in female adult progeny

description: Allergic airways disease model used to show developmental exposure to pm2.5 air pollution particulates causes worsened airway hyperreactivity in offspring, and associated changes in lung transcriptome and DNAm.
DOI: 10.5281/zenodo.14839581
title: unimpeded: wlcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:wlcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.5281/zenodo.14839582
title: unimpeded: wlcdm bao.sdss_dr16+sn.pantheon

description: cosmological model:wlcdm, dataset:bao.sdss_dr16+sn.pantheon
DOI: 10.6069/w68t-3s89
title: Serum Alpha-2-Macroglobulin Links Type 1 Diabetes Status and Incident Cardiovascular Disease

description: Background: Cardiovascular disease (CVD) is a leading cause of mortality in individuals with type 1 diabetes mellitus (T1DM), with conventional risk factors not fully explaining the heightened risk.
Study Design: We conducted a cross-sectional study comparing serum protein levels in 134 participants with T1DM from the Coronary Artery Calcification in Type 1 Diabetes study to 47 healthy controls, followed by a case-cohort study among 181 T1DM participants, including 47 with CVD events. Linear regression analyzed serum protein levels by diabetes status, while Cox proportional hazards regression assessed associations with incident CVD.
Findings: Among 28 serum proteins tested, five showed significant differences between T1DM patients and controls, with alpha-2-macroglobulin (A2M) being notably 1.6-fold higher in T1DM. Adjusted models revealed that A2M (mean hazard ratio [HR] 2.5, 95% confidence interval [CI] 1.5-4.1) and apolipoprotein C3 (APOC3, mean HR 1.7, 95% CI 1.1-2.7) were independently associated with incident CVD in T1DM.
Conclusions: Elevated serum levels of A2M in T1DM suggest its potential role as a marker—and possibly a mediator—of CVD risk in these patients, alongside APOC3. These findings underscore the significance of specific serum proteins in understanding and managing CVD risk in T1DM.
DOI: 10.5281/zenodo.14839603
title: unimpeded: wlcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:wlcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839604
title: unimpeded: wlcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:wlcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839607
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_CamSpec

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_CamSpec
DOI: 10.5281/zenodo.14839608
title: unimpeded: wlcdm bicep_keck_2018+planck_2018_CamSpec

description: cosmological model:wlcdm, dataset:bicep_keck_2018+planck_2018_CamSpec
DOI: 10.5281/zenodo.14840117
title: unimpeded: Nlcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:Nlcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14840118
title: unimpeded: Nlcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:Nlcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.48610/b95ea8e
title: Coral connectivity

description: In "Connectivity differs by orders of magnitude among co-distributed corals, affecting spatial scales of eco-evolutionary processes", we using complementary analyses to provide the first quantitative estimates of ecologically relevant dispersal and evolutionary relevant gene flow in corals. We show that they vary dramatically between co-distributed coral species on the Great Barrier Reef, affecting their adaptive responses. Australia. In this repository, we make available the data (including VCF files) and scripts used to produce results and figures presented in this study.
DOI: 10.5281/zenodo.14840087
title: unimpeded: Nlcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:Nlcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14840088
title: unimpeded: Nlcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:Nlcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.34740/kaggle/dsv/10718352
title: Layline Shareholder activism dataset
DOI: 10.5281/zenodo.14839945
title: unimpeded: walcdm bicep_keck_2018+sn.pantheon

description: cosmological model:walcdm, dataset:bicep_keck_2018+sn.pantheon
DOI: 10.5281/zenodo.14839946
title: unimpeded: walcdm bicep_keck_2018+sn.pantheon

description: cosmological model:walcdm, dataset:bicep_keck_2018+sn.pantheon
DOI: 10.5281/zenodo.14839971
title: unimpeded: nlcdm des_y1.joint

description: cosmological model:nlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839972
title: unimpeded: nlcdm des_y1.joint

description: cosmological model:nlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839975
title: unimpeded: Nlcdm des_y1.joint

description: cosmological model:Nlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839976
title: unimpeded: Nlcdm des_y1.joint

description: cosmological model:Nlcdm, dataset:des_y1.joint
DOI: 10.5281/zenodo.14839979
title: unimpeded: lcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:lcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.5281/zenodo.14839980
title: unimpeded: lcdm planck_2018_plik_nolens+sn.pantheon

description: cosmological model:lcdm, dataset:planck_2018_plik_nolens+sn.pantheon
DOI: 10.6084/m9.figshare.28386640.v1
title: Additional file 1 of Effects of a transient lack of dietary mineral phosphorus on renal gene expression and plasma metabolites in two high-yielding laying hen strains

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.28386640
title: Additional file 1 of Effects of a transient lack of dietary mineral phosphorus on renal gene expression and plasma metabolites in two high-yielding laying hen strains

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.28386675
title: Additional file 2 of The 40S ribosomal protein SA-2 inhibits citrus yellow vein clearing virus infection in Eureka lemon via activating jasmonic acid and photosynthetic pathways

description: Additional file 2: Table S1. Pairwise alignment of RPSA-2 protein sequences. Table S2. ClRPSA-2 binding sites were analyzed using PlantCARE. Table S3. The Eureka lemon ClRPSA-2 hairy root transformation system. Table S4. Primers used in this study.
DOI: 10.6084/m9.figshare.28386675.v1
title: Additional file 2 of The 40S ribosomal protein SA-2 inhibits citrus yellow vein clearing virus infection in Eureka lemon via activating jasmonic acid and photosynthetic pathways

description: Additional file 2: Table S1. Pairwise alignment of RPSA-2 protein sequences. Table S2. ClRPSA-2 binding sites were analyzed using PlantCARE. Table S3. The Eureka lemon ClRPSA-2 hairy root transformation system. Table S4. Primers used in this study.
DOI: 10.6084/m9.figshare.28386684
title: Additional file 2 of Proteomic profiling of human plasma and intervertebral disc tissue reveals matrisomal, but not plasma, biomarkers of disc degeneration

description: Supplementary Material 2: Title of the data: Differentially distributed proteins from mass spectrometry analyses of severe and mild degenerated intervertebral disc tissues. Description of the data: List of Log2 LFQ protein intensities and differentially distributed proteins obtained from label-free mass spectrometry analyses of severe and mild degenerated intervertebral disc tissues.
DOI: 10.6084/m9.figshare.28386684.v1
title: Additional file 2 of Proteomic profiling of human plasma and intervertebral disc tissue reveals matrisomal, but not plasma, biomarkers of disc degeneration

description: Supplementary Material 2: Title of the data: Differentially distributed proteins from mass spectrometry analyses of severe and mild degenerated intervertebral disc tissues. Description of the data: List of Log2 LFQ protein intensities and differentially distributed proteins obtained from label-free mass spectrometry analyses of severe and mild degenerated intervertebral disc tissues.
DOI: 10.6084/m9.figshare.28386687
title: Additional file 3 of Proteomic profiling of human plasma and intervertebral disc tissue reveals matrisomal, but not plasma, biomarkers of disc degeneration

description: Supplementary Material 3: Title of the data: Differentially distributed proteins from mass spectrometry analyses of plasma from donors with severe and mild intervertebral disc degeneration. Description of the data: 1. List of Log2 protein intensities and differentially distributed proteins obtained from DIA SWATH mass spectrometry analyses of plasma from donors with severe and mild intervertebral disc degeneration. 2. Correlation analyses between plasma A2M and proteins changed in IVD tissue in response to degeneration progression.