cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17724512
title: Ice thickness of the world's glaciers (IceBoost model)

description: The repository contains:



All the world's glaciers: regional zip files (Randolph Glacier Inventory RGI v.62, n=216,502 and RGI v.70, n=274,531) containing individual glacier tif files. 

IceBoost model (XGBoost  mudules: .json files, CatBoost modules: .cbm file). Total 6 files.

Training datasets. Users can find both the raw datasets, and the final glacier-encoded dataset used for training.


 

1. Modeled world's glaciers:

Every tif file contains 5 layers: the ice thickness, the ice thickness error, the surface elevation, the geoid elevation, and the Jensen Gap. Ice thickness measurements collected within the glacier, if any, can be found in the attributes. The projection is UTM, except for: Greenland (rgi5, EPSG:3413), and Antarctica (rgi19, south of 60° S, EPSG:3031). Glaciers in rgi19 north of 60° S are released in UTM projection. The horizontal resolution is 100 m, unless specified otherwise.

 

2. IceBoost models: there are 3 pairs of modules. Each pairs is trained with a different set of features. For XGBoost (the same applies for CatBoost):



iceboost_xgb_20251009_with_v.json: trained with all features, with velocity and without lmax.

iceboost_xgb_20251009_without_v.json: trained without velocity and without lmax.

iceboost_xgb_20251010_without_v_with_lmax.json: trained without velocity, and with lmax.


A human-readable brief explanation of the features:



'elevation': surface elevation.

'dist_from_border_km_geom': distance to any ice free region.

'slope50', 'slope75', 'slope100', 'slope125', 'slope150', 'slope300', 'slope450', 'slopegfa': surface slopes after smoothing with gaussian kernels.

'curv_50',  'curv_100', 'curv_150', 'curv_300', 'curv_450', 'curv_gfa': surface curvature.

'smb': surface mass balance.

't2m': temperature above 2 m.

'dist_from_ocean': distance to the ocean.

'v50', 'v100', 'v150', 'v300', 'v450', 'vgfa': ice velocity.

'lmax': length of the glacier (convex hull).


For each point inside the glacier, collect the feature set X, and run the model iceboost(X) to get the ice thickness.

3. Training datasets:



iceboost_train_20250927_hmineq1.0_tmin20050000_mean_grid_100.csv: training data encoded per glacier. This file is the one used for training. It is created by combining the following raw datasets together:

glathida44.csv

alaska_ice_thick_train_iceboost.csv

asia_ice_thick_train_iceboost.csv

jostedalsbreen_ice_thick_train_iceboost.csv

patagonia_ice_thick_train_iceboost.csv

ruth_glacier_ice_thick_train_iceboost.csv

polar_ice_thick_train_iceboost4.parquet


 

===============

IceBoost Web Visualizer at: https://nmaffe.github.io/iceboost_webapp/

IceBoost code on Github at: https://github.com/nmaffe/iceboost

===============
DOI: 10.5281/zenodo.12791379
title: Ice thickness of the world's glaciers (IceBoost model)

description: The repository contains:



All the world's glaciers: regional zip files (Randolph Glacier Inventory RGI v.62, n=216,502 and RGI v.70, n=274,531) containing individual glacier tif files. 

IceBoost model (XGBoost  mudules: .json files, CatBoost modules: .cbm file). Total 6 files.

Training datasets. Users can find both the raw datasets, and the final glacier-encoded dataset used for training.


 

1. Modeled world's glaciers:

Every tif file contains 5 layers: the ice thickness, the ice thickness error, the surface elevation, the geoid elevation, and the Jensen Gap. Ice thickness measurements collected within the glacier, if any, can be found in the attributes. The projection is UTM, except for: Greenland (rgi5, EPSG:3413), and Antarctica (rgi19, south of 60° S, EPSG:3031). Glaciers in rgi19 north of 60° S are released in UTM projection. The horizontal resolution is 100 m, unless specified otherwise.

 

2. IceBoost models: there are 3 pairs of modules. Each pairs is trained with a different set of features. For XGBoost (the same applies for CatBoost):



iceboost_xgb_20251009_with_v.json: trained with all features, with velocity and without lmax.

iceboost_xgb_20251009_without_v.json: trained without velocity and without lmax.

iceboost_xgb_20251010_without_v_with_lmax.json: trained without velocity, and with lmax.


A human-readable brief explanation of the features:



'elevation': surface elevation.

'dist_from_border_km_geom': distance to any ice free region.

'slope50', 'slope75', 'slope100', 'slope125', 'slope150', 'slope300', 'slope450', 'slopegfa': surface slopes after smoothing with gaussian kernels.

'curv_50',  'curv_100', 'curv_150', 'curv_300', 'curv_450', 'curv_gfa': surface curvature.

'smb': surface mass balance.

't2m': temperature above 2 m.

'dist_from_ocean': distance to the ocean.

'v50', 'v100', 'v150', 'v300', 'v450', 'vgfa': ice velocity.

'lmax': length of the glacier (convex hull).


For each point inside the glacier, collect the feature set X, and run the model iceboost(X) to get the ice thickness.

3. Training datasets:



iceboost_train_20250927_hmineq1.0_tmin20050000_mean_grid_100.csv: training data encoded per glacier. This file is the one used for training. It is created by combining the following raw datasets together:

glathida44.csv

alaska_ice_thick_train_iceboost.csv

asia_ice_thick_train_iceboost.csv

jostedalsbreen_ice_thick_train_iceboost.csv

patagonia_ice_thick_train_iceboost.csv

ruth_glacier_ice_thick_train_iceboost.csv

polar_ice_thick_train_iceboost4.parquet


 

===============

IceBoost Web Visualizer at: https://nmaffe.github.io/iceboost_webapp/

IceBoost code on Github at: https://github.com/nmaffe/iceboost

===============
DOI: 10.15468/dl.qsedu4
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tracheophyta)",
 "Geometry POLYGON ((13.0251 47.5355, 13.0331 47.5355, 13.0331 47.5435, 13.0251 47.5435, 13.0251 47.5355))"
 ]
}

 The dataset includes 31 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037173-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hd833w
title: Occurrence Download

description: A dataset containing 30743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((3.5 43.5, 12.5 43.5, 12.5 50.5, 3.5 50.5, 3.5 43.5))"
 ]
}

 The dataset includes 30743 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037172-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fu3er5
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((103.494 -1.331819, 103.423718 -1.337385, 103.355165 -1.353945, 103.29003 -1.381093, 103.229913 -1.41816, 103.176296 -1.464234, 103.130498 -1.51818, 103.093648 -1.578672, 103.066651 -1.64422, 103.050175 -1.71321, 103.044626 -1.783945, 103.050141 -1.854682, 103.066587 -1.92368, 103.093559 -1.98924, 103.130394 -2.049747, 103.176186 -2.10371, 103.229809 -2.1498, 103.289941 -2.186882, 103.355101 -2.214042, 103.423684 -2.230611, 103.494 -2.236179, 103.564316 -2.230611, 103.632899 -2.214042, 103.698059 -2.186882, 103.758191 -2.1498, 103.811814 -2.10371, 103.857606 -2.049747, 103.894441 -1.98924, 103.921413 -1.92368, 103.937859 -1.854682, 103.943374 -1.783945, 103.937825 -1.71321, 103.921349 -1.64422, 103.894352 -1.578672, 103.857502 -1.51818, 103.811704 -1.464234, 103.758087 -1.41816, 103.69797 -1.381093, 103.632835 -1.353945, 103.564282 -1.337385, 103.494 -1.331819))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037174-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30286581
title: The effectiveness and safety of various treatments for hemophilia in China: a literature review and evidence mapping

description: To evaluate the safety and effectiveness of treatments for hemophilia in China through a literature review and evidence mapping, we systematically searched PubMed, Web of Science, Cochrane Library, CNKI, Wanfang, and CBM. Descriptive statistics were used for data analysis in this evidence mapping and the review concluded on 21 April 2025. Results were compiled in tabular or graphical form. This review included 49 studies (two RCTs and 47 observational studies), involving 2274 patients, 41 articles focusing on hemophilia A, seven on hemophilia B, and one on both. The average (mean or median) age of subjects within the individual studies ranged from 5.77 to 34.6 years. This study revealed a decrease in both annualized bleeding rate (ABR) and annualized joint bleeding rate (AJBR) following prophylaxis treatment and immune tolerance induction (ITI) treatment. The reduction in target joint count post-treatment aligns with previous research indicating successful hemostasis in most people with hemophilia after alternative therapies; long-term follow-up studies consistently showed improved imaging scores at various dosage levels, indicating disease amelioration. Additionally, our findings suggest enhanced quality of life for people with hemophilia following treatment. Alternative therapies, encompassing prophylaxis therapy, on-demand treatment, and ITI therapy, demonstrated both efficacy and safety in the management of hemophilia among Chinese people with hemophilia.
DOI: 10.6084/m9.figshare.30286581.v1
title: The effectiveness and safety of various treatments for hemophilia in China: a literature review and evidence mapping

description: To evaluate the safety and effectiveness of treatments for hemophilia in China through a literature review and evidence mapping, we systematically searched PubMed, Web of Science, Cochrane Library, CNKI, Wanfang, and CBM. Descriptive statistics were used for data analysis in this evidence mapping and the review concluded on 21 April 2025. Results were compiled in tabular or graphical form. This review included 49 studies (two RCTs and 47 observational studies), involving 2274 patients, 41 articles focusing on hemophilia A, seven on hemophilia B, and one on both. The average (mean or median) age of subjects within the individual studies ranged from 5.77 to 34.6 years. This study revealed a decrease in both annualized bleeding rate (ABR) and annualized joint bleeding rate (AJBR) following prophylaxis treatment and immune tolerance induction (ITI) treatment. The reduction in target joint count post-treatment aligns with previous research indicating successful hemostasis in most people with hemophilia after alternative therapies; long-term follow-up studies consistently showed improved imaging scores at various dosage levels, indicating disease amelioration. Additionally, our findings suggest enhanced quality of life for people with hemophilia following treatment. Alternative therapies, encompassing prophylaxis therapy, on-demand treatment, and ITI therapy, demonstrated both efficacy and safety in the management of hemophilia among Chinese people with hemophilia.
DOI: 10.6084/m9.figshare.29626796
title: Prognostic value of miR-106a and miR-20a in AML patients with chemotherapy or allo-HSCT treatment

description: MiR-106a and miR-20a (miR-17 family members) are frequently dysregulated in carcinogenesis, but their prognostic significance in acute myeloid leukemia (AML) remains unclear. We analyzed miR-106a and miR-20a expression in bone marrow from 115 AML patients and 45 healthy controls using qRT-PCR. Additionally, we utilized TCGA data (n=188) to assess the association of these miRNAs with clinical factors and outcomes. Prognostic analysis evaluated the impact of miR-106a and miR-20a on overall survival (OS) and event-free survival (EFS). Differentially expressed genes (DEGs) were identified using Limma. GO and KEGG pathway analyses were performed by DAVID. GSEA and PPI were constructed using ClusterProfiler and STRING database. MiR-106a and miR-20a elevated in AML <i>versus</i> healthy controls. In chemotherapy group, miR-106a<sup>high</sup> or miR-20a<sup>high</sup> predicted poor OS and EFS, with dual-high expression conferring the worst outcome. In allo-HSCT group, miR-106a<sup>high</sup> or miR-20a<sup>high</sup> predicted poor OS but similar EFS, with dual-high cases showing the worst OS. In the miR-106a<sup>high</sup> or miR-20a<sup>high</sup> group, allo-HSCT prolonged OS (but not EFS) <i>versus</i> chemotherapy. In the miR-106a<sup>low</sup> or miR-20a<sup>low</sup> group, there were no obvious differences in OS or EFS between the chemotherapy and allo-HSCT regimens. Multivariable analyses confirmed miR-106a/miR-20a signature as an independent prognostic marker. Moreover, we identified 706 signature-associated DEGs. Bioinformatic analysis illuminated the involvement of miR-106a and miR-20a in regulating diverse biological processes and signaling pathways. MiR-106a and miR-20a are promising AML prognostic biomarkers for adverse outcome. The combined signature improves risk stratification and guides therapy selection (e.g., ⁣allo-HSCT for high-risk cases).
DOI: 10.6084/m9.figshare.29626796.v1
title: Prognostic value of miR-106a and miR-20a in AML patients with chemotherapy or allo-HSCT treatment

description: MiR-106a and miR-20a (miR-17 family members) are frequently dysregulated in carcinogenesis, but their prognostic significance in acute myeloid leukemia (AML) remains unclear. We analyzed miR-106a and miR-20a expression in bone marrow from 115 AML patients and 45 healthy controls using qRT-PCR. Additionally, we utilized TCGA data (n=188) to assess the association of these miRNAs with clinical factors and outcomes. Prognostic analysis evaluated the impact of miR-106a and miR-20a on overall survival (OS) and event-free survival (EFS). Differentially expressed genes (DEGs) were identified using Limma. GO and KEGG pathway analyses were performed by DAVID. GSEA and PPI were constructed using ClusterProfiler and STRING database. MiR-106a and miR-20a elevated in AML <i>versus</i> healthy controls. In chemotherapy group, miR-106a<sup>high</sup> or miR-20a<sup>high</sup> predicted poor OS and EFS, with dual-high expression conferring the worst outcome. In allo-HSCT group, miR-106a<sup>high</sup> or miR-20a<sup>high</sup> predicted poor OS but similar EFS, with dual-high cases showing the worst OS. In the miR-106a<sup>high</sup> or miR-20a<sup>high</sup> group, allo-HSCT prolonged OS (but not EFS) <i>versus</i> chemotherapy. In the miR-106a<sup>low</sup> or miR-20a<sup>low</sup> group, there were no obvious differences in OS or EFS between the chemotherapy and allo-HSCT regimens. Multivariable analyses confirmed miR-106a/miR-20a signature as an independent prognostic marker. Moreover, we identified 706 signature-associated DEGs. Bioinformatic analysis illuminated the involvement of miR-106a and miR-20a in regulating diverse biological processes and signaling pathways. MiR-106a and miR-20a are promising AML prognostic biomarkers for adverse outcome. The combined signature improves risk stratification and guides therapy selection (e.g., ⁣allo-HSCT for high-risk cases).
DOI: 10.6084/m9.figshare.30596975
title: DKK3 as a novel biomarker for risk stratification in pediatric acute lymphoblastic leukemia

description: Aberrant Wnt signaling drives oncogenesis. DKK proteins, key extracellular regulators of Wnt pathway, play critical roles in tumor suppression or promotion. This study enrolled 66 newly diagnosed acute lymphoblastic leukemia (ALL) patients, stratified into low-risk (LR) and intermediate/high-risk (IR/HR) groups, alongside 39 children with immune thrombocytopenia (ITP) as controls. Bone marrow samples were collected at diagnosis and remission (day 46). DKK3 expression was measured using qRT – PCR and ELISA. Predictive performance was evaluated via ROC analysis and logistic regression. DKK3 mRNA and protein levels were significantly lower at diagnosis than in remission and control groups (<i>P</i> &lt; 0.001). LR patients showed higher DKK3 expression than IR/HR patients (<i>P</i> &lt; 0.001). ROC analysis indicated that DKK3 mRNA and protein effectively predicted IR/HR status; combined AUC reached 0.889. No significant difference was found between B-ALL and T-ALL subgroups. Low DKK3 protein was an independent risk factor for event-free survival (<i>P</i> = 0.024). DKK3 shows promise as a biomarker for early risk stratification and prognosis prediction in pediatric ALL, potentially supporting personalized treatment strategies.
DOI: 10.6084/m9.figshare.30596975.v1
title: DKK3 as a novel biomarker for risk stratification in pediatric acute lymphoblastic leukemia

description: Aberrant Wnt signaling drives oncogenesis. DKK proteins, key extracellular regulators of Wnt pathway, play critical roles in tumor suppression or promotion. This study enrolled 66 newly diagnosed acute lymphoblastic leukemia (ALL) patients, stratified into low-risk (LR) and intermediate/high-risk (IR/HR) groups, alongside 39 children with immune thrombocytopenia (ITP) as controls. Bone marrow samples were collected at diagnosis and remission (day 46). DKK3 expression was measured using qRT – PCR and ELISA. Predictive performance was evaluated via ROC analysis and logistic regression. DKK3 mRNA and protein levels were significantly lower at diagnosis than in remission and control groups (<i>P</i> &lt; 0.001). LR patients showed higher DKK3 expression than IR/HR patients (<i>P</i> &lt; 0.001). ROC analysis indicated that DKK3 mRNA and protein effectively predicted IR/HR status; combined AUC reached 0.889. No significant difference was found between B-ALL and T-ALL subgroups. Low DKK3 protein was an independent risk factor for event-free survival (<i>P</i> = 0.024). DKK3 shows promise as a biomarker for early risk stratification and prognosis prediction in pediatric ALL, potentially supporting personalized treatment strategies.
DOI: 10.6084/m9.figshare.30343501
title: The prognostic impact of chromosome 7 with both arms loss [der(7)del(7p)del(7q)] in myelodysplastic syndrome/neoplasm

description: Chromosome 7 abnormality characterized by loss of both arms [der(7)del(7p)del(7q), hereafter ‘der(7)’] is very rare. The features and prognosis of patients with der(7) in myelodysplastic syndromes (MDS) remain unclear. We identified 35 MDS cases with der(7) using Metaphase Fluorescence In Situ Hybridization (metaphase-FISH), and compared them to 178 with del(7q), 390 with monosomy 7 (−7), and 603 with a normal karyotype (NK). Der(7) correlated with lower karyotypic complexity (odds ratios (ORs) 0.288, <i>P</i> = 0.001), more solitary abnormalities (ORs 3.652, <i>P</i> = 0.001), and frequent co-occurrence with −7 (40.9%; ORs 3.150, <i>P</i> = 0.004). Compared to NK, der(7) cases presented lower platelet counts, higher ferritin levels, and more frequent ≥3 mutations (<i>P</i> &lt; 0.05). Mutations in <i>ASXL1</i>(ORs 2.394)<i>, RUNX1</i>(ORs 2.618)<i>, SETBP1</i>(ORs 15.132)<i>,</i> and <i>ETV6</i> (ORs 5.525) were enriched in der(7)/−7/del(7q) patients compared to NK (all <i>P</i> &lt; 0.001), while <i>NF1</i> (ORs 15.492, <i>P</i> = 0.002) and <i>PTPN11</i> (ORs 6.653, <i>P</i> = 0.021) mutations were more prevalent in der(7) cases relative to NK. Prognostically, der(7) was identified as an independent risk factor (Hazard Ratios (HRs) 1.368, 95% CI 1.030–1.818; <i>P</i> = 0.031). Median overall survival (OS) of patients with der(7) was 17 months – shorter than NK (64 months, <i>P</i> = 0.005) but similar to −7 (20 months) and del(7q) (30 months). Hematopoietic stem cell transplantation improved survival (<i>P</i> = 0.018). Notably, 5 of 10 der(7) cases with follow-up evolved to −7. Der(7) defines a distinct high-risk subgroup with a unique molecular profile and poor prognosis comparable to −7.
DOI: 10.6084/m9.figshare.30343501.v2
title: The prognostic impact of chromosome 7 with both arms loss [der(7)del(7p)del(7q)] in myelodysplastic syndrome/neoplasm

description: Chromosome 7 abnormality characterized by loss of both arms [der(7)del(7p)del(7q), hereafter ‘der(7)’] is very rare. The features and prognosis of patients with der(7) in myelodysplastic syndromes (MDS) remain unclear. We identified 35 MDS cases with der(7) using Metaphase Fluorescence In Situ Hybridization (metaphase-FISH), and compared them to 178 with del(7q), 390 with monosomy 7 (−7), and 603 with a normal karyotype (NK). Der(7) correlated with lower karyotypic complexity (odds ratios (ORs) 0.288, <i>P</i> = 0.001), more solitary abnormalities (ORs 3.652, <i>P</i> = 0.001), and frequent co-occurrence with −7 (40.9%; ORs 3.150, <i>P</i> = 0.004). Compared to NK, der(7) cases presented lower platelet counts, higher ferritin levels, and more frequent ≥3 mutations (<i>P</i> &lt; 0.05). Mutations in <i>ASXL1</i>(ORs 2.394)<i>, RUNX1</i>(ORs 2.618)<i>, SETBP1</i>(ORs 15.132)<i>,</i> and <i>ETV6</i> (ORs 5.525) were enriched in der(7)/−7/del(7q) patients compared to NK (all <i>P</i> &lt; 0.001), while <i>NF1</i> (ORs 15.492, <i>P</i> = 0.002) and <i>PTPN11</i> (ORs 6.653, <i>P</i> = 0.021) mutations were more prevalent in der(7) cases relative to NK. Prognostically, der(7) was identified as an independent risk factor (Hazard Ratios (HRs) 1.368, 95% CI 1.030–1.818; <i>P</i> = 0.031). Median overall survival (OS) of patients with der(7) was 17 months – shorter than NK (64 months, <i>P</i> = 0.005) but similar to −7 (20 months) and del(7q) (30 months). Hematopoietic stem cell transplantation improved survival (<i>P</i> = 0.018). Notably, 5 of 10 der(7) cases with follow-up evolved to −7. Der(7) defines a distinct high-risk subgroup with a unique molecular profile and poor prognosis comparable to −7.
DOI: 10.6084/m9.figshare.28295445
title: Prognostic signature based on mitochondria- and angiogenesis-related genes associated with immune microenvironment of multiple myeloma

description: Mitochondria and angiogenesis play key roles in multiple myeloma (MM) development, but their interrelated genes affecting MM prognosis are under-studied. We analyzed TCGA_MMRF and GSE4581 datasets to identify four genes – CCNB1, CDC25C, HSP90AA1, and PARP1 – that significantly correlate with MM prognosis, with high expression indicating poor outcomes. A prognostic signature based on these genes stratified patients into high- and low-risk groups, with the latter showing better survival. The signature was validated as an independent prognostic factor. Biological function analysis revealed differences in cell cycle processes between risk groups, and immune microenvironment analysis showed distinct immune cell infiltration patterns. This mitochondria- and angiogenesis-related prognostic signature could enhance MM prognosis assessment and offer new therapeutic insights.