cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14101556.v1
title: Long non-coding RNA-based signature for predicting prognosis of hepatocellular carcinoma

description: Long non-coding RNAs (lncRNAs), as one common type of non-coding RNAs, play a critical role in the tumorigenesis and development of hepatocellular carcinoma (HCC). In the current study, we aimed to assess the correlation between lncRNAs expression levels and prognosis of HCC patients. A lncRNA-based signature was also developed to predict the prognosis of HCC in this work. The lncRNAs expression profiles in tissues of tumor and para-carcinoma were obtained from The Cancer Genome Atlas (TCGA) database. The lncRNA-based prognostic model was established by least absolute shrinkage and selection operator (LASSO). The multivariate Cox-regression analysis was applied to identify the independent risk factors and subsequently developed a prognostic nomogram. Based on the co-expression analyses, we identiﬁed the lncRNA-related mRNAs and performed the biological function analysis. Between HCC and para-carcinoma tissues, 220 differentially expressed lncRNAs were filtered. Among these lncRNAs, 19 lncRNAs were identified as prognostic factors and were used to build a prognostic signature of overall survival (OS). Furthermore, a nomogram with high performance for predicting the OS of HCC patients (C-index: 0.779) by combining the 19-lncRNA signature (P &lt; 0.001) and clinicopathologic factors including HBV (P = 0.005) and stage (P =0.017) was established. Functional enrichment analysis revealed that 19 lncRNAs had potential effects on tumor cell proliferation in HCC. In summary, we established a 19-lncRNA signature to predict the prognosis of HCC patients, which may perform a crucial role in guiding the management of HCC.
DOI: 10.48597/ysng-a2t7
title: Measurement of Inorganics in precipitation at Kårvatn

description: Measurement of Inorganics in precipitation at Kårvatn
DOI: 10.48597/ywdw-jdvy
title: Measurement of Inorganics in precipitation at Tustervatn

description: Measurement of Inorganics in precipitation at Tustervatn
DOI: 10.48597/zauf-qha8
title: Measurement of Inorganics in precipitation at Bjørnøya

description: Measurement of Inorganics in precipitation at Bjørnøya
DOI: 10.6084/m9.figshare.7285814
title: Additional file 10: of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 4. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-008_T, LTS-009_T, LTS-010_T, LTS-011_T, LTS-012_T, LTS-013_T, LTS-014_T, LTS-015_T, LTS-016_T. (TXT 13456 kb)
DOI: 10.48597/zk96-spvs
title: Measurement of Nitrogen_dioxide at Valle

description: Measurement of Nitrogen_dioxide at Valle
DOI: 10.15468/4fhqxr
title: Projet éolien de Camblain-Châtelain (SEPE Le Mont Duquenne) - Chiroptères

description: Projet éolien composé de 4 éoliennes de type Vestas V 112 d'une hauteur totale de 150 m et d'une puissance de 3 MW par machine. La zone d'étude se situe sur les communes de Camblain-Châtelain, Ourton et Divion.
DOI: 10.48597/2jdv-nyd8
title: Sulphate_total at Chopok

description: Measurement of Sulphate_total at Chopok
DOI: 10.48597/zph5-b7gx
title: Measurement of Sulphate_corrected at Vikedal

description: Measurement of Sulphate_corrected at Vikedal
DOI: 10.6084/m9.figshare.7285817
title: Additional file 8: of High-density genetic map construction and quantitative trait loci identification for growth traits in (Taxodium distichum var. distichum Ă T. mucronatum) Ă T. mucronatum

description: The SLAF markers encompassed in the major growth associated locus as revealed by QTL analysis. (XLSX 24Â kb)
DOI: 10.48597/2kqm-5zhk
title: Nitrogen_dioxide at Neuglobsow

description: Measurement of Nitrogen_dioxide at Neuglobsow
DOI: 10.15468/27ke9z
title: Demande d'extension de l'ISDND dédiée aux déchets de matériaux de construction contenant de l'amiante dans le cadre de la remise en état de la carrière autorisée - Données faune

description: Ensemble des données ponctuelles, linéaires et surfaciques pour les différents inventaires réalisés entre 2012 et 2017 pour la faune
DOI: 10.48597/2pj9-38b3
title: Inorganics in air and particle phase at Montelibretti

description: Measurement of Inorganics in air and particle phase at Montelibretti
DOI: 10.48597/2x6d-5v9s
title: Inorganics in air and particle phase at Chopok

description: Measurement of Inorganics in air and particle phase at Chopok
DOI: 10.6084/m9.figshare.7285817.v1
title: Additional file 8: of High-density genetic map construction and quantitative trait loci identification for growth traits in (Taxodium distichum var. distichum Ă T. mucronatum) Ă T. mucronatum

description: The SLAF markers encompassed in the major growth associated locus as revealed by QTL analysis. (XLSX 24Â kb)
DOI: 10.48597/398n-rn5e
title: pH at Keldsnor

description: Measurement of pH at Keldsnor
DOI: 10.48597/3gtz-xg7h
title: Sulphate_total at Hoburgen

description: Measurement of Sulphate_total at Hoburgen
DOI: 10.48597/3mt8-mbtd
title: Inorganics in precipitation at Lahemaa

description: Measurement of Inorganics in precipitation at Lahemaa
DOI: 10.48597/3ujg-stbq
title: Inorganics in precipitation at Keldsnor

description: Measurement of Inorganics in precipitation at Keldsnor
DOI: 10.48597/3zvn-u5g7
title: Inorganics in air and particle phase at Ispra

description: Measurement of Inorganics in air and particle phase at Ispra
DOI: 10.48597/4dax-2vg4
title: Susp_part_matter at Sniezka

description: Measurement of Susp_part_matter at Sniezka
DOI: 10.48597/4wn6-pnz6
title: pH at Illmitz

description: Measurement of pH at Illmitz
DOI: 10.48597/4zsg-mhjn
title: Toluene at Kosetice (NAOK)

description: Measurement of Toluene at Kosetice (NAOK)
DOI: 10.48597/59jv-m4yj
title: Inorganics in precipitation at Vilsandi

description: Measurement of Inorganics in precipitation at Vilsandi
DOI: 10.48597/5brz-477b
title: VOC (hydrocarbons) at Kosetice (NAOK)

description: Measurement of VOC (hydrocarbons) at Kosetice (NAOK)
DOI: 10.48597/6349-r9ft
title: Nitrogen_dioxide at Svratouch

description: Measurement of Nitrogen_dioxide at Svratouch
DOI: 10.48597/6kec-cn7g
title: Nitrogen_dioxide at Rörvik

description: Measurement of Nitrogen_dioxide at Rörvik
DOI: 10.15468/ygaxnu
title: Projet éolien de Flixecourt (SEPE La Croix Florent) - Chauves-souris - Points d'écoute au sol

description: Liste des chauves-souris observées dans le cadre des prospections de terrain réalisées au niveau de l'aire d'étude du projet éolien de la Croix Florent
DOI: 10.48597/6uzx-br5s
title: Inorganics in precipitation at Chopok

description: Measurement of Inorganics in precipitation at Chopok
DOI: 10.6084/m9.figshare.14101562
title: A signature of 13 autophagy‑related gene pairs predicts prognosis in hepatocellular carcinoma

description: Growing evidences suggest that autophagy plays a momentous part in the tumorigenesis and development of hepatocellular carcinoma (HCC). However, there are not many researches to predict the prognosis of HCC using autophagy-related genes. Therefore, based on the clinical information and RNA-Seq data of The Cancer Genome Atlas data portal (TCGA), 13 autophagy‑related gene pairs were screened to build the autophagy‑related signature to predict the prognosis by least absolute shrinkage and selection operator (LASSO) regression analysis. Besides, the International Cancer Genome Consortium (ICGC) cohort was further applied to verify the autophagy‑related prognostic signature. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were also used to predict the relevant function of the autophagy-related gene pairs signature. As shown in the results, the autophagy-related gene pairs were mainly involved in process utilizing autophagic mechanism, autophagy, macroautophagy and cellular response to oxidative stress. The immune cell levels in the high-risk and low-risk group were explored, which showed that the three immune cells were obviously increased in the high-risk group, while the five immune cells were obviously increased in the low-risk group. In conclusion, an autophagy‑related prognostic signature was established to predict the prognosis of HCC patients with great accuracy and we found that autophagy‑related prognostic signature was related to infiltrating immune cells.
DOI: 10.48597/6wae-w8h5
title: Sulphur_dioxide at Kecskemét

description: Measurement of Sulphur_dioxide at Kecskemét
DOI: 10.48597/6wc9-apxv
title: Sulphur_dioxide at Chopok

description: Measurement of Sulphur_dioxide at Chopok
DOI: 10.48597/7knp-94ne
title: Inorganics in air and particle phase at Rigi

description: Measurement of Inorganics in air and particle phase at Rigi
DOI: 10.6084/m9.figshare.14101562.v1
title: A signature of 13 autophagy‑related gene pairs predicts prognosis in hepatocellular carcinoma

description: Growing evidences suggest that autophagy plays a momentous part in the tumorigenesis and development of hepatocellular carcinoma (HCC). However, there are not many researches to predict the prognosis of HCC using autophagy-related genes. Therefore, based on the clinical information and RNA-Seq data of The Cancer Genome Atlas data portal (TCGA), 13 autophagy‑related gene pairs were screened to build the autophagy‑related signature to predict the prognosis by least absolute shrinkage and selection operator (LASSO) regression analysis. Besides, the International Cancer Genome Consortium (ICGC) cohort was further applied to verify the autophagy‑related prognostic signature. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were also used to predict the relevant function of the autophagy-related gene pairs signature. As shown in the results, the autophagy-related gene pairs were mainly involved in process utilizing autophagic mechanism, autophagy, macroautophagy and cellular response to oxidative stress. The immune cell levels in the high-risk and low-risk group were explored, which showed that the three immune cells were obviously increased in the high-risk group, while the five immune cells were obviously increased in the low-risk group. In conclusion, an autophagy‑related prognostic signature was established to predict the prognosis of HCC patients with great accuracy and we found that autophagy‑related prognostic signature was related to infiltrating immune cells.
DOI: 10.48597/7udc-8ebk
title: Sulphate_total at K-puszta

description: Measurement of Sulphate_total at K-puszta
DOI: 10.48597/7vgt-qmnh
title: Sulphate_total at Beregovo

description: Measurement of Sulphate_total at Beregovo
DOI: 10.48597/7vrs-umz6
title: Inorganics in air and particle phase at Ispra

description: Measurement of Inorganics in air and particle phase at Ispra
DOI: 10.48597/9247-692m
title: VOC (hydrocarbons) at Kosetice (NOAK)

description: Measurement of VOC (hydrocarbons) at Kosetice (NOAK)
DOI: 10.48597/9jde-dsuq
title: Sulphate_total at Payerne

description: Measurement of Sulphate_total at Payerne
DOI: 10.48597/a23s-jkj8
title: Inorganics in precipitation at Keldsnor

description: Measurement of Inorganics in precipitation at Keldsnor
DOI: 10.48597/a8md-68ag
title: VOC (hydrocarbons) at Kosetice (NAOK)

description: Measurement of VOC (hydrocarbons) at Kosetice (NAOK)
DOI: 10.48597/aax5-3nhm
title: Sulphur_dioxide at K-puszta

description: Measurement of Sulphur_dioxide at K-puszta
DOI: 10.48597/afp7-a8q7
title: Acidity at Ispra

description: Measurement of Acidity at Ispra
DOI: 10.48597/amk5-rsqg
title: Inorganics in air and particle phase at Sniezka

description: Measurement of Inorganics in air and particle phase at Sniezka
DOI: 10.6084/m9.figshare.7285826
title: Additional file 1: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S6. Specific data in Fig. 1d. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7285835
title: Additional file 11: of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 5. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-017_T, LTS-018_T, LTS-021_T. (TXT 18408 kb)
DOI: 10.6084/m9.figshare.7285826.v1
title: Additional file 1: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S6. Specific data in Fig. 1d. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7285835.v1
title: Additional file 11: of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 5. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-017_T, LTS-018_T, LTS-021_T. (TXT 18408 kb)
DOI: 10.6084/m9.figshare.24587344
title: Can digital technology promote sustainable agriculture? Empirical evidence from urban China

description: In the face of increasing global unsustainable risks such as poverty, hunger, and pollution. Building sustainable agriculture (SA) in the digital age is a fundamental task for human survival. Based on the coupled coordination perspective, this paper constructs an SA system that takes into account more stakeholders by considering poverty alleviation and income increase (PI), food security (FS), and green agriculture (GA) as subsystems. The impact of digital technology on SA is systematically analyzed through data from 276 prefecture-level and above cities in China from 2005 to 2020. The study shows that digital technology has a significant upgrading effect on SA and its subsystems. And digital technology is more likely to promote SA in the developed eastern region and peripheral cities. Moreover, agricultural productivity and labor productivity play a mediating mechanism in the process of digital technology for SA. Digital financial inclusion fuels the high input process of digital technology for incentivizing SA, PI, and GA, but it cannot affect the highly technical process of digital farming. Further research found that the incentives of digital technology for SA and GA are characterized by the nonlinear characteristic of increasing marginal effects. Due to the second digital divide, there is a U-shaped incentive process of digital technology for PI to fall and then rise. Finally, the spillover nature of digital technology leads to spatial spillovers in its contribution to SA development.
DOI: 10.6084/m9.figshare.24587344.v1
title: Can digital technology promote sustainable agriculture? Empirical evidence from urban China

description: In the face of increasing global unsustainable risks such as poverty, hunger, and pollution. Building sustainable agriculture (SA) in the digital age is a fundamental task for human survival. Based on the coupled coordination perspective, this paper constructs an SA system that takes into account more stakeholders by considering poverty alleviation and income increase (PI), food security (FS), and green agriculture (GA) as subsystems. The impact of digital technology on SA is systematically analyzed through data from 276 prefecture-level and above cities in China from 2005 to 2020. The study shows that digital technology has a significant upgrading effect on SA and its subsystems. And digital technology is more likely to promote SA in the developed eastern region and peripheral cities. Moreover, agricultural productivity and labor productivity play a mediating mechanism in the process of digital technology for SA. Digital financial inclusion fuels the high input process of digital technology for incentivizing SA, PI, and GA, but it cannot affect the highly technical process of digital farming. Further research found that the incentives of digital technology for SA and GA are characterized by the nonlinear characteristic of increasing marginal effects. Due to the second digital divide, there is a U-shaped incentive process of digital technology for PI to fall and then rise. Finally, the spillover nature of digital technology leads to spatial spillovers in its contribution to SA development.
DOI: 10.6084/m9.figshare.7285844
title: Additional file 2: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S2. Biological process of hub genes. (CSV 60 kb)
DOI: 10.6084/m9.figshare.7285844.v1
title: Additional file 2: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S2. Biological process of hub genes. (CSV 60 kb)
DOI: 10.6084/m9.figshare.7285847
title: Additional file 8: of Evidence of peripheral olfactory impairment in the domestic silkworms: insight from the comparative transcriptome and population genetics

description: Table S7. Differentially expressed genes between any two antennal samples. The P-values were adjusted for multiple testing using the Benjamini-Hochberg method. An adjusted P-value (padj) of 0.05 and fold-change of 3 was set as the threshold for significant differential expression. (XLSX 559 kb)
DOI: 10.6084/m9.figshare.7285847.v1
title: Additional file 8: of Evidence of peripheral olfactory impairment in the domestic silkworms: insight from the comparative transcriptome and population genetics

description: Table S7. Differentially expressed genes between any two antennal samples. The P-values were adjusted for multiple testing using the Benjamini-Hochberg method. An adjusted P-value (padj) of 0.05 and fold-change of 3 was set as the threshold for significant differential expression. (XLSX 559 kb)
DOI: 10.6084/m9.figshare.7285850
title: Additional file 12 of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 6. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-019_T, LTS-020_T, LTS-022_T, LTS-023_T, LTS-024_T, LTS-025_T, LTS-026_T, LTS-027_T, LTS-028_T. (TXT 19235 kb)
DOI: 10.6084/m9.figshare.7285850.v1
title: Additional file 12 of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 6. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-019_T, LTS-020_T, LTS-022_T, LTS-023_T, LTS-024_T, LTS-025_T, LTS-026_T, LTS-027_T, LTS-028_T. (TXT 19235 kb)
DOI: 10.6084/m9.figshare.7285853
title: Additional file 3: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S3. Cellular component of hub genes. (CSV 8 kb)
DOI: 10.6084/m9.figshare.7285853.v1
title: Additional file 3: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S3. Cellular component of hub genes. (CSV 8 kb)
DOI: 10.6084/m9.figshare.7285862
title: Additional file 4: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S4. Molecular function of hub genes. (CSV 5 kb)
DOI: 10.6084/m9.figshare.7285862.v1
title: Additional file 4: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S4. Molecular function of hub genes. (CSV 5 kb)
DOI: 10.6084/m9.figshare.7285865
title: Additional file 13: of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 7. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-029_T, LTS-030_T, LTS-031_T. (TXT 14352 kb)
DOI: 10.6084/m9.figshare.7285865.v1
title: Additional file 13: of Landscape of genomic alterations in high-grade serous ovarian cancer from exceptional long- and short-term survivors

description: All Mutect mutations 7. All SNV mutations called by Mutect and annotated by Oncotator for samples LTS-029_T, LTS-030_T, LTS-031_T. (TXT 14352 kb)
DOI: 10.6084/m9.figshare.7285871
title: Additional file 5: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S5. KEGG-enrichment of hub genes. (CSV 2 kb)
DOI: 10.6084/m9.figshare.7285871.v1
title: Additional file 5: of Identification of glioblastomaÂ gene prognosis modules based on weighted gene co-expression network analysis

description: Table S5. KEGG-enrichment of hub genes. (CSV 2 kb)
DOI: 10.14473/csda/nqqijt/v3une8
title: D_V1305.pdf

description: Dotazník
DOI: 10.14473/csda/nqqijt/bmn5sc
title: Nesstar_NS_1305_DataFile.tab

description: Data
DOI: 10.14473/csda/nqqijt/krp61y
title: TI_V1305.pdf

description: Technická informace
DOI: 10.14473/csda/nqqijt/gn1jdw
title: K_V1305.pdf

description: Karty
DOI: 10.14473/csda/nqqijt/qslwkr
title: OM_V1305.pdf

description: Ostatní materiály
DOI: 10.14473/csda/nqqijt/lh0nwx
title: PR06_V1305.pdf

description: Veřejnost o energetice – květen 2013. tisková zpráva CVVM.
DOI: 10.5281/zenodo.3816804
title: Age-depth model ensembles for SISAL v2 speleothem records

description: Age model ensembles created for the SISAL database v2, in supplement to Comas-Bru, Rehfeld, Roesch et al., 2020. Note that an earlier version of this upload contained only ensemble data for 5 methods (interpolation, regression, copRa, Bchron and Bacon). This version adds the trimmed ensemble data from OxCal.
description: SISAL (Speleothem Isotopes Synthesis and Analysis) is a working group of the Past Global Changes (PAGES) programme. We thank PAGES for their support for this activity. KR acknowledges the Deutsche Forschungsgemeinschaft (DFG) through the Emmy Noether programme (code RE3994-2/1) for funding. LCB and SAM acknowledge funding from the Geological Survey Ireland Short Call grant number 2017-SC-056. LCB acknowledges funding from the ERC-funded project GC2.0 (Global Change 2.0: Unlocking the past for a clearer future, grant no. 694481).
description: {"references": ["Comas-Bru, L., Rehfeld, K., Roesch, C., Amirnezhad-Mozhdehi, S., Harrison, S. P., Atsawawaranunt, K., Ahmad, S. M., Ait Brahim, Y., Baker, A., Bosomworth, M., Breitenbach, S. F. M., Burstyn, Y., Columbu, A., Deininger, M., Dem\u00e9ny, A., Dixon, B., Fohlmeister, J., Hatvani, I. G., Hu, J., Kaushal, N., Kern, Z., Labuhn, I., Lechleitner, F. A., Lorrey, A., Martrat, B., Novello, V. F., Oster, J., P\u00e9rez-Mej\u00edas, C., Scholz, D., Scroxton, N., Sinha, N., Ward, B. M., Warken, S., Zhang, H., and the SISAL members: SISALv2: A comprehensive speleothem isotope database with multiple age-depth models, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-39, in review, 2020."]}
DOI: 10.14473/csda/nqqijt/ubxxc7
title: PR04_V1305.pdf

description: Postoje veřejnosti k právům homosexuálů – květen 2013. Tisková zpráva CVVM.
DOI: 10.5281/zenodo.10570754
title: Age-depth model ensembles for SISAL v3 speleothem records

description: Depth-age model ensembles created for the SISAL database v3, in supplement to Kaushal et al., 2024  and building on Comas-Bru, Rehfeld, Roesch et al., 2020.

This upload includes ensemble data for 5 methods (interpolation, linear regression, copRa, Bchron and Bacon) created following the protocol  in previous versions but for newly included entities in the database.

Each file contains a matrix with the first column giving the row number, the second the SISAL v3 sample ID, the third the depth in the speleothem (in mm), and the fourth to 2003rd column contains the 2000 age model ensemble members.
description: SISAL (Speleothem Isotopes Synthesis and Analysis) is a working group of the Past Global Changes (PAGES) programme. We thank PAGES for their support for this activity. KR acknowledges the Deutsche Forschungsgemeinschaft (DFG) through the Emmy Noether programme (code RE3994-2/1) for funding.