cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24912627
title: Supplementary Material for: Higher depressive symptoms in irregular menstrual cycles - converging evidence from cross-sectional and prospective assessments

description: Background: Menstrual cycle regularity is an important marker of reproductive health and associated with physiological and psychological illnesses, as well as experiencing stress. We hypothesized that individuals with irregular menstrual cycles report higher depressive symptom severity, after controlling for stress occurrence. 
Methods: The hypothesis was examined through two measurement approaches: a cross-sectional and a prospective, longitudinal study. In the cross-sectional study, participants (n = 394) reported depressive symptoms and their overall menstrual cycle regularity. In the longitudinal study, participants (n = 77) completed questionnaires on depressive symptoms and stress during the mid-follicular and periovulatory phase of one menstrual cycle. Depressive symptoms were compared between participants with regular and irregular cycles through a Welch t-test and an ANCOVA. 
Results: Participants with irregular menstrual cycles reported more depressive symptoms in the cross-sectional analysis. Similarly, in the longitudinal analysis, the group with a current irregular menstrual cycle reported more depressive symptoms after controlling for stress occurrence. When including only complete data sets without multiple imputation (n = 52), the direction of the effects remained, but did not reach statistical significance. 
Limitations: Although we investigated the menstrual cycle prospectively, it would have been more precise to include two or more cycles and daily sex hormone measurements. Further limitations were the suboptimal statistical power and the data collection during the COVID pandemic. 
Conclusions: The results indicate an association between depressive symptoms and menstrual cycle irregularity. We give recommendations on how to incorporate this in future study designs on women’s mental health.
DOI: 10.13120/c80fbb3e-575c-4c18-bd2d-2376a71ccebf
title: Black Sea - Eutrophication and Acidity aggregated datasets 1935/2023 v2023
title: Black_Sea_-_Eutrophication_and_Acidity_aggregated_datasets_1935/2023_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Black Sea, Marmara Sea and Sea of Azov. Data were aggregated and quality controlled by 'National Institute for Marine Research and Development 'Grigore Antipa' in Romania.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.60893/figshare.jap.24873147.v1
title: Supplementary Material

description: Supplementary Material: Understanding electronic structure tunability by metal dopants for promoting MgB2 decomposition during hydrogenation
DOI: 10.60893/figshare.jap.24873147
title: Supplementary Material

description: Supplementary Material: Understanding electronic structure tunability by metal dopants for promoting MgB2 decomposition during hydrogenation
DOI: 10.13120/a54e0103-137a-4237-8857-005c4f48358e
title: Baltic Sea - Eutrophication and Acidity aggregated datasets 1902/2022 v2023
title: Baltic_Sea_aggregated_eutrophication_and_acidity_datasets_1902-2022_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Baltic Sea. Data were aggregated and quality controlled by "Swedish Meteorological and Hydrological Institute (SMHI)" in Sweden.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.6084/m9.figshare.24968247.v1
title: Basel phages annotation and clusters

description: Annotation of Basel phages using current taxonomy information (Family, Subfamily, Genus) extracted from NCBI Taxonomy (version of DATE) and ICTV (sheet 1); The clustering results (sheet 2).
DOI: 10.13120/74158cb0-a21f-42ea-8a29-72a96b2a0da2
title: Mediterranean Sea - Eutrophication and Acidity aggregated datasets 1911/2022 v2023
title: Mediterranean_Sea_-_Eutrophication_and_Acidity_aggregated_datasets_1911/2022_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Mediterranean Sea. Data were aggregated and quality controlled by the 'Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)' in Greece. 
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets. 
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions (https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.13120/584da372-0a9a-4a9d-9e44-e1bc4b5daf1a
title: Black Sea - Contaminants aggregated datasets 1974/2022 v2023
title: Black_Sea_Contaminants_aggregated_datasets_1974/2022_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Black Sea. Data were harmonised and validated by the ‘National Institute for Marine Research and Development "Grigore Antipa" in Romania. 
The dataset contains water, sediment and biota profiles. The temporal coverage is 1974–2021 for water measurements, 1990–2022 for sediment measurements and 2008–2019 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.6084/m9.figshare.24720567
title: Supplementary Material for: Impact of tumor shrinkage pattern with biweekly triplet gemcitabine+cisplatin+S-1 regimen for biliary tract cancers: Implications for neoadjuvant therapy from the data of KHBO1401 (KHBO1401-1A study)

description: Background:
The multicenter randomized phase III KHBO1401 study (gemcitabine+cisplatin+S-1 [GCS] versus GC in biliary tract cancers [BTC]) demonstrated that GCS not only prolonged patient survival but also achieved a high response rate and that it should be good for neoadjuvant therapy. Therefore, to explore the possibilities of neoadjuvant therapy, we investigated the tumor shrinkage pattern.
Methods:
Among the total of 246 patients enrolled in the KHBO1401, the tumor shrinkage pattern and survival were investigated in patients with measurable BTC (n=183, 74%; GCS, n=91; GC, n=92). 
Results:
The tumor shrinkage pattern could be divided to 4 categories based on the response at 100 days after enrollment: category A (&lt;-30% in size), B (-30% to 0%), C (0% to +20%), and D (&gt;+20%). The GCS arm included more category A and B cases (61 [67%] vs. 33 [36%], P&lt;0.0001). Each category predicted best response and overall survival (P&lt;0.0001). Category A showed sustained tumor response compared with category B; in GCS, the time to maximum tumor response was 165 ± 76 days in category A and 139 ± 78 in category B. Categories C and D did not achieve tumor shrinkage. The maximum tumor shrinkage size in category A was -53% in the GCS arm and -65% in the GC arm (P=0.0892). Twenty percent of patients in the GCS showed tumor regrowth 154 ± 143 days later. 
Conclusion:
GCS provided faster and greater tumor shrinkage with better survival in comparison to GC, although 20% of patients showed re-growth after 6 cycles.
DOI: 10.6084/m9.figshare.24720567.v1
title: Supplementary Material for: Impact of tumor shrinkage pattern with biweekly triplet gemcitabine+cisplatin+S-1 regimen for biliary tract cancers: Implications for neoadjuvant therapy from the data of KHBO1401 (KHBO1401-1A study)

description: Background:
The multicenter randomized phase III KHBO1401 study (gemcitabine+cisplatin+S-1 [GCS] versus GC in biliary tract cancers [BTC]) demonstrated that GCS not only prolonged patient survival but also achieved a high response rate and that it should be good for neoadjuvant therapy. Therefore, to explore the possibilities of neoadjuvant therapy, we investigated the tumor shrinkage pattern.
Methods:
Among the total of 246 patients enrolled in the KHBO1401, the tumor shrinkage pattern and survival were investigated in patients with measurable BTC (n=183, 74%; GCS, n=91; GC, n=92). 
Results:
The tumor shrinkage pattern could be divided to 4 categories based on the response at 100 days after enrollment: category A (&lt;-30% in size), B (-30% to 0%), C (0% to +20%), and D (&gt;+20%). The GCS arm included more category A and B cases (61 [67%] vs. 33 [36%], P&lt;0.0001). Each category predicted best response and overall survival (P&lt;0.0001). Category A showed sustained tumor response compared with category B; in GCS, the time to maximum tumor response was 165 ± 76 days in category A and 139 ± 78 in category B. Categories C and D did not achieve tumor shrinkage. The maximum tumor shrinkage size in category A was -53% in the GCS arm and -65% in the GC arm (P=0.0892). Twenty percent of patients in the GCS showed tumor regrowth 154 ± 143 days later. 
Conclusion:
GCS provided faster and greater tumor shrinkage with better survival in comparison to GC, although 20% of patients showed re-growth after 6 cycles.
DOI: 10.13120/5ba9d89c-1bdc-4b9f-a5c7-3e25c06714fe
title: Greater North Sea and Celtic Seas - Eutrophication and Acidity aggregated datasets 1921/2023 v2023
title: North_Sea_-_Eutrophication_and_Acidity_aggregated_datasets_1921/2023_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Greater North Sea and Celtic Seas. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' in Denmark.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.13120/2b36b4dd-3048-4346-abcc-f6d4e8f65179
title: Baltic Sea - Contaminants aggregated datasets 1974/2021 v2023
title: Baltic_Sea_Contaminants_aggregated_datasets_1974/2021_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Baltic Sea. Data were harmonised and validated by the ‘Swedish Meteorological and Hydrological Institute (SMHI)’ in Sweden. 
The dataset contains water, sediment and biota profiles. The temporal coverage is 1987–2021 for water measurements, 1974–2021 for sediment measurements and 1972-2021 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.13120/0f7e2a09-181a-4984-b5ca-f3d46a1d266c
title: Mediterranean Sea - Contaminants aggregated datasets 1971/2022 v2023
title: Mediterranean_Sea_Contaminants_aggregated_datasets_1971/2022_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Mediterranean Sea. Data were harmonised and validated by the ‘Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)’ in Greece.
The dataset contains water, sediment and biota profiles and timeseries. The temporal coverage is 1974–2020 for water measurements, 1971–2020 for sediment measurements and 1979-2022 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.13120/0db52c13-7e88-41a3-ac63-4db123096cfc
title: Arctic Ocean - Eutrophication and Acidity aggregated datasets 1923/2023 v2023
title: Arctic_Ocean_aggregated_eutrophication_and_acidity_datasets_1923-2023_v2023

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)' in Norway.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).