cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6362526
title: GERONTE H2020 Project - GERDAT002 - Composition of the health care professional consortium

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community</strong> <strong>with a dataset of core health care professionals that should be involvoed in the evaluation and treatment trajectories of older patients with cancer and multimorbidity.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of the GerOnTe care pathway was to determine which health care professionals should be included in the health care professional consortium (HPC) providing care for the patient. Beforehand, we had considered the option of four core members and at least eight other participants depending on the patient’s specificities or profile. Based on clinical experience, we developed a list of 15 potential participants, including general practitioner, one or more oncology specialists (such as surgeons, medical oncologists, radiotherapists), geriatrician, oncology nurse, social worker, clinical pharmacist, physiotherapist, anaesthesiologist, home care nurse, dietician, occupational therapist, spiritual helpers/clerics, psychologist/psychiatrist, palliative care specialist, organ-specific physician(s) such as cardiologist, pulmonologist, nephrologist, rheumatologist etc. This list was presented to the expert panel, and they were asked to determine whether or not these participants should be involved in decision-making and/or the subsequent oncologic care trajectory; experts could specify if these participants should be involved for all patients, only in specific situations/profiles, or did not need to be involved. The results of this expert panel survey and the subsequent composition of the health care professional consortium forms the basis of this dataset.
DOI: 10.5281/zenodo.6362527
title: GERONTE H2020 project - GERDAT003 - Core intrinsic capacity dataset

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a dataset of intrinsic capacity/frailty data to be included and assessed in the evaluation of older patients with cancer and multimorbidity.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of the GerOnTe care pathway was to determine which intrinsic capacity/frailty information is need for optimizing treatment decision making and the subsequent care trajectory. We developed a list of comorbidities and intrinsic capacity/frailty itmes from literature and subsequently asked an expert panel to determine which of these were relevant for oncologic decision making and care. This led to the composition of a dataset to be included in the GERONTE care pathway, which is shown in this dataset. These data can to be included in the evaluation of older patients with cancer and multimorbidity to determine the feasibility of treatment and additional care needs
DOI: 10.5281/zenodo.6334723
title: GERONTE H2020 project - GERDAT003 - Core intrinsic capacity dataset

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a dataset of intrinsic capacity/frailty data to be included and assessed in the evaluation of older patients with cancer and multimorbidity.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of the GerOnTe care pathway was to determine which intrinsic capacity/frailty information is need for optimizing treatment decision making and the subsequent care trajectory. We developed a list of comorbidities and intrinsic capacity/frailty itmes from literature and subsequently asked an expert panel to determine which of these were relevant for oncologic decision making and care. This led to the composition of a dataset to be included in the GERONTE care pathway, which is shown in this dataset. These data can to be included in the evaluation of older patients with cancer and multimorbidity to determine the feasibility of treatment and additional care needs
DOI: 10.6073/pasta/f00a245fd9461529b8cd9d992d7e3a2f
title: LAGOS - Predicted and observed maximum depth values for lakes in a 17-state region of the U.S.

description: This dataset includes predicted and observed values of maximum depth for lakes in the upper Midwest and northeast United States. All observed values came from LAGOS ver 1.040.0 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 40 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, observed maximum depth values (n = 8164) were used to train and validate a predictive mixed effects model for lake depth using terrestrial and lake morphology as predictors (Oliver et al., submitted). Predicted values (n = 50 607) generated by the model had a root mean squared error of 7.1 m. This research was supported by the NSF Macrosystem Biology awards 1065786, 1065818, and 1065649.
DOI: 10.5281/zenodo.6362529
title: GERONTE H2020 project - GERDAT004 - Dataset of self-management recommendations

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a dataset of self-management recommendations that can be used in the care for older patients with cancer and multimorbidity.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. Patient empowerment by supporting self-management is an important component of the Geronte care pathway. As patients will be monitoring themselves at home, to register side-effects of treatment, decompensation of comorbidities and signs of functional decline, they will also be faced with questions about how to deal with the issues that they are having. While one important component of the care pathway is early signalling of complications to allow for early intervention by health care professionals, there is also a lot that patients can do for themselves at home to enhance their life-style, decrease burden of signs and symptoms or to improve outcomes. This led to the composition of a dataset to be included in the GERONTE care pathway, which is presented here.
DOI: 10.5281/zenodo.6334770
title: GERONTE H2020 project - GERDAT004 - Dataset of self-management recommendations

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a dataset of self-management recommendations that can be used in the care for older patients with cancer and multimorbidity.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. Patient empowerment by supporting self-management is an important component of the Geronte care pathway. As patients will be monitoring themselves at home, to register side-effects of treatment, decompensation of comorbidities and signs of functional decline, they will also be faced with questions about how to deal with the issues that they are having. While one important component of the care pathway is early signalling of complications to allow for early intervention by health care professionals, there is also a lot that patients can do for themselves at home to enhance their life-style, decrease burden of signs and symptoms or to improve outcomes. This led to the composition of a dataset to be included in the GERONTE care pathway, which is presented here.
DOI: 10.6084/m9.figshare.16578275
title: Meta-regression data

description: Dataset of meta-regression included in the study "Effects of physical activity levels on efficacy of vaccination"<br>
DOI: 10.5281/zenodo.6362534
title: GERONTE H2020 project - GERDAT005 - Intrinsic capacity evaluation and intervention protocol

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a protocol for the evaluation of intrinsic capacity and frailty, with subsequent interventions aimed at optimizing health status and support for older patients with multimorbidity and cancer.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of Geronte is to take account of intrinsic capacity. Most older patients who are diagnosed with cancer also suffer from other illnesses and impairments that could affect their prognosis, priorities and ability to tolerate and benefit from treatment. For tailored oncologic decision making, it is essential to obtain a complete overview of the patient’s health status. This dataset contains the protocol for evaluation intrinsic capacity and potential interventions for impairments or vulnerabilities that were identified in this evaluation. It is going to be used in the assessment and management of older patients with multimorbidity and cancer, within the GERONTE care pathway.
DOI: 10.5281/zenodo.6334779
title: GERONTE H2020 project - GERDAT005 - Intrinsic capacity evaluation and intervention protocol

description: <strong>The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a protocol for the evaluation of intrinsic capacity and frailty, with subsequent interventions aimed at optimizing health status and support for older patients with multimorbidity and cancer.</strong> GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of Geronte is to take account of intrinsic capacity. Most older patients who are diagnosed with cancer also suffer from other illnesses and impairments that could affect their prognosis, priorities and ability to tolerate and benefit from treatment. For tailored oncologic decision making, it is essential to obtain a complete overview of the patient’s health status. This dataset contains the protocol for evaluation intrinsic capacity and potential interventions for impairments or vulnerabilities that were identified in this evaluation. It is going to be used in the assessment and management of older patients with multimorbidity and cancer, within the GERONTE care pathway.
DOI: 10.5281/zenodo.6362535
title: GERONTE H2020 project - GERDAT006 - Dataset of symptoms and proms for specific cancer types and gender

description: This dataset describes a series of symptoms, potentially indicative of treatment-related complications, destabilised comorbidity or functional decline, to be used in the Geronte project for symptoms monitoring in older patients with multimorbidity during and after their cancer treatment
DOI: 10.5281/zenodo.6342645
title: GERONTE H2020 project - GERDAT006 - Dataset of symptoms and proms for specific cancer types and gender

description: This dataset describes a series of symptoms, potentially indicative of treatment-related complications, destabilised comorbidity or functional decline, to be used in the Geronte project for symptoms monitoring in older patients with multimorbidity during and after their cancer treatment
DOI: 10.5517/ccdc.csd.cc27n48b
title: CCDC 2074931: Experimental Crystal Structure Determination

description: Related Article: Paul T. Ludford, Shenghua Yang, Marcela S. Bucardo, Yitzhak Tor|2022|Chem.-Eur.J.|28|e202104472|doi:10.1002/chem.202104472
DOI: 10.5517/ccdc.csd.cc27nnyj
title: CCDC 2075448: Experimental Crystal Structure Determination

description: Related Article: Paul T. Ludford, Shenghua Yang, Marcela S. Bucardo, Yitzhak Tor|2022|Chem.-Eur.J.|28|e202104472|doi:10.1002/chem.202104472
DOI: 10.5517/ccdc.csd.cc28cwfz
title: CCDC 2096791: Experimental Crystal Structure Determination

description: Related Article: Jiwei Wang, Congyun Xie, Xiang Cheng, Ye Liu, Jun Zhang|2022|Chem.-Eur.J.|28|e202103306|doi:10.1002/chem.202103306
DOI: 10.5517/ccdc.csd.cc298st6
title: CCDC 2123618: Experimental Crystal Structure Determination

description: Related Article: Emily A. Boyd, Julie A. Hopkins Leseberg, Emma L. Cosner, Davide Lionetti, Wade C. Henke, Victor W. Day, James D. Blakemore|2022|Chem.-Eur.J.|28|e202104389|doi:10.1002/chem.202104389
DOI: 10.5517/ccdc.csd.cc29hvg4
title: CCDC 2130396: Experimental Crystal Structure Determination

description: Related Article: Akinori Honda, Yukie Hibi, Kazuma Matsumoto, Masato Kawai, Kazuo Miyamura|2022|RSC Advances|12|7229|doi:10.1039/D2RA00942K
DOI: 10.5517/ccdc.csd.cc2bbtgz
title: CCDC 2155351: Experimental Crystal Structure Determination

description: Related Article: M. Chodkiewicz, S. Pawlędzio, M. Woińska, K. Woźniak|2022|IUCrJ|9|298|doi:10.1107/S2052252522000690
DOI: 10.5517/ccdc.csd.cc2bbth0
title: CCDC 2155352: Experimental Crystal Structure Determination

description: Related Article: M. Chodkiewicz, S. Pawlędzio, M. Woińska, K. Woźniak|2022|IUCrJ|9|298|doi:10.1107/S2052252522000690
DOI: 10.5517/ccdc.csd.cc2bbtj1
title: CCDC 2155353: Experimental Crystal Structure Determination

description: Related Article: M. Chodkiewicz, S. Pawlędzio, M. Woińska, K. Woźniak|2022|IUCrJ|9|298|doi:10.1107/S2052252522000690
DOI: 10.5517/ccdc.csd.cc2bbtk2
title: CCDC 2155354: Experimental Crystal Structure Determination

description: Related Article: M. Chodkiewicz, S. Pawlędzio, M. Woińska, K. Woźniak|2022|IUCrJ|9|298|doi:10.1107/S2052252522000690
DOI: 10.5517/ccdc.csd.cc2bbtl3
title: CCDC 2155355: Experimental Crystal Structure Determination

description: Related Article: M. Chodkiewicz, S. Pawlędzio, M. Woińska, K. Woźniak|2022|IUCrJ|9|298|doi:10.1107/S2052252522000690
DOI: 10.5281/zenodo.6362545
title: dataset related to article "EXPANDING THE GENETIC SPECTRUM OF PRIMARY FAMILIAL BRAIN CALCIFICATION DUE TO SLC2OA2 MUTATIONS: A CASE SERIES"

description: Sanger sequences (.abi files) of all patients of our Fondazione Besta Cohort.
DOI: 10.5281/zenodo.6362544
title: dataset related to article "EXPANDING THE GENETIC SPECTRUM OF PRIMARY FAMILIAL BRAIN CALCIFICATION DUE TO SLC2OA2 MUTATIONS: A CASE SERIES"

description: Sanger sequences (.abi files) of all patients of our Fondazione Besta Cohort.
DOI: 10.5281/zenodo.6362510
title: Head movement and heartbeat data while playing VR games

description: This dataset was collected while 30 different participants played five different VR games (Aircar, Beat Saber, Moss, Arizona Sunshine, and SUPERHOT). It includes the head movement data, heartbeat data, and SSQ data.
DOI: 10.5281/zenodo.6362583
title: SciExpeM - 10.5281/zenodo.6362583

description: Sun, Wenyu; Wang, Guoqing; Li, Shuang; Zhang, Ruzheng; Yang, Bin; Yang, Jiuzhong; Li, Yuyang; Westbrook, Charles K., 0000-0001-6552-2342; Law, Chung K. - Proceedings Of The Combustion Institute, 2017, (36), 1269-1278
DOI: 10.5281/zenodo.6362582
title: SciExpeM - 10.5281/zenodo.6362583

description: Sun, Wenyu; Wang, Guoqing; Li, Shuang; Zhang, Ruzheng; Yang, Bin; Yang, Jiuzhong; Li, Yuyang; Westbrook, Charles K., 0000-0001-6552-2342; Law, Chung K. - Proceedings Of The Combustion Institute, 2017, (36), 1269-1278
DOI: 10.6084/m9.figshare.19368788.v1
title: Med student survey breakdown results.pdf

description: Medical student perceptions of medical teaching during COVID - individual responses
DOI: 10.6084/m9.figshare.19368788
title: Med student survey breakdown results.pdf

description: Medical student perceptions of medical teaching during COVID - individual responses
DOI: 10.25345/c50c4sn8q
title: MassIVE MSV000089070 - GNPS East Mediterranean seaweed samples
title: Screening of various East Mediterranean seaweeds collected during 2019 as part of Ph.D. project