cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8095046
title: Data from: Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.

description: This data accompanies the paper entitled <strong><em>Biochemical, structural and dynamical characterizations of the lactate dehydrogenase from Selenomonas ruminantium provide information about an intermediate evolutionary step prior to complete allosteric regulation acquisition in the super family of lactate and malate dehydrogenases.</em></strong> The zip archive contains the results of molecular dynamics simulations of the 2 systems investigated in the paper: <em>S. rum</em> and <em>T. mar</em> LDHs. The systems have been simulated at 315 K for <em>S. rum </em>and 340 K for <em>T. mar</em>. Final configurations of the proteins after productions are provided for all the systems in GRO Gromos87 format. Trajectories with the positions of the proteins every 100 ps are provided for all the systems in XTC gromacs format.
DOI: 10.25934/pr00009066
title: Data Challenge - MICRES - Bridging the Gap in Antimicrobial Resistance Decision-Making

description: Antimicrobial Resistance (AMR) remains a pressing global concern that demands a comprehensive, multidisciplinary approach. We have identified a critical gap in the field: the lack of technical expertise among decision-makers to effectively leverage AMR surveillance data for informed actions. To address this challenge, we propose the development of MICRES, an innovative open-source AI-powered AMR analysis and visualization platform. Our goal is to empower decision-makers with minimal or no analytics experience to make sense of AMR data and drive impactful interventions.

MICRES will serve as a groundbreaking solution, enabling stakeholders to unlock the potential of AMR surveillance data through intuitive interfaces and powerful analytics. By harnessing the capabilities of artificial intelligence, MICRES will process and analyze vast amounts of AMR data, providing decision-makers with comprehensive insights into AMR trends, patterns, and risk factors. With this newfound understanding, stakeholders will be able to make informed decisions, identify emerging threats, and optimize resource allocation to combat AMR effectively.

Recognizing the urgency of the AMR crisis, we aim to make MICRES an inclusive platform, accessible to decision-makers with diverse backgrounds and technical proficiencies. By prioritizing user-centric design, we will ensure that individuals with minimal or no analytics experience can easily navigate the platform and derive meaningful insights from complex AMR data. Through intuitive visualizations and interactive features, MICRES will bridge the gap between data and decision-making, empowering users to drive impactful change.

We envision MICRES as an open-source platform, fostering collaboration and knowledge sharing among a wide range of stakeholders and thus expanding the user-base of AMR surveillance data. By creating a community of practice, we will encourage the exchange of expertise and best practices, enabling researchers, healthcare professionals, and policymakers to collectively address the AMR challenge. Through collaborative efforts, we can maximize the potential of MICRES as a transformative tool in the fight against antimicrobial resistance.

In conclusion, we believe we can revolutionize the way decision-makers approach AMR, making informed interventions based on a deeper understanding of complex AMR data. Together, let us bridge the gap in AMR decision-making and pave the way for a future where antimicrobial resistance is effectively managed, ensuring the health and well-being of generations to come.

Thank you for considering our expression of interest, and we eagerly anticipate the opportunity to work together to combat antimicrobial resistance.
DOI: 10.6084/m9.figshare.23618964
title: Escherichia flexneri MAG 02

description: <strong>Genome reconstruction from the Metagenome</strong>
DOI: 10.6084/m9.figshare.23618964.v1
title: Escherichia flexneri MAG 02

description: <strong>Genome reconstruction from the Metagenome</strong>
DOI: 10.5517/ccdc.csd.cc2bf1d7
title: CCDC 2157488: Experimental Crystal Structure Determination

description: Related Article: Na Yang, Anni Li, Hui Gao, Li-Mei Liao, Yu-Ping Yang, Pei-Long Wang, Hongji Li|2023|Green Chemistry|25|5128|doi:10.1039/D2GC04782A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.23618997
title: Clostridiaceae MAG 06

description: <strong>Genome reconstruction from the Metagenome</strong>
DOI: 10.6084/m9.figshare.23618997.v1
title: Clostridiaceae MAG 06

description: <strong>Genome reconstruction from the Metagenome</strong>
DOI: 10.5281/zenodo.8109373
title: Long term contamination (2009-2022) dataset of DDTs and PCBs in zooplankton of Lake Maggiore (Italy)

description: <pre>We reported a 13-year (2009-2022) dataset of legacy POPs (DDT<sub>tot</sub> and sumPCB<sub>14</sub>, from 2016 also isomers and congeners concentrations are reported) in the zooplankton of Lake Maggiore (≥450 µm size fraction). The data were collected seasonally in the framework of a research program, funded by CIPAIS (Commissione Italiana per la Protezione delle Acque Italo-Svizzere), aimed at monitoring the presence of pollutants in the lake biota, particularly in the zooplankton size fraction directly linked to fish consumption. The dataset provides also the Standing Stock Density (SSD) and Standing Stock Biomass (SSB) of pelagic zooplankton organisms belonging to the size fraction ≥450 µm. </pre>
DOI: 10.5281/zenodo.8109372
title: Long term contamination (2009-2022) dataset of DDTs and PCBs in zooplankton of Lake Maggiore (Italy)

description: <pre>We reported a 13-year (2009-2022) dataset of legacy POPs (DDT<sub>tot</sub> and sumPCB<sub>14</sub>, from 2016 also isomers and congeners concentrations are reported) in the zooplankton of Lake Maggiore (≥450 µm size fraction). The data were collected seasonally in the framework of a research program, funded by CIPAIS (Commissione Italiana per la Protezione delle Acque Italo-Svizzere), aimed at monitoring the presence of pollutants in the lake biota, particularly in the zooplankton size fraction directly linked to fish consumption. The dataset provides also the Standing Stock Density (SSD) and Standing Stock Biomass (SSB) of pelagic zooplankton organisms belonging to the size fraction ≥450 µm. </pre>
DOI: 10.25934/pr00009056
title: Data Challenge

description: Our research will exploit the wealth of data available in this challenge on minimum inhibitory concentration (MIC) values to explore how the distributions in MIC vary by key population groupings (such as age or infection type). We will develop a research methodology that quantifies and characterizes these distributions across user-defined groupings and over time to gain insights into different infecting strains and selection pressures. We hypothesize that variation in MIC distribution across different population groupings can provide insight into commonalities or variation in transmission, infection and selective pressure by subpopulations. This will support improved public health practice and better targeting of antibiotic stewardship programmes. 
As a test case, we will explore how resistance prevalence varies by patient age and sex. Antibiotic exposure, healthcare contact and immune system function all vary by age and sex. While preliminary research suggests that there is substantial variation in the trends in antibiotic resistance by demographic factors, it has not been quantified globally. 
We will develop a stepwise analysis that will firstly test for resistance prevalence differences by age and sex across bacteria and antibiotics. Secondly, we will compare MIC distributions with the hypothesis that if MIC distributions within a bacteria for a certain antibiotic vary by age or sex, then the bacteria causing the infections or the resistance mechanisms vary by age suggesting different transmission sources or antibiotic effects. Thirdly, we will explore MIC creep within subpopulations over the years of data provided. We will highlight our findings in a limited number of bacteria-antibiotic combinations (likely within S. aureus and E. coli). 
Finally, we will generate a generalized framework, with open-source code that would allow users to explore MIC distributions across their own desired characteristics (such as infection type). Such analysis would enable more detailed analysis of the most commonly available phenotypic AMR data.
DOI: 10.6084/m9.figshare.19807327
title: Study 1 Metacognitive Accuracy Smartphone Use.omt

description: This file depicts the data from Study 1 from the metacognitive study on smartphone use.
DOI: 10.6084/m9.figshare.19807327.v1
title: Study 1 Metacognitive Accuracy Smartphone Use.omt

description: This file depicts the data from Study 1 from the metacognitive study on smartphone use.
DOI: 10.25934/pr00009059
title: Global Geographic Patterns and Trends of WHO Priority Pathogens and AWaRe Antibiotic Resistances among Children: An Epidemiological Surveillance Study

description: Background and Objectives: Antimicrobial resistance (AMR) is a global health threat affecting all age groups, but the increasing trend of AMR in infants and children has been relatively overlooked. In 2019, antibiotic-resistant bacterial infections led to 1.2 million deaths worldwide, with children under 5 accounting for 20% of these deaths. Urgent actions are needed to address emerging threats specific to children, such as extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales and carbapenem-resistant Enterobacterales, by improving surveillance data.
The burden of AMR in children is compounded by limited availability of paediatric-specific antibiotics and formulations. Given the challenges of conducting clinical trials in this population, leveraging surveillance data becomes crucial to understand the distribution and trends of paediatric AMR. Our previous review identified a lack of paediatric data in this context.
To address this gap, we will utilize the Vivli platform to achieve the following objectives:
Identify global geographic patterns and trends of paediatric WHO priority pathogens using Vivli ATLAS_Antibiotics data.
Investigate geographic patterns and trends of paediatric WHO Access, Watch, and Reserve (AWaRe) antibiotic resistances globally using Vivli ATLAS Antibiotics data.
Examine changes in antimicrobial susceptibility/resistance profiles among children.
 
Methods and Statistical Analysis: Descriptive and analytical epidemiological techniques will assess the data. Geographic mapping and spatial analysis will visualize the global distribution patterns of paediatric WHO priority pathogens and AWaRe antibiotic resistances. Temporal analysis will identify trends and changes in antimicrobial susceptibility profiles over time.
 
Outcomes: This project will provide critical evidence on the distribution and density of paediatric WHO priority pathogens and AWaRe antibiotic resistances. The findings will serve as an alert, highlighting regions and specific antibiotics that require targeted interventions. Ultimately, this study can lead to significant changes in antibiotic usage for paediatric patients, enabling more effective and tailored treatment strategies for children worldwide.
DOI: 10.6084/m9.figshare.21433599
title: Metagenome Assmbled Genomes recovered from the tropical peatlands in the Peruvian Amazon

description: The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store 7.07 Gt of organic carbon while releasing 31.6 – 41.1 Tg methane year–1. However, little is understood about how the microbial communities regulate greenhouse gas (GHG) fluxes from tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic nutrient gradients. we reconstructed 519 metagenome assembled genomes spanning 28 phyla. This folder contains high quality to medium quality metagenome assembled genomes that were used in our annalysis that is published at TBD.
DOI: 10.5517/ccdc.csd.cc2dm226
title: CCDC 2222857: Experimental Crystal Structure Determination

description: Related Article: Jun-Qiang Chen, Hai-Xia Zhang, Zhi-Run Wang, Qin-Long Hong, Jian Zhang|2023|Inorg.Chem.Front.|10|2136|doi:10.1039/D2QI02742A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dybpd
title: CCDC 2232734: Experimental Crystal Structure Determination

description: Related Article: Pan-Ke Zhou, Xiao-Li Lin, Mun Yin Chee, Wen Siang Lew, Tao Zeng, Hao-Hong Li, Xiong Chen, Zhi-Rong Chen, Hui-Dong Zheng|2023|Materials Horizons|10|2535|doi:10.1039/D3MH00037K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dybqf
title: CCDC 2232735: Experimental Crystal Structure Determination

description: Related Article: Pan-Ke Zhou, Xiao-Li Lin, Mun Yin Chee, Wen Siang Lew, Tao Zeng, Hao-Hong Li, Xiong Chen, Zhi-Rong Chen, Hui-Dong Zheng|2023|Materials Horizons|10|2535|doi:10.1039/D3MH00037K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dybrg
title: CCDC 2232736: Experimental Crystal Structure Determination

description: Related Article: Pan-Ke Zhou, Xiao-Li Lin, Mun Yin Chee, Wen Siang Lew, Tao Zeng, Hao-Hong Li, Xiong Chen, Zhi-Rong Chen, Hui-Dong Zheng|2023|Materials Horizons|10|2535|doi:10.1039/D3MH00037K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dybsh
title: CCDC 2232737: Experimental Crystal Structure Determination

description: Related Article: Pan-Ke Zhou, Xiao-Li Lin, Mun Yin Chee, Wen Siang Lew, Tao Zeng, Hao-Hong Li, Xiong Chen, Zhi-Rong Chen, Hui-Dong Zheng|2023|Materials Horizons|10|2535|doi:10.1039/D3MH00037K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f163t
title: CCDC 2235475: Experimental Crystal Structure Determination

description: Related Article: Fangzhi Hu, Zhipeng Sun, Mengzhe Pan, Liang Wang, Lubin Xu, Xiong-Li Liu, Shuai-Shuai Li|2023|Green Chemistry|25|5134|doi:10.1039/D3GC00166K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dxp12
title: CCDC 2232094: Experimental Crystal Structure Determination

description: Related Article: Olamilekan Joseph Ibukun, Milan Gumtya, Surajit Singh, Ananda Shit, M. Douzapau, Debasish Haldar|2023|Mol. Syst. Des. Eng.|8|922|doi:10.1039/D2ME00273F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d1891
title: CCDC 2205752: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d18b2
title: CCDC 2205753: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d18c3
title: CCDC 2205754: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d18d4
title: CCDC 2205755: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d18f5
title: CCDC 2205756: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d18g6
title: CCDC 2205757: Experimental Crystal Structure Determination

description: Related Article: Raju Ram Puniya, Priyanka Takhar, Tanmoy Kalita, Dhruba Jyoti Kalita, Devendra Singh|2023|Mol. Syst. Des. Eng.|8|929|doi:10.1039/D2ME00266C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.8091191
title: Dataset: Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion

description: This dataset is related to "Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion" and contains the raw data obtained.
DOI: 10.5281/zenodo.8091192
title: Dataset: Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion

description: This dataset is related to "Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion" and contains the raw data obtained.
DOI: 10.48329/yc4c-3471
title: CPRD GOLD July 2023

description: The CPRD GOLD database contains longitudinal routinely-collected electronic health records (EHR data) from UK primary care practices using Vision® general practice patient management software. The database captures information on demographic characteristics; diagnoses and symptoms; drug exposures; vaccination history; laboratory tests; and referrals to hospital and specialist care. Access to anonymised data from CPRD is subject to a full licence agreement containing detailed terms and conditions of use. Anonymised patient datasets can be extracted for researchers against specific study specifications, following protocol approval. Further information is available at https://www.cprd.com/data-access.
DOI: 10.6084/m9.figshare.22022938
title: How Endogenous Cultural Institutions May (Not) Shape Farmers’ Climate Adaptation Practices: Learning from Rural Cameroon

description: Climate change is high on the science and policy agenda of sub-Saharan Africa (SSA), requiring context-specific adaptation. Studies on endogenous cultural institutions (ECIs) in climate adaptation are fragmented, impeding policy orientation. This suggests the need for complementary evidence on ECIs to inform adaptation practice. Through a sample of 158 households in rural Cameroon, we contribute to bridge this gap, by: (1) exploring socio-political factors shaping peasant farmers’ compliance with agro-based ECIs, and (2) estimating the effect of ECI compliance on farmers’ adaptation practices. Our estimation revealed the following: While political factors do not sufficiently explain compliance, state influence, mirrored through the application of formal rules negatively affects ECI compliance. Traditional rain forecast significantly explains climate adaptation; however, the pouring of libation does not. The age of peasant farmers also positively affects compliance with ECIs. We conclude that compliance with ECIs manifest in climate adaptation in varying proportions.