cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1kqvdj
title: CCDC 1451928: Experimental Crystal Structure Determination

description: Related Article: Jacob A. Johnson,  Brenna M. Petersen,  Attila Kormos,  Elena Echeverría,  Yu-Sheng Chen,  and Jian Zhang|2016|J.Am.Chem.Soc.|138|10293|doi:10.1021/jacs.6b05626
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.cc1ltkfd
title: CCDC 1484324: Experimental Crystal Structure Determination

description: Related Article: Nadiia I. Gumerova, Alexander Roller, Annette Rompel|2016|Eur.J.Inorg.Chem.|2016|5507|doi:10.1002/ejic.201601198
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.cc1408s6
title: CCDC 1042957: Experimental Crystal Structure Determination

description: Related Article: Jacob A. Johnson,  Brenna M. Petersen,  Attila Kormos,  Elena Echeverría,  Yu-Sheng Chen,  and Jian Zhang|2016|J.Am.Chem.Soc.|138|10293|doi:10.1021/jacs.6b05626
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.cc1kqvfk
title: CCDC 1451929: Experimental Crystal Structure Determination

description: Related Article: Jacob A. Johnson,  Brenna M. Petersen,  Attila Kormos,  Elena Echeverría,  Yu-Sheng Chen,  and Jian Zhang|2016|J.Am.Chem.Soc.|138|10293|doi:10.1021/jacs.6b05626
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.cc1klgby
title: CCDC 1447710: Experimental Crystal Structure Determination

description: Related Article: Jacob A. Johnson,  Brenna M. Petersen,  Attila Kormos,  Elena Echeverría,  Yu-Sheng Chen,  and Jian Zhang|2016|J.Am.Chem.Soc.|138|10293|doi:10.1021/jacs.6b05626
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: 10.25345/c5sb3x99s
title: MassIVE MSV000096579 - Reconstructing Medieval Diets (TRI-DENTUM project, H2020-MSCA-IF-2020 No. 891511)
title: Historical (medieval) dental calculus was analyzed. This dataset is associated to the paper entitled "Reconstructing Medieval Diets: Integrating Stable Isotope and Proteomic Analyses from two European Burial Sites".
DOI: 10.15468/dl.vb7j43
title: Occurrence Download

description: A dataset containing 596 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Senecio cineraria DC.)"
 ]
}

 The dataset includes 596 records from 99 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014533-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-4600
title: FabFramework.Core: Task-Based Robotic Fabrication Framework

description: FabFramework is designed around a Task-Based Fabrication methodology, which transforms digital design models into sequential, data-driven robotic tasks. This approach ensures precise fabrication operations through simulation and predefined parameters, following a three-step process. &lt;br&gt;&lt;br&gt;

The framework begins with the Design layer, where the user design model is converted into a model consisting of beams and plates with defined geometric attributes. The Fab layer builds on this by adjusting these elements to fit specific fabrication requirements, such as positioning, assembly sequence, and alignment within the robotic workspace. This layer also accommodates unique connection methods and robotic adjustments. Finally, the Task layer sequences the robot’s actions—like picking, placing, and tool changes—to streamline assembly, with frame-based tasks for precise movements and non-frame-based tasks for simpler actions. &lt;br&gt;&lt;br&gt;

FabFramework is setup to be integrated with the ICD Virtual Robot Grasshopper Plugin, allowing users to simulate and verify the entire fabrication process digitally before fabrication.
description: Visual Studio, 2022
DOI: 10.15468/dl.53t2k8
title: Occurrence Download

description: A dataset containing 260 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-5.47703 36.1175,-5.4823 36.11497,-5.49008 36.11531,-5.49555 36.11274,-5.49243 36.11217,-5.48895 36.11472,-5.48694 36.11404,-5.48173 36.11451,-5.47703 36.1175))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 260 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014534-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.20363/zfmk-coll.blattodea-2023-02
title: ZFMK Blattodea collection

description: The Blattodea collection at the Leibniz Institute for the Analysis of Biodiversity Change (LIB) - Museum Koenig Bonn contains large parts of the collection of Johann Klapperich as well as the collection of A. Schoop and the permanent loan of the Zoo Cologne
DOI: 10.5281/zenodo.14266573
title: Dataset: Evaluation of Physicochemical Properties of Ipsapirone  Derivatives Based on Chromatographic and Chemometric  Approaches

description: Dataset for publication
DOI: 10.5281/zenodo.14266574
title: Dataset: Evaluation of Physicochemical Properties of Ipsapirone  Derivatives Based on Chromatographic and Chemometric  Approaches

description: Dataset for publication
DOI: 10.15468/dl.dwx37w
title: Occurrence Download

description: A dataset containing 226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Narcissus cuatrecasasii Fern.Casas, M.Laínz & Ruíz Rejón"
 ]
}

 The dataset includes 226 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014535-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.env7fn
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Senecio calthifolius (Maxim.) Maxim.)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014536-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.20363/zfmk-coll.phasmatodea-2018-11
title: ZFMK Phasmatodea collection

description: The Phasmatodea Collection at the Zoological Research Museum Alexander Koenig contains large parts of the collection of Johann Klapperich as well as the collections of D. Bornhalm, Sigfrid Ingrisch, Josef Szijj and the permanent loan of the Zoo Cologne.
DOI: 10.15468/dl.nwd95b
title: Occurrence Download

description: A dataset containing 234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-5.4823 36.11497,-5.49008 36.11531,-5.49555 36.11274,-5.49243 36.11217,-5.48895 36.11472,-5.48694 36.11404,-5.48173 36.11451,-5.4823 36.11497)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 234 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014538-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-3784
title: Data for: Olefin Metathesis under Spatial Confinement and Continuous Flow: Investigation of Isomeric Side Reactions with a Grubbs-Hoveyda Type Catalyst

description: Olefin Metathesis under Spatial Confinement and Continuous Flow: We study olefin metathesis with a focus on isomers formed as by-products. For that purpose, a 2D-LC/MS system is implemented, showing decisive advantages over common 1H NMR analysis. As a consequence, it became possible to determine the influence of catalyst deactivation on both yield and selectivity of the reaction.
DOI: 10.6084/m9.figshare.26378702
title: Identification of <i>MORN3</i> and <i>LLGL2</i> as novel diagnostic biomarkers for latent tuberculosis infection using machine learning strategies and experimental verification

description: Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible molecular mechanisms of LTBI pathogenesis. Three GEO datasets (GSE19439, GSE19444, and GSE62525) were utilized to analyze the differentially expressed genes (DEGs). Functional enrichment studies were then performed on these DEGs. To ascertain potential diagnostic biomarkers, we utilized two different machine learning techniques: LASSO and RF. ROC curves were constructed in both the training and validation datasets to assess the diagnostic efficacy. The expression of identified biomarkers was verified by RT-qPCR in our own Chinese cohort. Using CIBERSORT, we estimated the abundances of 22 immune cell types in LTBI group, and subsequently analyzed the relationship between biomarker expression and immune cell infiltration. 166 DEGs were identified between ATB and LTBI groups, which are primarily associated with immune responses, inflammatory signaling pathways, and infection factors. Following that, 22 candidate diagnostic biomarkers for LTBI were selected in the machine learning process. Three up-regulated genes, <i>MORN3</i>, <i>LLGL2</i>, and <i>IFT140</i>, whose expression levels were not previously reported in TB, were validated using the training and validation cohort datasets. In our own Chinese cohort, we also found that <i>MORN3</i> and <i>LLGL2</i> showed good diagnostic effect using RT-qPCR method. Finally, we revealed the specific infiltration features of immune cells in LTBI and observed a notable correlation between potential marker expression and immune cells. <i>MORN3</i> and <i>LLGL2</i> emerged as candidate diagnostic biomarkers for LTBI, following the elucidation of the key immune cell types involved. Our findings will contribute to providing a potential target for early noninvasive diagnosis of LTBI patients.
DOI: 10.6084/m9.figshare.27087948
title: Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma

description: The role of chronoradiobiology in nasopharyngeal carcinoma (NPC) has not been fully elucidated. We sought to investigate the impact of radiotherapy rhythm on the survival outcomes of individuals to explore a chronomodulated radiation strategy to improve prognosis of NPC. A cohort comprising non-metastatic NPC patients subjected to intensity-modulated radiotherapy at Fujian Cancer Hospital between Jan. 2016 and Dec. 2019 was assembled. Rhythmic fluctuation of radiotherapy (RFRT) was quantified based on the temporal distribution of radiation delivery. Cox proportional hazard model was performed to explore the impact of radiotherapy rhythm on all-cause mortality. The maximally selected rank statistics method was employed to discern an optimal cutoff. Sensitivity analyses were conducted to ensure the robustness of observed associations. Our analysis encompassed 2245 patients, with a median follow-up duration of 55 months, during which 315 individuals succumbed. Multivariate Cox regression analysis unveiled a significant correlation between prolonged RFRT and heightened mortality risk in NPC patients (HR, 1.17, 95% CI, 1.07-1.27, <i>p</i> &lt; .001), a relationship robust to comprehensive adjustment for confounding variables. A cutoff value of 3 h was selected for potential clinical application, beyond which patients exhibited markedly poorer survival outcomes. Subgroup analyses consistently underscored the directional consistency of observed effects. Our study sheds light on the potential advantages of scheduling radiotherapy sessions at consistent times. These findings have implications for optimizing radiotherapy schedules and warrant further investigation into personalized chronotherapy approaches in NPC management.
DOI: 10.6084/m9.figshare.27087948.v1
title: Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma

description: The role of chronoradiobiology in nasopharyngeal carcinoma (NPC) has not been fully elucidated. We sought to investigate the impact of radiotherapy rhythm on the survival outcomes of individuals to explore a chronomodulated radiation strategy to improve prognosis of NPC. A cohort comprising non-metastatic NPC patients subjected to intensity-modulated radiotherapy at Fujian Cancer Hospital between Jan. 2016 and Dec. 2019 was assembled. Rhythmic fluctuation of radiotherapy (RFRT) was quantified based on the temporal distribution of radiation delivery. Cox proportional hazard model was performed to explore the impact of radiotherapy rhythm on all-cause mortality. The maximally selected rank statistics method was employed to discern an optimal cutoff. Sensitivity analyses were conducted to ensure the robustness of observed associations. Our analysis encompassed 2245 patients, with a median follow-up duration of 55 months, during which 315 individuals succumbed. Multivariate Cox regression analysis unveiled a significant correlation between prolonged RFRT and heightened mortality risk in NPC patients (HR, 1.17, 95% CI, 1.07-1.27, <i>p</i> &lt; .001), a relationship robust to comprehensive adjustment for confounding variables. A cutoff value of 3 h was selected for potential clinical application, beyond which patients exhibited markedly poorer survival outcomes. Subgroup analyses consistently underscored the directional consistency of observed effects. Our study sheds light on the potential advantages of scheduling radiotherapy sessions at consistent times. These findings have implications for optimizing radiotherapy schedules and warrant further investigation into personalized chronotherapy approaches in NPC management.
DOI: 10.6084/m9.figshare.26378702.v1
title: Identification of <i>MORN3</i> and <i>LLGL2</i> as novel diagnostic biomarkers for latent tuberculosis infection using machine learning strategies and experimental verification

description: Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible molecular mechanisms of LTBI pathogenesis. Three GEO datasets (GSE19439, GSE19444, and GSE62525) were utilized to analyze the differentially expressed genes (DEGs). Functional enrichment studies were then performed on these DEGs. To ascertain potential diagnostic biomarkers, we utilized two different machine learning techniques: LASSO and RF. ROC curves were constructed in both the training and validation datasets to assess the diagnostic efficacy. The expression of identified biomarkers was verified by RT-qPCR in our own Chinese cohort. Using CIBERSORT, we estimated the abundances of 22 immune cell types in LTBI group, and subsequently analyzed the relationship between biomarker expression and immune cell infiltration. 166 DEGs were identified between ATB and LTBI groups, which are primarily associated with immune responses, inflammatory signaling pathways, and infection factors. Following that, 22 candidate diagnostic biomarkers for LTBI were selected in the machine learning process. Three up-regulated genes, <i>MORN3</i>, <i>LLGL2</i>, and <i>IFT140</i>, whose expression levels were not previously reported in TB, were validated using the training and validation cohort datasets. In our own Chinese cohort, we also found that <i>MORN3</i> and <i>LLGL2</i> showed good diagnostic effect using RT-qPCR method. Finally, we revealed the specific infiltration features of immune cells in LTBI and observed a notable correlation between potential marker expression and immune cells. <i>MORN3</i> and <i>LLGL2</i> emerged as candidate diagnostic biomarkers for LTBI, following the elucidation of the key immune cell types involved. Our findings will contribute to providing a potential target for early noninvasive diagnosis of LTBI patients.
DOI: 10.6084/m9.figshare.25505437
title: The prevalence and risk factors of rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis

description: Interstitial lung disease (ILD) is the most widespread and fatal pulmonary complication of rheumatoid arthritis (RA). Existing knowledge on the prevalence and risk factors of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is inconclusive. Therefore, we designed this review to address this gap. To find relevant observational studies discussing the prevalence and/or risk factors of RA-ILD, EMBASE, Web of Science, PubMed, and the Cochrane Library were explored. The pooled odds ratios (ORs) / hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated with a fixed/ random effects model. While subgroup analysis, meta-regression analysis and sensitivity analysis were carried out to determine the sources of heterogeneity, the <i>I<sup>2</sup></i> statistic was utilized to assess between-studies heterogeneity. Funnel plots and Egger’s test were employed to assess publication bias. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, our review was conducted. A total of 56 studies with 11,851 RA-ILD patients were included in this meta-analysis. The pooled prevalence of RA-ILD was 18.7% (95% CI 15.8–21.6) with significant heterogeneity (<i>I<sup>2</sup></i> = 96.4%). The prevalence of RA-ILD was found to be more likely as a result of several identified factors, including male sex (ORs = 1.92 95% CI 1.70–2.16), older age (WMDs = 6.89, 95% CI 3.10–10.67), having a smoking history (ORs =1.91, 95% CI 1.48–2.47), pulmonary comorbidities predicted (HRs = 2.08, 95% CI 1.89–2.30), longer RA duration (ORs = 1.03, 95% CI 1.01–1.05), older age of RA onset (WMDs =4.46, 95% CI 0.63–8.29), positive RF (HRs = 1.15, 95%CI 0.75-1.77; ORs = 2.11, 95%CI 1.65–2.68), positive ACPA (ORs = 2.11, 95%CI 1.65–2.68), higher ESR (ORs = 1.008, 95%CI 1.002–1.014), moderate and high DAS28 (≥3.2) (ORs = 1.87, 95%CI 1.36–2.58), rheumatoid nodules (ORs = 1.87, 95% CI 1.18-2.98), LEF use (ORs = 1.42, 95%CI 1.08–1.87) and steroid use (HRs= 1.70, 1.13–2.55). The use of biological agents was a protective factor (HRs = 0.77, 95% CI 0.69–0.87). The pooled prevalence of RA-ILD in our study was approximately 18.7%. Furthermore, we identified 13 risk factors for RA-ILD, including male sex, older age, having a smoking history, pulmonary comorbidities, older age of RA onset, longer RA duration, positive RF, positive ACPA, higher ESR, moderate and high DAS28 (≥3.2), rheumatoid nodules, LEF use and steroid use. Additionally, biological agents use was a protective factor.
DOI: 10.6084/m9.figshare.25505437.v1
title: The prevalence and risk factors of rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis

description: Interstitial lung disease (ILD) is the most widespread and fatal pulmonary complication of rheumatoid arthritis (RA). Existing knowledge on the prevalence and risk factors of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is inconclusive. Therefore, we designed this review to address this gap. To find relevant observational studies discussing the prevalence and/or risk factors of RA-ILD, EMBASE, Web of Science, PubMed, and the Cochrane Library were explored. The pooled odds ratios (ORs) / hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated with a fixed/ random effects model. While subgroup analysis, meta-regression analysis and sensitivity analysis were carried out to determine the sources of heterogeneity, the <i>I<sup>2</sup></i> statistic was utilized to assess between-studies heterogeneity. Funnel plots and Egger’s test were employed to assess publication bias. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, our review was conducted. A total of 56 studies with 11,851 RA-ILD patients were included in this meta-analysis. The pooled prevalence of RA-ILD was 18.7% (95% CI 15.8–21.6) with significant heterogeneity (<i>I<sup>2</sup></i> = 96.4%). The prevalence of RA-ILD was found to be more likely as a result of several identified factors, including male sex (ORs = 1.92 95% CI 1.70–2.16), older age (WMDs = 6.89, 95% CI 3.10–10.67), having a smoking history (ORs =1.91, 95% CI 1.48–2.47), pulmonary comorbidities predicted (HRs = 2.08, 95% CI 1.89–2.30), longer RA duration (ORs = 1.03, 95% CI 1.01–1.05), older age of RA onset (WMDs =4.46, 95% CI 0.63–8.29), positive RF (HRs = 1.15, 95%CI 0.75-1.77; ORs = 2.11, 95%CI 1.65–2.68), positive ACPA (ORs = 2.11, 95%CI 1.65–2.68), higher ESR (ORs = 1.008, 95%CI 1.002–1.014), moderate and high DAS28 (≥3.2) (ORs = 1.87, 95%CI 1.36–2.58), rheumatoid nodules (ORs = 1.87, 95% CI 1.18-2.98), LEF use (ORs = 1.42, 95%CI 1.08–1.87) and steroid use (HRs= 1.70, 1.13–2.55). The use of biological agents was a protective factor (HRs = 0.77, 95% CI 0.69–0.87). The pooled prevalence of RA-ILD in our study was approximately 18.7%. Furthermore, we identified 13 risk factors for RA-ILD, including male sex, older age, having a smoking history, pulmonary comorbidities, older age of RA onset, longer RA duration, positive RF, positive ACPA, higher ESR, moderate and high DAS28 (≥3.2), rheumatoid nodules, LEF use and steroid use. Additionally, biological agents use was a protective factor.