cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1159803.10fu
title: SH1159803.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159807.10fu
title: SH1159807.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159814.10fu
title: SH1159814.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159815.10fu
title: SH1159815.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159827.10fu
title: SH1159827.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159830.10fu
title: SH1159830.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1159836.10fu
title: SH1159836.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.tbx2hy
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample)",
 "Country is China",
 "OccurrenceStatus is Present",
 "StateProvince is 浙江",
 "TaxonKey is Yushania Keng f."
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000523-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.675t44
title: Occurrence Download

description: A dataset containing 461 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Venezuela (Bolivarian Republic of), Brazil, French Guiana, Peru, Colombia, Bolivia (Plurinational State of), Ecuador, Paraguay)",
 "Geometry POLYGON((-46.3556 -2.04041,-48.55401 11.32991,-71.87951 13.64733,-87.13109 0.65034,-54.97937 -28.61914,-53.57282 -23.35466,-63.75489 -9.33495,-46.3556 -2.04041))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Astronotus ocellatus (Agassiz, 1831)"
 ]
}

 The dataset includes 461 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000525-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5zn49w
title: Occurrence Download

description: A dataset containing 352882 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA",
 "Geometry POLYGON((-127.95761 48.96976,-128.32532 33.52832,-115.7644 26.07842,-93.47546 23.32099,-77.96843 22.72361,-67.2426 34.61942,-63.5878 46.86059,-77.44421 54.29894,-115.01156 53.10905,-126.09003 49.04002,-127.95761 48.96976))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Libellulidae",
 "Year 1990-2020"
 ]
}

 The dataset includes 352882 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000517-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uk6y3x
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "TaxonKey is Branchinotogluma Pettibone, 1985"
 ]
}

 The dataset includes 26 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000526-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25376/hra.28660988
title: Paper s10522-024-10181-z.pdf

description:  Alzheimer's disease (AD) and osteoporosis (OP) pose distinct but  interconnected health challenges, both significantly impacting the aging  population. AD, a neurodegenerative disorder characterized by memory  impairment and cognitive decline, is primarily associated with the  accumulation of abnormally folded amyloid beta (Aβ) peptides and  neurofibrillary tangles in the brain. OP, a skeletal disorder marked by  low bone mineral density, involves dysregulation of bone remodeling and  is associated with an increased risk of fractures. Recent studies have  revealed an intriguing link between AD and OP, highlighting shared  pathological features indicative of common regulatory pathophysiological  pathways. In this article, we elucidate the signaling mechanisms that  regulate the pathology of AD and OP and offer insights into the  intricate network of factors contributing to these conditions. We also  examine the role of bone-derived factors in the progression of AD,  underscoring the plausibility of bidirectional communication between the  brain and the skeletal system. The presence of amyloid plaques in the  brain of individuals with AD is akin to the accumulation of brain Aβ in  vascular dementia, pointing towards the need for further investigation  of shared molecular mechanisms. Moreover, we discuss the role of  bone-derived microRNAs that may regulate the pathological progression of  AD, providing a novel perspective on the role of skeletal factors in  neurodegenerative diseases. The insights presented here should help  researchers engaged in exploring innovative therapeutic approaches  targeting both neurodegenerative and skeletal disorders in aging  populations.
DOI: 10.25376/hra.28660988.v1
title: Paper s10522-024-10181-z.pdf

description:  Alzheimer's disease (AD) and osteoporosis (OP) pose distinct but  interconnected health challenges, both significantly impacting the aging  population. AD, a neurodegenerative disorder characterized by memory  impairment and cognitive decline, is primarily associated with the  accumulation of abnormally folded amyloid beta (Aβ) peptides and  neurofibrillary tangles in the brain. OP, a skeletal disorder marked by  low bone mineral density, involves dysregulation of bone remodeling and  is associated with an increased risk of fractures. Recent studies have  revealed an intriguing link between AD and OP, highlighting shared  pathological features indicative of common regulatory pathophysiological  pathways. In this article, we elucidate the signaling mechanisms that  regulate the pathology of AD and OP and offer insights into the  intricate network of factors contributing to these conditions. We also  examine the role of bone-derived factors in the progression of AD,  underscoring the plausibility of bidirectional communication between the  brain and the skeletal system. The presence of amyloid plaques in the  brain of individuals with AD is akin to the accumulation of brain Aβ in  vascular dementia, pointing towards the need for further investigation  of shared molecular mechanisms. Moreover, we discuss the role of  bone-derived microRNAs that may regulate the pathological progression of  AD, providing a novel perspective on the role of skeletal factors in  neurodegenerative diseases. The insights presented here should help  researchers engaged in exploring innovative therapeutic approaches  targeting both neurodegenerative and skeletal disorders in aging  populations.
DOI: 10.34760/67e2c973d525b
title: UC4M
title: URinControl4men

description: A pragmatic non-inferiority randomized controlled trial in men with lower urinary tract symptoms that compares the cost-effectiveness of an online self-management program to Care-as-usual.
description: General Design

Type: Clinical trial
Data collection type: Prospective
Design: Longitudinal
Design description: A pragmatic non-inferiority randomized controlled trial with 6 month follow-up
Start/End data collection: 2022 until 2024
External identifiers: Clinical Trials.gov: NCT05356260


Population

Countries: Netherlands (the)
Number of participants: 175
Number of participants with samples: 0
Population age groups: Adult (18+ years)
Main medical condition: XVIII Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified
Inclusion criteria: Health status inclusion criterion
Other inclusion criteria: Men with lower urinary tract symptoms aged over 18
Exclusion criteria: Health status inclusion criterion
Other exclusion criteria: Men with complicated LUTS who should seek urgent care, including those with nocturnal incontinence (e.g., chronic urinary retention), the inability to void despite urgency (e.g., acute urinary retention), and with sudden onset or worsening LUTS (e.g., urinary tract infections).
DOI: 10.15468/dl.aa9jk2
title: Occurrence Download

description: A dataset containing 3391 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Felis silvestris silvestris"
 ]
}

 The dataset includes 3391 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000527-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60629/p82q-a843
title: Joint Growth Trajectories of Ideal L2 Writing Self, Enjoyment, and Anxiety as Predictors of L2 Writing Achievement: Linear vs. Curvilinear Growth Curve Modeling

description: <p><span style="color:rgb( 51 , 51 , 51 )">This study investigated the co-development of the ideal L2 writing self, writing enjoyment, and writing anxiety over time, as well as their predictive role in L2 writing achievement, using latent growth curve modeling (LGCM). A total of 145 EFL students in an IELTS writing course completed scales for these constructs across four one-month intervals. Polynomial LGCMs were applied to compare linear, piecewise, and quadratic growth models. Results revealed linear growth with increasing trends from T1 to T4 for the ideal L2 writing self and writing enjoyment, while writing anxiety followed a piecewise trajectory, with an initial decline (T1–T2) followed by stabilization (T2–T4). Significant covariances among the three constructs indicated their interconnected development over time. Initial levels of these factors were not predictive of L2 writing achievement, but their growth trajectories significantly predicted outcomes. These findings highlight the dynamic interplay of emotional and motivational factors in L2 writing development and underscore the importance of longitudinal research in capturing their evolving influence on L2 writing achievement.</span></p>
description: <p>Before conducting the statistical analysis, a normality test was performed on all three variables. Skewness and kurtosis estimates were used to verify the variables&#39; normal distribution. The skewness and kurtosis values were within the -1.96 to 1.96 range, confirming the normal distribution of the data (Collier, 2020). Next, an examination of the assumptions regarding the feasibility of employing LGCM in the research was carried out. Subsequently, LGCM was utilized to test the proposed hypothetical model, which explored the relationships between the initial and growth levels of L2 writing ideal self, L2 writing enjoyment, and L2 writing anxiety using multiwave data (Wickrama et al., 2021). This analysis aimed to investigate the shape (linear vs. nonlinear) and trend (decreasing and increasing) of the trajectories of the three variables at both intra- and inter-individual levels on the four measurement occasions, as well as the dynamic interplay among the variables. Additionally, the study investigated the effect of the covariate, L2 writing achievement, on the intercepts and slopes of L2 writing enjoyment, anxiety, and L2 writing ideal self. Data analysis was conducting using LGCM in Mplus 7.4. (Muthen & Muthen, 2017). To evaluate the model fit, goodness-of-fit indices were employed, including the comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). The acceptance criteria of these indices were as follows: CFI and TLI ⩾ .90 and ⩾ .95, and RMSEA and SRMR ⩽ .08 and ⩽ .05, indicating adequate and excellent fit indices, respectively (Hu & Bentler, 1999).</p>
DOI: 10.15468/dl.3wns79
title: Occurrence Download

description: A dataset containing 23922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-4.33433 39.8009,-4.21871 39.8009,-4.21871 39.90645,-4.33433 39.90645,-4.33433 39.8009))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 23922 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000528-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9pkkrp
title: Occurrence Download

description: A dataset containing 136566 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "OccurrenceStatus is Present",
 "TaxonKey is Canidae"
 ]
}

 The dataset includes 136566 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000519-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48544/a1ab4e54-ed51-4bac-b72f-dc65e442d4c7
title: HELIO's in de Praktijk
DOI: 10.15468/dl.hrf5d9
title: Occurrence Download

description: A dataset containing 299222 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Occurrence evidence)",
 "Country is New Caledonia",
 "IucnRedListCategory is one of (NE, DD, LC)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 299222 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000514-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9ghht
title: Occurrence Download

description: A dataset containing 176391 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Canidae"
 ]
}

 The dataset includes 176391 records from 186 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000522-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2k7ymd
title: CCDC 2361134: Experimental Crystal Structure Determination

description: Related Article: Alexander G. Medvedev, Elena A. Mel'nik, Alexey A. Mikhaylov, Nikita S. Mayorov, Tatiana A. Tripol'skaya, Ovadia Lev, Petr V. Prikhodchenko, Andrei V. Churakov|2025|CrystEngComm|27|1896|doi:10.1039/D4CE01109K
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.cc2klcn6
title: CCDC 2371148: Experimental Crystal Structure Determination

description: Related Article: Hayato Fujimoto, Teruki Nishioka, Kazuya Imachi, Satoshi Ogawa, Rio Nishimura, Mamoru Tobisu|2025|J.Am.Chem.Soc.|147|8138|doi:10.1021/jacs.5c00882
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.cc2kmqb8
title: CCDC 2372440: Experimental Crystal Structure Determination

description: Related Article: Yicong Lv, Xiantan Lin, Fafa Wu, Zengshan Yue, Fen Zhang, Xiaoqi Li, Qingyin Wei, Kai Li, Qianxi Wang, Junhua Luo, Xitao Liu|2025|Inorg.Chem.Front.|12|2691|doi:10.1039/D5QI00263J
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.