cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30497771
title: Living sensor display implanted on skin for long-term biomarker monitoring

description: This study introduces a novel approach to biomarker monitoring through the development of a "Living Sensor Display" implanted on the skin, designed for long-term, continuous tracking of biomarkers, such as inflammatory cytokines. By leveraging the natural high selectivity and sensitivity of keratinocyte stem cells (KSCs) to environmental stimuli, we genetically engineered these cells to express fluorescent proteins in response to specific biomarker signals, specifically TNF-α signaling. This innovation allows for the real-time, non-invasive observation, with the only invasive step being the initial implantation, of biomarker levels directly from the skin surface. We constructed tissue-engineered skin with genetically modified KSCs and transplanted it onto mice, where it successfully engrafted long-term, matured to mimic human skin structures, and responsively indicated the presence of TNF-α through visible fluorescence. This living sensor could repeatedly detect inflammatory responses induced by TNF-α and lipopolysaccharides, highlighting its potential for monitoring various physiological and pathological processes over extended periods. This live-sensor display holds promise for advancing health monitoring and disease prevention strategies by enabling continuous, sensitive, and specific in vivo biomarker tracking.
DOI: 10.6084/m9.figshare.30497771.v1
title: Living sensor display implanted on skin for long-term biomarker monitoring

description: This study introduces a novel approach to biomarker monitoring through the development of a "Living Sensor Display" implanted on the skin, designed for long-term, continuous tracking of biomarkers, such as inflammatory cytokines. By leveraging the natural high selectivity and sensitivity of keratinocyte stem cells (KSCs) to environmental stimuli, we genetically engineered these cells to express fluorescent proteins in response to specific biomarker signals, specifically TNF-α signaling. This innovation allows for the real-time, non-invasive observation, with the only invasive step being the initial implantation, of biomarker levels directly from the skin surface. We constructed tissue-engineered skin with genetically modified KSCs and transplanted it onto mice, where it successfully engrafted long-term, matured to mimic human skin structures, and responsively indicated the presence of TNF-α through visible fluorescence. This living sensor could repeatedly detect inflammatory responses induced by TNF-α and lipopolysaccharides, highlighting its potential for monitoring various physiological and pathological processes over extended periods. This live-sensor display holds promise for advancing health monitoring and disease prevention strategies by enabling continuous, sensitive, and specific in vivo biomarker tracking.
DOI: 10.15156/bio/sh1377130.10fu
title: SH1377130.10FU

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.9s6hce
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.29.30_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 17 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005698-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89mvfb
title: Occurrence Download

description: A dataset containing 1698 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Atrichum undulatum",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 1698 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023946-260208012135463/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.cc23gq6j
title: CCDC 1950557: Experimental Crystal Structure Determination

description: Related Article: Anindita Bhattacharjee, Subramanya Hegde, Abdul Majeed Kurumbala, Vinay Kumar D․ C․, Nagarajaiah Honnappa, Mohd Sajid Ali, T. N. Lohith, M. B. Madhusudana Reddy|2025|J.Mol.Struct.|1338|142135|doi:10.1016/j.molstruc.2025.142135
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.cc29xs12
title: CCDC 2142814: Experimental Crystal Structure Determination

description: Related Article: Can Yang, Lixing Shen, Ying Xie, Jianzhang Li, Huanfeng Jiang, Wei Zeng|2025|Org.Lett.|27|4052|doi:10.1021/acs.orglett.5c01051
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.cc2dk279
title: CCDC 2220940: Experimental Crystal Structure Determination

description: Related Article: Juan Xu, Ao Li, Wei Gao, Ming Lu, Li-Feng Ning|2025|J.Mol.Struct.|1338|142271|doi:10.1016/j.molstruc.2025.142271
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.cc2gnnf7
title: CCDC 2283969: Experimental Crystal Structure Determination

description: Related Article: Xiang Zhong, Rajanikanta Rana, Tong-Kai Luo, Yan- Fang Wu, Yan Peng, Sui-Jun Liu, Gopalan Rajaraman, He-Rui Wen|2025|J.Mol.Struct.|1338|142270|doi:10.1016/j.molstruc.2025.142270
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.cc2l4d38
title: CCDC 2387499: Experimental Crystal Structure Determination

description: Related Article: Shijie Zhu, Jiaojiao Lei, Shengwen Yang, Zhifei Zhao, Ning Liu, Shi-Wu Li|2025|Org.Lett.|27|3831|doi:10.1021/acs.orglett.5c00489
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.cc2l70sn
title: CCDC 2390031: Experimental Crystal Structure Determination

description: Related Article: Xiu'e Jiang, Ruihui Wang, Mingren Fan, Siwei Song, Yi Wang, Qinghua Zhang|2025|Dalton Trans.|54|7056|doi:10.1039/D5DT00488H
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.cc2l70tp
title: CCDC 2390032: Experimental Crystal Structure Determination

description: Related Article: Xiu'e Jiang, Ruihui Wang, Mingren Fan, Siwei Song, Yi Wang, Qinghua Zhang|2025|Dalton Trans.|54|7056|doi:10.1039/D5DT00488H
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.cc2l70vq
title: CCDC 2390033: Experimental Crystal Structure Determination

description: Related Article: Xiu'e Jiang, Ruihui Wang, Mingren Fan, Siwei Song, Yi Wang, Qinghua Zhang|2025|Dalton Trans.|54|7056|doi:10.1039/D5DT00488H
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.cc2l70wr
title: CCDC 2390034: Experimental Crystal Structure Determination

description: Related Article: Xiu'e Jiang, Ruihui Wang, Mingren Fan, Siwei Song, Yi Wang, Qinghua Zhang|2025|Dalton Trans.|54|7056|doi:10.1039/D5DT00488H
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.cc2m53kh
title: CCDC 2417986: Experimental Crystal Structure Determination

description: Related Article: Xiandie Zhang, Xiuying Liu, Xiaoli Li, Yini Wang, Rui He, Guofu Zhong, Jian Zhang|2025|Org.Lett.|27|4074|doi:10.1021/acs.orglett.5c01106
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.cc2mgm2t
title: CCDC 2427116: Experimental Crystal Structure Determination

description: Related Article: Mao Yi, Shan Wang, Shenfang Li, Shuo Zhang, Yilian Liu, Laiyu Zhang, Zifeng You, Xiongli Liu, Lin Li, Junhua Wang, Hao Wang, Qiao Zhao, Baiyan Li, Xian-He Bu|2025|J.Am.Chem.Soc.|147|13592|doi:10.1021/jacs.5c00658
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.cc2mmg5x
title: CCDC 2431769: Experimental Crystal Structure Determination

description: Related Article: Xiaohan Jin, Na Gao, Bingwei Hu, Mei Chen, Yan Zheng, Bingfei Shi, Wenhui Ma, Yiren Xu, Jianqiang Zhang|2025|Tetrahedron Lett.|162|155559|doi:10.1016/j.tetlet.2025.155559
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: 10.15468/dl.dp5ggq
title: Occurrence Download

description: A dataset containing 1409 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Eurycea nana Bishop, 1941)"
 ]
}

 The dataset includes 1409 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008037-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15310799
title: Invasive non-native riparian vegetation indirectly destabilises riverbanks: code and dataset

description: Code and data to support the study: 'Invasive non-native riparianvegetation indirectly destablishes riverbanks'



Code is is in the form of R markdown written in R
DOI: 10.15468/dl.zjkpqb
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Croton ovalifolius Vahl"
 ]
}

 The dataset includes 348 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008038-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f24qxx
title: Occurrence Download

description: A dataset containing 7133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Crocuta crocuta (Erxleben, 1777)"
 ]
}

 The dataset includes 7133 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008039-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wmpebk
title: Occurrence Download

description: A dataset containing 3659 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Bombus campestris (Panzer, 1801)"
 ]
}

 The dataset includes 3659 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008040-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15230600
title: Supporting data for "Amber-OL15-ECC: an Amber force field for nucleic acids with improved ion binding properties"

description: Supporting data for the paper "Amber-OL15-ECC: an Amber force field for nucleic acids with improved ion binding properties" by J. Puyo-Fourtine, M. Zgarbova, P. Jurecka and E. Duboué-Dijon.This folder contains the all-atom molecular dynamics trajectories (without water) of the different systems analyzed in the associated paper, as follows: Dickerson-Drew dodecamer d(CGCGAATTCGCG)2 (PDB ID 1NAJ), the antiparallel guanine quadruplex (G-DNA) formed by the sequence d(G4T4G4 ) (PDB ID 2GWQ, chain A) , a left-handed Z-DNA hexamer duplex d(CGCGCG)2 (PDB ID 1ICK 91, not including spermine and Mg2+ ions)  and a double stranded A-RNA decamer r(GCACCGUUGG)2 (1QC0’ excised from PDB 1QC0). The nucleic acid sequences are explicitly solvated and neutralized with KCl, with an additional 150mM KCl background electrolyte (2M for Z-DNA).Simulations for each systems are provided with both the Amber-OL15 and Amber-OL15-ECC force fields (as well as with Amber-OL21 and Amber-OL21-ECC for Z-DNA and G-DNA), combined with the SPC/E force field for water. Simulations have been performed using the Gromacs2019.6 software, in 3 1-us long replicates for each system and force field, at 300K, with an additional 10-us simulation for the G-DNA and Z-DNA systems.In each folder, in addition to the trajectory (without water molecules) and structure file, we provide the employed topology (.top and .itp) and input (.mdp) files. We also provide the CPPTRAJ scripts to analyze conformational properties, as well as the raw output of this analysis for each system. The ionmaps folder contains for each system and force field the computed K+ density maps.
DOI: 10.15468/dl.pecfrh
title: Occurrence Download

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Eurycea naufragia Chippindale, Price, Wiens & Hillis, 2000)"
 ]
}

 The dataset includes 108 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008043-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c3q35m
title: Occurrence Download

description: A dataset containing 157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Luffa acutangula (L.) Roxb.",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Occurrence evidence)"
 ]
}

 The dataset includes 157 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008042-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13026/mrg5-ja22
title: Swiss-Mammo: A physician-written, synthetic dataset of German mammography reports

description: This dataset, **Swiss-Mammo** , contains 28 manually constructed German
mammography reports, each paired with an English translation. The reports are
stratified across BI-RADS categories 0 through 6, with three reports per
category. All reports were manually created by a radiology resident without
the use of generative AI and independently reviewed by a senior radiologist
specialized in breast imaging to ensure clinical plausibility and linguistic
accuracy.

Swiss-Mammo was developed to support research on information extraction from
radiology reports using large language models (LLMs) and frame semantics. The
dataset provides a high-quality, controlled benchmark for evaluating systems
designed to structure free-text radiological narratives. It is particularly
suited for applications in natural language processing, clinical informatics,
and decision support systems in breast imaging.
DOI: 10.13026/a66y-aa53
title: Medical Expert Annotations of Unsupported Facts in Doctor-Written and LLM-Generated Patient Summaries

description: Large language models in healthcare can generate informative patient summaries
while reducing the documentation workload of healthcare professionals.
However, these models are prone to producing hallucinations, that is,
generating unsupported information, which is problematic in the sensitive
healthcare domain. To better characterize unsupported facts in medical texts,
we developed a rigorous labeling protocol. Following this protocol, two
medical experts annotated unsupported facts in 100 doctor-written summaries
from the MIMIC-IV-Note Discharge Instructions and hallucinations 100 LLM-
generated patient summaries. Here, we are releasing two datasets based on
these annotations: _Hallucinations-MIMIC-DI_ and _Hallucinations-Generated-
DI_. We find that using these datasets to train on hallucination-free examples
effectively reduces hallucinations for both Llama 2 (2.60 to 1.55
hallucinations per summary) and GPT-4 (0.70 to 0.40). Furthermore, we created
a preprocessed version of the MIMIC-IV-Notes Discharge Instructions, releasing
both a full-context version ( _MIMIC-IV-Note-Ext-DI_ ) and a version that only
uses the Brief Hospital Course for context ( _MIMIC-IV-Note-Ext-DI-BHC_ ).
DOI: 10.13026/gedc-j464
title: Medical Expert Annotations of Unsupported Facts in Doctor-Written and LLM-Generated Patient Summaries

description: Large language models in healthcare can generate informative patient summaries
while reducing the documentation workload of healthcare professionals.
However, these models are prone to producing hallucinations, that is,
generating unsupported information, which is problematic in the sensitive
healthcare domain. To better characterize unsupported facts in medical texts,
we developed a rigorous labeling protocol. Following this protocol, two
medical experts annotated unsupported facts in 100 doctor-written summaries
from the MIMIC-IV-Note Discharge Instructions and hallucinations 100 LLM-
generated patient summaries. Here, we are releasing two datasets based on
these annotations: _Hallucinations-MIMIC-DI_ and _Hallucinations-Generated-
DI_. We find that using these datasets to train on hallucination-free examples
effectively reduces hallucinations for both Llama 2 (2.60 to 1.55
hallucinations per summary) and GPT-4 (0.70 to 0.40). Furthermore, we created
a preprocessed version of the MIMIC-IV-Notes Discharge Instructions, releasing
both a full-context version ( _MIMIC-IV-Note-Ext-DI_ ) and a version that only
uses the Brief Hospital Course for context ( _MIMIC-IV-Note-Ext-DI-BHC_ ).