cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29091733.v1
title: Additional file 22 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 22.
DOI: 10.6084/m9.figshare.29091736
title: Additional file 23 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 23.
DOI: 10.6084/m9.figshare.29091736.v1
title: Additional file 23 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 23.
DOI: 10.6084/m9.figshare.29091739
title: Additional file 24 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 24.
DOI: 10.6084/m9.figshare.29091739.v1
title: Additional file 24 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 24.
DOI: 10.6084/m9.figshare.29091742
title: Additional file 25 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 25.
DOI: 10.6084/m9.figshare.29091742.v1
title: Additional file 25 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 25.
DOI: 10.6084/m9.figshare.29091745
title: Additional file 26 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 26.
DOI: 10.6084/m9.figshare.29091745.v1
title: Additional file 26 of HBV-driven host chromatin accessibility changes affect liver metabolic pathways, iron homeostasis and promote a preneoplastic phenotype

description: Supplementary Material 26.
DOI: 10.57761/5b7c-pm72
title: MedAlign

description: jason-fries@stanford.edu (Jason Fries)
description: MedAlign is a benchmark dataset of 983 clinician-curated natural language instructions for EHR data, grounded by 275 longitudinal EHRs. It includes reference responses for 303 instructions and supports evaluation of LLMs on healthcare-specific tasks.
description: **IMPORTANT USAGE NOTE: **MedAlign **only includes test set examples**. No training examples are provided for fine-tuning models.



**1\. Overview**

MedAlign is a **longitudinal EHR** **benchmark** for instruction-following with LLMs. The dataset includes:

- 275 patients
- 46,252 clinical notes
- 128 clinical note types
- 3\.6 million clinical events

<!-- -->



**2\. EHR Data**

EHR data is sourced from [Stanford’s STARR-OMOP database. ](<https://academic.oup.com/jamiaopen/article/6/3/ooad054/7236015>)Data are standardized in the [OMOP CDM](<https://www.ohdsi.org/data-standardization/>) schema and are scrubbed on identifying PHI information. Complete technical details are included in the paper, but key highlights:

- Dates are jittered within patient to conceal real dates (but preserve deltas between dates)
- Data for patients >= 90 years old are removed

<!-- -->

- Unstructured text fields not mappable to OMOP standard concepts are redacted

<!-- -->

- All clinical note text has been scrubbed of PHI variables using hiding-in-plain-sight (HIPS) [Carrell et al. 2013](<https://pubmed.ncbi.nlm.nih.gov/22771529/>).
- HIV test results are redacted.
- Provider names and NPIs are redacted

<!-- -->





**3\. Instruction Following Benchmark**



See "medalign\_instructions\_responses\_v1\_2.zip" for instructions, responses, and EHR text timelines.

Please see our Github repo to obtain code for loading the dataset.




description: Access to the MedAlign dataset requires the following:

- Verified Affiliation (Academic, Government, Industry Research Lab). Please use your **verified email address** when applying, **do not use gmail or personal emails. **Applications using personal, unverified email addresses will be rejected.
- Encryption Verification / Attestation for Data Storage
- Signing the terms of the MedAlign Data Set License 1.0
- Providing a short description of your intended research use of MedAlign
- CITI Training

<!-- -->

**These data must remain on your encrypted machine. Redistribution of data is FORBIDDEN and will result in immediate termination of access privileges. **



**IMPORTANT NOTES**:

- Our policy on derived works aligns with PhysioNet's guidelines, requiring that these artifacts be hosted on Redivis. If you create derived research artifacts based on MedAlign (such as additional annotations or synthetic data), please contact us to discuss hosting arrangements.
- Sending MedAlign data over a non-HIPAA-compliant API is a violation of the DUA.

<!-- -->



Please allow 7-10 business days to process applications.
DOI: 10.6084/m9.figshare.29091765
title: Additional file 3 of Host taxonomy and environment shapes insectivore viromes and viral spillover risks in Southwestern China

description: Additional file 3: Table S1. Sampling information of insectivores in 12 counties in Yunnan province. Table S2. Pooling of samples of insectivores captured in Yunnan province. Table S3. Summary of the viruses detected in this study. Table S4. Virus species demarcation criteria used in this study.
DOI: 10.6084/m9.figshare.29091765.v1
title: Additional file 3 of Host taxonomy and environment shapes insectivore viromes and viral spillover risks in Southwestern China

description: Additional file 3: Table S1. Sampling information of insectivores in 12 counties in Yunnan province. Table S2. Pooling of samples of insectivores captured in Yunnan province. Table S3. Summary of the viruses detected in this study. Table S4. Virus species demarcation criteria used in this study.
DOI: 10.57761/ngh9-6h30
title: MedAlign

description: jason-fries@stanford.edu (Jason Fries)
description: MedAlign is a benchmark dataset of 983 clinician-curated natural language instructions for EHR data, grounded by 275 longitudinal EHRs. It includes reference responses for 303 instructions and supports evaluation of LLMs on healthcare-specific tasks.
description: **IMPORTANT USAGE NOTE: **MedAlign **only includes test set examples**. No training examples are provided for fine-tuning models.



**1\. Overview**

MedAlign is a **longitudinal EHR** **benchmark** for instruction-following with LLMs. The dataset includes:

- 275 patients
- 46,252 clinical notes
- 128 clinical note types
- 3\.6 million clinical events

<!-- -->



**2\. EHR Data**

EHR data is sourced from [Stanford’s STARR-OMOP database. ](<https://academic.oup.com/jamiaopen/article/6/3/ooad054/7236015>)Data are standardized in the [OMOP CDM](<https://www.ohdsi.org/data-standardization/>) schema and are scrubbed on identifying PHI information. Complete technical details are included in the paper, but key highlights:

- Dates are jittered within patient to conceal real dates (but preserve deltas between dates)
- Data for patients >= 90 years old are removed

<!-- -->

- Unstructured text fields not mappable to OMOP standard concepts are redacted

<!-- -->

- All clinical note text has been scrubbed of PHI variables using hiding-in-plain-sight (HIPS) [Carrell et al. 2013](<https://pubmed.ncbi.nlm.nih.gov/22771529/>).
- HIV test results are redacted.
- Provider names and NPIs are redacted

<!-- -->





**3\. Instruction Following Benchmark**



See "medalign\_instructions\_responses\_v1\_2.zip" for instructions, responses, and EHR text timelines.

Please see our Github repo to obtain code for loading the dataset.




description: Access to the MedAlign dataset requires the following:

- Verified Affiliation (Academic, Government, Industry Research Lab). Please use your **verified email address** when applying, **do not use gmail or personal emails. **Applications using personal, unverified email addresses will be rejected.
- Encryption Verification / Attestation for Data Storage
- Signing the terms of the MedAlign Data Set License 1.0
- Providing a short description of your intended research use of MedAlign
- CITI Training

<!-- -->

**These data must remain on your encrypted machine. Redistribution of data is FORBIDDEN and will result in immediate termination of access privileges. **



**IMPORTANT NOTES**:

- Our policy on derived works aligns with PhysioNet's guidelines, requiring that these artifacts be hosted on Redivis. If you create derived research artifacts based on MedAlign (such as additional annotations or synthetic data), please contact us to discuss hosting arrangements.
- Sending MedAlign data over a non-HIPAA-compliant API is a violation of the DUA.

<!-- -->



Please allow 7-10 business days to process applications.
DOI: 10.6084/m9.figshare.29091767
title: Additional file 1 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.29091767.v1
title: Additional file 1 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.29091770
title: Additional file 2 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.29091770.v1
title: Additional file 2 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.29091773
title: Additional file 3 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.29091773.v1
title: Additional file 3 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.29091776
title: Additional file 4 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.29091779
title: Additional file 5 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.29091776.v1
title: Additional file 4 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.29091779.v1
title: Additional file 5 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.29091782
title: Additional file 6 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.29091782.v1
title: Additional file 6 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.29091785
title: Additional file 7 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.29091785.v1
title: Additional file 7 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.29091788
title: Additional file 8 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.29091788.v1
title: Additional file 8 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.29091791
title: Additional file 9 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.29091791.v1
title: Additional file 9 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.29091794
title: Additional file 10 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.29091794.v1
title: Additional file 10 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.29091797
title: Additional file 11 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 11
DOI: 10.6084/m9.figshare.29091797.v1
title: Additional file 11 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 11
DOI: 10.6084/m9.figshare.29091800.v1
title: Additional file 12 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 12
DOI: 10.6084/m9.figshare.29091800
title: Additional file 12 of Single-cell transcriptomics reveals metabolic remodeling and functional specialization in the immune microenvironment of bone tumors

description: Supplementary Material 12
DOI: 10.15468/dl.xsp2d8
title: Occurrence Download

description: A dataset containing 459959 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dasypsyllus gallinulae gallinulae, Ceratophyllus gallinae (Schrank, 1803), Philopterus chloridis (Schrank, 1776), Brueelia breueri Balat, 1955, Menacanthus wipszyckii Eichler & Zlotorzycka, 1963, Myrsidea serini (Seguy, 1944), Philopterus citrinellae (Schrank, 1776), Menacanthus eurysternus (Burmeister, 1838), Opecoelina pacifica Manter, 1940, Stenella attenuata (Gray, 1846), Cotesia empretiae (Viereck, 1913), Phycis phycis (Linnaeus, 1766), Anilocra frontalis H.Milne Edwards, 1840, Holacanthus passer Valenciennes, 1846, Nyctalus leisleri (Kuhl, 1817), Eunica margarita Godart, 1823, Cydia saltitans (Westwood, 1858), Pleotrichophorus chrysanthemi (Theobald, 1920), Basiria gracilis (Thorne, 1949) Siddiqi, 1963, Paraphytoptus chrysanthemi Keifer, 1940, Bryobia eharai Pritchard & Keifer, 1958, Pelagodes aucta (Prout, 1912), Condica albigera Guenée, 1852, Rhinia obsoleta (Wiedemann, 1830), Liriomyza tanaceti Meijere, 1924, Cryptocephalus bilineatus (Linnaeus, 1767), Colletes similis Schenck, 1853, Bombylella atra Scopoli, 1763, Puccinia horiana Henn., Septoria chrysanthemella Sacc., Stagonosporopsis ligulicola (K.F.Baker, Dimock & L.H.Davis) Aveskamp, Gruyter & Verkley, Gyranusoidea austrina Annecke & Mynhardt, 1970, Allocerellus paulus Annecke & Mynhardt, 1970, Gretna carmen Evans, 1937, Ommatissus tumidulus Linnavuori, 1973, Melanerpes superciliaris (Temminck, 1827), Cricula elaezia Jordan, 1909, Bothrogonia sclerotica Young, 1986, Bothrogonia keralana Young, 1986, Atkinsoniella opponens (Walker, 1851), Daphnis hypothous Cramer, 1780, Mokrzeckia orientalis Subba Rao, 1973, Nomada lathburiana (Kirby, 1802), Anagyrus ferus Noyes & Hayat, 1984, Anagyrus nigricorpus Shafee, Alam & Agarwal, 1975, Neastymachus burksi (Shafee, Alam & Agarwal, 1975), Cheiloneurus latifrons Hayat, Alam & Agarwal, 1975, Mashhoodia indica Shafee, 1972, Necora puber (Linnaeus, 1767), Pilocrocis laralis Hampson, 1909)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 459959 records from 4253 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002776-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a3as4c
title: Occurrence Download

description: A dataset containing 21615 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 Myadestes obscurus (Gmelin, 1789)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 21615 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030348-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d6s9ca
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ethiopia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Urena lobata L."
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030349-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11073938
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Montenegro

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, and 2023, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2023 – Center for Eco-Toxicological Research

OCC-CHEMMON2024 – Center for Eco-Toxicological Research
description: ME; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.11073939
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Montenegro

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2023 split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2023 – Center for Eco-Toxicological Research
description: ME; CSV; data.collection@efsa.europa.eu
DOI: 10.5281/zenodo.15407913
title: Results from national testing programs on the occurrence of chemical contaminants in food and feed - Montenegro

description: In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.  

The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. 

Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:  



Commission Regulation (EU) 625/2017, on the application of food and feed law

Commission Delegated Regulation (EU) 2022/931

Commission Implementing Regulation (EU) 2022/932

Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006


These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, and 2023, split by sampling year (data element ‘sampY’). 

More details are available in last year's finalised call for data ‘Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA’.

REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: 

OCC-CHEMMON2023 – Center for Eco-Toxicological Research

OCC-CHEMMON2024 – Center for Eco-Toxicological Research
description: ME; CSV; data.collection@efsa.europa.eu
DOI: 10.15468/dl.7d6gwu
title: Occurrence Download

description: A dataset containing 686 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ctenomys mendocinus Philippi, 1869"
 ]
}

 The dataset includes 686 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030350-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.