cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11254977
title: Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns

description: This dataset accompanies an article titled, 'Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns', by T. Harris et al. A preprint can be found at https://arxiv.org/abs/2406.01639.

Abstract:

Social contact patterns are key drivers of infectious disease transmission. During the COVID-19 pandemic, differences between pre-COVID and COVID-era contact rates were widely attributed to non-pharmaceutical interventions such as lockdowns. However, the factors that drive changes in the distribution of contacts between different subpopulations remain poorly understood. Here, we present a clustering analysis of 33 contact matrices generated from surveys conducted before and during the COVID-19 pandemic, and analyse key features distinguishing their structures such as the extent of age assortativity. Our analysis demonstrates that, while aspects of pandemic scenarios (such as the implementation of lockdowns) could account for some of these distinguishing features, they can also be explained by differences in study design and, to a lesser extent, long-term demographic trends. Our results caution against using survey data from different studies in counterfactual analysis of epidemic mitigation strategies. Doing so risks attributing differences stemming from survey design choices or long-term changes to the short-term effects of interventions.

See 'README.md' in main upload folder for information on repository structure.
DOI: 10.5281/zenodo.11254978
title: Apparent structural changes in contact patterns during COVID-19 were driven by survey design and long-term demographic trends

description: This dataset accompanies the an article titled, 'Apparent structural changes in contact patterns during COVID-19 were driven by survey design and long-term demographic trends', by T. Harris et al. which can be found at https://arxiv.org/abs/2406.01639.

Abstract:

Social contact patterns are key drivers of infectious disease transmission. During the COVID-19 pandemic, differences between pre-COVID and COVID-era contact rates were widely attributed to non-pharmaceutical interventions such as lockdowns. However, the factors that drive changes in the distribution of contacts between different subpopulations remain poorly understood. Here, we present a clustering analysis of 33 contact matrices generated from surveys conducted before and during the COVID-19 pandemic, and analyse key features distinguishing their topological structures. While we expected to identify aspects of pandemic scenarios responsible for these features, our analysis demonstrates that they can be explained by differences in study design and long-term demographic trends. Our results caution against using survey data from different studies in counterfactual analysis of epidemic mitigation strategies. Doing so risks attributing differences stemming from methodological choices or long-term changes to the short-term effects of interventions.

See 'README.md' in main upload folder for information on repository structure.
DOI: 10.5281/zenodo.14752503
title: Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns

description: This dataset accompanies an article titled, 'Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns', by T. Harris et al. A preprint can be found at https://arxiv.org/abs/2406.01639.

Abstract:

Social contact patterns are key drivers of infectious disease transmission. During the COVID-19 pandemic, differences between pre-COVID and COVID-era contact rates were widely attributed to non-pharmaceutical interventions such as lockdowns. However, the factors that drive changes in the distribution of contacts between different subpopulations remain poorly understood. Here, we present a clustering analysis of 33 contact matrices generated from surveys conducted before and during the COVID-19 pandemic, and analyse key features distinguishing their structures such as the extent of age assortativity. Our analysis demonstrates that, while aspects of pandemic scenarios (such as the implementation of lockdowns) could account for some of these distinguishing features, they can also be explained by differences in study design and, to a lesser extent, long-term demographic trends. Our results caution against using survey data from different studies in counterfactual analysis of epidemic mitigation strategies. Doing so risks attributing differences stemming from survey design choices or long-term changes to the short-term effects of interventions.

See 'README.md' in main upload folder for information on repository structure.
DOI: 10.25582/data.2024-01.3018111/2510362
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018162/2510363
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018177/2510364
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018233/2510365
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018244/2510366
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018292/2510367
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018299/2510368
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018328/2510369
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018331/2510370
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018368/2510371
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018376/2510372
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018409/2510373
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018414/2510374
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018480/2510375
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018491/2510376
title: Data for EMSL Project 51637 from January 2024
DOI: 10.25582/data.2024-01.3018307/2510377
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018308/2510378
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018319/2510379
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018323/2510380
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018327/2510381
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018332/2510382
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018350/2510383
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018356/2510384
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018360/2510385
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018364/2510386
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018369/2510387
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018371/2510388
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018378/2510389
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018379/2510390
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018390/2510391
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018401/2510392
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018413/2510393
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018418/2510394
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018438/2510395
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018441/2510396
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018457/2510397
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018462/2510398
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018487/2510399
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018489/2510400
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018490/2510401
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018500/2510402
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018509/2510403
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018510/2510404
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018517/2510405
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018518/2510406
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018519/2510407
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018524/2510408
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018526/2510409
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018527/2510410
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018546/2510411
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018576/2510412
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018603/2510413
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018605/2510414
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018610/2510415
title: Data for EMSL Project 60052 from January 2024
DOI: 10.15468/dl.dqpqj9
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "Geometry MULTIPOLYGON (((142.36 -29.01, 142.36 -29.39, 142.74 -29.39, 142.74 -29.01, 142.36 -29.01)))"
 ]
}

 The dataset includes 27 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011010-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2024-01.3018618/2510416
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018622/2510417
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018625/2510418
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018632/2510419
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018635/2510420
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018640/2510421
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018645/2510422
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018649/2510423
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-01.3018678/2510424
title: Data for EMSL Project 60052 from January 2024
DOI: 10.25582/data.2024-02.3023191/2510425
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023194/2510426
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023195/2510427
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023203/2510428
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023205/2510429
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023207/2510430
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-02.3023208/2510431
title: Data for EMSL Project 60052 from February 2024
DOI: 10.25582/data.2024-01.3018769/2510432
title: Data for EMSL Project 60144 from January 2024
DOI: 10.25582/data.2024-02.3023694/2510433
title: Data for EMSL Project 60582 from February 2024
DOI: 10.15468/dl.t5avh3
title: Occurrence Download

description: A dataset containing 116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "GeoDistance is in a distance of 0.5km from (-33.7,151.3)"
 ]
}

 The dataset includes 116 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011012-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c59k4652c
title: MassIVE MSV000096722 - Cyanobacterial circadian regulation enhances bioproduction under subjective nighttime through rewiring of carbon partitioning dynamics, redox balance orchestration, and cell cycle modulation
title: GC-MS extracellular metabolite profiling of circadian clock regulation impacts of carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 for enhanced bioproduction strategy investigation. Metabolomic targeted analysis of PCC 7942 light-dark cycle cultures transitioned to constant light revealed distinct temporal patterns in sucrose production. Culture samples (8 mL) were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours then dried under speed vacuum and dissolved in pyridine and chemically derivatized by methoxyamination and trimethylsilylation for extracellular sucrose analysis. Data was analyzed using Agilent Mass Hunter. Culture samples (8 mL) were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours then dried under speed vacuum and dissolved in pyridine and chemically derivatized by methoxyamination and trimethylsilylation for extracellular sucrose analysis.
DOI: 10.25584/2510499
title: PPI DataHub Project Data Package: S. elongatus PCC 7942 Circadian Control Bioproduction Metabolomics (PB-DP5)

description: The purpose of this experiment was to evaluate how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942 in providing insights to strategies for enhanced bioproduction. Culture samples were collected at 0, 0.5, 1, 2, 4, 6, and 8 hours for extracellular sucrose analysis. Circadian metabolomics data was acquired using a Agilent single quadrupole gas chromatography-mass spectrometer and processed using Agilent Mass Hunter for targeted sucrose quantification. Metabolomic analysis of PCC 7942 light-dark cycle cultures transitioned to constant light revealed distinct temporal patterns in sucrose production. Processed metabolomic datasets are openly accessible from the PNNL DataHub project dataset download page and contain secondary processed GC-MS results files and supporting metadata materials linked to relevant source code information supporting data transparency and reuse.
DOI: 10.5281/zenodo.14792464
title: DynamicAtlas Demo Dataset

description: This data respository contains the Demo Dataset used in the tutorial for the MATLAB-based code in DynamicAtlas.
DOI: 10.25919/856g-ye07
title: Parkes observations for project PX500 semester 2024OCTS_10

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.25919/zksh-rt36
title: Parkes observations for project P1338 semester 2024OCTS_43

description: Fast radio bursts (FRBs) are millisecond-duration radio bursts of extragalactic origin. Since the discovery of the first FRB in the archival Parkes/Murriyang multibeam data, a broad dichotomy in population has emerged. Some FRBs have been seen to be repeating, while others are not, despite a significant amount of follow-up using different radio telescopes. The repeating FRB 20240114A was recently discovered by CHIME/FRB, which has been seen to have an exceptionally high burst activity. Such extreme burst activity has not been seen in any other source. The repeating FRBs, such as FRB 20240114A, provide an unparalleled window into their circumburst environment due to their repeating nature, which can be used to constrain possible progenitor models and test underlying emission mechanisms. The previous Parkes/Murriyang source follow-up has also revealed intriguing spectro-polarimetric properties, such as frequency-dependent evolution of burst central frequency or chromaticity, a possible activity window, significantly large circular polarisation (CP), and frequency-dependent CP. These properties hold the key towards understanding the circumburst environment of the FRBs, and test possible progenitor models. A large bandwidth instrument with reliable polarimetry has been critical in uncovering these properties. The ultra-wideband low (UWL) receiver on Parkes/Murriyang is ideally suited to explore the source's wideband spectro-temporal and polarimetric behaviour. We propose a campaign to regularly follow up FRB 20240114A to ascertain its long-term evolution of spectro-temporal properties.
DOI: 10.15468/dl.y4ugyn
title: Occurrence Download

description: A dataset containing 20379 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-94.48682 -15.74158,-89.83992 -52.80882,-64.66926 -58.07121,-47.24341 -48.38877,-29.04308 -0.45379,-76.28649 18.5741,-94.48682 -15.74158))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Iguana iguana (Linnaeus, 1758)",
 "Year 2000-2025"
 ]
}

 The dataset includes 20379 records from 217 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011014-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26826466
title: <b>Chromosome-scale </b><b>assemblies of three </b><b><i>Ormosia</i></b><b> species</b>

description: <b>Chromosome-scale </b><b>assemblies of three </b><b><i>Ormosia</i></b><b> species</b>
DOI: 10.6084/m9.figshare.26826466.v14
title: <b>Chromosome-scale </b><b>assemblies of three </b><b><i>Ormosia</i></b><b> species</b>

description: <b>Chromosome-scale </b><b>assemblies of three </b><b><i>Ormosia</i></b><b> species</b>
DOI: 10.6084/m9.figshare.26500814
title: Knockdown of KCNQ1OT1 Alleviates the Activation of NLRP3 Inflammasome Through miR-17-5p/TXNIP Axis in Retinal Müller Cells

description: Diabetic retinopathy (DR) is one of the most severe and common complications caused by diabetic mellites. Inhibiting NLRP3 inflammasome activation displays a crucial therapeutic value in DR. Studies have shown that KCNQ1OT1 plays a critical role in regulating NLRP3 inflammasome activation and participates in the pathogenesis of diabetic complications. The present study aims to explore the role, and the potential mechanism of KCNQ1OT1 in regulating the activation of NLRP3 inflammasome in DR. qRT-PCR was used to detect the expression of KCNQ1OT1, miR-17-5p, TXNIP, NLRP3, ASC, caspase-1 and IL-1β. Western blot was performed to detect the expression of NLRP3, ASC, caspase-1, IL-1β and TXNIP. Immunohistochemistry and immunostaining were performed to detect the expression of caspase-1. The levels of the inflammatory cytokine IL-1β were determined by ELISA assay. FISH was used to detect the subcellular localisation of KCNQ1OT1. Bioinformatic analysis, luciferase reporter assay and <i>in vitro</i> studies were performed to elucidate the mechanism of KCNQ1OT1-mediated dysfunction. The expression of KCNQ1OT1 and the activation of NLRP3 inflammasome were increased in experimental DR models. KCNQ1OT1 knockdown alleviated NLRP3 inflammasome-associated molecules expression. In addition, KCNQ1OT1 was found to be localized mainly in the cytoplasm of Müller cells and facilitated TXNIP expression by acting as a miR-17-5p sponge. KCNQ1OT1 promoted the activation of NLRP3 inflammasome through miR-17-5p/TXNIP axis. In conclusion, it was found in this study that KCNQ1OT1 promoted the activation of NLRP3 inflammasome both <i>in vitro</i> and <i>in vivo</i>, which was mediated by miR-17-5p/TXNIP axis. KCNQ1OT1 might be an effective interference target for the prevention and treatment of DR.
DOI: 10.6084/m9.figshare.26500814.v1
title: Knockdown of KCNQ1OT1 Alleviates the Activation of NLRP3 Inflammasome Through miR-17-5p/TXNIP Axis in Retinal Müller Cells

description: Diabetic retinopathy (DR) is one of the most severe and common complications caused by diabetic mellites. Inhibiting NLRP3 inflammasome activation displays a crucial therapeutic value in DR. Studies have shown that KCNQ1OT1 plays a critical role in regulating NLRP3 inflammasome activation and participates in the pathogenesis of diabetic complications. The present study aims to explore the role, and the potential mechanism of KCNQ1OT1 in regulating the activation of NLRP3 inflammasome in DR. qRT-PCR was used to detect the expression of KCNQ1OT1, miR-17-5p, TXNIP, NLRP3, ASC, caspase-1 and IL-1β. Western blot was performed to detect the expression of NLRP3, ASC, caspase-1, IL-1β and TXNIP. Immunohistochemistry and immunostaining were performed to detect the expression of caspase-1. The levels of the inflammatory cytokine IL-1β were determined by ELISA assay. FISH was used to detect the subcellular localisation of KCNQ1OT1. Bioinformatic analysis, luciferase reporter assay and <i>in vitro</i> studies were performed to elucidate the mechanism of KCNQ1OT1-mediated dysfunction. The expression of KCNQ1OT1 and the activation of NLRP3 inflammasome were increased in experimental DR models. KCNQ1OT1 knockdown alleviated NLRP3 inflammasome-associated molecules expression. In addition, KCNQ1OT1 was found to be localized mainly in the cytoplasm of Müller cells and facilitated TXNIP expression by acting as a miR-17-5p sponge. KCNQ1OT1 promoted the activation of NLRP3 inflammasome through miR-17-5p/TXNIP axis. In conclusion, it was found in this study that KCNQ1OT1 promoted the activation of NLRP3 inflammasome both <i>in vitro</i> and <i>in vivo</i>, which was mediated by miR-17-5p/TXNIP axis. KCNQ1OT1 might be an effective interference target for the prevention and treatment of DR.