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Dataset Title:  [Heat priming in Nematostella vectensis: Expression of heat shock protein
70 (HSP70)] - Expression of heat shock protein 70 (HSP70) in larvae at 11 days
post-fertilization (DPF) from experiments investigating heat priming in
Nematostella vectensis (Influence of environmental pH variability and thermal
sensitivity on the resilience of reef-building corals to acidification stress)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_923415_v1)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Priming_temperature_C {
    Int32 actual_range 18, 39;
    String long_name "Priming_temperature_c";
    String units "degrees Celsius";
  }
  Group {
    Int32 actual_range 1, 3;
    String long_name "Group";
    String units "unitless";
  }
  Days_post_fertilizaiton {
    Int32 actual_range 11, 11;
    String long_name "Days_post_fertilizaiton";
    String units "unitless";
  }
  HSP70 {
    Float32 actual_range 3998.389, 9637.693;
    String long_name "Hsp70";
    String units "unitless";
  }
  Tubulin {
    Float32 actual_range 25280.1, 35855.77;
    String long_name "Tubulin";
    String units "unitless";
  }
  Normalized_HSP70 {
    Float32 actual_range 0.1487495, 0.332332;
    String long_name "Normalized_hsp70";
    String units "unitless";
  }
  LT50_C {
    Float32 actual_range 41.25, 41.92;
    String long_name "Lt50_c";
    String units "degrees Celsius";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.923415.1";
    String history 
"2024-09-21T18:02:28Z (local files)
2024-09-21T18:02:28Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_923415_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/923415";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String sourceUrl "(local files)";
    String summary 
"Across diverse taxa, sublethal exposure to abiotic stressors early in life can lead to benefits such as increased stress tolerance upon repeat exposure. This phenomenon, known as hormetic priming, is largely unexplored in early life stages of marine invertebrates, which are increasingly threatened by anthropogenic climate change. To investigate this phenomenon, larvae of the sea anemone and model marine invertebrate Nematostella vectensis were exposed to control (18 °C) or elevated (24 °C, 30 °C, 35 °C, or 39 °C) temperatures for 1 hour at 3 days post-fertilization (DPF), followed by return to control temperatures (18 °C). The animals were then assessed for growth, development, metabolic rates, and heat tolerance at 4, 7, and 11 DPF. To investigate a possible molecular mechanism for the observed changes in heat tolerance, the expression of heat shock protein 70 (HSP70) was quantified at 11 DPF. The study's findings suggest heat priming may augment the climate resilience of marine invertebrate early life stages via the modulation of key developmental and physiological phenotypes, while also affirming the need to limit further anthropogenic ocean warming.

This dataset includes data pertaining to the expression of heat shock protein 70 (HSP70) in larvae at 11 days post-fertilization (DPF). See related datasets for other results from these experiments. These data and results are published in Glass et al. (2023) (DOI: 10.7717/peerj.16574).";
    String title "[Heat priming in Nematostella vectensis: Expression of heat shock protein 70 (HSP70)] - Expression of heat shock protein 70 (HSP70) in larvae at 11 days post-fertilization (DPF) from experiments investigating heat priming in Nematostella vectensis (Influence of environmental pH variability and thermal sensitivity on the resilience of reef-building corals to acidification stress)";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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