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          <dc:subject>immunotherapy</dc:subject>
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1H, 13 C NMR and crystallographic data stored by collaboration partner (Heidelberg University)</dc:description>
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          <dc:subject>GPC3</dc:subject>
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          <dc:subject>Liver cancer</dc:subject>
          <dc:title>Data publication: In vitro characterization of the published glypican 3 targeting peptide TJ12P2 reveals a lack of specificity and potency</dc:title>
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          <dc:subject>FDG PET</dc:subject>
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          <dc:creator>Maus, Jens</dc:creator>
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          <dc:description>Collection of neural network models for metabolic tumor volume delineation in (Non-Hodgkin) lymphoma patients in FDG-PET/CT images. Intended to use within nnU-Net deep learning framework. Trained with a total of 1192 [18F]FDG-PET/CT scans from 716 patients with Non-Hodgkin lymphoma participating in the PETAL trial.

For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/LyROI

Please cite nnU-Net and the respective paper when using LyROI.

 

List of available models:


	LyROI_Orig.zip: regular U-Net
	LyROI_ResM.zip: residual encoder U-Net (medium)
	LyROI_ResL.zip: residual encoder U-Net (large)
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          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by-sa/4.0/legalcode</dc:rights>
          <dc:subject>FDG PET</dc:subject>
          <dc:subject>Total Metabolic Tumor Volume</dc:subject>
          <dc:subject>TMTV</dc:subject>
          <dc:subject>Non-Hodgkin Lymphoma</dc:subject>
          <dc:subject>Convolutional Neural Network</dc:subject>
          <dc:subject>Delineation</dc:subject>
          <dc:title>LyROI – nnU-Net-based Lymphoma Total Metabolic Tumor Volume Delineation</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>software</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:2720</identifier>
        <datestamp>2024-08-14T12:27:05Z</datestamp>
        <setSpec>openaire_data</setSpec>
        <setSpec>user-casus</setSpec>
        <setSpec>user-matter</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Martinetto, Vincent</dc:creator>
          <dc:creator>Shah, Karan</dc:creator>
          <dc:creator>Cangi, Attila</dc:creator>
          <dc:creator>Pribram-Jones, Aurora</dc:creator>
          <dc:date>2024-02-01</dc:date>
          <dc:description>This data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning". 

It contains the data generation scripts, datasets for the systems used in the paper (Single Well - 1D atom, Double Well - 1D diatomic molecule) and output potentials generated by the physics-informed machine learning models (physics-informed neural networks and Fourier neural operators).</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/2720</dc:identifier>
          <dc:identifier>10.14278/rodare.2720</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:2720</dc:identifier>
          <dc:relation>doi:10.48550/arXiv.2312.15301</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-38725</dc:relation>
          <dc:relation>doi:10.14278/rodare.2719</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/casus</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/matter</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
          <dc:subject>density functional theory</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:title>Inverting the Kohn-Sham equations with physics-informed machine learning</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:3891</identifier>
        <datestamp>2025-08-14T11:58:22Z</datestamp>
        <setSpec>openaire_data</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Brandt, Florian</dc:creator>
          <dc:creator>Ullrich, Martin</dc:creator>
          <dc:creator>Laube, Markus</dc:creator>
          <dc:creator>Löser, Reik</dc:creator>
          <dc:creator>Kotzerke, Jörg</dc:creator>
          <dc:creator>Kopka, Klaus</dc:creator>
          <dc:creator>Pietzsch, Jens</dc:creator>
          <dc:creator>van den Hoff, Jörg</dc:creator>
          <dc:creator>Wodtke, Robert</dc:creator>
          <dc:date>2025-07-29</dc:date>
          <dc:description>Kd shift, binding and PET data</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/3891</dc:identifier>
          <dc:identifier>10.14278/rodare.3891</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:3891</dc:identifier>
          <dc:relation>doi:10.1021/acs.jmedchem.5c00890</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-41661</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-40957</dc:relation>
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          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/closedAccess</dc:rights>
          <dc:title>Data publication: Deciphering the tumor uptake of heterobivalent (SST₂/albumin) [⁶⁴Cu]Cu-NODAGA-cLAB-TATEs</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:4143</identifier>
        <datestamp>2026-01-12T06:47:21Z</datestamp>
        <setSpec>openaire_data</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
        <setSpec>user-health</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Kogler, Jürgen</dc:creator>
          <dc:creator>Donat, Cornelius</dc:creator>
          <dc:creator>Trommer, Johanna</dc:creator>
          <dc:creator>Kopka, Klaus</dc:creator>
          <dc:creator>Stadlbauer, Sven</dc:creator>
          <dc:date>2025-11-19</dc:date>
          <dc:description>Analytical data for chemical synthesis (HPLC, NMR, HRMS), biological data for in vitro and in vivo evaluation (binding assays, small animal imaging)</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/4143</dc:identifier>
          <dc:identifier>10.14278/rodare.4143</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:4143</dc:identifier>
          <dc:relation>doi:10.1186/s41181-025-00398-9</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42251</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42101</dc:relation>
          <dc:relation>doi:10.14278/rodare.4142</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/restrictedAccess</dc:rights>
          <dc:subject>FAP</dc:subject>
          <dc:subject>FAPI</dc:subject>
          <dc:subject>PET</dc:subject>
          <dc:subject>fluorescence-guided surgery</dc:subject>
          <dc:subject>noninvasive molecular imaging</dc:subject>
          <dc:title>Data publication: Synthesis and preclinical evaluation of FAP-targeting radiotracers for PET and optical imaging</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:2561</identifier>
        <datestamp>2024-08-14T12:37:47Z</datestamp>
        <setSpec>openaire_data</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Craig, Austin</dc:creator>
          <dc:creator>Kogler, Jürgen</dc:creator>
          <dc:creator>Laube, Markus</dc:creator>
          <dc:creator>Ullrich, Martin</dc:creator>
          <dc:creator>Donat, Cornelius</dc:creator>
          <dc:creator>Wodtke, Robert</dc:creator>
          <dc:creator>Kopka, Klaus</dc:creator>
          <dc:creator>Stadlbauer, Sven</dc:creator>
          <dc:date>2023-11-17</dc:date>
          <dc:description>The data concerns the preparation of two new 18F-labeled radiotracers using a ultra-fast radiolabeling method for tumor detection using positron emission tomography (PET) imaging.</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/2561</dc:identifier>
          <dc:identifier>10.14278/rodare.2561</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:2561</dc:identifier>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-37850</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-37644</dc:relation>
          <dc:relation>doi:10.14278/rodare.2560</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
          <dc:subject>Automation</dc:subject>
          <dc:subject>cancer-associated fibroblast</dc:subject>
          <dc:subject>FAPI</dc:subject>
          <dc:subject>18F-fluorination</dc:subject>
          <dc:subject>positron emission tomography (PET)</dc:subject>
          <dc:subject>[18F]SuFEx</dc:subject>
          <dc:title>Data publication: Preparation of 18F-Labeled Tracers Targeting Fibroblast Activation Protein via Sulfur [18F]Fluoride Exchange Reaction</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:2342</identifier>
        <datestamp>2024-08-14T12:38:14Z</datestamp>
        <setSpec>openaire_data</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Ullrich, Martin</dc:creator>
          <dc:creator>Brandt, Florian</dc:creator>
          <dc:creator>Löser, Reik</dc:creator>
          <dc:creator>Pietzsch, Jens</dc:creator>
          <dc:creator>Wodtke, Robert</dc:creator>
          <dc:date>2023-06-24</dc:date>
          <dc:description>Saturation binding data</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/2342</dc:identifier>
          <dc:identifier>10.14278/rodare.2342</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:2342</dc:identifier>
          <dc:relation>doi:10.1021/acsomega.3c02755</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-37151</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-36797</dc:relation>
          <dc:relation>doi:10.14278/rodare.2341</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/closedAccess</dc:rights>
          <dc:title>Data publication: Comparative saturation binding analysis of ⁶⁴Cu-labeled somatostatin analogs using cell homogenates and intact cells</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>dataset</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:4199</identifier>
        <datestamp>2026-01-07T15:21:39Z</datestamp>
        <setSpec>software</setSpec>
        <setSpec>user-health</setSpec>
        <setSpec>user-hzdr</setSpec>
        <setSpec>user-pet-center</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Maus, Jens</dc:creator>
          <dc:creator>Nitschke, Janina</dc:creator>
          <dc:creator>Nikulin, Pavel</dc:creator>
          <dc:creator>Hofheinz, Frank</dc:creator>
          <dc:creator>Barth, Mareike</dc:creator>
          <dc:creator>Lemm, Sandy</dc:creator>
          <dc:creator>Richter, Lena</dc:creator>
          <dc:creator>Pietzsch, Jens</dc:creator>
          <dc:creator>Braune, Anja</dc:creator>
          <dc:creator>Ullrich, Martin</dc:creator>
          <dc:date>2026-01-07</dc:date>
          <dc:description>Collection of neural network models for automatic image segmentation of microscopic tumor spheroids. Intended to be used with nnU-Net deep-learning framework. Trained and tested on a total of microscopic images of mouse pheochromocytoma (MPC) tumor cells.

In addition to the trained network model, a PyQt5-based graphical user interface tool is provided. This tool provides a complete pipeline for handling microscopic spheroid image data, running deep-learning–based delineation, and curating results for continuous model improvement.

For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/pyMarAI

Please cite nnU-Net and the respective paper when using pyMarAI.

List of available model types:


	pyMarAI-1.0.0-ecat.zip: nnUNetv2 ready network (for ECAT7)
	pyMarAI-1.0.0-nifti.zip: nnUNetv2 ready network (for NIFTI)
</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/4199</dc:identifier>
          <dc:identifier>10.14278/rodare.4199</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:4199</dc:identifier>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42498</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42497</dc:relation>
          <dc:relation>url:https://github.com/hzdr-MedImaging/pyMarAI</dc:relation>
          <dc:relation>doi:10.14278/rodare.4198</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/hzdr</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by-sa/4.0/legalcode</dc:rights>
          <dc:subject>Tumor Spheroid Imaging</dc:subject>
          <dc:subject>Radiopharmacological Treatment Response Assays</dc:subject>
          <dc:subject>Delineation</dc:subject>
          <dc:subject>Cancer</dc:subject>
          <dc:subject>Deep-Learning</dc:subject>
          <dc:subject>Artifical Intelligence</dc:subject>
          <dc:subject>Convolutional Neural Networks</dc:subject>
          <dc:subject>Network model</dc:subject>
          <dc:title>pyMarAI: nnU-Net-based Tumor Spheroids Auto Delineation</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>software</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
    <record>
      <header>
        <identifier>oai:rodare.hzdr.de:4621</identifier>
        <datestamp>2026-04-20T18:10:40Z</datestamp>
        <setSpec>software</setSpec>
        <setSpec>user-health</setSpec>
        <setSpec>user-pet-center</setSpec>
        <setSpec>user-rodare</setSpec>
        <setSpec>user-zrt</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:creator>Nikulin, Pavel</dc:creator>
          <dc:creator>Hoberück, Sebastian</dc:creator>
          <dc:creator>Apostolova, Ivayla</dc:creator>
          <dc:creator>Maus, Jens</dc:creator>
          <dc:creator>Hüttmann, Andreas</dc:creator>
          <dc:creator>Dührsen, Ulrich</dc:creator>
          <dc:creator>Kroschinsky, Frank</dc:creator>
          <dc:creator>Kotzerke, Jörg</dc:creator>
          <dc:creator>von Bonin, Malte</dc:creator>
          <dc:creator>Bundschuh, Ralph</dc:creator>
          <dc:creator>Braune, Anja</dc:creator>
          <dc:creator>Hofheinz, Frank</dc:creator>
          <dc:date>2025-11-26</dc:date>
          <dc:description>Collection of neural network models for metabolic tumor volume delineation in (Non-Hodgkin) lymphoma patients in FDG-PET/CT images. Intended to use within nnU-Net deep learning framework. Trained with a total of 1192 [18F]FDG-PET/CT scans from 716 patients with Non-Hodgkin lymphoma participating in the PETAL trial.

For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/LyROI

Please cite nnU-Net and the respective paper when using LyROI.

 

List of models:


	PET/CT:
	
		LyROI_Orig.zip: regular U-Net
		LyROI_ResM.zip: residual encoder U-Net (medium)
		LyROI_ResL.zip: residual encoder U-Net (large)
	
	
	PET-only:
	
		LyROI_PET_Orig.zip: regular U-Net
		LyROI_PET_ResM.zip: residual encoder U-Net (medium)
		LyROI_PET_ResL.zip: residual encoder U-Net (large)
	
	
</dc:description>
          <dc:identifier>https://rodare.hzdr.de/record/4621</dc:identifier>
          <dc:identifier>10.14278/rodare.4621</dc:identifier>
          <dc:identifier>oai:rodare.hzdr.de:4621</dc:identifier>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42318</dc:relation>
          <dc:relation>url:https://www.hzdr.de/publications/Publ-42236</dc:relation>
          <dc:relation>url:https://github.com/hzdr-MedImaging/LyROI</dc:relation>
          <dc:relation>doi:10.14278/rodare.4160</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/health</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/pet-center</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
          <dc:relation>url:https://rodare.hzdr.de/communities/zrt</dc:relation>
          <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
          <dc:rights>https://creativecommons.org/licenses/by-sa/4.0/legalcode</dc:rights>
          <dc:subject>FDG PET</dc:subject>
          <dc:subject>Total Metabolic Tumor Volume</dc:subject>
          <dc:subject>TMTV</dc:subject>
          <dc:subject>Non-Hodgkin Lymphoma</dc:subject>
          <dc:subject>Convolutional Neural Network</dc:subject>
          <dc:subject>Delineation</dc:subject>
          <dc:title>LyROI – nnU-Net-based Lymphoma Total Metabolic Tumor Volume Delineation</dc:title>
          <dc:type>info:eu-repo/semantics/other</dc:type>
          <dc:type>software</dc:type>
        </oai_dc:dc>
      </metadata>
    </record>
  </ListRecords>
</OAI-PMH>
