<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-13T06:24:51Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10256/23529" metadataPrefix="mets">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10256/23529</identifier><datestamp>2025-04-30T23:48:04Z</datestamp><setSpec>com_2072_452955</setSpec><setSpec>com_2072_2054</setSpec><setSpec>col_2072_453069</setSpec></header><metadata><mets xmlns="http://www.loc.gov/METS/" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" ID="&#xa;&#x9;&#x9;&#x9;&#x9;DSpace_ITEM_10256-23529" TYPE="DSpace ITEM" PROFILE="DSpace METS SIP Profile 1.0" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd" OBJID="&#xa;&#x9;&#x9;&#x9;&#x9;hdl:10256/23529">
   <metsHdr CREATEDATE="2026-04-13T08:24:51Z">
      <agent ROLE="CUSTODIAN" TYPE="ORGANIZATION">
         <name>RECERCAT</name>
      </agent>
   </metsHdr>
   <dmdSec ID="DMD_10256_23529">
      <mdWrap MDTYPE="MODS">
         <xmlData xmlns:mods="http://www.loc.gov/mods/v3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
            <mods:mods xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Palarea Albaladejo, Javier</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>McNeilly, Tom N.</mods:namePart>
               </mods:name>
               <mods:name>
                  <mods:role>
                     <mods:roleTerm type="text">author</mods:roleTerm>
                  </mods:role>
                  <mods:namePart>Nisbet, Alasdair J.</mods:namePart>
               </mods:name>
               <mods:originInfo>
                  <mods:dateIssued encoding="iso8601">2024-02</mods:dateIssued>
               </mods:originInfo>
               <mods:identifier type="none"/>
               <mods:abstract>This work discusses and demonstrates the novel use of multivariate analysis and data dimensionality reduction techniques to handle the variety and complexity of data generated in efficacy trials for the development of a prototype vaccine to protect sheep against the Teladorsagia circumcincta nematode. A curated collection of data dimension reduction and visualisation techniques, in conjunction with sensible statistical modelling and testing which explicitly model key features of the data, offers a synthetic view of the relationships between the multiple biological parameters measured. New biological insight is gained into the patterns and associations involving antigen-specific antibody levels, antibody avidity and parasitological parameters of efficacy that is not achievable by standard statistical practice in the field. This approach can therefore be used to guide vaccine refinement and simplification through identifying the most immunologically relevant antigens, and it can be analogously implemented for similar studies in other areas. To facilitate this, the associated data and computer codes written for the R open system for statistical computing are made freely availableThe authors gratefully acknowledge funding for this project from Scottish Government Rural &amp; Environment Science &amp; Analytical Services (RESAS) and from the BBSRC, award number BB/L027186/1. We acknowledge funding from the European Union’s Horizon 2020 Research and Innovation Programme (Grant Number: 635408).&#xd;
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature</mods:abstract>
               <mods:language>
                  <mods:languageTerm authority="rfc3066"/>
               </mods:language>
               <mods:accessCondition type="useAndReproduction">Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess</mods:accessCondition>
               <mods:subject>
                  <mods:topic>Anàlisi multivariable</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Multivariate analysis</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Ovelles -- Paràsits</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Sheep -- Parasites</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Vacunes veterinàries</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Veterinary vaccines</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>A curated multivariate approach to study efficacy and optimisation of a prototype vaccine against teladorsagiasis in sheep</mods:title>
               </mods:titleInfo>
               <mods:genre>info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion peer-reviewed</mods:genre>
            </mods:mods>
         </xmlData>
      </mdWrap>
   </dmdSec>
   <structMap LABEL="DSpace Object" TYPE="LOGICAL">
      <div TYPE="DSpace Object Contents" ADMID="DMD_10256_23529"/>
   </structMap>
</mets></metadata></record></GetRecord></OAI-PMH>