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    <responseDate>2026-10-15T02:01:04Z</responseDate>
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    <identifier>10.57760/sciencedb.41966</identifier>
    <datestamp>2026-07-09T16:49:49Z</datestamp>
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  <dc:date>2026-07-09</dc:date>
  <dc:title>Metabolomics of Liriomyza trifolii treated with bitter gourd leaf extract</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.41966</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>For metabolomics, an LC-MS/MS system (Waters Acquity I-Class PLUS UHPLC coupled with Xevo G2-XS QTof) equipped with an HSS T3 column (1.8 &amp;mu;m, 2.1&amp;times;100 mm) was used. Mobile phases were 0.1% formic acid in water (A) and acetonitrile (B), with a 2 &amp;mu;L injection. MassLynx V4.2-controlled MSe mode acquired MS and MS/MS data at 0.2 s/scan (low/high collision energy: off/10&amp;ndash;40 V). ESI parameters: capillary &amp;plusmn;2500/&amp;ndash;2000 V, cone 30 V, source/desolvation temps 100/500&amp;deg;C, cone/desolvation gas 50/800 L/h. Raw data were processed by Progenesis QI for peak picking, alignment, and identification against METLIN and an in-house library. After total peak area normalization, PCA and Spearman correlation assessed repeatability and QC. Identified compounds were annotated via KEGG, HMDB, and Lipidmaps. Differential metabolites were screened by FC &amp;gt; 2,&amp;nbsp;P&amp;nbsp;&amp;lt; 0.05, and VIP &amp;gt; 1 (OPLS-DA, ropls R package, 200 permutations). KEGG enrichment was tested by hypergeometric distribution.</dc:description>
  <dc:subject>Metabolomics; Liriomyza trifolii ; Bitter gourd leaf extract</dc:subject>
  <dc:creator>Yawen Chang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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