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    <identifier>10.57760/sciencedb.27361</identifier>
    <datestamp>2025-09-02T11:11:57Z</datestamp>
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  <dc:date>2025-09-02</dc:date>
  <dc:title>Development and optimization of green extraction of naringin in Citrus grandis &amp;lsquo;Tomentosa&amp;rsquo; using natural deep eutectic solvents (NADES) and investigation of anti-Lung cancer mechanisms</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.27361</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Natural bioactive compounds derived from traditional Chinese medicine have garnered widespread research interest. In this study, a green and efficient method for extracting naringin from&amp;nbsp;Citrus grandis&amp;nbsp;&amp;lsquo;Tomentosa&amp;rsquo;&amp;nbsp;(CGT) was developed using ultrasonic-assisted extraction with the natural deep eutectic solvent (NADES) composed of choline chloride and levulinic acid (ChCl-Le). Under optimized conditions&amp;mdash;40% (w/w) water content in NADES, solid-to-liquid ratio of 1:66 (w/v), temperature of 61&amp;deg;C, extraction time of 39 minutes, and ultrasonic power of 300 W&amp;mdash;the naringin yield reached 4.686%, significantly higher than those obtained using methanol (4.102%) or ethanol (4.054%).Furthermore, the CGT extracts were evaluated for anti-lung cancer activity, leading to the identification of several key bioactive compounds, including Poncirin, Isosinensetin, Sinensetin, Nobiletin, Didymin, Neohesperidin, and Naringenin. These components were found to primarily target CYP17A1, CYP19A1, and AR, and are involved in regulating multiple&amp;nbsp;	pathways such as EGFR tyrosine kinase inhibitor resistance and prostate cancer pathways, thereby exerting anti-lung cancer effects.This study not only establishes an efficient and environmentally friendly extraction process for naringin but also elucidates the multi-component, multi-target, and multi-pathway mechanisms underlying the anti-lung cancer activity of CGT extracts.</dc:description>
  <dc:subject>Natural deep eutectic solvents; Citrus grandis ‘Tomentosa’; Process optimization</dc:subject>
  <dc:creator>YangJiaqi</dc:creator>
  <dc:creator>Zhang Guihua</dc:creator>
  <dc:creator>XingYanghuan</dc:creator>
  <dc:creator>GaoBixin</dc:creator>
  <dc:creator>Du Hua</dc:creator>
  <dc:creator>JiangGuihua</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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