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<p>Acute lung injury (ALI) and lung inflammation are key causes of death in bacterial or viral lung infections, largely due to cytokine storms and the lack of effective therapies. <i>Gymnema sylvestre</i> hydroalcoholic extract has been reported to exert anti-inflammatory effects in both in vitro and in vivo models of lung inflammation; however, the specific bioactive constituent responsible for its therapeutic efficacy remains unidentified. This study aimed to screen the bioactive molecules and evaluate their therapeutic potential using a lipopolysaccharide (LPS)-induced differentiation model in both in&#xa0;vitro and in&#xa0;vivo systems. Isolation and characterization results revealed that Gymnemagenin-3-O-glucuronide (G3OG) has been identified as the major bioactive ingredient from the extract. NMR and LC-HRMS analysis were performed to characterize G3OG. Gene expression analysis using RT-qPCR and reactive oxygen species assays demonstrated a significant upregulation of inflammatory cytokines, chemokines, and oxidative stress indicators in LPS-stimulated RAW 264.7 and BEAS-2B cells, which was markedly attenuated by G3OG treatment. Consistent with these in&#xa0;vitro findings, G3OG administration in an LPS-induced ALI model significantly reduced the inflammatory cell infiltration, cytokine/chemokine expression, and lung tissue damage, while enhancing antioxidant defence mechanisms&#xa0;and lung mechanics in a dose-dependent manner. Collectively, both in&#xa0;vitro and in&#xa0;vivo findings demonstrated that G3OG treatment significantly reduced the expression of inflammatory markers and improved lung histopathology and function, primarily through modulation of the NF-κB/MAPK signaling pathway. These findings underscore the potential of G3OG as a plant-derived, promising lead in an ALI model and highlight its translational potential.</p> Graphical Abstract <p></p>

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Gymnemagenin-3-O-glucuronide mitigates lipopolysaccharide-induced acute lung inflammation/injury by regulating the NF-κB/MAPK signalling

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Aruna Jangam,
  • Sarva Lakshmi Pusarapu,
  • Vaishnavi Kambhampati,
  • Swarna Kumari Gaja,
  • Anitha Rolla,
  • Ankitha Kondepudi,
  • Nagendla Narendra Kumar,
  • Mohana Krishna Reddy Mudiam,
  • Sai Balaji Andugulapati,
  • Anthony Addlagatta

摘要

Acute lung injury (ALI) and lung inflammation are key causes of death in bacterial or viral lung infections, largely due to cytokine storms and the lack of effective therapies. Gymnema sylvestre hydroalcoholic extract has been reported to exert anti-inflammatory effects in both in vitro and in vivo models of lung inflammation; however, the specific bioactive constituent responsible for its therapeutic efficacy remains unidentified. This study aimed to screen the bioactive molecules and evaluate their therapeutic potential using a lipopolysaccharide (LPS)-induced differentiation model in both in vitro and in vivo systems. Isolation and characterization results revealed that Gymnemagenin-3-O-glucuronide (G3OG) has been identified as the major bioactive ingredient from the extract. NMR and LC-HRMS analysis were performed to characterize G3OG. Gene expression analysis using RT-qPCR and reactive oxygen species assays demonstrated a significant upregulation of inflammatory cytokines, chemokines, and oxidative stress indicators in LPS-stimulated RAW 264.7 and BEAS-2B cells, which was markedly attenuated by G3OG treatment. Consistent with these in vitro findings, G3OG administration in an LPS-induced ALI model significantly reduced the inflammatory cell infiltration, cytokine/chemokine expression, and lung tissue damage, while enhancing antioxidant defence mechanisms and lung mechanics in a dose-dependent manner. Collectively, both in vitro and in vivo findings demonstrated that G3OG treatment significantly reduced the expression of inflammatory markers and improved lung histopathology and function, primarily through modulation of the NF-κB/MAPK signaling pathway. These findings underscore the potential of G3OG as a plant-derived, promising lead in an ALI model and highlight its translational potential.

Graphical Abstract