Multimodal Evaluation of the Anxiolytic Activity of Phyllanthus niruri Extract in Mice: A Comparative Behavioral and Neuropharmacological Approach

Anxiety is a widespread mental health issue that impacts millions of individuals globally, often interfering with daily functioning and overall well-being. While conventional anti-anxiety medications like benzodiazepines are widely used, their prolonged use is often limited due to side effects such as sedation, dependence, and drug tolerance. As a result, there is increasing interest in exploring herbal remedies with better safety profiles. Phyllanthus niruri Linn., a medicinal herb widely recognized in Ayurvedic medicine for treating liver and urinary problems, is known to contain neuroactive constituents such as flavonoids, tannins, phenolics, and alkaloids. This study aimed to assess the anti-anxiety potential of the hydroalcoholic extract of Phyllanthus niruri in Swiss albino mice using multiple validated behavioral models. The plant was collected and authenticated, then extracted using a 70:30 ethanol-water mixture and screened for key phytochemical constituents. Mice were randomly assigned into four groups: a control group, a standard group receiving diazepam (2 mg/kg), and two test groups treated orally with the extract at 100 mg/kg and 200 mg/kg. Behavioral tests including the Elevated Plus Maze (EPM), Open Field Test (OFT), Actophotometer, and Rotarod were conducted to evaluate anxiety levels, movement activity, and motor coordination. The extract demonstrated a dose-related reduction in anxiety-like behaviors, with effects comparable to the standard drug, and did not cause significant motor impairment. Phytochemical screening confirmed the presence of active compounds likely responsible for the observed anxiolytic action. These findings support the traditional claims of Phyllanthus niruri in stress relief and highlight its potential as a safe, natural alternative for managing anxiety disorders. Keywords: Phyllanthus niruri, anxiolytic activity, hydroalcoholic extract, behavioral models