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Dr. Jyoti Markam*, Dr. Lalchand, Dr. Madhuri Daharia, Dr. R. K. Singh and Dr. O. P. Rout


Mansoa alliacea or Garlic vine plants are not only an ornamental. Garlic vine has many properties like anti-inflammatory, ant-arthritic, anti-oxidant, anti-cancer therefore in the present study Mansoa alliacea leaves hydroalcoholic extract preparation was evaluated for its analgesic efficacy by making use of different central and peripheral pain models in mice. Material and Method: The analgesic efficacy of hydroalcoholic extract was assessed by employing different pain models such as i) Acetic acid induced writhing reflex method as peripheral analgesic model ii) Tail immersion model iii)Tail flick model for central analgesia. The percentage inhibition of writhes and prolongation of reaction time were the parameters of evaluation. The results obtained were analysed by ANOVA and Student‟s unpaired “t”- test. Result: Hydroalcoholic extract of M. alliacea (Lam.) leaf (100 & 200 mg/kg) reduced writhing episodes significantly in 3% of acetic acid induced writhing in mice as compared to control indicating it‟s analgesic effect. The highest percentage inhibition of pain was seen with 200 mg/kg of hydroalcoholic extract of Mansoa alliacea (Lam.) leaf. Tail immersion model the standard drug morphine (5 mg/kg) showed 18.90 protection of analgesia while the M. alliacea leaf (100 & 200 mg/kg) produced 7.78 & 8.80 protection of analgesia respectively which is significant. In tail flick method hydroalcoholic extract of the M. alliacea leaf showed analgesic activity as there was significant increase in Tail flick latency time from 0 to 180 min. The maximum analgesic effect was shown at higher dose (200mg/kg, p.o.) which was comparable to that of diclofenac. Conclusions: Hydroalcoholic extract of Mansoa alliacea (Lam.) leaf was found to be effective in all three models of experimental pain. However it is less potent than standard analgesic drugs and could be employed safely in higher doses.

Keywords: Analgesic, hydroalcoholic extract, pain models.

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