ANTIMALARIAL AND ANTIOXIDANT EFFECTS OF Persea Americana (avocado) LEAF EXTRACT IN Plasmodium berghei-INFECTED MICE
DOI:
https://doi.org/10.33003/fjs-2025-0904-3577Keywords:
Antimalaria, Antioxidant, Persea Americana, Oxidative stressAbstract
The emergence of drug-resistant Plasmodium strains necessitates the search for alternative treatment strategies, including plant-derived bioactive compounds with antimalarial and antioxidant properties. Persea americana (avocado) leaves have been reported to possess medicinal benefits, but their antimalarial potential remains underexplored. This study evaluates the antimalarial and antioxidant effects of P. americana leaf extract in Plasmodium berghei-infected mice. Mice infected with P. berghei were treated with varying doses of the extract, and body weight, rectal temperature, packed cell volume (PCV), parasitemia levels, and oxidative stress markers were assessed. Results demonstrated a significant improvement in body weight and PCV, as well as reductions in rectal temperature, parasitemia, improved parasite clearance, and enhanced antioxidant enzyme activity in treated groups compared to the untreated control. These findings suggest that P. americana leaf extract possesses potent antimalarial and antioxidant properties, supporting its potential as a complementary therapeutic agent. Further studies are needed to elucidate its mechanisms of action and optimize dosage for clinical applications. This study contributes to the ongoing search for plant-based alternatives in malaria treatment and oxidative stress management.
References
Abdul K., and Jahir U. C. (1995) A comparison of four distributions used in flood frequency analysis in Bangladesh Hydrological Sciences -Journal- des Sciences Hydrologiques, 40(l): 55-65.
Carlos E. S. and Jose R. V. (2008). Trivariate generalized extreme value distribution in flood frequency analysis. Hydrological SciencesJournaldes Sciences Hydrologiques, 53(3): 550 -567.
.
Cunnane, C. (1978). Unbiased Plotting Positions- A Review, Journal of Hydrology. 3(7): 205-222.
Ehiorobo J.O and Audu HAP (2012) Monitoring of Gully Erosion in an Urban Area Using Geoinformatics Technology Journal of Emerging Trends in Engineering and Applied Science (JETEAS), 3(2): 270-275
Erah, P.O., Akujieze, C.N and Oteze G.E. (2002). The Quality of groundwater in Benin City: a baseline study on inorganic chemicals and microbial contaminants of health importance inboreholes and open wells. Tropical Journal of Pharmaceutical Research, 1(2): 75-82.
Ewemoje T. A., Ewemooje O. S. (2011). Best distribution and plotting positions of daily maximum flood estimation at Ona River in Ogun-oshun river basin, Nigeria. Agricultural Engineering International: CIGR Journal. 13(3): 78-100.
Gobo, A.E. (1988). On the Relationship between Rainfall Trends and Flooding in the Niger- Benue River Basins The Journal of Meteorology 13(132): 318 324.
Hasan M. (2003), Studies on the Flood Analysis of the Congaree Swamp National Monument KSU Journal Science and Engineering. 6(2): 130 141.
Hosking, J.R.M. (1990) L- moment: Analysis and estimation of distributions using linear combination of order statistics, Journal Resource Statistic Society Service. (52): 105-124
Hirsch, R.M., 1982: A comparison of four record extension techniques, Water Resources Research, 18(4): 10811088.
Ibrahim H. M. and Isiguzo, E. A. (2009) Flood frequency analysis of Gurara River catchment at Jere, Kaduna State Scientific Research and Essay 4(6): 636-646.
Izinyon O. C, Ihimekpen N. and Igbinoba G.E (2011) Frequency Analysis of Ikpoba River Catchment at Benin City Using Log Pearson Type 111 Distribution. Journal of Emerging Trends in Engineering and Applied Sciences. 2(1): 50-55.
Izinyon O.C. and Ajumuka H. N. (2013), Probability distribution models for flood prediction in upper Benue River Basin Part II. Civil and Environment Research, 3(2): 62-74.
Khosravi, K., Shahabi, H., Pham, B. T., Adamowski, J., Shirzadi, A., Pradhan, B., Prakash, I. (2019). A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods. Journal of Hydrology, 573: 311323. https://doi.org/10.1016/j.jhydrol.2019.03.073
Mahdavi M., Khaled O., Sayed A., Naghi S., Bakhtiar K. and Jalil M. (2010) Determining SuiTable Probability Distribution Models for Annual Data (A Case Study of Mazandaran and Golestan Provinces). Journal of Sustainable Development. 3(1): 159-168.
Morrison, J. E., and J. A. Smith (2002), Stochastic modeling of flood peaks using the generalized extreme value distribution, Water Resource Journal., 38(12): 1305.
Olofintoye, O.O, Sule, B.F and Salami, A.W (2009) Best- Fit Probability Distribution Model for Peak Daily Rainfall of Selected Cities in Nigeria, New York Science Journal. 6(2): 76.
Omofonmwan, S.I. and Eseigbe, J.O (2009). Effects of solid waste on the quality of underground water in Benin Metropolis, Nigeria. Journal of Human Ecology, 26(2): 99 -105.
Sulaiman Yunus (2021) Delineation of Urban Flood Risk Areas Using Geospatial Technique Fudma Journal of Sciences, 5(1): 1-10
Sathe B.K., Khire M.V., Dhumal H.T. and Sankhua R.N. (2011). Design Flood Estimation Of River Krishna Koyana Confluence Basin Catchment Area In Western Maharashtra Using Log Person Type Iii Distribution. Journal of Sustainable Development. 2(1): 59-68
Takashi (1982) Increased sedimentation rates in reservoirs, Journal of Human Ecology. (3): 9
Ummi N. A., Ani S. and Zahrahtul A. Z. (2011). Flood Frequency Analysis of Annual Maximum Stream Flows using L-Moments and TL-Moments Approach Applied Mathematical Science Journal, 5(5): 243 253.
Published
How to Cite
Issue
Section
FUDMA Journal of Sciences
