Underutilized plants are referred to a plant species whose potential is not fully utilized yet and they are usually found abundantly in certain local areas but are globally rare. Sabah is known for high biodiversity and contains many underutilized plants. To our knowledge, this is the first review to provide overview information of the medicinal value and pharmacological properties of underutilized plants in Sabah. Extract and metabolites in different parts of several underutilized plants contain multiple beneficial bioactive compounds and the exploitation of these compounds was supported by additional data that plays various biological activities, including anti-atherosclerotic, anti-cancer antihypercholesterolemic and anti-ulcerogenic. A handful of pharmacological studies on these underutilized plants have conclusively outlined the mode of action in treatment of several diseases and in other health aspects. This paper limits its scope to review and highlight the potential of using underutilized plants in Sabah only which could serve as reliable resource for health product development in pharmaceutical and nutraceutical through continuous discovering of more active and sustainable resources as well as ingredients for food and medicine.
The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in hydrological records is an important and neglecting non-stationary patterns in flood data can lead to significant biases in estimating flood quantiles. Consequently, adopting a non-stationary flood frequency analysis appears to be a suitable approach to challenge the assumption of independent and identically distributed observations in the sample. This research employed the generalized extreme value (GEV) distribution to examine annual maximum flood series. To estimate non-stationary models in the flood data, several statistical tests, including the TL-moment method was utilized on the data from ten stream-flow stations in Johor, Malaysia, which revealed that two stations, namely Kahang and Lenggor, exhibited non-stationary behaviour in their annual maximum streamflow. Two non-stationary models efficiently described the data series from these two specific stations, the control of which could reduce outbreak of infectious diseases when used for controlling the development measures of the hydraulic structures. Thus, the application of these models may help prevent biased prediction of flood occurrences leading to lower number of cases infected by disease.