Universiti Malaysia Sabah

About: Universiti Malaysia Sabah is a education organization based out in Kota Kinabalu, Malaysia. It is known for research contribution in the topics: Population & Iterative method. The organization has 3945 authors who have published 5910 publications receiving 78556 citations. The organization is also known as: Malaysian University of Sabah & University Malaysia Sabah.

Global diversity and geography of soil fungi

Abstract: Fungi play major roles in ecosystem processes, but the determinants of fungal diversity and biogeographic patterns remain poorly understood. Using DNA metabarcoding data from hundreds of globally distributed soil samples, we demonstrate that fungal richness is decoupled from plant diversity. The plant-to-fungus richness ratio declines exponentially toward the poles. Climatic factors, followed by edaphic and spatial variables, constitute the best predictors of fungal richness and community composition at the global scale. Fungi show similar latitudinal diversity gradients to other organisms, with several notable exceptions. These findings advance our understanding of global fungal diversity patterns and permit integration of fungi into a general macroecological framework.

Scale for the assessment and rating of ataxia: development of a new clinical scale.

Abstract: OBJECTIVE: To develop a reliable and valid clinical scale measuring the severity of ataxia. METHODS: The authors devised the Scale for the Assessment and Rating of Ataxia (SARA) and tested it in two trials of 167 and 119 patients with spinocerebellar ataxia. RESULTS: The mean time to administer SARA in patients was 14.2 +/- 7.5 minutes (range 5 to 40). Interrater reliability was high, with an intraclass coefficient (ICC) of 0.98. Test-retest reliability was high with an ICC of 0.90. Internal consistency was high as indicated by Cronbach's alpha of 0.94. Factorial analysis revealed that the rating results were determined by a single factor. SARA ratings showed a linear relation to global assessments using a visual analogue scale, suggesting linearity of the scale (p < 0.0001, r(2) = 0.98). SARA score increased with the disease stage (p < 0.001) and was closely correlated with the Barthel Index (r = -0.80, p < 0.001) and part IV (functional assessment) of the Unified Huntington's Disease Rating Scale (UHDRS-IV) (r = -0.89, p < 0.0001), whereas it had only a weak correlation with disease duration (r = 0.34, p < 0.0002). CONCLUSIONS: The Scale for the Assessment and Rating of Ataxia is a reliable and valid measure of ataxia, making it an appropriate primary outcome measure for clinical trials.

A review of the effects of emerging contaminants in wastewater and options for their removal

Abstract: The occurrence of emerging or newly identified contaminants in our water resources is of continued concern for the health and safety of consuming public. The existing conventional water treatment plants were not designed for these unidentified contaminants. The endocrine disrupting chemicals (EDCs) comprise pharmaceuticals, personal care products, surfactants, various industrial additives and numerous chemicals purported to be endocrine disrupter. These have become a threat to our water supply network. The current wastewater treatment system is not effective in elimination of these different classes of emerging contaminants as these have not been monitored due to the absence of stringent regulation specific to these contaminants. These undesirable compounds are being released, knowingly or unknowingly, into the aquatic environment that affect the whole living organism. The paper discusses adverse effects of these emerging contaminants to water consumers and discusses the potential removal processes. The use of activated carbon, oxidation, activated sludge, nanofiltration and reverse osmosis membranes, and their efficiencies in removal of these pollutants, are reviewed. In particular, the nanofiltration removal mechanism is emphasized because of its utmost importance in eliminating micropollutants.

A review of the antioxidant potential of medicinal plant species

Abstract: Some researchers suggest that two-thirds of the world's plant species have medicinal value; in particular, many medicinal plants have great antioxidant potential. Antioxidants reduce the oxidative stress in cells and are therefore useful in the treatment of many human diseases, including cancer, cardiovascular diseases and inflammatory diseases. This paper reviews the antioxidant potential of extracts from the stems, roots, bark, leaves, fruits and seeds of several important medicinal species. Synthetic antioxidants such as butylated hydroxytoluene (BHT) and butylated hydroxylanisole (BHA) are currently used as food additives, and many plant species have similar antioxidant potentials as these synthetics. These species include Diospyros abyssinica, Pistacia lentiscus, Geranium sanguineum L., Sargentodoxa cuneata Rehd. Et Wils, Polyalthia cerasoides (Roxb.) Bedd, Crataeva nurvala Buch-Ham., Acacia auriculiformis A. Cunn, Teucrium polium L., Dracocephalum moldavica L., Urtica dioica L., Ficus microcarpa L. fil., Bidens pilosa Linn. Radiata, Leea indica, the Lamiaceae species, Uncaria tomentosa (Willd.) DC, Salvia officinalis L., Momordica Charantia L., Rheum ribes L., and Pelargonium endlicherianum. The literature reveals that these natural antioxidants represent a potentially side effect-free alternative to synthetic antioxidants in the food processing industry and for use in preventive medicine.

The importance of correcting for sampling bias in MaxEnt species distribution models

Abstract: Aim Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo. Location Borneo, Southeast Asia. Methods We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas. Results Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased. Main Conclusions We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.