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  1. Salman NH, Mok Sam L, Ador K, Binjamin B, Johny-Hasbulah MIJ, Benedick S
    J Toxicol, 2022;2022:4478082.
    PMID: 36246191 DOI: 10.1155/2022/4478082
    Honey is a natural product of bees, and its chemical composition depends on the nectar sources of the surrounding flora as well as environmental factors. However, keeping hives in areas polluted with heavy metals can affect the quality of bee products such as honey. To date, there have been very few studies on the health risks of consuming honey at various locations in the Malaysian state of Sabah, Borneo, in relation to food standards and heavy metal contamination of honey from the stingless bee, Heterotrigona itama in association with pollutant sources. A total of 63 samples of raw and unprocessed honey were collected directly from beekeepers producing honey at five sites in the industrial areas. All selected heavy metals were measured using an inductively coupled plasma optical emission spectrophotometer (ICP-OES). Overall, the most frequently detected element was Zn (0.090 mg/kg), followed by Pb (0.012 mg/kg), As (0.004 mg/kg), and Cr (0.003 mg/kg), while Cd (0.001 mg/kg) was the lowest element in honey from all areas. With the exception of Cr and Zn, a significant correlation was found between PCA factor score 1 and heavy metal concentration in honey for Pb, Cd, and As, suggesting that the source of pollution for these metal elements was from hives closer to major roads, cities/town, petrochemical hub, and power plants. Although the heavy metal concentrations in the honey samples did not exceed the food standard limits and therefore do not pose a health risk, the observed increase in heavy metal concentrations in honey in industrial areas could pose a potential risk in the future due to the growing interest in rearing of stingless bees for honey production in these areas of Sabah.
  2. Kono Y, Tsukamoto K, Abd Hamid M, Darus A, Lian TC, Sam LS, et al.
    Am J Trop Med Hyg, 2001 5 19;63(1-2):94-101.
    PMID: 11358004
    A new virus named Sitiawan virus (SV) was isolated from sick broiler chicks in chicken embryos. The virus replicated well with cytopathogenic effect (CPE) in the chicken B-lymphocyte cell line LSCC-BK3. The virus was an enveloped RNA virus of approximately 41 nm in size with hemagglutinating activity (HA) to goose erythrocytes. It was cross-reactive with Japanese encephalitis virus (JEV), a member of flaviviruses by HA inhibition tests but not by cross-virus neutralization tests. The cDNA fragment of NS5 gene was amplified with primers corresponding to NS5 gene of flaviviruses. The nucleotide sequences were 92% homologous to Tembusu virus, a member of the mosquito-borne virus cluster of the genus Flavivirus. In cross-neutralization tests with Tembusu virus, antiserum to SV did not neutralize Tembusu virus, and antiserum to Tembusu virus neutralized more weakly to SV than against homologous virus. These results indicate that SV is a new virus which can be differentiated serologically from Tembusu virus but is otherwise similar with respect to nucleotide sequence. The virus causes encephalitis, growth retardation, and increased blood glucose levels in inoculated chicks.
  3. Colwell RK, Gotelli NJ, Ashton LA, Beck J, Brehm G, Fayle TM, et al.
    Ecol Lett, 2016 09;19(9):1009-22.
    PMID: 27358193 DOI: 10.1111/ele.12640
    We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.
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