Fumonisin B-1 as a Urinary Biomarker of Exposure in a Maize Intervention Study Among South African Subsistence Farmers

Background: The consumption of maize highly contaminated with carcinogenic fumonisins has been linked to high oesophageal cancer rates. The aim of this study was to validate a urinary fumonisin B-1 (UFB1) biomarker as a measure of fumonisin exposure and to investigate the reduction in exposure following a simple and culturally acceptable intervention.

Methods: At baseline home-grown maize, maize-based porridge, and first-void urine samples were collected from female participants (n = 22), following their traditional food practices in Centane, South Africa. During intervention the participants were trained to recognize and remove visibly infected kernels, and to wash the remaining kernels. Participants consumed the porridge prepared from the sorted and washed maize on each day of the two-day intervention. Porridge, maize, and urine samples were collected for FB1 analyses.

Results: The geometric mean (95% confidence interval) for FB1 exposure based on porridge (dry weight) consumption at baseline and following intervention was 4.84 (2.87-8.14) and 1.87 (1.40-2.51) mg FB1/kg body weight/day, respectively, (62% reduction, P < 0.05). UFB1C, UFB1 normalized for creatinine, was reduced from 470 (295-750) at baseline to 279 (202-386) pg/mg creatinine following intervention (41% reduction, P = 0.06). The UFB1C biomarker was positively correlated with FB1 intake at the individual level (r - 0.4972, P < 0.01). Urinary excretion of FB1 was estimated to be 0.075% (0.054%-0.104%) of the FB1 intake.

Conclusion: UFB1 reflects individual FB1 exposure and thus represents a valuable biomarker for future fumonisin risk assessment.

Impact: The simple intervention method, hand sorting and washing, could positively impact on food safety and health in communities exposed to fumonisins. Cancer Epidemiol Biomarkers Prev; 20(3); 483-9. (C)2011 AACR.

The 0.5M(J) transiting exoplanet WASP-13b

We report the discovery of WASP-13b, a low-mass M-p = 0.46(-0.05)(+0.06) M-J transiting exoplanet with an orbital period of 4.35298 +/- 0.00004 days. The transit has a depth of 9 mmag, and although our follow-up photometry does not allow us to constrain the impact parameter well (0 <b <0.46), with radius in the range R-p similar to 1.06-1.21 R-J the location of WASP-13b in the mass-radius plane is nevertheless consistent with H/He-dominated, irradiated, low core mass and core-free theoretical models. The G1V host star is similar to the Sun in mass (M-* = 1.03(-0.09)(+0.11) M-circle dot) and metallicity ([M/H] = 0.0 +/- 0.2), but is possibly older (8.5(-4.9)(+5.5) Gyr).

Dielectronic recombination in He-like, Li-like, and Be-like highly charged ions in the KLL and KLM manifolds

This paper reports a systematic study of the dependence on atomic number of the dielectronic recombination resonance strengths for He-like, Li-like and Be-like ions. Recent measurements of dielectronic recombination resonance strengths for the KLL and KLM manifolds for iron, yttrium, iodine, holmium, and bismuth are also described. The resonance strengths were normalized to calculated electron impact ionization cross sections. The measured resonance strengths generally agree well with theoretical calculations using the distorted wave approximation. However, KLM resonance strength measurements on high atomic number open-shell ions gave higher values than those suggested by calculations. Using recently measured data, along with existing results, scaling laws have been generated as a function of atomic number for He-like, Li-like, and Be-like ions in the KLL and KLM manifolds.

Extinction risk from climate change

Climate change over the past ,30 years has produced numerous shifts in the distributions and abundances of species1,2 and has been implicated in one species-level extinction3. Using projections of species’ distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth’s terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a powerlaw relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15–37% of species in our sample of regions and taxa will be ‘committed to extinction’. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction (,18%) than mid-range (,24%) and maximum change (,35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.