Distribution and assessment of cadmium contamination in sediments from the Four River inlets to Dongting Lake, China.

The total concentrations of Cd in bulk sediments and those of the BCR sequential extraction fractions of sediments from inlets of the Four Rivers that feed Dongting Lake were determined using ICP-MS techniques. The results suggested that Cd was heterogeneously distributed in the inlet sediments of the rivers, with the highest degree of enrichment in sediments from the Xiangjiang River. The Cd anomaly was defined as Cd enrichment in sediments with an EF (enrichment factor) > 10.0, and it was identified in the inlet sediments of the Xiangjiang River. Cd in the sediments was dominated by acid-soluble Cd at a proportion of 23.9-69.8 (%) compared to its total concentrations in the sediments. The inlet sediments of the Four Rivers were contaminated with Cd, with the highest degree of contamination in the inlet sediments of the Xiangjiang River. The Cd contamination as well as the Cd anomaly in the sediments were closely related to the industrial activities (e.g. smelting and refining for ore minerals) in the areas, and Cd contamination at high levels may represent an ecological risk for the lake watershed. Cd contamination of the inlet sediments may also impact the lake basin sediments and is harmful to the lake ecological system, particularly for sediments of the Xiangjiang River. Therefore, it is essential to control and treat Cd contamination in the inlet sediments for ecological environmental protection of lake watersheds.

Analysis of the Diffusivity Change from Single-Molecule Trajectories on Living Cells.

With the wide application of live-cell single-molecule imaging and tracking of biomolecules at work, deriving diffusion state changes of individual molecules is of particular interest as these changes reflect molecular oligomerization or interaction with other cellular components and thus correlate with functional changes. We have developed a Rayleigh mixture distribution-based hidden Markov model method to analyze time-lapse diffusivity change of single molecules, especially membrane proteins, with unknown dynamic states in living cells. With this method, the diffusion parameters, including diffusion state number, state transition probability, diffusion coefficient, and state mixture ratio, can be extracted from the single-molecule diffusion trajectories accurately via easy computation. The validity of our method has been demonstrated with not only experiments on synthetic trajectories but also single-molecule fluorescence imaging data of two typical membrane receptors. Our method offers a new analytical tool for the investigation of molecular interaction kinetics at the single-molecule level.

Analysis of the steps in single-molecule photobleaching traces by using the hidden markov model and maximum-likelihood clustering.

The step analysis of single-molecule photobleaching data offers a new approach for studying protein stoichiometry under physiological conditions. As such, it is important to develop suitable algorithms that can accurately extract the step events from the noisy single-molecule data. Herein, we report a HMM method that combines maximum-likelihood clustering for initializing the emission-probability distribution of the HMMs with an extended silhouette clustering criterion for estimating the state number of single molecules. In this way, the limitations of standard HMM in terms of processing typical single-molecule data with a short sequence are overcome. By using this method, the number and time points of the step events are automatically determined, without the introduction of any subjectivity. Simulation experiments on the experimental photobleaching data indicate that our method is very effective and robust in the analysis of single-molecule fluorescence photobleaching curves if the signal/noise ratio is larger than 2:1. This method was employed for processing photobleaching data that were obtained from single-molecule fluorescence imaging of transforming growth factor typeII receptors on a cell surface. This method is also expected to be applicable to the analysis of other stepwise events.