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It was shown that all compounds containing carbon atoms, tested in this study, were degraded by the coincident influence of light, oxygen (air), and water. By this photooxidation, saturated as well as unsaturated aliphatic and aromatic compounds, monomeric, polymeric and high polymeric compounds were degraded and the carbon atoms of these compounds as well as carbon itself in the form of amorphous carbon or diamond, were converted to carbon dioxide, if dispersed in water or together with water as very small solid, liquid, or gaseous particles. As such conditions occur extensively in nature, it was concluded that this degradation of organic substances is of great importance in nature, in addition to microbial and enzymatic degradation. This photooxidation further represents a possibility for pollution control to prevent damage to environment by degrading organic substances which are either slightly soluble or practically insoluble in water, as well as compounds which will not be destroyed by microbial and enzymatic degradation. [ABSTRACT FROM AUTHOR]

Single cell analysis techniques have great potential in the cancer genomics field. The detection and characterization of circulating tumour cells are important for identifying metastatic disease at an early stage and monitoring it. This protocol is based on transcript profiling using Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (RT-MLPA), which is a specific method for simultaneous detection of multiple mRNA transcripts. Because of the small amount of (circulating) tumour cells, a pre-amplification reaction is performed after reverse transcription to generate a sufficient number of target molecules for the MLPA reaction. We designed a highly sensitive method for detecting and quantifying a panel of seven genes whose expression patterns are associated with breast cancer, and optimized the method for single cell analysis. For detection we used a fluorescence-dependent semi-quantitative method involving hybridization of unique barcodes to an array. We evaluated the method using three human breast cancer cell lines and identified specific gene expression profiles for each line. Furthermore, we applied the method to single cells and confirmed the heterogeneity of a cell population. Successful gene detection from cancer cells in human blood from metastatic breast cancer patients supports the use of RT-MLPA as a diagnostic tool for cancer genomics. [ABSTRACT FROM AUTHOR]