Aguirre Kaufman (robertcarp98)

The strategy exhibited the limit of detection as low as 0.009 U mL-1 and 0.003 U mL-1 for Dnmt1 and UDG, respectively. Meanwhile, this strategy was successfully applied to detect Dnmt1 and UDG activities in living cell samples at single-cell level and assay the inhibitors of Dnmt1 and UDG. Therefore, the strategy provided a potential method to detect Dnmt1 and UDG activities in biological samples for early clinic diagnosis and therapeutics. Gasotransmitter hydrogen sulfide (H2S), produced enzymatically in body, has important functions in biological signaling and metabolic processes. An abnormal level of H2S expression is associated with different diseases, therefore, development of novel bioanalytical methods for rapid and effective detection of H2S in biological conditions is of great importance. In this work, we report the development of a new responsive nanosensor for ratiometric luminescence detection of H2S in aqueous solution and live cells. The nanosensor (Ru@FITC-MSN) was prepared by immobilizing a luminescent ruthenium(II) (Ru(II)) complex into a fluorescein isothiocyanate (FITC) conjugated water-dispersible mesoporous silica nanoparticle (MSN), showing dual emission bands at 520 nm (FITC) and 600 nm (Ru complex). The red luminescence of the formed Ru@FITC-MSN was quenched in the presence of Cu2+. check details The in-situ generated Ru-Cu@FITC-MSN responded to H2S rapidly and selectively, showing a linear ratiometric luminescence change in FITC and Ru(II) channels with the H2S concentration (0.5-4 μM). Limit of detection (LoD) and limit of quantification (LoQ) were determined to be 0.36 and 1.21 μM. Followed by investigation of cellular uptake processes, the utility of the nanosensor for ratiometric imaging of H2S in live cells and its capability to monitor H2S levels in inflammatory breast cancer cells were then demonstrated. This study provides a powerful approach for detection of highly reactive and unstable H2S biomolecules in live systems. Model-based algorithms have recently attracted much attention for data pre-processing in tissue mapping and imaging by Fourier transform infrared micro-spectroscopy (FTIR). Their versatility, robustness and computational performance enabled the improvement of spectral quality by mitigating the impact of scattering and fringing in FTIR spectra of chemically homogeneous biological systems. However, to date, no comprehensive algorithm has been optimized and automated for large-area FTIR imaging of histologically complex tissue samples. Herein, for the first time, we propose a unique, integrated and fully-automated Multiple Linear Regression Multi-Reference (MLR-MR) method for correcting linear baseline effects due to diffuse scattering, for compensating substrate thickness inhomogeneity and accounting for sample chemical heterogeneity in FTIR images. In particular, the algorithm uses multiple-reference spectra for histologically heterogeneous biological samples. The performance of the procedure was demonstrated for FTIR imaging of chemically complex rat brain frontal cortex tissue samples, mounted onto Ultralene® films. The proposed MLR-MR correction algorithm allows the efficient retrieval of "pure" absorbance spectra and greatly improves the histological fidelity of FTIR imaging data, as compared with the one-reference approach. In addition, the MLR-MR algorithm here presented opens up the possibility for extracting information on substrate thickness variability, thus enabling the indirect evaluation of its topography. As a whole, the MLR-MR procedure can be easily extended to more complex systems for which Mie scattering effects must also be eliminated. In this work, we developed a ''naked-eye'' colorimetric and ratiometric fluorescence probe for a very important biomarker of uric acid (UA). The method was based on the oxidation of UA by uricase to allantoin and hydrogen peroxide, and then o-Phenylenediamine (OPD) was oxidized to the yellow-col