ABSTRACT
Zeolite supportedα-cyano-4-hydroxycinnamic acid ( CHCA) as novel composite matrix was applied in matrix assisted laser desorption ionization time-of-flight mass spectrometry ( MALDI-TOF-MS ) analysis of substance P and small molecular compounds of fluoroquinolones. In the experiment, this new matrix was examined and compared with conventional organic matrix CHCA. The results indicated that the novel composite matrix was capable of suppressing the alkali metal related peaks and interference fragments, simplifying mass spectra in low-molecular-weight region, and promoting ionization efficiency. The influence of SiO2/Al2 O3 ratio of ZSM-5 and porous diameter of ZSM-5 and Beta zeolites on performance of MALDI-TOF-MS analysis of substance P was also investigated under the same conditions. In contrast, it was regarded that the strong surface acidity and sufficient cavity for loading CHCA were beneficial for interference fragments suppression and peak intensity enhancement. Additionally, it was successfully applied in the detection of enrofloxacin and ciprofloxacin in complex samples.
ABSTRACT
Zeolite supportedα-cyano-4-hydroxycinnamic acid ( CHCA) as novel composite matrix was applied in matrix assisted laser desorption ionization time-of-flight mass spectrometry ( MALDI-TOF-MS ) analysis of substance P and small molecular compounds of fluoroquinolones. In the experiment, this new matrix was examined and compared with conventional organic matrix CHCA. The results indicated that the novel composite matrix was capable of suppressing the alkali metal related peaks and interference fragments, simplifying mass spectra in low-molecular-weight region, and promoting ionization efficiency. The influence of SiO2/Al2 O3 ratio of ZSM-5 and porous diameter of ZSM-5 and Beta zeolites on performance of MALDI-TOF-MS analysis of substance P was also investigated under the same conditions. In contrast, it was regarded that the strong surface acidity and sufficient cavity for loading CHCA were beneficial for interference fragments suppression and peak intensity enhancement. Additionally, it was successfully applied in the detection of enrofloxacin and ciprofloxacin in complex samples.
ABSTRACT
<p><b>OBJECTIVE</b>To improve the accuracy and efficiency of pulmonary nodule segmentation of thoracic CT image for computer-aided diagnostic (CAD) system, especially for those nodules adhering to the pleural or blood vessels.</p><p><b>METHODS</b>We proposed the automatic process of pulmonary nodule segmentation, and using region growing method based on the contrast and gradient, the pulmonary nodule images were acquired. A self-adapted morphologic segmentation algorithm was presented for the unsuccessful nodule segmentation using region growing.</p><p><b>RESULTS AND CONCLUSIONS</b>Experiments on clinical 2D pulmonary images showed that the solitary pulmonary nodules and those adhering to the pleural or blood vessels could all be segmented. This pulmonary nodule segmentation algorithm is feasible for automated segmentation of the thoracic CT images.</p>