PubMed · 14071011
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R TERANISHI, T R MON. 1963. LARGE DIVIDED COLUMNS.. https://doi.org/10.1016/s0021-9673(01)83706-7
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The Mycobacterium tuberculosis (MTB) shows different virulence and host infection range from other members of the M. tuberculosis complex (MTBC). Differential identification of MTB from MTBC is thus important in certain occasions. The currently commercially available molecular assays which use either IS6110 or 16S rDNA fragment as identification targets are mainly designed for identifying MTBC but not for MTB. Comparative genomic DNA analysis has provided valuable information on regions of difference (RD) present in MTB but not in other members of the MTBC. RD9 region is further suggested to be a potential target for differential identification of MTB from MTBC. In this study, using IS6110 and Rv3618 (belong to RD9) as the specific identification targets for MTBC and MTB, respectively, we developed and tested a multiplex nested PCR-ICT (immuno-chromatography test) assay for simultaneously and directly detecting not only MTBC but also MTB from 1500 clinical sputum specimens. The results were compared with traditional culture and biochemical identification results together with patients' clinical assessments. This assay showed a 95.5% sensitivity, 97.9% specificity, 2.1% false positive rate and 4.5% false negative rate towards detection of MTBC, and a 93.0% sensitivity, 99.8% specificity, 0.2% false positive rate and 7.0% false negative rate for detection of MTB. This detection system shows great potential in clinical application.
The retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides was studied by quantitative structure-property relationships (QSPR) method. Heuristic method (HM) and support vector machine (SVM) method were used to build linear and nonlinear models, respectively. Compared the results of these two methods, those obtained by the SVM model are much better. For the test set, a predictive correlation coefficient (R) of 0.9755 and root-mean-square (RMS) error of 0.1403 were obtained. The proposed QSPR models, both by HM and SVM, contain the same descriptors that agree with the classical Abraham parameters of well-known linear solvation energy relationships (LSER).
Experimental implementation of an optimizing controller based on identified model for the separation of nucleosides in a laboratory scale simulated moving bed (SMB) unit is reported in this study. The manipulative variables are the three external and one internal flow rates while the outputs are productivity, solvent consumption, and purities of extract and raffinate streams averaged over a switching period. The feedback information is the concentration profile of extract and raffinate measured online using two ultraviolet (UV) detectors. Experimental results show that the designed controller is able to operate the SMB units under optimal condition fulfilling the purity requirements. Besides, the controller demonstrated excellent performance in terms of rejecting disturbances that may occur during SMB operations.