Prediction of the Outcome of Esophageal Epithelium Dysplasia by High Resolution Image Analysis

Objective: To predict the outcome of dysplasia of esophageal epithelium by means of high resolution image analysis (HRIA). Methods: Asymptomatic adults were examined for balloon cytology of the esophagus in 1983 from Heshun Commune of Linxian County. 93 severe dysplasias and 122 mild dysplasias of the esophagus were selected. By means of an Axiomat-microscope equipped with TV-camera, 100 normal nuclei of well-preserved cells in the intermediate layer of Pap-stained squamous epithelium were randomly examined. Results: Of the 93 cytologically diagnosed severe dysplasia cases, 24, 14 and 7 progressed to carcinoma in 3, 5 and 9 years, respectively. In the other 48 cases, dysplasia remained stable or regressed to normal. The other cases were used as the control. According to chromatin features, correct diagnosis of cases was achieved by HRIA in 75.0% (18/24), 85.7% (12/14) and 85.7% (6/7) of the cases examined, respectively (P<0.001). Of the 122 cytologically diagnosed mild dysplasia, 16, 13 and 12 cases progressed to carcinoma in 3, 5 and 9 years, respectively. The other 81 cases remained stable or regressed to normal. Correct diagnosis was made by HRIA in 93.8% (15/16), 76.9% (10/13) and 83.3% (10/12) of the cases examined, respective1y (P<0.001). Conclusion: Chromatin nuclear features examined by HRIA can predict the outcome of precancerous lesions and discriminate progressor from non-progressor ones. It can be used as surrogate endpoint biomarkers for the evaluation of efficiency of chemo-prevention trial.

High Resolution Melting Curve Analysis for Rapid Detection of Pyrazinamide Resistance in Mycobacterium tuberculosis Clinical Isolates

Background: Pyrazinamide (PZA) is one of the most important drugs for tuberculosis (TB) treatment, however, its susceptibility is not routinely tested. High-resolution melting (HRM) curve analysis has been widely used for many applications. In this study, HRM assay was developed and evaluated for the detection of PZA resistance in Mycobacterium tuberculosis clinical isolates. Methods: Ninety five M. tuberculosis clinical isolates with different susceptibility patterns to anti-TB drugs were used to evaluate this assay. Isolates were phenotypically (Bactec MGIT 960) and genotypically (HRM and pncA gene sequencing) analysed for PZA resistance. Results: Bactec MGIT 960 analysis revealed that 29 of the 95 M. tuberculosis isolates were PZA resistant. In comparison to the Bactec MGIT 960, HRM showed a sensitivity of 47.7% and specificity of 74.6%, and the overall agreement between the two methods was 68.4%. Based on DNA sequencing, a correlation of 0.67 (significant at p-value pncA mutations was observed. PZA resistance was strongly associated with multi-drug resistant (MDR)-TB as it was shown in 79.3% of the MDR isolates included in the study. Conclusion: HRM is simple and useful for screening clinical M. tuberculosis isolates for PZA resistance, however, further modifications to improve its performance are required.

Optimization of wavelength range and data interval in chemometric analysis of complex pharmaceutical mixtures

The performance of different chemometric approaches was evaluated in the spectrophotometric determination of pharmaceutical mixtures characterized by having the amount of components with a very high ratio. Principal component regression （PCR）, partial least squares with one dependent variable （PLS1） or multi-dependent variables （PLS2）, and multivariate curve resolution （MCR） were applied to the spectral data of a ternary mixture containing paracetamol, sodium ascorbate and chlorpheniramine （150：140：1, m/m/m）, and a quaternary mixture containing paracetamol, caffeine, phenylephrine and chlorpheniramine （125：6. 25：1.25：1, m/m/m/m）. The UV spectra of the calibration samples in the range of 200-320 nm were pre-treated by removing noise and useless data, and the wavelength regions having the most useful analytical information were selected using the regression coefficients calculated in the multivariate modeling. All the defined chemometric models were validated on external sample sets and then applied to commercial pharmaceutical formulations. Different data intervals, fixed at 0.5, 1.0, and 2.0 point/nm, were tested to optimize the prediction ability of the models. The best results were obtained using the PLSlcalibration models and the quantification of the species of a lower amount was sig- nificantly improved by adopting 0.5 data interval, which showed accuracy between 94.24% and 107.76%.

DETECTION OF ELECTROMAGNETIC INCLUSIONS USING TOPOLOGICAL SENSITIVITY

In this article, a topological sensitivity framework for far-field detection of a diamet- rically small electromagnetic inclusion is established. The cases of single and multiple measurements of the electric far-field scattering amplitude at a fixed frequency are tak- en into account. The performance of the algorithm is analyzed theoretically in terms of its resolution and sensitivity for locating an inclusion. The stability of the framework with respect to measurement and medium noises is discussed. Moreover, the quantitative results for signal-to-noise ratio are presented. A few numerical results are presented to illustrate the detection capabilities of the proposed framework with single and multiple measurements.