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Background. Mounting evidence suggests that most tumors consist of a heterogeneous population of cells with a subset population that has the exclusive tumorigenic ability. They are called cancer stem cells (CSCs). CSCs can selfrenew to generate additional CSCs and also differentiate to generate phenotypically diverse cancer cells with limited proliferative potential. They have been identified in a variety of tumors. In this study, we identify the marker of CSCs in the established human laryngeal tumor Hep-2 cell line in vivo. Our in vitro experiment shown as CD133, a 5-transmembrane glycoprotein expressed in Hep-2 cell line. CD133 was supposed as a candidate of CSC in laryngeal carcinoma. In this study, the expression of CD133 was detected in a Hep-2 cell line. Applying the magnetic cell sorting (MACS) technology, we reported the results of purifying CD133 positive cells from a Hep-2 cell line.

Objectives/Hypothesis-Esophageal voice is a method of communication after total laryngectomy. Previous research suggests that perturbation analysis may inaccurately measure aperiodic voices and that nonlinear dynamic methods may be more appropriate for analyzing signals of this type. Therefore, we hypothesized that nonlinear dynamic analysis would be more capable than perturbation parameters for reliable measurement of the aperiodic esophageal voice.Study Design-Acoustic comparison of esophageal and normal voice cohorts using nonlinear dynamic and perturbation measures.Methods-Twenty subjects in two age-matched groups participated in the study. Jitter, shimmer, signal-to-noise ratio, correlation dimension, and second-order entropy were measured from audio recordings of subjects' voices.Results-Jitter and shimmer values were significantly higher for esophageal voices and signalto-noise ratio values were significantly lower for esophageal voices than for normal voices. Error count values, which indicate perturbation analysis reliability, were 0 in normal voices and significantly higher in esophageal voices. Error was attributable to signal aperiodicity and demonstrated that perturbation analysis yielded questionable results for esophageal voice. However, nonlinear dynamics measures analyzed both cohorts reliably and indicated that esophageal voice was significantly more chaotic than normal voice. Conclusions-The results demonstrated the capability of nonlinear dynamic methods to reliably quantify both aperiodic and periodic signals and to differentiate normal from esophageal voices. It is suggested that nonlinear dynamic analysis be used preferentially for acoustic characterization of aperiodic voices such as esophageal voice. Future research should focus on clarification of perturbation analysis reliability and further application of nonlinear dynamic measures to aperiodic voices.

Objective: We aim to examine the abilities of objective acoustic analysis methods (nonlinear dynamic and traditional perturbation measures) to describe voices from individuals with vocal nodules and polyps. Subjects and Methods: Sustained vowel recordings from normal subjects, patients with vocal nodules, and patients with vocal polyps were analyzed. Perturbation measures of jitter and shimmer were obtained with the Multi-Dimensional Voice Program (MDVP) and CSpeech. Signal-to-noise ratio was calculated using CSpeech. Nonlinear dynamic measures of phase space reconstruction and correlation dimension were also applied to analyze the voices. Results: A significant difference between normal and polyp groups was found in jitter and shimmer obtained from MDVP, as well as in jitter and signal-to-noise ratio from CSpeech. However, no parameters significantly differentiated between normal and nodule groups. Shimmer from CSpeech did not reveal any significant differences among any of the groups. Correlation dimension values for the nodule and polyp groups were significantly higher than the normal group. Conclusion: Nonlinear dynamic analysis has great potential value for the characterization of voice from patients with vocal nodules and polyps. The combination of traditional perturbation and nonlinear dynamic measures may improve our ability to provide objective clinical analysis of voices with vocal mass lesions.

In this paper, we investigate the biomechanical applications of spatiotemporal analysis and nonlinear dynamic analysis to quantitatively describe regular and irregular vibrations of twelve excised larynges from high-speed image recordings. Regular vibrations show simple spatial symmetry, temporal periodicity, and discrete frequency spectra, while irregular vibrations show complex spatiotemporal plots, aperiodic time series, and broadband spectra. Furthermore, the global entropy and correlation length from spatiotemporal analysis and the correlation dimension from nonlinear dynamic analysis reveal a statistical difference between regular and irregular vibrations. In comparison with regular vibrations, the global entropy and correlation dimension of irregular vibrations are statistically higher, while the correlation length is significantly lower. These findings show that spatiotemporal analysis and nonlinear dynamic analysis are capable of describing the complex dynamics of vocal fold vibrations from high-speed imaging and may potentially be helpful for understanding disordered behaviors in biomedical laryngeal systems.