Monitoring of beta-Blockers Ozone Degradation via Electrospray Ionization Mass Spectrometry

Santos, LS (reprint author), Talca Univ, Lab Asymmetr Synth, POB 747, Talca, Chile.The structures of intermediate products of ozone degradation of different pharmaceutical compounds have been studied. Under the conditions employed, complete ozone degradation of nadolol was achieved after 100 min. The degradation products obtained in aqueous solution were characterized by electrospray ionization mass (and tandem mass) spectrometry (ESI-MS and ESI-MS/MS). The proposed mechanism for degradation, ozone attacks at the aniline amino group giving rise to nitro compounds and further degradation occurs via a series of oxidative processes. Continuous online monitoring by ESI-MS(/MS) with high accuracy mass measurements showed that ozone degradation of atenolol (ATE) and acebutolol (ACE) occurs via mechanisms similar to that of nadolo

Using dynamic time warping for sleep and wake discrimination

In previous work, a Linear Discriminant (LD) classifier was used to classify sleep and wake states during single-night polysomnography recordings (PSG) of actigraphy, respiratory effort and electrocardiogram (ECG). In order to improve the sleep-wake discrimination performance and to reduce the number of modalities needed for class discrimination, this study incorporated Dynamic Time Warping (DTW) to help discriminate between sleep and wake states based on actigraphy and respiratory effort signal. DTW quantifies signal similarities manifested in the features extracted from the respiratory effort signal. Experiments were conducted on a dataset acquired from nine healthy subjects, using an LD-based classifier. Leave-one- out cross-validation shows that adding this DTW-based feature to the original actigraphy- and respiratory-based feature set results in an epoch-by-epoch Cohen’s Kappa agreement coefficient of ¿ = 0.69 (at an overall accuracy of 95.4%), which represents a significant improvement when compared with the performance obtained without using this feature. Furthermore it is comparable to the result obtained in the previous work which used additional ECG features (¿ = 0.70)

System and method for determining spectral boundaries for sleep stage classification

The present disclosure pertains to a system (10) configured to determine spectral boundaries (216, 218) for sleep stage classification in a subject (12). The spectral boundaries may be customized and used for sleep stage classification in an individual subject. Spectral boundaries determined by the system that are customized for the subject may facilitate sleep stage classification with higher accuracy relative to classifications made based on static, fixed spectral boundaries that are not unique to the subject. In some implementations, the system comprises one or more of a sensor (16), a processor (20), electronic storage (22), a user interface (24), and/or other components

System and method for cardiorespiratory sleep stage classification

The present disclosure pertains to a system configured to determine one or more parameters based on cardiorespiratory information from a subject and determine sleep stage classifications based on a discriminative undirected probabilistic graphical model such as Conditional Random Fields using the determined parameters. The system is advantageous because sleep is a structured process in which parameters determined for individual epochs are not independent over time and the system determines the sleep stage classifications based on parameters determined for a current epoch, determined relationships between parameters, sleep stage classifications determined for previous epochs, and/or other information. The system does not assume that determined parameters are discriminative during an entire sleep stage, but maybe indicative of a sleep stage transition alone. In some embodiments, the system comprises one or more sensors, one or more physical computer processors, electronic storage, and a user interface