ABSTRACT
cis-Diamminedichloroplatinum(II) (CDDP), which is mostly referred to as cisplatin, is a widely used antineoplastic. The efficacy of cisplatin can be improved by combining it with the vitamin B6 precursor pyridoxine. Here, we evaluated the putative synergistic interaction of CDDP with pyridoxine in the treatment of an orthotopic mouse model of non-small-cell lung cancer (NSCLC). CDDP and pyridoxine exhibited hyperadditive therapeutic effects. However, this synergy was only observed in the context of an intact immune system and disappeared when the otherwise successful drug combination was applied to the same NSCLC cancer implanted in the lungs of athymic mice (which lack T lymphocytes). Immunocompetent mice that had been cured from NSCLC by the combined regimen of CDDP plus pyridoxine became resistant against subcutaneous rechallenge with the same (but not with an unrelated) cancer cell line. In vitro, CDDP and pyridoxine did not only cause synergistic killing of NSCLC cells but also elicited signs of immunogenic cell death including an endoplasmic reticulum stress response and exposure of calreticulin at the surface of the NSCLC cells. NSCLC cells treated with CDDP plus pyridoxine in vitro elicited a protective anticancer immune response upon their injection into immunocompetent mice. Altogether, these results suggest that the combined regimen of cisplatin plus pyridoxine mediates immune-dependent antineoplastic effects against NSCLC.
Subject(s)
Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/immunology , Cisplatin/administration & dosage , Lung Neoplasms/drug therapy , Lung Neoplasms/immunology , Pyridoxine/administration & dosage , Animals , Calreticulin/metabolism , Cell Line, Tumor , Drug Synergism , Drug Therapy, Combination , Endoplasmic Reticulum Stress , Mice , Mice, SCID , Neoplasm Transplantation , Xenograft Model Antitumor AssaysABSTRACT
Wheezes are abnormal sounds which are known to be relevant to Chronic Obstructive Pulmonary Diseases (COPD). The analysis of such signals is especially useful in patient monitoring or pharmacology. Respiratory sounds are dependent on the flow and the volume. Furthermore, they can be the result of a complex mixture of events. The analysis of lung sounds can be greatly improved with time-frequency techniques because these methods highlight the evolution of the spectra of events. In this paper, we present the application of the Adaptive Local Trigonometric Decomposition (ALTD) to lung sound analysis. This analysis provides an optimal representation of the signal in the time-frequency domain with a lattice which is adapted in time. In our work, the parameterization of the ALTD is studied for the detection of wheezing phenomena.
Subject(s)
Numerical Analysis, Computer-Assisted , Respiratory Sounds , Signal Processing, Computer-Assisted , Sound Spectrography/methods , Algorithms , Humans , Numerical Analysis, Computer-Assisted/instrumentation , Reproducibility of Results , Respiratory Sounds/physiopathology , Signal Processing, Computer-Assisted/instrumentation , Sound Spectrography/instrumentationABSTRACT
In this paper, a wavelet packet-based method is used for detection of abnormal respiratory sounds. The sound signal is divided into segments, and a feature vector for classification is formed using the results of the search for the best wavelet packet decomposition. The segments are classified as containing crackles, wheezes or normal lung sounds, using Learning Vector Quantization. The method is tested using a small set of real patient data which was also analysed by an expert observer. The preliminary results are promising, although not yet good enough for clinical use.
Subject(s)
Lung Diseases/diagnosis , Lung Diseases/physiopathology , Numerical Analysis, Computer-Assisted , Respiratory Sounds/classification , Respiratory Sounds/physiopathology , Signal Processing, Computer-Assisted , Sound Spectrography/methods , Algorithms , Humans , Numerical Analysis, Computer-Assisted/instrumentation , Reproducibility of Results , Respiratory Sounds/physiology , Sensitivity and Specificity , Signal Processing, Computer-Assisted/instrumentation , Sound Spectrography/instrumentationABSTRACT
Respiratory sounds are composed of various events: normal and so-called adventitious sounds. These phenomena present a wide range of characteristics which make difficult their analysis with a single technique. Adapted time-frequency and time-scale techniques allow to fit best, under constraints, the accuracy of analysis of a time segmentation and, by the way, make feasible the study of complex signals. We present here new approaches based only on the wavelet packet decomposition to segment respiratory sounds.
Subject(s)
Lung Diseases, Obstructive/diagnosis , Lung Diseases, Obstructive/physiopathology , Numerical Analysis, Computer-Assisted , Respiratory Sounds/physiopathology , Signal Processing, Computer-Assisted , Sound Spectrography/methods , Algorithms , Humans , Numerical Analysis, Computer-Assisted/instrumentation , Reproducibility of Results , Respiratory Sounds/physiology , Signal Processing, Computer-Assisted/instrumentation , Sound Spectrography/instrumentation , Time FactorsABSTRACT
We investigate nonlinear multirate filterbanks with maximal decimation and perfect reconstruction. Definitions of the desired properties of such structures are given for general nonlinear filterbanks. We then consider a triangular representation of linear filterbanks and see that it may be easily extended to the nonlinear case. Furthermore, general nonlinear filterbanks are presented, for which perfect reconstruction is either inherently guaranteed or ensured subject to an easily verified condition. Extensions to bidimensional filters are also discussed and an application for nonlinear multiresolution schemes to feature sieves is shown.
