Non-invasive optical imaging of cathepsin B with activatable fluorogenic nanoprobes in various metastatic models.

An increasing number of treatments of metastases rely on diagnostics and imaging these days. The facts that the activity of cathepsin B (CB) is markedly linked to the metastatic process and that CB is found highly expressed in the pericellular regions in this process make CB an attractive target for diagnosing metastases. We have developed a CB-sensitive nanoprobe (CB-CNP) consisting of self-quenched CB-sensitive fluorogenic peptide probes conjugated onto the surface of tumor-targeting glycol chitosan nanoparticles (CNPs). The freshly prepared CB-CNP formed a spherical nanoparticle structure (280 nm in diameter) and the fluorescence intensity of CB-CNP was strongly quenched in physiological condition. However, self-quenched CB-CNP boosted strong fluorescence signals in the presence of CB, not of cathepsin l or cathepsin d, due to the CB-specific cleavage of self-quenched peptide probes. Importantly, the intravenously injected CB-CNP demonstrated the potential to discriminate metastases in vivo in three metastatic mouse models, including 4T1-luc2 liver metastases, RFP-B16F10 lung metastases and HT1080 peritoneal metastases. Indeed, Western blot analysis confirmed that the CB expression of metastases had increased compared to normal organ in these metastatic mouse models. CB-CNPs may be useful for depicting metastases through non-invasive CB molecular imaging.

Motor noise removal for determining gait events over treadmill walking using wavelet filter.

The conventional method for filtering force plate data, low-pass filtering, does not always give accurate results when applied to force data from a custom-made, instrumented treadmill. Therefore, this study compares low-pass filtered data to the same data passed through a wavelet filter. We collected data with the treadmill running. However these include motor noise with ground reaction force at two force plates. We found that he proposed wavelet method eliminated motor noise to result in more accurate force plate data than the conventional low-pass filter, particularly at high speed motor operation. In this study we suggested the convolution wavelet (CNW) which was compared to that of a low-pass filter. The CNW showed better performance as compared to band-pass filtering particularly for low signal-to-noise ratios, and a lower computational load.