Browsing by Author "Sutherland, Garnette Roy"

Now showing 1 - 1 of 1
  • Thumbnail Image
    ItemOpen Access
    Vibrational Profiling of Brain Cells and Tumours using Atomic Force Microscopy
    (2018-03-08) Nelson, Sultan; Amrein, Matthias; Green, Francis H. Y.; Sutherland, Garnette Roy
    Nanoscopic mechanical vibration is observed as a periodic plasma-membrane fluctuation in living cells. The study of this physiological phenomenon is an emerging field of research. All prior experimental work has been limited to single cell study, including erythrocytes (1,2), leukocytes (3), and cardiomyocytes (4). Moreover, the intensity of fluctuation has been shown to be indicative of cells’ overall metabolic activity (5,6). The fluctuation can be modulated using pharmacological blockers (7,8), thus excluding stochastic Brownian motion as the sole explanation. Given our main interest in the potential clinical application of this phenomenon for qualitative and efficient brain tumor identification, we examined vibration waves emanating from cultured cells, and tissues harvested from the brains of newborn rats, as well as from brain tumors and neocortex specimens. In this research project, we first developed a novel atomic force microscope-based (AFM-based) mechanical vibration detection method and a custom-written MATLAB vibration signal analysis algorithm. The AFM system used in this report utilized sensitive cantilevers (probes) to enhance the signal-to-noise ratio, and to improve overall performance. The method was also designed to detect cellular vibration without direct physical contact between the sample and the cantilever probe. Using this unique method, we recorded vibrations emitted from newborn rat hippocampus and cerebellum samples; these brain regions showed distinct vibration profiles. The effect of pharmacological agents on the tissue samples examined suggested synaptic activity is the major contributor to the subtle vibrations observed. For assessment of potential clinical applications of the method, we examined human surgical brain biopsy samples. Malignant astrocytoma tissue samples vibrated with markedly different frequency peaks and amplitude, compared to tissue from meningioma or normal lateral temporal cortex, thus providing a quantifiable measurement to accurately distinguish the three types of tissues. Lastly, we developed a method to convert cellular oscillation signals into sound within the frequency range of normal human hearing to provide medical specialists with a way to differentiate tumors from healthy brain tissue without the need for extensive, complex vibration, spectral analysis training. Evidence attested through this project has shown that vibrational profiling of cells and tissues can be adopted for simultaneous mapping of neuronal and metabolic activity in the brain. Further, the results of this research may have translational clinical implications as a prompt diagnostic technique, which may aid clinicians in discerning between healthy and cancerous tissues in real-time.