20 research outputs found
Atomic Force Microscopy Study of Nano-Physiological Response of Ladybird Beetles to Photostimuli
Background: Insects are of interest not only as the most numerous and diverse group of animals but also as highly efficient bio-machines varying greatly in size. They are the main human competitors for crop, can transmit various diseases, etc. However, little study of insects with modern nanotechnology tools has been done. Methodology/Principal Findings: Here we applied an atomic force microscopy (AFM) method to study stimulation of ladybird beetles with light. This method allows for measuring of the internal physiological responses of insects by recording surface oscillations in different parts of the insect at sub-nanometer amplitude level and sub-millisecond time. Specifically, we studied the sensitivity of ladybird beetles to light of different wavelengths. We demonstrated previously unknown blindness of ladybird beetles to emerald color (,500nm) light, while being able to see UV-blue and green light. Furthermore, we showed how one could study the speed of the beetle adaptation to repetitive flashing light and its relaxation back to the initial stage. Conclusions: The results show the potential of the method in studying insects. We see this research as a part of what might be a new emerging area of ‘‘nanophysiology’ ’ of insects
Representative spectra of vibrations of elytra of a ladybird beetle exposed to a flashing monochromatic light of wavelengths (1) 375 nm, (2) 550 nm, and (3) 700 nm.
<p>Black curve (4) shows the spectrum of a dead beetle. The shown spectra are averaged over a 100 sec interval.</p
The beetle's spectral response to flashing light of different wavelengths.
<p>(a) Representative spectra measured for a beetle exposed to flashing monochromatic light of various wavelengths ranging from 700 nm (curve 3) to 375 nm (curve 10) with 50-nm step. Curves (1) and (2) are the reference spectra recorded on a dead and living (with no illumination) beetle, respectively. The vertical shift of 10 dB was added to each consequent spectrum except (1) for better visibility. The spectrum of the room noise collected from a microphone is shown in the bottom. Peaks typical for the beetle are (47, ∼150, and 187 Hz) shown with arrows. (b) Spectral amplitudes averaged in 10Hz windows within 10–100Hz range. The average value and one standard deviation are shown for each frequency. Grey area is the variation of the spectra for the beetle with no flashing light.</p
“Measure of disturbance” of the series of flashing (0.5–1 Hz) UV light of 375nm light.
<p>The gray region is the area of fluctuations of a presumably relaxed insect. The series of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012834#pone-0012834-g002" target="_blank">Fig. 2</a> are repeated several times with 2–3, 4–5 min and 1 hour beaks in-between.</p
A special insect holder that restricts the motion of the insect.
<p>A special insect holder that restricts the motion of the insect.</p
AFM Study of Polymer Brush Grafted to Deformable Surfaces: Quantitative Properties of the Brush and Substrate Mechanics
Atomic Force Microscopy Detects the Difference in Cancer Cells of Different Neoplastic Aggressiveness via Machine Learning
Cell Surface Parameters for Accessing Neutrophil Activation Level with Atomic Force Microscopy
In this study, we examine the topography and adhesion images of the cell surface of neutrophils during the activation process. Our analysis of cell surface parameters indicates that the most significant changes in neutrophils occur within the first 30 min of activation, suggesting that reactive oxygen species may require approximately this amount of time to activate the cells. Interestingly, we observed surface granular structure as early as 10 min after neutrophil activation when examining atomic force microscopy images. This finding aligns with the reorganization observed within the cells under confocal laser scanning microscopy. By analyzing the cell surface images of adhesion, we identified three spatial surface parameters that correlate with the activation time. This finding enables us to estimate the degree of activation by using atomic force microscopy maps of the cell surface