Extraction and analysis of neuron firing signals from deep cortical video microscopy

Author(s):  
Ryan Kerekes ◽  
Jay Blundon
Nanoscale ◽  
2019 ◽  
Vol 11 (44) ◽  
pp. 21147-21154 ◽  
Author(s):  
Raymond W. Friddle ◽  
Konrad Thürmer

Video microscopy and AFM are used to relate surface topography to a mineral's ability to promote ice growth. On feldspar, abundant as atmospheric dust, basic surface steps can facilitate condensation and freezing when air becomes saturated.


Cryobiology ◽  
1987 ◽  
Vol 24 (6) ◽  
pp. 551-552
Author(s):  
Ch. Körber ◽  
S. Englich ◽  
G. Lipp

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ossama Mahmoud ◽  
Mahmoud El-Sakka ◽  
Barry G. H. Janssen

AbstractMicrovascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging process, evaluating experiments very time consuming and susceptible to human error. Since more advanced digital cameras are used in IVM, the experimental data volume will also increase significantly. This study presents a new two-step image processing algorithm that uses a trained Convolutional Neural Network (CNN) to functionally analyze IVM microscopic images without the need for manual analysis. While the first step uses a modified vessel segmentation algorithm to extract the location of vessel-like structures, the second step uses a 3D-CNN to assess whether the vessel-like structures have blood flowing in it or not. We demonstrate that our two-step algorithm can efficiently analyze IVM image data with high accuracy (83%). To our knowledge, this is the first application of machine learning for the functional analysis of microvascular blood flow in vivo.


2001 ◽  
Vol 7 (S2) ◽  
pp. 34-35
Author(s):  
Derek Toomre ◽  
Patrick Keller ◽  
Elena Diaz ◽  
Jamie White ◽  
Kai Simons

Post-Golgi sorting of different classes of newly synthesized proteins and lipids is central to the generation and maintenance of cellular polarity. to directly visualize the dynamics and location of apical/basolateral sorting and trafficking we used fast time-lapse multicolor video microscopy in living cells. Specifically, green fluorescent protein color variants (cyan, CFP; yellow, YFP) of apical cargo (GPI-anchored) and basolateral cargo (vesicular stomatitis virus glycoprotein, VSVG) were generated; see FIG 1. Fast dual color fluorescence video microscopy allowed visualization with high temporal and spatial resolution. Our studies revealed that apical and basolateral cargo progressively segregated into large domains in Golgi/TGN structures, excluded resident proteins, and exited in separate transport containers. These carries remained distinct and did not merge with endocytic structures en route to the plasma membrane. Interestingly, our data suggest that the primary sorting occurs by lateral segregation in the Golgi, prior to budding (FIG 2). Further characterization of morphological differences of apical versus basolateral transport carriers was achieved using a specialized microscopy technique called total internal reflection (TIR) microscopy. with this approach only the bottom of the cell (<100 nm) was illuminated by an exponentially decaying evanescent “wave” of light. A series of images, taken at ∼1 second intervals, shows a bright “flash” of fluorescence when the vesicle fuse with the plasma membrane and the fluorophore diffuses into the plasma membrane (FIG 3).


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