Researchers at the Southern University of Science and Technology in China have created an automated intracellular sensing system. They claim it offers a high-efficiency method for revealing cellular intrinsic characteristics and heterogeneity for improved disease progression or early disease diagnosis analysis.
The measurement of internal biochemical activities is essential, say the researchers, to quantitatively comprehend how biological systems work. Intracellular sensing using nanopipettes is a non-destructive, in situ measuring technique. A barrier to obtaining statistically significant data is the tiny size of cells and the nanopipette tip, which make it challenging to accomplish intracellular measurement by manual manipulation. Therefore, the researchers created a very effective and reliable intracellular sensor system using automation technologies.
Researchers Use AIs to Find Disease
First, a nanopipette-based sensor with a tip diameter of around 100 nm was created, as described in Cyborg and Bionic Systems. Researchers used a platinum ring on the nanopipette tip as a working electrode for the electrochemical detection of reactive oxygen species (ROS). Researchers installed the sensor on a very accurate micromanipulator with a motion resolution of 5 nm, and visual input was provided using an inverted fluorescence microscope.
The researchers also put forth a label-free cell detection method, which can identify cells without labeling them and precisely pinpoint the penetration sites for intracellular measurements with high efficiency without subjecting cells to fluorescent staining. To maximize the grayscale difference between the adhering cells and the background, the algorithm automatically shifts the cells to a defocus plane, making cell detection easier and increasing the rate at which cells are recognized.
How AIs Find Sick Cells
To prevent tip damage from the tip striking the cell dish during autofocusing, researchers created a non-overshoot nanopipette tip placement. In particular, Drug Target Review said the focus measure to autofocus the nanopipette tip without overshooting and tip damage was based on the normalized correlation coefficients during template matching at various z-axis locations.
Due to the highly variable thickness of the adhering cells, researchers used proximity detection based on ion current feedback to precisely measure the relative height between the nanopipette tip and the cell surface. Ionic current via the tip opening will diminish when the nanopipette tip approaches the cell and is progressively stopped by the cell. As a result, it is possible to precisely quantify the relative height between the tip and the cell.
AIs Still Capable of Assessing Sickness
Human breast cancer cells and zebrafish embryo cells were used to test the cell penetration and electrochemical detection of ROS, Calltutors wrote. The variance in ROS signals showed that the system is capable of both a highly selective response to ROS and a quantitative assessment of intracellular ROS.
The researchers stress that their study offers an organized method for automated intracellular sensing for adherent cells, setting the groundwork for high-throughput detection, identification, and categorization of many biochemical responses within single cells. Lineage tracing for developmental biology and high-resolution manipulation of organelles in living single cells for determining the precise causes of illnesses and creating innovative therapies are two further major applications of the proposed system.
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