From unicellular protozoa to the largest cetaceans in the world’s oceans, all living organisms are composed of cells. The fact that the human body can be reduced to tens of trillions of structural units is one of the core tenets of cell theory, now universally accepted as fact.
This pioneering idea laid the groundwork for modern cellular biology and many discoveries that have come since. For example, molecular genetics, biotechnology and vaccinations would not be possible if not for our ability to characterize dynamics and structures at the cellular level.
It is because of this the history of cell identification goes hand in hand with microscopy.
Image Credit: MIPAR Image Analysis
Brief history of cell identification
When it comes to life sciences and cell identification, resolving power is a vital metric. It defines the ability to establish adjacent objects which are close together, optically.
On average, the human eye has a resolving power near to 200 micrometers (μm), which means it is impossible to observe even the ovum (approximately 10 μm), the largest human cell, with the naked eye.
It was not until a novel optical system based on existing compound microscopes was built by renowned scientist Robert Hooke that magnifications were good enough to visualize the microscopic.
With a maximum resolving power of approximately 0.2 μm, or 200 nanometers (nm), advanced compound microscopes have now reached the limits of visible light.
Cells are small and also extremely complex. It can be a challenge to determine their molecular composition and establish their functions based purely on light-based microscopy and visual cell identification, even with the best magnifications.
Biochemists rely heavily on fluorescent tagging with tried-and-tested fluorophores like propidium iodide (PI), green fluorescent protein (GFP) and acridine orange (AO) for this purpose.
These unique reagents bind to cells depending on their viability and composition. When excited by light in a given wavelength range, they emit characteristic fluorescent signals. This makes it much simpler to visually count and identify cells based on a large variety of physicochemical properties.
Challenges of cell identification
There are a number of challenges associated with modern cell identification, but the margin for human error is one of the most pervasive.
The element of subjectivity when it comes to visual characterization, in addition to the huge amount of cells in a sample, means it can still be a challenge to identify cells in solution accurately with the level of quantitative assurance that is needed in modern life sciences.
In order to establish the weak fluorescent signals emitted by assayed samples and to eliminate the margin for human error, biochemistry facilities rely on automated imaging systems more and more.
Cell identification with MIPAR
MIPAR Image Analysis reliably and efficiently extracts data from complicated imagery and is an industry-leading expert in algorithmic image analysis.
They have pioneering image analysis software that can be used for fluorescence-based cell identification processes, including subcellular localization, colocalization and cell polarization.
About MIPAR Image Analysis
MIPAR Image Analysis is a world-leading algorithm development and image analysis software company. They specialize in efficiently, accurately, and reliably extracting measurements from complex images. From material and life sciences to aerospace and manufacturing solutions, our extensive portfolio can assist a variety of real-world applications.
Their flagship MIPAR product offers an intuitive user-experience, drag-and-drop custom algorithm development, and a powerful deep learning toolbox. Combined with expert consultative services, they offer clients an end-to-end solution that suits their particular project needs. MIPAR helps clients implement sophisticated algorithms that save time and cost while increasing accuracy and supervision over results.
MIPAR was founded in 2017 and is headquartered in Columbus, Ohio, United States. Additional software distributors and applications specialists are located in Australia, India, China, Europe, Japan, and Taiwan.
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