Optical Block Detection
Optical Block Detection - Related Videos
05:11
Wild-Type Blocking PCR to Detect Low-Frequency Somatic Mutations
0 Views •
2025
This video describes wild-type blocking polymerase chain reaction, or WTB-PCR, which detects somatic mutations. The PCR-based technique uses a locked nucleic acid, or LNA, an oligonucleotide that binds to its complementary wild-type allele and blocks its elongation. The blocking selectively allows the amplification of low-level mutant alleles over their wild-type variants in the sample.
10:21
Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers
0 Views •
Cited by 18 •
2016
Multicolor fluorescence detection in droplet microfluidics typically involves bulky and complex epifluorescence microscope-based detection systems. Here we describe a compact and modular multicolor detection scheme that utilizes an array of optical fibers to temporally encode multicolor data collected by a single photodetector.
08:53
Label-free Single Molecule Detection Using Microtoroid Optical Resonators
0 Views •
Cited by 32 •
2015
We have developed a label-free biosensing system based on optical resonator technology known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that is capable of detecting single molecules in solution. Here the procedures behind this work are described and presented.
13:21
Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
0 Views •
Cited by 6 •
2012
In this study, we describe an improved protocol for a multiplexed high-throughput antibody microarray with lectin detection method that can be used in glycosylation profiling of specific proteins. This protocol features new reliable reagents and significantly reduces the time, cost, and lab equipment requirements as compared to the previous procedure.
07:19
Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)
0 Views •
Cited by 5 •
2017
This protocol describes the implementation of an asymmetric-detection time-stretch optical microscopy system for single-cell imaging in ultrafast microfluidic flow and its applications in imaging flow cytometry.
FAQs
The process establishes a baseline for detected light before monitoring begins. It then compares subsequent readings with that reference and identifies changes associated with cells, particles, specimens, or obstructions in the optical path. This baseline comparison is important because it converts a biological or instrument event into a measurable signal that can be recognized consistently during automated observation.
Interruption and attenuation represent different ways that an object can alter the light path. A strong obstruction may produce a substantial loss of detected light, whereas partial blocking or another optical change may produce a smaller or different signal. Recognizing these possibilities helps investigators interpret whether a flagged event reflects an occupying specimen, a passing particle, or another obstruction.
Detection depends on the relationship between the biological material and the monitored optical path. Cells, particles, and specimens are identified when their passage through, or presence within, that path changes the detected intensity relative to baseline. The method is therefore suited to workflows in which samples move through a monitored region or remain positioned within an instrument.
Unlike contact-based monitoring, this approach can observe a sample or instrument path without physically touching the biological material. That noncontact feature allows monitoring during automated operation while preserving the optical basis of detection. It can therefore complement broader sample-monitoring workflows in microscopy, microfluidics, and handling systems where direct observation of the light path is useful.
A basic workflow begins by establishing the light-intensity baseline, followed by monitoring the optical path during sample or instrument operation. The system compares each detected change with the reference and flags events associated with an interruption, attenuation, or other alteration. Researchers can then use the resulting signals to follow activity in real time or standardize when observations are recorded.
In microfluidic monitoring, the technique can track cells or particles as they pass through an optical path, while automated microscopy can use related signals to recognize changes involving specimens or the monitored path. During sample handling, the same approach supports consistent detection of occupancy or movement. These uses connect optical sensing with automated biological workflows rather than requiring continuous manual observation.
Optical Block Detection can monitor the instrument itself, not only the biological sample. An unexpected change in the monitored light path may indicate a physical obstruction or another instrument condition that alters detection. Using such signals for fault detection can improve experimental reliability by identifying problems during operation and helping distinguish instrument-related events from sample-related events.
The signal can indicate that a cell, particle, specimen, or obstruction has entered, occupied, or altered the monitored path, and it can mark when that change occurs relative to the baseline. Because signals are collected during operation, the approach supports real-time observation and more standardized data collection across repeated biological research workflows.