Diagnostic Region
Diagnostic Region - Related Videos
21:15
Diagnostic Necropsy and Tissue Harvest
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2016
Source: Kay Stewart, RVT, RLATG, CMAR; Valerie A. Schroeder, RVT, RLATG. University of Notre Dame, IN Many animal experiments rely on final data collection time points that are gathered from the harvesting and testing of organs and tissues. The use of appropriate methods for the collection of organs and tissues can impact the quality of the samples and the analysis of the data that is gleaned for the testing of the tissues. The method of euthanasia of the animal can also impact the quality of...
10:21
Microfluidic Applications for Disposable Diagnostics
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Cited by 1 •
2008
In this interview, Dr. Klapperich discusses the fabrication of thermoplastic microfluidic devices and their application for development of new diagnostics.
07:12
Diagnostic Ultrasound Imaging of Mouse Diaphragm Function
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Cited by 7 •
2014
Diagnostic ultrasound imaging has proven to be effective in diagnosing various respiratory diseases in human and animal subjects. We demonstrate a comprehensive ultrasound protocol utilized by Dr. Zuo's lab to analyze diaphragm kinetics specifically in mouse models. This is also a non-invasive research technique which can provide quantitative information on mouse respiratory muscle function.
01:03
IR Frequency Region: Fingerprint Region
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2024
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1. The...
07:42
Magnetic Levitation Coupled with Portable Imaging and Analysis for Disease Diagnostics
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Cited by 11 •
2017
We present a magnetic levitation technique coupled with automated imaging and analysis in both a smartphone-compatible device and a device with embedded imaging and processing. This is applied to measure the density distribution of cells with two demonstrated biomedical applications: sickle cell disease diagnosis and separating white and red blood cells.
FAQs
Peak positions and intensities change because molecular bonds absorb at frequencies that match specific vibrational transitions. A bond's stretching or bending motion therefore produces a characteristic spectral feature, while its intensity reflects how strongly that transition appears. Comparing these variations helps connect observed signals with molecular structure.
Stretching and bending vibrations generate different molecular motions, so their absorptions contribute distinct spectral patterns. Examining both types can reveal which structural features may be present in a sample, rather than relying on one isolated signal. This vibrational interpretation gives chemical meaning to peak positions and intensities.
The diagnostic region offers characteristic signals, whereas the fingerprint region supplies an additional pattern for comparison. Using both reduces reliance on a single spectral feature and strengthens compound identification. In practice, agreement between the two regions provides more convincing support for assigning an unknown than either region considered alone.
Reference spectra provide comparison standards for interpreting observed signals. Analysts examine whether the positions and intensities in a sample correspond to characteristic features in a known spectrum. This comparison supports compound identification and helps distinguish a plausible assignment from an interpretation based only on an isolated peak.
When an unknown material is analyzed, analysts examine its characteristic spectral features and compare them with reference spectra. They can use the diagnostic region to propose or evaluate compound identities, while the fingerprint region supplies supporting evidence. The resulting interpretation connects measured signals with the material's molecular structure.
Chemists can apply this analysis to verify reaction products, monitor purity, and assess sample composition. The observed pattern can be considered alongside reference spectra to determine whether the expected material is present and whether additional spectral features indicate compositional differences. These uses make the approach valuable in teaching and research laboratories.