After reaction with CO, protein solutions were loaded into the IR cell (50 micron pathlength) at a final concentration of 1 mM in copper. After the protein data was collected, the cell was flushed with buffer and a baseline was recorded. FTIR data was recorded on a Bruker Tensor 27 FTIR spectrometer at room temperature with a sample chamber that was continuously purged with dry CO2-free air. Samples were equilibrated inside the instrument sample chamber for 15 min to allow purging of water vapor and CO2 prior to data collection. One thousand scans were collected for each sample and buffer spectrum from 2200 to 1950 cm−1 at a nominal resolution of 2 cm−1. Baseline subtraction and spectral analysis were performed using the GRAMS AI Spectroscopy Software (Thermo).
Grams ai spectroscopy software
Manufactured by Thermo Fisher Scientific
GRAMS AI Spectroscopy Software is a data analysis and visualization tool for spectroscopy applications. It provides capabilities for processing, analyzing, and interpreting spectral data from various analytical instruments.
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Lab products found in correlation
6 protocols using grams ai spectroscopy software
1
Protein FTIR Spectroscopy with CO
2
Quantification of EPR-Detectable Cu(II) in PHM
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Six hundred microliters of
a 500 μM solution of oxidized PHM (1 mM in Cu(II)) was split
into three portions of 200 μL each. Sample 1 was transferred
directly to an EPR tube for determination of the EPR-detectable Cu(II)
in fully oxidized PHM. Samples 2 and 3 were reduced anaerobically
with ascorbate and made ascorbate-free as described above. Sample
2 was transferred anaerobically to an EPR tube for determination of
the EPR-detectable signal in the fully reduced anaerobic ascorbate-free
enzyme. Sample 3 was exposed to air with shaking for 120 s and then
transferred to an EPR tube for Cu(II) quantitation. EPR spectra of
all samples were measured, and the concentration of EPR-detectable
Cu(II) was determined via double integration versus a 300 μM
Cu(II)–EDTA standard measured under identical conditions. Spectral
analysis was performed using GRAMS AI spectroscopy software (Thermo).
EPR spectra were measured on a Bruker Elexsys E500 spectrometer equipped
with a superX microwave bridge and a dual-mode cavity with a helium
flow cryostat (ESR900, Oxford Instrument, Inc.). The following experimental
conditions were used: frequency 9.63 GHz, temperature 100 K, microwave
power 20 mW, gain 10 dB, modulation amplitude 10 G, and sweep time
84 s.
a 500 μM solution of oxidized PHM (1 mM in Cu(II)) was split
into three portions of 200 μL each. Sample 1 was transferred
directly to an EPR tube for determination of the EPR-detectable Cu(II)
in fully oxidized PHM. Samples 2 and 3 were reduced anaerobically
with ascorbate and made ascorbate-free as described above. Sample
2 was transferred anaerobically to an EPR tube for determination of
the EPR-detectable signal in the fully reduced anaerobic ascorbate-free
enzyme. Sample 3 was exposed to air with shaking for 120 s and then
transferred to an EPR tube for Cu(II) quantitation. EPR spectra of
all samples were measured, and the concentration of EPR-detectable
Cu(II) was determined via double integration versus a 300 μM
Cu(II)–EDTA standard measured under identical conditions. Spectral
analysis was performed using GRAMS AI spectroscopy software (Thermo).
EPR spectra were measured on a Bruker Elexsys E500 spectrometer equipped
with a superX microwave bridge and a dual-mode cavity with a helium
flow cryostat (ESR900, Oxford Instrument, Inc.). The following experimental
conditions were used: frequency 9.63 GHz, temperature 100 K, microwave
power 20 mW, gain 10 dB, modulation amplitude 10 G, and sweep time
84 s.
3
Quantification of Oxidized and Reduced PHM
4
FTIR Analysis of CO-Bound Proteins
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After reaction
with CO, protein solutions were loaded into the IR cell (50 μm
path length) at a final concentration of 1 mM in copper. After the
protein data had been collected, the cell was flushed with buffer
and a baseline was recorded. FTIR data were recorded on a Bruker Tensor
27 FTIR spectrometer at room temperature with a sample chamber that
was continuously purged with dry CO2-free air. Samples
were equilibrated inside the instrument sample chamber for 15 min
to allow purging of water vapor and CO2 prior to data collection.
One thousand scans were collected for each sample and buffer spectrum
from 2200 to 1950 cm–1 at a nominal resolution of
2 cm–1. Baseline subtraction and spectral analysis
were performed using the GRAMS AI Spectroscopy Software (Thermo).
with CO, protein solutions were loaded into the IR cell (50 μm
path length) at a final concentration of 1 mM in copper. After the
protein data had been collected, the cell was flushed with buffer
and a baseline was recorded. FTIR data were recorded on a Bruker Tensor
27 FTIR spectrometer at room temperature with a sample chamber that
was continuously purged with dry CO2-free air. Samples
were equilibrated inside the instrument sample chamber for 15 min
to allow purging of water vapor and CO2 prior to data collection.
One thousand scans were collected for each sample and buffer spectrum
from 2200 to 1950 cm–1 at a nominal resolution of
2 cm–1. Baseline subtraction and spectral analysis
were performed using the GRAMS AI Spectroscopy Software (Thermo).
5
Raman Spectroscopy for NHL Diagnosis
6
Raman Spectroscopy for NHL Diagnosis
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Outlier spectra were removed and each spectrum was manually baseline corrected and normalized in the region of 700 to 1800 cm−1 using Grams/AI Spectroscopy Software (Thermo Fisher Scientific, Waltham, MA) [16 (link)]. MATLAB was used to convert the spectroscopy files from the RS instrument to excel files. Spectra from the processed data were averaged to produce an RS profile of each sample which produced characteristic unique peaks of the NHL and follicular hyperplasia specimens. Signal to noise ratios were determined in MATLAB using the ratio of the mean over standard deviation of the 1003 cm−1 phenylalanine peaks with an average of 6.50 and 7.56 for the RESpect probe and laboratory RS instrument respectively. To compare RS data between different NHL pathologies, Principal Component Analyses (PCA) were conducted for each of the NHL pathologies using the ChemoSpec package in R version 3.5.1. The obtained principal components (PC) were visualized using the first two PCs where the RS peaks were identified as local maxima with signal to noise ratio of 2, span of 40 points each to the left and right to estimate the local variance, and span of 5 points each to the left and right for smoothing.
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