Baseline with spectrum

Figures 8 and 9 show the first order kinetic plots for the isomerization and crosslinking reactions, respectively. In the data analysis the area of the isoimide peak was measured between consistent limits chosen to exclude any contribution from the 1775 cm imide band. These data were generated by measuring the area of the appropriate peak in a baseline corrected spectrum and ratioing this area to that of a reference peak (which was invarient during the experiment) in the same spectrum. This concentration indicative number was then ratioed to the concentration ratio observed on the initial scan. Plots of the log of the ratio of the concentration of the functionality at time "t" to the concentration of the functionality at t = 0 were then constructed. In order to insure that the trends in the data were not artifacts of this procedure or of the baseline correction routine, we also plotted the data in terms of peak intensity in absorbance units and observed the same trends but with more scatter in the data.

Another way to detect small molecules in the final formulated protein product without the interference from the protein signals is to remove the protein by ultrafiltration. Figure 12.4 compares a section of the proton NMR spectra of a biopharmaceutical protein product before (upper spectrum) and after (bottom spectrum) the protein was removed by ultrafiltering the sample with a Centricon-10 (Millipore Corp, Bedford, MA). Removing protein results in a flatter baseline (bottom spectrum). If small molecules are present in a protein sample, the removal of the protein may allow for unobstructed detection of the small molecules. In this case, a small amount of acetate ( 1 pg/rnl) is detected in the sample [bottom trace, Figure 12.4], Figure 12.5 shows that spikes of 10 p.g/ml of acetate and MES into the protein sample are fully recovered after the ultrafiltration to remove the protein. This example demonstrates that the interference of protein with the detection and quantitation of small-molecule impurities in a formulated protein product can be effectively eliminated by ultrafiltration. 

Fig. 8.2 Electronic absorption spectrum of in n-hexane. The absorption maximum is indicated by the vertical line and is located at 217 nm with a e217 = 16,480 L cm 1 mol1. After 120 s photolysis the intensity of the peak at 217 nm is reduced and the baseline with X > 260 nm shows a strong increase in optical density due to light scattering caused by the formation of a white insoluble photoproduct...

In many spectroscopic techniques, it is not unusual to encounter baseline offsets from spectrum to spectrum. If present, these kinds of effects can have a profound effect on a PCA model by causing extra factors to appear. In some cases, the baseline effect may consist of a simple offset however, it is not uncommon to encounter other kinds of baselines with a structure such as a gentle upward or downward sloping line caused by instrument drift, or even a broad curved shape. For example, in Raman emission spectroscopy a small amount of fluorescence background signals can sometimes appear as broad, weak curves. 

Figure 12.18 shows a typical chromatogram obtained from an on-line product gas analysis for the oxidation of CH4. The chromatograms obtained from the TCD were typically characterized by steady baselines with well-resolved peaks. The product spectrum indicates that both partial and total combustion reactions of CH4 are present. Both CO2 and H2O are baseline-resolved using a Hayesep R column while the O2, N2, CH4, and CO are baseline-resolved on a molecular sieve column. The overall analysis time requires about 9 min. Some gaps exist in the retention times for the various components, but no attempt was made to reduce these by additional optimization of the temperature program. The overall analysis time could have been reduced if the dual-oven method had been used as described elsewhere (Delaney and Mills, 1999 Nicole et al., 2000). 

For construction of the baseline, the spectrum is divided into n ranges (n being the number of baseline points) of equal size. In the case of absorbance spectra the minimum y-value of each range is determined. Connecting the minima with straight lines creates the baseline. Starting from below , a rubber band is stretched over this curve. The rubber band is the baseline. The baseline points that do not lie on the rubber band are discarded. 

Figures IS.laand 18.1b are differential spectra of natural human blood serumand human blood serum concentrated five times. Figure 18.2 is a differential spectrum of normal human blood serum in which the reference cell also contained the same fluid. The figure shows a relatively flat baseline with which to compare abnormal specimens. Figure 18.3 shows marked diflerences in the spectrum of the blood serum from a patient with the disease lupus erythematosus disseminatus. Figure 18.4...

In measuring a spectrum, it is routine to first record a baseline with pure solvent or a reagent blank in both the sample and reference cuvets. Cuvets are sold in matched pairs that are as identical as possible to each other. In principle, the baseline absorbance should be 0. However, small mismatches between the two cuvets and instrumental imperfections lead to small positive or negative baseline absorbance. The absorbance of the sample is then recorded and the absorbance of the baseline is subtracted from that of the sample to obtain true absorbance. 

Fig. IV-13. Example of a p-polarized reflection spectrum from Ref. [154] for a stearyl alcohol monolayer on water. The dashed line is the baseline to be subtracted from the spectra. [Reprinted with permission from Joseph T. Buontempo and Stuart A. Rice, J. Chem. Phys. 98(7), 5835-5846 (April 1, 1993). Copyright 1993, American Institute of Physics.]...

A mass spectrum consists of a series of peaks at different m/z values, with the height of the peak proportional to the number of ions. A partial mass spectrum is shown in Figure 44.3 and is seen to be an analog signal that varies as the peaks rise from and fall to the baseline. Between the peaks are relatively long intervals when there is only the baseline. As described above, the signal is first digitized. 

Figure 25 contains plots of the pure component spectra for the two calibrations. It is apparent that, in the absence of the extraneous absorbances from Component 4, CLS is now able to do a good job of estimating the pure component spectra. However, even with nonzero intercepts, CLS is unable to remove the sloping baseline from the spectra. Both calibrations distributed most of the baseline effect onto the spectrum for Component 2 and some onto the Component 3 spectrum. 

TLC analysis of the crude product (elution with 50 1 pentane ether, visualization with iodine) showed three non-baseline spots Rf 0.65 (cis isomer), Rf 0.52 (unknown impurity), and Rf 0.32 (trans isomer). The unknown impurity is intensely sensitive to iodine and largely coelutes with the cw-isomer in the subsequent column chromatography. However, the ll NMR spectrum of this isomer shows excellent purity despite the presence of this spot on TLC. In 100 1 pentane ether, Rf values of the cis and trans isomers are about 0.50 and 0.15, respectively. 

The mainstay of treatment for vaso-occlusive crisis includes hydration and analgesia (see Table 65-7). Pain may involve the extremities, back, chest, and abdomen. Patients with mild pain crises may be treated as outpatients with rest, warm compresses to the affected (painful) area, increased fluid intake, and oral analgesia. Patients with moderate to severe crises should be hospitalized. Infection should be ruled out because it may trigger a pain crisis, and any patient presenting with fever or critical illness should be started on empirical broad-spectrum antibiotics. Patients who are anemic should be transfused to their baseline. Intravenous or oral fluids at 1.5 times maintenance is recommended. Close monitoring of the patient s fluid status is important to avoid overhydration, which can lead to ACS, volume overload, or heart failure.6,27... 

A strong negative signal is always observed at the irradiation position. The baseline of the spectrum is very uneven, and it is not possible to correct the phase of all the signals at the same time this is typical of NOE difference spectra, and is due to inexact subtraction of the FIDs. However, we can see a strong positive signal for one half of the AA BB multiplet due to the para-substituted aromatic moiety this positive signal must be due to the protons closer to the methine proton. No further useful information is available from this experiment, which we can compare with the second technique described below. 

A typical MALDI spectrum of a bacterial sample has a number of peaks that vary greatly in intensity superimposed on a relatively noisy baseline. This can be problematic for many peak detection routines. Therefore methods that eliminate the need for peak detection also eliminate problems associated with poor peak detection performance. Full-spectrum identification algorithms use the (usually smoothed) spectral data without first performing peak detection. 

Fig. 8. Dependence of (A) corrected diffusion coefficient (D), (B) steady-state fluorescence intensity, and (C) corrected number of particles in the observation volume (N) of Alexa488-coupled IFABP with urea concentration. The diffusion coefficient and number of particles data shown here are corrected for the effect of viscosity and refractive indices of the urea solutions as described in text. For steady-state fluorescence data the protein was excited at 488 nm using a PTI Alphascan fluorometer (Photon Technology International, South Brunswick, New Jersey). Emission spectra at different urea concentrations were recorded between 500 and 600 nm. A baseline control containing only buffer was subtracted from each spectrum. The area of the corrected spectrum was then plotted against denaturant concentrations to obtain the unfolding transition of the protein. Urea data monitored by steady-state fluorescence were fitted to a simple two-state model. Other experimental conditions are the same as in Figure 6.

One last cautionary note the first order phase can be increased beyond +/- 360° - but shouldn t be If this happens, you will end up with a distorted, wavy baseline. A sine wave is in effect superimposed on the spectrum, so if you see a wavy baseline, check that you haven t wrapped the phase too far. Spectrum 4.4 shows what happens when you go a bit mad with first order phase If you end up in this position, do not attempt any kind of baseline correction as this will add to your problems. Just set both your phase parameters back to zero and start again... 

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