Baseline, spikes

Spikes on baseline Spikes on baseline (Figure 10.7c) are caused by air bubbles out-gassing in the detector flow cell. They can be eliminated by mobile phase degassing and/or by placing a pressure restrictor in the detector outlet (e.g., with 50-psi back pressure). Spikes can also be caused by poor signal wire connections (loose or damaged wiring) or malfunction of the detector or the data system. 

An example of an absorption spectrum—that of ethanol exposed to infrared radiation—is shown in Figure 12.12. The horizontal axis records the wavelength, and the vertical axis records the intensity of the various energy absorptions in percent transmittance. The baseline corresponding to 0% absorption (or 100% transmittance) runs along the top of the chart, so a downward spike means that energy absorption has occurred at that wavelength. 

There are several other problems that can occur with uv flow cells. Air bubbles in the cell can produce a series of very fast noise spikes on the chromatogram, or pronounced drift in the baseline, followed by sudden changes in the baseline position, or both effects at once. 

Intracellular calcium oscillations generally fall into one of two categories involving different mechanisms baseline transients, or spikes, and sinusoidal oscillations. Figure 22-4 illustrates these two oscillatory patterns. 

If the perturbations are in the form of spikes of an irregular nature, the problem is likely to be detector contamination. Such spikes are especially observed when dust particles have settled into the FID flame orifice. Of course, the problem may also be due to interference from electrical pulses from some other source nearby. Regular spikes can be due to condensation in the flow lines causing the carrier, or hydrogen (FID), to pulse, or they can be due to a bubble flow meter attached to the outlet of the TCD, as well as the electrical pulses referred to above. Baseline perturbations can also be caused by pulses in the carrier flow due to a faulty flow valve or pressure regulator. 

If the x-data of an object are time-series or digitized data from a continuous spectrum (infrared, IR near infrared, NIR) then smoothing and/or transformation to first or second derivative may be appropriate preprocessing techniques. Smoothing tries to reduce random noise and thus removes narrow spikes in a spectrum. Differentiation extracts relevant information (but increases noise). In the first derivative an additive baseline is removed and therefore spectra that are shifted in parallel to other... 

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. 

Spike and bench-scale tests were performed in order to size the pilot test. For this purpose, soil samples of about 10kg each and groundwater samples (about 5kg each) were retrieved/collected both during and after the installation of the test wells in, respectively, sealed plastic bags and glass containers, and these were preserved under refrigeration. The samples were analysed for content of chlorinated solvents, sulphates, nitrates and metals (baseline analysis). 

System suitability errors often include profiles that are not consistent with historical data such as (1) excessive peak tailing, poor resolution of critical components or noisy baseline (2) peak spikes due to micro bubbles or electric shock and (3) integration parameters such as percent main peak area out of range for the assay reference control sample. 

Detector sensitivity is one of the most important properties of the detector. The problem is to distinguish between the actual component and artifact caused by the pressure fluctuation, bubble, compositional fluctuation, etc. If the peaks are fairly large, one has no problem in distinguishing them however, the smaller the peaks, the more important that the baseline be smooth, free of noise and drift. Baseline noise is the short time variation of the baseline from a straight line. Noise is normally measured "peak-to-peak" i.e., the distance from the top of one such small peak to the bottom of the next. Noise is the factor which limits detector sensitivity. In trace analysis, the operator must be able to distinguish between noise spikes and component peaks. For qualitative purposes, signal/noise ratio is limited by 3. For quantitative purposes, signal/noise ratio should be at least 10. This ensures correct quantification of the trace amounts with less than 2% variance. The baseline should deviate as little as possible from a horizontal line. It is usually measured for a specified time, e.g., 1/2 hour or one hour and called drift. Drift usually associated to the detector heat-up in the first hour after power-on. 

The inset in A is a representative evoked potential recorded from the CA1 pyramidal cell layer. Calibration hards vertical 2 mV, horizontal 10 msec. The population spike amplitude was defined as an average of the amplitude from the first positive peak 1 to the succeeding negative peak 2 and the amplitude from die negative peak 2 to the second positive peak 3. A Time-course of potentiation induced by strong tetanic stimulation in the control slices (O, n=23) and in the slices treated with 30% of ethanol (IS ml/kg) (, n=27 ) and in the slices treated with 30% of ethanol (IS ml/kg) and 20 mg/kg crocin ( A, n-7). (1) and (2) indicated 30% ethanol of IS ml/kg and 10 ml/kg, respectively. Ethanol or crocin was added in the perfusing ACSF from 15 or 20 min, respectively, before tetanic stimulation. The ordinate indicates the population spike amplitude expressed as a percentage of the baseline values immediately before tetanic stimulation. 

Incorrectly set experimental parameters or spectrometer problems/instabilities may cause unwanted effects (baseline-roll, spikes,...). 

The same protocol could also be used to clean up an effluent form the textile industry. Figure 7 (Fig. 8 of the original) shows that the investigated triazines were retained on the MIP and the baseline was quite clean. An alternative method using conventional hydrophobic SPE produced a much worse baseline. Phenylurea herbicides were also spiked to the samples to check the selectivity of the procedure for triazines. The MIP proved selective (i.e., did not retain the phenylureas) while the traditional sorbent was not selective and also retained the phenylureas. 

Kim, Kim and Kim (2005) evaluated the treatment of arsenic in two fine-grained soils with an ex situ electrokinetic technology, which consisted placing the samples in a three-compartment chamber with a platinum anode and titanium cathode on opposite ends. One soil consisting of a Korean kaolinite was spiked with 1500 mg kg-1 of As(V). The second soil sample, which contained 3210 mg kg-1 of arsenic, was collected from the abandoned Myungbong gold mine in southern South Korea. The soils were treated with NaOH or KH2P04 electrolyte solutions. Deionized water was used with control samples to establish a baseline. 

Fig. 1. Behavioral response and hippocampal synaptic transmission during exposure to open field stress in freely moving rats. Behavior analysis and electrophysiological experiments were performed simultaneously during the postadolescent period (10-12 weeks old). (A) Locomotor activity estimated by total crossings for 30 min and (B) time-course of crossings during exposure to open field stress. (C) Time-course of population spike amplitude (PSA) in the hippocampal CA1 field evoked by Schaffer collaterals stimulation. Values are expressed as a percentage of the baseline level before open field stress. Non-FS, pups exposed to the footshock (FS) box without FS 2W-FS and 3W-FS, pups exposed to FS during the second and third postnatal weeks, respectively. Each value represents the mean S.E.M. p < 0.05 versus non-FS controls (modified from Koseki etal., 2007).

In-source transformation effects can only be perceived during method development if extracts of biological samples are analyzed under extended chromatographic runs. Interference by in-source transformation will not become evident if only spiked quality control materials are used which do not contain relevant metabolites. If one or more additional peak in the SRM trace of the target analyte is observed in comparison to analyte reference solutions, chromatography may only be accelerated to such degree that these peaks still remain baseline separated from the analyte. 

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