Health disorders like hepatic disorders or pancreatic insufficiency often result in malabsorption and maldigestion. Useful information for medical diagnostics can be derived by analyzing the changes in stool composition like the nitrogen, moisture or fat content.
Traditional laboratory methods like titration for determining the fat content are time consuming. Newer methods like rapid near-infrared spectroscopy (NIRS) are suitable alternatives to such time-intensive lab methods. Determination of fat, moisture and nitrogen content in human feces using the NIRS DS2500 Analyzer (Figure 1) is described in this article.
Figure 1. The NIRS DS2500 Analyzer
Experimental Setup
Analysis of 522 human feces samples was done on the NIRS DS2500 analyzer with the experimental setup listed in Table 1. Table 2 presents the three parameters that were analyzed.
Table 1. Equipment
|
Analyzer
|
NIRS DS2500
|
|
Accessories
|
Customer ring cup (modified)
Mini ISI ring cup (FOSS)
|
|
Software
|
Vision 4.01
|
Table 2. Analysis parameters
|
Moisture content
|
(Humidity)
|
|
Fat content
|
(STOT)
|
|
Nitrogen content
|
(CRTOT)
|
Method Development
The first step in method development was selecting the samples using the Vision software. A total of 57 samples were determined as outliers during sample selection using the maximum distance in wavelength space method. As per this method, the mean spectrum of 522 samples was estimated using the software, and those samples whose spectra fell outside the 5-standard-deviation acceptance range were classified as outliers.
The spectra of the remaining 465 samples were considered for quantitative method development. The chosen sample lot was divided into two subsets of 25% and 75% for cross validation and calibration, respectively. External validation using 15 additional samples was done in order to mitigate the risk of over-fitting the model. Table 3 summarizes the reference values.
Table 3. Humidity, STOT and CRTOT content of the 522 samples split into 23 classes
|
STOT reference value
|
CRTOT reference value
|
Humidity reference value
|
|
0.24
|
0.19
|
64.66
|
|
1.28
|
0.26
|
65.96
|
|
2.33
|
0.32
|
67.26
|
|
3.37
|
0.39
|
68.57
|
|
4.41
|
0.46
|
69.87
|
|
5.46
|
0.52
|
71.17
|
|
6.50
|
0.59
|
72.47
|
|
7.54
|
0.66
|
73.78
|
|
8.59
|
0.72
|
75.08
|
|
9.63
|
0.79
|
76.38
|
|
10.67
|
0.86
|
77.68
|
|
11.72
|
0.93
|
78.98
|
|
12.76
|
0.99
|
80.29
|
|
13.80
|
1.06
|
81.59
|
|
14.84
|
1.13
|
82.89
|
|
15.89
|
1.19
|
84.19
|
|
16.93
|
1.26
|
85.50
|
|
17.97
|
1.33
|
86.80
|
|
19.02
|
1.39
|
88.10
|
|
20.06
|
1.46
|
89.40
|
|
21.10
|
1.53
|
90.71
|
|
22.15
|
1.59
|
92.01
|
As pretreatment of the data, the Vision software calculated the 2nd derivative (gap: 0nm and segment: 10 nm) in conjunction with N-point smooth (segment: 10nm). Due to the complex matrix of human feces, smoothing was required, which led to a high variance in spectra and baseline shift. This, in turn, resulted in random noise.
Method Description
The partial least square (PLS) model along with either five factors - CRTOT, SEV = 0.07, or four factors - STOT, SEV = 0.38; humidity, SEV = 1.06 were used for building the regression for wavelength ranges of 1200–2300 nm (CRTOT) or 1200–1500 nm plus 1600–2000 nm (TOT and humidity).
Results for CRTOT
Based on the results of the PLS method development for CRTOT, a relationship was established between the predicted (calculated) values and the reference (lab) values. The correlation for the calibration set and the validation set was characterized by R2 = 0.92 and SEC = 0.07, and R2 = 0.95 and SEP = 0.11, respectively (Figure 2).
Figure 2. Calibration set for CRTOT
Results for STOT
Similarly, the PLS method development for STOT demonstrated that the lab and the calculated values were correlated. The correlation for the calibration set and the validation set was characterized by R2 = 0.96 and a SEC = 0.37, and by R2 = 0.91 and SEP = 0.42, respectively (Figure 3).
Figure 3. Calibration set for STOT
Results for Humidity
The lab values were shown to be in correlation with the calculated values by the PLS method development for humidity. This correlation for the calibration set and the validation set was characterized by R2 = 0.90 and a SEC = 1.69, and by R2 = 0.97 and SEP = 1.81, respectively (Figure 4).
Figure 4. Calibration set for humidity
Conclusion
From the results, it is evident that the quantification analysis of the fat, moisture and nitrogen content of human feces can be effectively performed in a single run on the NIRS DS2500 Analyzer.
References
- J.H. van de Kamer, H.te Bokkel Huinink, H.A. Weyers: “Rapid method for the determination of fat in feces”, J.Biol.Chem. 1949, 177:347-355.
About Metrohm
At Metrohm is one of the world’s most trusted manufacturers of high-precision instruments for chemical analysis. Metrohm was founded in 1943 by engineer Bertold Suhner in Herisau, Switzerland. Today, Metrohm is represented in 120 countries by subsidiaries and exclusive distributors. The global Metrohm Group also includes the Dutch companies Metrohm Applikon and Metrohm Autolab, manufacturers of online analyzers and instruments for electrochemical research, respectively. Recently, the Metrohm Group was joined by Metrohm Raman, a leading manufacturer of handheld Raman spectrometers.
Metrohm is the global market leader in analytical instruments for titration. Instruments for ion chromatography, voltammetry, conductivity, and stability measurement make the Metrohm portfolio for ion analysis complete. Instruments for Near-infrared and Raman spectroscopy are another, strongly growing segment of the Metrohm portfolio.
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