ATR-FTIR rapid detection method for cis-trans vitamin K1 content

Abstract

The invention discloses a method for rapidly detecting the content of cis-trans vitamin K1 by ATR-FTIR, including: step 1, preparing a mixed standard sample solution of cis-vitamin K1 and trans-vitamin K1 of multiple different gradient concentrations; step 2, detecting the ATR-FTIR data of the mixed standard sample solution; step 3, importing spectral analysis software, performing standard normal variable transformation preprocessing to obtain corresponding preprocessed spectral data; step 4, using the actual content of trans-vitamin K1 as the dependent variable Y, and the corresponding preprocessed spectral data as the independent variable X, establishing a partial least squares regression model; step 5, detecting the ATR-FTIR data of the sample solution to be tested, performing standard normal variable transformation preprocessing to obtain preprocessed spectral data, inputting the partial least squares regression model, and outputting the content of trans-vitamin K1 of the sample solution to be tested. The present invention has the beneficial effect of accurately, quickly and simply detecting the content of trans-vitamin K1.

Description

Technical Field

[0001] The present invention relates to the technical field of vitamin K1 cis- and trans-isomer content detection, and more specifically, to a method for rapid detection of cis- and trans-vitamin K1 content by ATR-FTIR. Background Art

[0002] Vitamin K1 is an essential nutrient for maintaining human health. It affects the normal functioning of human physiological functions. Coagulation function is its main physiological function. It is a necessary substance for the liver to synthesize prothrombin (coagulation factor II), Stewart factor (coagulation factor X), conversion accelerating factor precursor (coagulation factor VII) and plasma thromboplastin (coagulation factor IX). Activating coagulation factors is a necessary condition for the body's coagulation function to function normally. Vitamin K1 is often added to health products as a nutritional supplement, which has a good preventive effect on vitamin K1 deficiency. Vitamin K1 often exists in the form of a mixture, including cis vitamin K1 and trans vitamin K1. Trans vitamin K1 has physiological activity, while cis vitamin K1 has almost no physiological activity. The 2020 edition of the Chinese Pharmacopoeia stipulates the content of cis vitamin K1, stipulating that the content of cis vitamin K1 shall not exceed 21% when measured by high performance liquid chromatography. However, this method is complicated, time-consuming, and requires professional personnel to operate, so it is not conducive to the rapid determination of cis-isomers in vitamin K1 and real-time monitoring of the production process. Therefore, exploring a method that can quickly determine the content of cis- and trans-isomers of vitamin K1 is of great significance for production monitoring and rapid evaluation of drug quality. Summary of the invention

[0003] An object of the present invention is to solve at least the above problems and to provide at least the advantages which will be described hereinafter.

[0004] In order to achieve these purposes and other advantages according to the present invention, a method for rapid detection of cis-trans vitamin K1 content by ATR-FTIR is provided, comprising the following steps:

[0005] Step 1, preparing a plurality of mixed standard solutions of cis-vitamin K1 and trans-vitamin K1 with different gradient concentrations;

[0006] Step 2, detecting ATR-FTIR data of multiple mixed standard sample solutions;

[0007] Step 3, importing the ATR-FTIR data in step 2 into spectral analysis software, and performing standard normal variable transformation preprocessing to obtain preprocessed spectral data of trans-vitamin K1;

[0008] Step 4: Using the actual content of trans vitamin K1 in multiple mixed standard sample solutions as the dependent variable Y and the corresponding pre-processed spectral data of trans vitamin K1 as the independent variable X, a partial least squares regression model is established in the spectral analysis software;

[0009] Step 5: Detect the ATR-FTIR data of the sample solution to be tested, then import it into the spectral analysis software, perform standard normal variable transformation preprocessing to obtain preprocessed spectral data, input the preprocessed spectral data into the partial least squares regression model established in step 4, and output the content of trans-vitamin K1 in the sample solution to be tested.

[0010] Preferably, it also includes:

[0011] Step 6, importing the ATR-FTIR data in step 2 into spectral analysis software, performing first-order derivative preprocessing to obtain preprocessed spectral data of cis-vitamin K1;

[0012] Step 7: Using the actual content of cis-vitamin K1 in multiple mixed standard sample solutions as the dependent variable Y and the corresponding pre-processed spectral data of cis-vitamin K1 as the independent variable X, a partial least squares regression model is established in the spectral analysis software;

[0013] Step 8: Detect the ATR-FTIR data of the sample solution to be tested, then import it into the spectral analysis software, perform first-order derivative preprocessing to obtain preprocessed spectral data, input the preprocessed spectral data into the partial least squares regression model established in step 7, and output the content of cis-vitamin K1 in the sample solution to be tested.

[0014] Preferably, the content of cis-vitamin K1 in the mixed standard solution is 0-100%, a mixed standard solution is set at every 5% content interval, 3 mixed standard solutions of each content are set, and the concentration range of cis-vitamin K1 is 0-100 μg / mL.

[0015] Preferably, multiple mixed standard sample solutions are randomly divided into a training set and a validation set, the training set being 3 / 4 of the number of mixed standard sample solutions, a partial least squares regression model is established based on the actual content of trans vitamin K1 in the training set and the corresponding pre-processed spectral data of trans vitamin K1, and the partial least squares regression model is verified based on the actual content of trans vitamin K1 in the validation set and the corresponding pre-processed spectral data of trans vitamin K1.

[0016] Preferably, a partial least squares regression model is established based on the actual content of cis-vitamin K1 in the training set and the corresponding pre-processed spectral data of cis-vitamin K1, and the partial least squares regression model is verified based on the actual content of cis-vitamin K1 in the validation set and the corresponding pre-processed spectral data of cis-vitamin K1.

[0017] Preferably, the spectral range of ATR-FTIR is 650-4000cm -1 , resolution 4cm -1 .

[0018] Preferably, the solvent of the mixed standard solution is isopropanol.

[0019] The present invention at least includes the following beneficial effects: The present invention establishes a quantitative prediction model (two partial least squares regression models) and uses the quantitative model to detect unknown samples. The method can solve the problem that the existing vitamin K1 cis-trans isomer detection method is time-consuming, labor-intensive, and difficult to monitor in real-time production. The present invention has the advantages of high accuracy, small sample dosage, simplicity, and rapidity.

[0020] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The original spectrum of the mixed standard solution of one of the technical solutions of the present invention;

[0022] Figure 2 A preprocessing spectrum of a standard normal variable transformation of one of the technical solutions of the present invention;

[0023] Figure 3 A pre-processed spectrum for multivariate scattering correction according to one of the technical solutions of the present invention;

[0024] Figure 4 A preprocessed graph of the first-order derivative of one of the technical solutions of the present invention;

[0025] Figure 5 A preprocessed graph of the second-order derivative of one of the technical solutions of the present invention;

[0026] Figure 6 The content prediction result of cis-vitamin K1 pretreated by the first-order derivative of one of the technical solutions of the present invention;

[0027] Figure 7 This is the predicted result of the content of trans vitamin K1 pretreated by standard normal variable transformation according to one of the technical solutions of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0029] It should be noted that the experimental methods described in the following embodiments are conventional methods unless otherwise specified, and the reagents and materials can be obtained from commercial channels unless otherwise specified.

[0030] 1. Instruments and Equipment

[0031] ATR-FTIR spectra (attenuated total reflection Fourier transform infrared spectra) were obtained using a Nicolet iS20 Fourier transform infrared spectrometer from Thermo Fisher Scientific, USA, equipped with a ZnSe crystal; the original spectra of the samples were collected using OMNIC9.0 software. Spectral preprocessing and partial least squares regression model establishment were performed using TQ Analyst 8.3 software.

[0032] 2. Samples

[0033] Take 1 mg of cis-vitamin K1 standard and trans-vitamin K1 standard, add them to 10 mL volumetric flasks respectively. Use isopropanol to make up to the mark. Then mix the cis-vitamin K1 and trans-vitamin K1 dissolved in isopropanol so that the content of cis-vitamin K1 is 0-100% of the total mass of the two, and the interval between two adjacent contents is 5%. A total of 21 mixed standard solutions are designed. Repeat the mixing of each mixed standard solution for 3 times to obtain a total of 63 mixed standard solutions. The concentration range of cis-vitamin K1 is 0-100 μg / mL.

[0034] 3. Infrared spectrum collection

[0035] Each mixed standard solution was tested at room temperature with 16 scans and a resolution of 4 cm -1 , scanning range is 650~4000cm -1 The method is to use a pipette to draw 200 μL of the mixed standard solution and drop it on the ZnSe body, measure the ATR-FTIR data of the mixed standard solution, and scan the background before the measurement.

[0036] 4. ATR-FTIR data preprocessing

[0037] The original spectrum is affected by baseline offset, instrument noise, etc., so it is necessary to perform spectral preprocessing on the original spectrum to eliminate the influence of irrelevant information. Four different preprocessing methods were used to preprocess the original spectrum (such as Figure 1 Different pre-processing spectra are shown in Figures 2 to 5 12 mixed standard samples were randomly selected from the 63 mixed standard samples as the validation set to test the prediction ability of the model.

[0038] 4.1. Partial least squares regression model establishment

[0039] The infrared regions associated with changes in cis-vitamin K1 content were calculated by TQ analyst. These regions are 1380-1395 cm -1 , 1428~1453cm -1 , 3707~3723cm -1 The infrared region related to the change of trans-vitamin K1 content is 952-1035 cm -1 、1299~1343cm -1 、3707~3734cm -1 . These infrared regions were used to establish partial least squares regression models under different pretreatments in TQ analyst. The actual contents of cis-vitamin K1 and trans-vitamin K1 were used as dependent variables Y, and the pretreated spectral data were used as independent variables X.

[0040] 4.2 Prediction of the content of cis-vitamin K1 and trans-vitamin K1 in mixed standard samples

[0041] The validation set data was imported into the partial least squares regression model. Table 1 shows the prediction results of the partial least squares regression model for the content of cis vitamin K1 under different pretreatments. Table 2 shows the prediction results of the partial least squares regression model for the content of trans vitamin K1 under different pretreatments. For the validation set, the first-order derivative pretreatment was the best prediction result for the content of cis vitamin K1, with a prediction correlation coefficient R of 0.996 and a root mean square error of 2.42 μg / mL ( Figure 6 The prediction correlation coefficient R was 0.9956, and the root mean square error was 2.46 μg / mL ( Figure 7 shown).

[0042] Table 1. Effects of different pretreatment methods on the predicted results of cis-vitamin K1 content

[0043]

[0044]

[0045] Note: Rc (correlation coefficient of training set); RMSEC (root mean square error of training set); Rv (correlation coefficient of validation set); RMSEP (root mean square error of validation set).

[0046] Table 2. Effects of different pretreatment methods on the predicted results of trans-vitamin K1 content

[0047]

[0048] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation modes, and they can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. ATR-FTIR rapid detection method for cis and trans vitamin K1 content, characterized in that: The following steps are involved: Step 1, preparing a plurality of mixed standard solutions of cis-vitamin K1 and trans-vitamin K1 with different gradient concentrations; Step 2, detecting ATR-FTIR data of multiple mixed standard sample solutions; Step 3, importing the ATR-FTIR data in step 2 into spectral analysis software, and performing standard normal variable transformation preprocessing to obtain preprocessed spectral data of trans-vitamin K1; Step 4: Using the actual content of trans vitamin K1 in multiple mixed standard sample solutions as the dependent variable Y and the corresponding pre-processed spectral data of trans vitamin K1 as the independent variable X, a partial least squares regression model is established in the spectral analysis software; Step 5, detecting the ATR-FTIR data of the sample solution to be tested, then importing the data into the spectrum analysis software, performing standard normal variable transformation preprocessing to obtain preprocessed spectrum data, inputting the preprocessed spectrum data into the partial least squares regression model established in step 4, and outputting the content of trans-vitamin K1 in the sample solution to be tested; Step 6, importing the ATR-FTIR data in step 2 into spectral analysis software, performing first-order derivative preprocessing to obtain preprocessed spectral data of cis-vitamin K1; Step 7: Using the actual content of cis-vitamin K1 in multiple mixed standard sample solutions as the dependent variable Y and the corresponding pre-processed spectral data of cis-vitamin K1 as the independent variable X, a partial least squares regression model is established in the spectral analysis software; Step 8: Detect the ATR-FTIR data of the sample solution to be tested, then import it into the spectral analysis software, perform first-order derivative preprocessing to obtain preprocessed spectral data, input the preprocessed spectral data into the partial least squares regression model established in step 7, and output the content of cis-vitamin K1 in the sample solution to be tested.

2. The method for rapid detection of cis and trans vitamin K1 content by ATR-FTIR according to claim 1, characterized in that: The content of cis-vitamin K1 in the mixed standard solution is 0-100%, a mixed standard solution is set at every 5% content interval, 3 mixed standard solutions of each content are set, and the concentration range of cis-vitamin K1 is 0-100 μg / mL.

3. The method for rapid detection of cis and trans vitamin K1 content by ATR-FTIR according to claim 1, characterized in that: Multiple mixed standard sample solutions were randomly divided into training sets and validation sets. The training set was 3 / 4 of the number of mixed standard sample solutions. A partial least squares regression model was established based on the actual content of trans vitamin K1 in the training set and the corresponding preprocessed spectral data of trans vitamin K1. The partial least squares regression model was verified based on the actual content of trans vitamin K1 in the validation set and the corresponding preprocessed spectral data of trans vitamin K1.

4. The method for rapid detection of cis and trans vitamin K1 content by ATR-FTIR according to claim 3, characterized in that: A partial least squares regression model was established based on the actual content of cis-vitamin K1 in the training set and the corresponding pre-processed spectral data of cis-vitamin K1, and the partial least squares regression model was verified based on the actual content of cis-vitamin K1 in the validation set and the corresponding pre-processed spectral data of cis-vitamin K1.

5. The method for rapid detection of cis- and trans-vitamin K1 content by ATR-FTIR according to claim 1, characterized in that: The spectral range of ATR-FTIR is 650~4000 cm −1 , with a resolution of 4 cm -1 .

6. The method for rapid detection of cis and trans vitamin K1 content by ATR-FTIR according to claim 1, characterized in that: The solvent for the mixed standard solution is isopropanol.

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