阅读说明：本技术 一种朱墨时序鉴别或辅助鉴别的质谱成像分析方法 (Mass spectrum imaging analysis method for sequential identification or auxiliary identification of vermilion and black ) 是由 王蔚昕 罗志刚 再帕尔.阿不力孜 尹宝华 廉哲 贺玖明 张瑞萍 李志豪 于 2020-02-04 设计创作，主要内容包括：本发明公开了一种朱墨时序鉴别或辅助鉴别的质谱成像分析方法。该方法可以在保持样品原貌的情况下,对朱墨样本进行微观化学成分分析。基于质谱成像技术的数据化输出结果,朱墨时序判定依据可适当向数据化、可量化转变,避免基于鉴定人思维方式和观察角度互有差别而造成的意见分歧,有利于促进司法鉴定技术的规范化与科学化。同时,朱墨时序质谱成像分析方法的建立增加了文书朱墨时序无损检验方法的种类,提高了朱墨时序检出率,使鉴定结论更为科学可靠。(The invention discloses a mass spectrometry imaging analysis method for sequential identification or auxiliary identification of vermilion and black. The method can be used for carrying out microscopic chemical component analysis on the vermilion ink sample under the condition of keeping the original appearance of the sample. Based on the data output result of the mass spectrometry imaging technology, the jujube timing sequence judgment basis can be properly converted into data and quantized, the phenomenon that opinion divergence is caused by difference between the thinking mode and the observation angle of an appraiser is avoided, and the standardization and the scientization of the judicial appraisal technology are facilitated. Meanwhile, the establishment of the vermilion ink time sequence mass spectrum imaging analysis method increases the variety of non-destructive testing methods of vermilion ink time sequences of the paperwork, improves the detection rate of vermilion ink time sequences, and enables the identification conclusion to be more scientific and reliable.)

1. A method for identifying or assisting in identifying the sequence of printed text and handwriting comprises the following steps:

1) preparing a sample useful for mass spectrometry imaging;

2) performing mass spectrometry imaging on the sample obtained in the step 1) to obtain a mass spectrogram;

3) converting the acquired raw format mass spectrum data file into a mass spectrum image file, selecting characteristic ions in the mass spectrum image according to the presented print and writing outlines, extracting the print unique characteristic ions and writing unique characteristic ions with close intensity levels, respectively performing independent image reconstruction and overlapped image reconstruction to form a print characteristic ion mass spectrum image, a writing characteristic ion mass spectrum image and a superimposed image thereof, and then performing data processing according to the following steps:

a) background ion deduction of blank areas is carried out on the total mass spectrum imaging data, then a pixel point sampling range is set, a plurality of cross points are randomly selected from cross points of the printed text and the handwriting in the superposed mass spectrum image as points to be deduced, a plurality of points are selected from the non-cross printed text and the handwriting image as standard points respectively, the points are marked as a standard point A series and a standard point B series, the points to be deduced and the standard points are marked by different colors, and the standard points of the same series are marked by the same color;

b) setting a mass-to-charge ratio tolerance of 0.001 and ion filtering of 0.1-1% for the full-scan mass spectrum data of the points to be inferred and the standard points, selecting a data processing mode of natural logarithm transformation, and performing PCA clustering analysis by adopting an unsupervised PCA statistical mode, wherein if the analysis result shows that a plurality of inferred points are aggregated, the main material components and the formation sequence of the intersection points at different parts of the sample are not obviously different;

c) if the main material components and the forming sequence of the cross points at different parts of the sample are not obviously different, setting the mass-to-charge ratio tolerance of 0.001 and the ion filtration of 0.1-1% for the full-scan mass spectrum data of the point to be inferred and the standard point, selecting a data processing mode of natural logarithm transformation, judging and analyzing a PLS-DA method by using a statistical partial least square method, adopting a supervised grouping mode, and identifying the order of the print text and the handwriting according to the clustering tropism of the point to be inferred and the standard point A and the standard point B on a score chart;

if the point to be inferred is more towards the standard point A or has data overlapping with the standard point A, the sample is inferred to be signed first and then sealed;

if the point to be inferred is more towards the standard point B or has data overlapping with the standard point B, the sample is inferred to be signed after being stamped.

2. The method of claim 1, wherein: in the step 2), the mass spectrometry is an aerodynamic assisted desorption electrospray ionization mass spectrometry imaging method;

the spray solvent is acetonitrile;

the system parameters are as follows:

the spraying voltage is 7000V;

the voltage of a transmission tube is 0V;

the pressure of the spraying gas is 0.5 MPa;

the air extraction flow rate is 40L/min;

the flow rate of the spray solvent is 5 mu L/min;

the X-axis moving speed is 0.2 mm/s;

the step length of the Y axis is 0.2 mm;

the distance between the spray needle and the conveying pipe is 3 mm;

the distance between the spray needle and the surface of the sample is 4 mm;

the scanning mode is a full scanning mode;

the mass range m/z is 100-1000;

the polarity is positive;

the maximum injection time is 100 ms;

the AGC target is 5e6 for Full MS;

the resolution is 70000;

the capillary temperature is 350 ℃;

the sample scanning speed is 0.2 mm/s;

the step distance was 0.2 mm.

3. The method according to claim 1 or 2, characterized in that: in the step 3), the step of converting the acquired raw-format mass spectrum data file into a mass spectrum image file includes:

and converting the collected raw-format mass spectrum data file into a cdf-format file, and importing the cdf-format file into Massimage1.0 software to generate a mass spectrum image file.

4. A method according to any one of claims 1 to 3, wherein: the software used for data processing in the step 3) is MassImager1.0 mass spectrum imaging data processing software.

5. The method according to any one of claims 1 to 4, wherein: the step 1) of preparing a sample comprises: after extracting the stamp sample to be identified in the order of stamp and signature, fixing the stamp sample on a blank glass slide, and then placing the blank glass slide on a mass spectrum imaging platform.

6. The method according to any one of claims 1 to 5, wherein: in the step 3), the sampling range of the pixel point is 3 × 3;

and selecting an average number of 9 pixel points of mass spectrum data at each intersection point.

7. The method according to any one of claims 1 to 6, wherein: the method further comprises the following steps: in the step 3) and the step b), if the main material components and/or the forming sequence of the cross points at different positions of the sample are obviously different, selecting other cross points from the cross points of the printed text and the handwriting in the superimposed mass spectrum image as points to be deduced, and repeating the step a) and the step b) until the analysis result of the step b) shows that the main material components and/or the forming sequence of the cross points at different positions of the sample are not obviously different.

Technical Field

The invention belongs to the field of detection and analysis, and relates to a mass spectrometry imaging analysis method for sequential identification or auxiliary identification of vermilion and black.

Background

The test of the vermilion ink time sequence is always an important content in the practice of the judicial identification of the document, wherein the identification of the vermilion ink time sequence of the mutual soluble coloring material is a problem which is difficult to solve in the field of the cultural inspection. The traditional vermilion ink time sequence nondestructive testing method is mostly based on the analysis of apparent morphology or three-dimensional hierarchical characteristics, the appearance and the hierarchical characteristics of the vermilion ink sample of the mutual soluble pigment are not obvious or disappear, and the detection rate is low. The Mass Spectrometry Imaging (MSI) technology is a label-free imaging technology which combines mass spectrometry analysis and image visualization and extends to the molecular level. The method can perform multi-point sampling and multi-dimensional data acquisition on the surface of a sample under the condition of no damage to the sample, realize high-sensitivity detection of different molecules, and can directly provide spatial distribution and molecular structure information of a target compound. The mass spectrum imaging technology is applied to the identification of the sequence of the Zhu ink in the document, so that the inspection mode can be deep into the material from the apparent form. Because the apparent form and the three-dimensional hierarchical characteristics are not obvious, the mutual soluble pigment vermilion ink time sequence inspection is always a problem which is difficult to solve in the field of file inspection. Based on the detection principle, the mass spectrum imaging technology which matures day by day can provide richer microstructure and chemical composition information, is expected to be used as a novel detection means for detecting the cinnabar-ink time sequence of the mutual soluble pigment, and provides a more objective detection result.

The existing analysis method for the sequence of the vermilion and black mainly comprises a stereo microscope inspection method, a three-dimensional stereo microscope inspection method, a fluorescence microscope inspection method, a biological microscope inspection method, a graphometer inspection method, a Raman technology, a cross-point section microscopic inspection method, a scanning electron microscope inspection method, a powder adsorption method, a decolorization method and a pressure-dissolution transfer method. In view of the uniqueness and non-reproducibility of the inspected material, ensuring the integrity of the inspected material is an important point of establishing a file inspection method. Therefore, the three-dimensional microscope inspection method and the fluorescence microscope inspection method are widely applied to actual cases as nondestructive inspection methods, but both the two common methods have certain limitations. When the vermilion ink pigments are oil-soluble or water-soluble, the vermilion ink pigments are mutually dissolved and permeated, and the spatial stereo hierarchical characteristics at the intersection have no obvious difference, so that the method is not suitable for the observation and identification of a three-dimensional stereo microscope. The fluorescence microscopy is suitable for materials with light writing pressure and water-soluble writing coloring materials or light printing colors, but is not suitable for distinguishing and identifying black writing coloring material forming materials containing more carbon because the carbon can absorb a large amount of fluorescence emitted by red prints to make the distinguishing of the characteristics formed in different sequences not obvious.

The vermilion ink time sequence inspection is an important problem in the file inspection practice, along with the increasing high-tech and high-intelligent criminal means, the vermilion ink time sequence inspection not only receives more and more attention, but also becomes a problem that identification personnel often encounter but is difficult to solve, the formation reason is mostly blank paper sheets or pirate cover seal marks of the reserved seal marks of counterfeiters and changers, and required text contents are added in due time. Therefore, the key for judging the authenticity and the relative manufacturing time of the documents is to check the sequence of the handwriting and the seal on the documents.

Disclosure of Invention

The invention aims to provide a mass spectrometry imaging analysis method for vermilion timing sequence identification or auxiliary identification.

The AFAI-MSI mass spectrum imaging technology has the characteristics of in-situ sampling, rapidness, no damage and visual visualization, can obtain the relationship characteristics of the distribution and mutual coverage of the chemical substance components of the ink marks and the seal imprints on the paper documents, can provide objective data and information of a quantitative relationship, and is expected to provide a new method for identifying the vermilion ink time sequence.

The method for identifying or assisting in identifying the sequence of the seal and the handwriting, provided by the invention, comprises the following steps:

1) preparing a sample useful for mass spectrometry imaging;

2) performing mass spectrometry imaging on the sample obtained in the step 1) to obtain a mass spectrogram;

3) converting the acquired raw format mass spectrum data file into a mass spectrum image file, selecting characteristic ions in the mass spectrum image according to the presented print and writing outlines, extracting the print unique characteristic ions and writing unique characteristic ions with close intensity levels, respectively performing independent image reconstruction and overlapped image reconstruction to form a print characteristic ion mass spectrum image, a writing characteristic ion mass spectrum image and a superimposed image thereof, and then performing data processing according to the following steps:

a) background ion deduction of blank areas is carried out on the total mass spectrum imaging data, then a pixel point sampling range is set, a plurality of cross points are randomly selected from cross points of the printed text and the handwriting in the superposed mass spectrum image as points to be deduced, a plurality of points are selected from the non-cross printed text and the handwriting image as standard points respectively, the points are marked as a standard point A series and a standard point B series, the points to be deduced and the standard points are marked by different colors, and the standard points of the same series are marked by the same color;

setting a mass-to-charge ratio tolerance of 0.001 and ion filtering of 0.1-1% for the full-scan mass spectrum data of the points to be inferred and the standard points, selecting a data processing mode of natural logarithm transformation, and performing PCA clustering analysis by adopting an unsupervised PCA statistical mode, wherein if the analysis result shows that a plurality of inferred points are aggregated, the main material components and the formation sequence of the intersection points at different parts of the sample are not obviously different;

if the main material components and the forming sequence of the cross points at different parts of the sample are not obviously different, setting the mass-to-charge ratio tolerance of 0.001 and the ion filtration of 0.1-1% for the full-scan mass spectrum data of the point to be inferred and the standard point, selecting a data processing mode of natural logarithm transformation, judging and analyzing a PLS-DA method by using a statistical partial least square method, adopting a supervised grouping mode, and identifying the order of the print text and the handwriting according to the clustering tropism of the point to be inferred and the standard point A and the standard point B on a score chart;

if the point to be inferred is more towards the standard point A or has data overlapping with the standard point A, the sample is inferred to be signed first and then sealed;

if the point to be inferred is more towards the standard point B or has data overlapping with the standard point B, the sample is inferred to be signed after being stamped.

The method comprises the following steps of 1) preparing a sample: after extracting the stamp sample to be identified in the order of stamp and signature, fixing the stamp sample on a blank glass slide, and then placing the blank glass slide on a mass spectrum imaging platform.

In the step 2), the mass spectrometry is an aerodynamic assisted desorption electrospray ionization mass spectrometry imaging method (AFADESI-MSI);

the spray solvent is acetonitrile;

the system parameters are as follows:

the spraying voltage is 7000V;

the voltage of a transmission tube is 0V;

the pressure of the spraying gas is 0.5 MPa;

the air extraction flow rate is 40L/min;

the flow rate of the spray solvent is 5 mu L/min;

the X-axis moving speed is 0.2 mm/s;

the step length of the Y axis is 0.2 mm;

the distance between the spray needle and the conveying pipe is 3 mm;

the distance between the spray needle and the surface of the sample is 4 mm;

the scanning mode is a full scanning mode;

the mass range m/z is 100-1000;

the polarity is positive;

the maximum injection time is 100 ms;

the AGC target is 5e6 for Full MS;

the resolution is 70000;

the capillary temperature is 350 ℃;

the sample scanning speed is 0.2 mm/s;

the stepping distance is 0.2 mm;

in the step 3), the step of converting the acquired raw-format mass spectrum data file into a mass spectrum image file includes: and converting the collected raw-format mass spectrum data file into a cdf-format file, and importing the cdf-format file into Massimage1.0 software to generate a mass spectrum image file.

The software used for data processing in the step 3) is MassImager1.0 mass spectrum imaging data processing software; specifically MassImager^TM1.0 (Kyoto technologies, Inc., Beijing) Mass Spectroscopy imagingStation software;

in the step 3), the sampling range of the pixel point is 3 × 3;

and selecting an average number of 9 pixel points of mass spectrum data at each intersection point.

The method further comprises the following steps: in the step 3), if the main material components and/or the forming sequence of the cross points at different positions of the sample are obviously different, selecting other cross points from the cross points of the print and the handwriting in the superimposed mass spectrum image as points to be deduced, and repeating the step a) and the step b) until the analysis result of the step b) shows that the main material components and/or the forming sequence of the cross points at different positions of the sample (namely, the points to be deduced) are not obviously different.

The invention carries out mass spectrum imaging analysis on 25 combined samples of the seal and the handwriting provided by the material evidence identification center of the ministry of public security, and the imaging result is shown in the attached drawing. From the results, the cross-point clustering tendency of 23 samples (except 3-S7-Xzh-D) among the 24 samples was consistent with the actual results. And judging the sample as a signed and then stamped sample according to the analysis result of the real sample.

The mass spectrum imaging test of the vermilion ink time sequence can analyze the microscopic chemical components of the vermilion ink sample under the condition of keeping the original appearance of the sample. Based on the data output result of the mass spectrometry imaging technology, the jujube timing sequence judgment basis can be properly converted into data and quantized, the phenomenon that opinion divergence is caused by difference between the thinking mode and the observation angle of an appraiser is avoided, and the standardization and the scientization of the judicial appraisal technology are facilitated. Meanwhile, the establishment of the vermilion ink time sequence mass spectrum imaging analysis method increases the variety of non-destructive testing methods of vermilion ink time sequences of the paperwork, improves the detection rate of vermilion ink time sequences, and enables the identification conclusion to be more scientific and reliable.

Drawings

FIG. 1 is a photograph of a sample of a mixture of writing and printing ink and stamp imprint;

FIG. 2 is a mass spectrum image of the crossed part of the vermilion ink sample under different solvent conditions;

FIG. 3 is a comparison of the results of mass spectrometric images of samples 1-S7 using methanol and acetonitrile as solvents;

FIG. 4 is the results of mass spectrometric imaging analysis of samples 1_ S7_ Xzh _ D and 1_ S7_ Xzi _ D (completed in 4 months of 2019);

FIG. 5 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 1-S7 (2019.4);

FIG. 6 shows the cross-point mass spectra of two samples 1-S7(2019.4) and the result of PLS-DA statistical analysis of pixel data from neighboring sample points;

FIG. 7 is the results of mass spectrometric imaging analysis of samples 1_ S7_ Xzh _ D and 1_ S7_ Xzi _ D (completed in 10 months of 2019);

FIG. 8 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 1-S7 (2019.10);

FIG. 9 shows the cross-point mass spectra of two samples 1-S7(2019.10) and the result of PLS-DA statistical analysis of pixel data from neighboring sample points;

FIG. 10 is the results of mass spectrometric imaging analysis of samples 1_ S7_ Xzh _ L and 1_ S7_ Xzi _ L;

FIG. 11 shows the results of PCA statistical analysis of the cross-point pixel data of two types of samples 1-S7-L;

FIG. 12 shows the PLS-DA statistical analysis of the cross-point mass spectra of two samples 1-S7-L and pixel data from neighboring sample points;

FIG. 13 is the results of mass spectrometry imaging analysis of samples 1_ S8_ Xzh _ D and 1_ S8_ Xzi _ D;

FIG. 14 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 1-S8;

FIG. 15 shows the cross-point mass spectra of two samples 1-S8 and the result of PLS-DA statistical analysis of pixel data from neighboring samples;

FIG. 16 is the results of mass spectrometry imaging analysis of samples 1_ S9_ Xzh _ D and 1_ S9_ Xzi _ D;

FIG. 17 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 1-S9;

FIG. 18 shows the cross-point mass spectra of two samples 1-S9 and the result of PLS-DA statistical analysis of pixel data from neighboring samples;

FIG. 19 is the results of mass spectrometry imaging analysis of samples 3_ S7_ Xzh _ D and 3_ S7_ Xzi _ D;

FIG. 20 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 3-S7;

FIG. 21 shows the cross-point mass spectra of two samples 3-S7 and the result of PLS-DA statistical analysis of pixel data from neighboring samples;

FIG. 22 is the results of mass spectrometry imaging analysis of samples 3_ S8_ Xzh _ D and 3_ S8_ Xzi _ D;

FIG. 23 shows the results of PCA statistical analysis of cross-point pixel data for two samples 3-S8;

FIG. 24 shows the cross-point mass spectra of two samples 3-S8 and the result of PLS-DA statistical analysis of pixel data from neighboring samples;

FIG. 25 is the results of mass spectrometry imaging analysis of samples 3_ S9_ Xzh _ D and 3_ S9_ Xzi _ D;

FIG. 26 shows the results of PCA statistical analysis of cross-point pixel data for two types of samples 3-S9;

FIG. 27 is a PLS-DA statistical analysis of cross-point mass spectra of two types of samples 3-S9 and pixel data from neighboring sample points;

FIG. 28 is the results of mass spectrometric imaging analysis of samples PD1_1_ Xzh and PD1_1_ Xzi;

FIG. 29 is the results of PCA statistical analysis of two types of sample PD1_1 cross-point pixel data;

FIG. 30 shows the cross-point mass spectra of two types of PD1_1 samples and the result of PLS-DA statistical analysis of pixel data of neighboring sample points;

FIG. 31 is the results of mass spectrometric imaging analysis of samples PD1_2_ Xzh and PD1_2_ Xzi;

FIG. 32 shows the PCA statistical analysis of two types of sample PD1_2 cross-point pixel data;

FIG. 33 is a PLS-DA statistical analysis of two types of PD1_2 cross-point mass spectra and pixel data from neighboring sample points;

FIG. 34 is the results of mass spectrometric imaging analysis of samples PD1_3_ Xzh and PD1_3_ Xzi;

FIG. 35 is the results of PCA statistical analysis of two types of sample PD1_3 intersection pixel data;

FIG. 36 shows the two types of PD1_3 cross-point mass spectra and the result of PLS-DA statistical analysis of pixel data of neighboring sample points;

FIG. 37 is the results of mass spectrometric imaging analysis of samples PD2_1_ Xzh and PD2_1_ Xzi;

FIG. 38 is the results of PCA statistical analysis of two types of sample PD2_1 cross-point pixel data;

FIG. 39 is a PLS-DA statistical analysis of two types of PD2_1 cross-point mass spectra and pixel data from neighboring sample points;

FIG. 40 is the results of mass spectrometric imaging analysis of samples PD2_2_ Xzh and PD2_2_ Xzi;

FIG. 41 shows the PCA statistical analysis of two types of PD2_2 cross-point pixel data

FIG. 42 shows the cross-point mass spectra of two types of PD2_2 samples and the result of PLS-DA statistical analysis of pixel data of neighboring sample points;

FIG. 43 is the result of mass spectrometric imaging analysis of sample 1999-A2;

FIG. 44 is the result of PCA statistical analysis of the 1999-A2 cross point pixel data;

FIG. 45 is a sample 1999-A2 cross-point mass spectrum and PLS-DA statistical analysis of pixel data from neighboring sample points.

Detailed Description

The present invention will be further illustrated with reference to the following specific examples, but the present invention is not limited to the following examples. The method is a conventional method unless otherwise specified. The starting materials are commercially available from the open literature unless otherwise specified.