Carbon quantum dots, preparation methods, detection methods, and application of XGBoost in identifying piroxicam-like ingredients

Abstract

The present invention relates to carbon quantum dots, preparation methods, detection methods, and the application of XGBoost in the identification of piroxicam-like ingredients. Piroxicam can cause fluorescence quenching in the quantum dots provided by the present invention, resulting in a non-proportional decrease in the fluorescence intensity corresponding to two excitation wavelengths. The ratio of the fluorescence intensities corresponding to the two excitation wavelengths can, to a certain extent, determine the type and concentration of piroxicam. Based on the quantum dots provided by the present invention, XGBoost can effectively identify the specific type of piroxicam. Furthermore, a CNN based on the quantum dots provided by the present invention can further accurately identify the concentration of piroxicam. This combination of XGBoost and XGBoost enables low-cost, high-precision detection of piroxicam-like ingredients.

Description

Technical Field

[0001] The present invention relates to the field of piroxicam-like detection, and in particular to carbon quantum dots, a preparation method, a detection method, and the application of XGBoost in the identification of piroxicam-like ingredients. Background Art

[0002] Paxicam, a nonsteroidal anti-inflammatory drug (NSAID), inhibits cyclooxygenase activity, providing anti-inflammatory and analgesic effects. Therefore, it is widely used for inflammatory and postoperative management. However, long-term use of pxicam can also damage the hematopoietic system, leading to adverse reactions such as aplastic anemia and coagulopathy. To prevent the abuse of pxicam, detection of pxicam is crucial. However, existing detection methods for pxicam suffer from low precision, difficulty in quantification, poor accuracy, and high cost. Summary of the Invention

[0003] Based on this, it is necessary to provide a carbon quantum dot, a preparation method, a detection method, and the application of XGBoost in the identification of Paxicam-like ingredients to address the problems of poor accuracy and high cost in the detection of Paxicam-like ingredients.

[0004] A carbon quantum dot, whose chemical formula is: .

[0005] A method for preparing carbon quantum dots comprises dissolving fleroxacin in ethanol and reacting the mixture in a reactor at 180-220° C. to obtain the carbon quantum dots.

[0006] An application of the carbon quantum dots in detecting piroxicam.

[0007] A method for detecting piroxicam, comprising:

[0008] Before mixing the carbon quantum dots with the piroxicam, the carbon quantum dots were irradiated with 340nm and 280nm excitation light to obtain the 440nm fluorescence intensity f emitted by the carbon quantum dots. 340 and f 280 ;

[0009] After the carbon quantum dots were mixed with piroxicam, the carbon quantum dots were irradiated with 340nm and 280nm excitation light to obtain the 440nm fluorescence intensity F emitted by the carbon quantum dots. 340 and F 280 ;

[0010] At least based on F 280 / F 340 and f 280 / f 340 , determine the concentration and type of nitroglycerin.

[0011] A training set, the construction method includes:

[0012] preparing mixed solutions of the carbon quantum dots and different types of piroxicam at different concentrations;

[0013] Detect the PLE spectrum corresponding to each mixed solution;

[0014] Combining the PLE spectrum and the piroxicam-type species corresponding to the PLE spectrum to form a first training array;

[0015] At least a portion of the first training arrays are combined into a training set.

[0016] An XGBoost trained on the training set.

[0017] An application of the XGBoost in identifying Paxicam-like ingredients.

[0018] A training set, the construction method includes:

[0019] A solution of one of the piroxicam compounds mixed with carbon quantum dots at different concentrations was prepared;

[0020] Irradiating the solution with 280 nm and 340 nm excitation light respectively and photographing to obtain a first photograph and a second photograph;

[0021] Get the RGB values ​​of the pixels in the first and second photos;

[0022] The second training array is composed of the concentration of the piroxicam, the RGB value of the pixel point in the first photo corresponding to the concentration, and the RGB value of the pixel point in the second photo corresponding to the concentration;

[0023] At least a portion of the second training arrays are combined into a training set.

[0024] A CNN is trained using the training set.

[0025] An application of the CNN in detecting the concentration of piroxicam.

[0026] A method for detecting piroxicam, comprising:

[0027] Adding the carbon quantum dots to a test solution, detecting the PLE spectrum of the test solution, inputting the test data of the PLE spectrum into the XGBoost, and having XGBoost output the type of piroxicam in the test solution;

[0028] According to the type of piroxicam output by XGBoost, the corresponding CNN is selected;

[0029] The test solution is illuminated with 280nm and 340nm excitation light respectively and photographed, and the RGB values ​​of the pixels in the two photos are input into the CNN, which outputs the corresponding concentration of the piroxicam.

[0030] A carbon quantum dot, characterized in that the chemical formula is: .

[0031] A method for preparing carbon quantum dots comprises dissolving meta-naphthalene diol and tris(hydroxymethyl)aminomethane in ethanol, and reacting the mixture in a reactor at 140° C.-180° C. to obtain the carbon quantum dots.

[0032] Paxicam can cause fluorescence quenching of the quantum dots provided by the present invention, and reduce the fluorescence intensities corresponding to the two excitation wavelengths non-proportionally. The type and concentration of the pxicam can be determined to a certain extent by the ratio of the fluorescence intensities corresponding to the two excitation wavelengths.

[0033] Using the quantum dots provided by the present invention, XGBoost can effectively identify specific types of piroxicam. Furthermore, using the quantum dots provided by the present invention, a CNN can further accurately identify the concentration of piroxicam. This combination of the two enables low-cost, high-precision detection of piroxicam. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 TEM image of carbon quantum dots in Example 1 of the present invention;

[0035] Figure 2 This is the XRD pattern of the carbon quantum dots in Example 1 of the present invention;

[0036] Figure 3 This is the Raman spectrum of the carbon quantum dots in Example 1 of the present invention;

[0037] Figure 4 FT-IR spectrum (Fourier transform infrared spectrum) of the carbon quantum dots in Example 1 of the present invention;

[0038] Figure 5 This is the XPS spectrum of the carbon quantum dots in Example 1 of the present invention;

[0039] Figure 6 is the high-resolution XPS spectrum of C 1s in Example 1 of the present invention;

[0040] Figure 7 is the high-resolution XPS spectrum of N 1s in Example 1 of the present invention;

[0041] Figure 8 is the high-resolution XPS spectrum of O 1s in Example 1 of the present invention;

[0042] Figure 9 is the high-resolution XPS spectrum of F 1s in Example 1 of the present invention;

[0043] Figure 10 The UV-visible absorption spectrum (Abs), PL spectrum and PLE spectrum of the carbon quantum dots in Example 1 of the present invention;

[0044] Figure 11 The Fourier emission spectra of the carbon quantum dots in Example 1 of the present invention under light of different wavelengths;

[0045] Figure 12 This is the excitation-emission matrix (EEM) diagram of the carbon quantum dots in Example 1 of the present invention;

[0046] Figure 13 is the relative fluorescence intensity of 440 nm fluorescence emitted by the carbon quantum dots in Example 1 of the present invention after being irradiated with ultraviolet light for different lengths;

[0047] Figure 14 is the relative fluorescence intensity of 440 nm fluorescence emitted by the carbon quantum dots in Example 1 of the present invention after being exposed to sunlight for different lengths;

[0048] Figure 15 is the relative fluorescence intensity of the 440 nm fluorescence emitted by the carbon quantum dots in Example 1 of the present invention in NaCl solutions of different concentrations;

[0049] Figure 16 is the fluorescence intensity of 440 nm fluorescence emitted by the carbon quantum dots in Example 1 of the present invention in solutions with different pH values;

[0050] Figure 17 This is the EEM image of carbon quantum dots before and after mixing with MLX in Example 2 of the present invention;

[0051] Figure 18 The PLE spectra of carbon quantum dots mixed with different concentrations of MLX in Example 2 of the present invention are shown;

[0052] Figure 19 F in Example 2 of the present invention 280 / F 340 Curves changing with MLX concentration;

[0053] Figure 20 F in Example 2 of the present invention 280 / F 340 Curve 1 changes with LNX concentration;

[0054] Figure 21 F in Example 2 of the present invention 280 / F 340 Curve 2 with LNX concentration change;

[0055] Figure 22 F in Example 2 of the present invention 280 / F 340 Curve 1 changes with PRX concentration;

[0056] Figure 23 F in Example 2 of the present invention 280 / F 340 Curve 2 with changes in PRX concentration;

[0057] Figure 24 F in Example 2 of the present invention 280 / F 340 Curve 1 with TNX concentration change;

[0058] Figure 25 F in Example 2 of the present invention 280 / F 340 Curve 2 with TNX concentration change;

[0059] Figure 26 UV-visible absorption spectra of MLX, carbon quantum dots, and a mixture of MLX and carbon quantum dots;

[0060] Figure 27 UV-visible absorption spectrum of MLX, PL spectrum of carbon quantum dots, and PLE spectrum;

[0061] Figure 28 The fluorescence decay curves of carbon quantum dots before and after mixing with MLX under 280nm and 340nm illumination in Example 2 of the present invention are shown;

[0062] Figure 29 This is a typical scoring graph when MLX, LNX, PRX and TNX are 100 μM in Example 3 of the present invention;

[0063] Figure 30 This is a typical scoring graph when MLX, LNX, PRX and TNX are 30 μM in Example 3 of the present invention;

[0064] Figure 31 This is the test result of XGBoost in identifying piroxicam-like ingredients in Example 3 of the present invention;

[0065] Figure 32 This is the test result of random forest in identifying piroxicam-like ingredients in Example 3 of the present invention;

[0066] Figure 33 The test results of logistic regression in the identification of piroxicam-like ingredients in Example 3 of the present invention are as follows;

[0067] Figure 34This is a deviation diagram between the CNN-predicted MLX concentration and the actual MLX concentration in Example 4 of the present invention;

[0068] Figure 35a This is a graph showing the deviation between the CNN-predicted LNX concentration and the actual concentration in Example 4 of the present invention;

[0069] Figure 35b This is a graph showing the deviation between the CNN-predicted PRX concentration and the actual concentration in Example 4 of the present invention;

[0070] Figure 35c This is a graph showing the deviation between the TNX concentration prediction result and the actual concentration by CNN in Example 4 of the present invention;

[0071] Figure 36 FT-IR spectrum of the carbon quantum dots in Example 5 of the present invention;

[0072] Figure 37 This is the XPS spectrum of the carbon quantum dots in Example 5 of the present invention;

[0073] Figure 38 This is the EEM spectrum of the carbon quantum dots in Example 5 of the present invention;

[0074] Figure 39 I is the carbon quantum dots after mixing different substances in Example 5 of the present invention 425 / I 533 Numerical bar graph. DETAILED DESCRIPTION

[0075] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0076] Example 1:

[0077] This embodiment provides a carbon quantum dot, the chemical formula of which is: .

[0078] It is not difficult to see that the carbon quantum dots are doped with N and F.

[0079] The preparation method of the carbon quantum dots comprises the following steps: adding 1 mmol of fleroxacin to 30 mL of ethanol and ultrasonically dispersing for 5 minutes, transferring the mixture to a 50 mL reactor after complete dispersion, and reacting at 180°C-220°C (200°C in this embodiment) for 8 hours; cooling the mixture after the reaction is completed, filtering it with a filter with a pore diameter of 0.22 μm, and then dialyzing it with a dialysis membrane with a molecular weight cutoff of 500 Da at room temperature for 12 hours to obtain the above-mentioned carbon quantum dots.

[0080] The TEM image of the carbon quantum dots is shown in Figure 1 As shown, it shows that the carbon quantum dots of this embodiment have a good spherical structure and good dispersion. After further testing, the particle size of the carbon quantum dots of this embodiment is mainly distributed between 3nm-7nm, with an average of about 5nm. In addition, based on Figure 1 From the high-resolution TEM image shown in the upper right corner, it can be seen that the carbon quantum dots have a clear lattice structure with a lattice plane spacing of 0.21nm.

[0081] See also Figure 2 The carbon quantum dots in this embodiment have a broad peak at 2θ=23.1°, indicating that the carbon quantum dots have a layered structure. Figure 3 , the D peak in the Raman spectrum (1365cm -1 ) intensity and G peak (1600 cm -1 ) intensity ratio is 0.91, which further proves that the above-mentioned carbon quantum dots are highly graphitized.

[0082] See also Figure 4 , the carbon quantum dots in this embodiment are at 3340cm -1 and 3590cm -1 There is a large absorption peak between them, which corresponds to the OH and NH inside. The carbon quantum dots have a peak at 2830 cm -1 and 2972cm -1 The characteristic peak between 1042cm corresponds to CH. -1 、1480cm -1 、1624cm -1 、1725cm -1 The characteristic peaks at the corresponding groups are CF, CN, C=N and C=O. Figure 5 The XPS spectrum of the carbon quantum dots has characteristic peaks at 284.4 eV, 398.1 eV, 530.5 eV and 685.5 eV, corresponding to C 1s, N 1s, O 1s and F 1s, respectively. The final calculation shows that the atomic concentrations of C, N, O and F in the carbon quantum dots are 54.90%, 18.29%, 20.74% and 6.07%, respectively.

[0083] See further Figure 6-Figure 9 Specifically, Figure 6 It exhibits three peaks, located at 287.4 eV (corresponding to CN / CF), 284.8 eV (corresponding to C=O / CO), and 283.3 eV (corresponding to C=C / CC); Figure 7 Two peaks are shown, located at 398.1 eV (corresponding to pyridinic N) and 399.6 eV (corresponding to graphitic N); Figure 8 It shows two peaks, located at 530.5 eV (corresponding to CO) and 531.7 eV (corresponding to C=O); Figure 9 Two peaks are shown, located at 684.2 eV (corresponding to semi-ionized CF) and 685.5 eV (corresponding to covalent CF).

[0084] pass Figure 4-Figure 9 , which can effectively prove that the carbon quantum dots prepared according to the method of this embodiment can be used to obtain the carbon quantum dots of the aforementioned chemical formula.

[0085] like Figure 10 As shown in the figure, the UV-visible absorption spectrum of the carbon quantum dots has a peak at 210nm, corresponding to the π-π* transition of C=C. In addition, there is also a peak at 283nm, corresponding to the n-π* transition of C=O. There is also a weak absorption peak between 300nm and 350nm, corresponding to the n-π* transition of CF and CN. The emission wavelength in the PL spectrum is 440nm. Furthermore, in the PLE spectrum, the emission wavelength of 440nm corresponds to two excitation wavelengths of 280nm and 340nm. Figure 10 As shown in the middle illustration, the carbon quantum dot solution of this embodiment appears light yellow under sunlight and bright blue under ultraviolet light.

[0086] See further Figure 11 and Figure 12 In this embodiment, the emission wavelength of the carbon quantum dots is constantly maintained at 440 nm and does not change with the change of the excitation light wavelength.

[0087] Taking quinine sulfate as a standard, the fluorescence quantum yield of the carbon quantum dots in this embodiment is 43%.

[0088] like Figure 13 As shown, the relative fluorescence intensity of the ordinate represents the ratio of the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots after a certain period of ultraviolet light exposure to the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots without ultraviolet light exposure, and the abscissa represents the duration of ultraviolet light exposure to the carbon quantum dots. Figure 13 It can be seen that the fluorescence intensity of the carbon quantum dots in this embodiment hardly changes even after being exposed to ultraviolet light for 24 hours.

[0089] like Figure 14 As shown, the relative fluorescence intensity of the ordinate represents the ratio of the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots after a certain period of sunlight exposure to the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots without sunlight exposure, and the abscissa represents the duration of sunlight exposure to the carbon quantum dots. Figure 14 It can be seen that the fluorescence intensity of the carbon quantum dots in this embodiment hardly changes even after being exposed to sunlight for 30 days.

[0090] like Figure 15 As shown, the relative fluorescence intensity of the ordinate represents the ratio of the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots in a NaCl solution of a specific concentration to the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots in deionized water, and the abscissa represents the concentration of NaCl. Figure 15 It can be seen that the fluorescence intensity of the carbon quantum dots in this embodiment remains almost unchanged even in a 2.1 mol / L NaCl concentrated solution.

[0091] like Figure 16 As shown in the figure, the ordinate represents the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots. When the excitation light wavelength is 280nm, the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots only decreases slightly as the pH value of the solution increases. Similarly, when the excitation light wavelength is 320nm, the fluorescence intensity of the 440nm fluorescence emitted by the carbon quantum dots also only decreases slightly as the pH value of the solution increases.

[0092] based on Figure 14-16 It can be seen that the carbon quantum dots in this embodiment have extremely strong light resistance, salt resistance, and acid and alkali resistance, and show extremely strong stability.

[0093] Example 2:

[0094] This embodiment provides an application of the carbon quantum dots described in Example 1 for detecting oxicams residues. Oxicams herein include at least meloxicam (MLX), lornoxicam (LNX), piroxicam (PRX), and tenoxicam (TNX).

[0095] Take MLX as an example, Figure 17 and Figure 18As shown in the figure, after carbon quantum dots are mixed with MLX, the 440nm fluorescence intensity produced by the carbon quantum dots decreases regardless of whether they are excited by 280nm or 340nm excitation light. The higher the concentration of MLX, the lower the 440nm fluorescence intensity. This provides a basis for the quantitative detection of MLX using carbon quantum dots.

[0096] exist Figure 19-Figure 25 Among them, F 280 F represents the fluorescence intensity of 440nm emitted by carbon quantum dots when they are irradiated with 280nm excitation light. 340 It represents the 440nm fluorescence intensity emitted by the carbon quantum dots when the carbon quantum dots are irradiated with 340nm excitation light, wherein the 280nm excitation light and the 340nm excitation light excite the carbon quantum dots with the same light intensity (the excitation light source voltage is uniformly 650V in this embodiment and subsequent embodiments).

[0097] from Figure 19 It can be seen from the figure that after carbon quantum dots and MLX are mixed, as the concentration of MLX increases, F 280 / F 340 There is an obvious positive correlation between F 280 / F 340 The value of can determine the concentration of MLX mixed in carbon quantum dots. In particular, when the MLX concentration is in the range of 0-25μM, the MLX concentration and F 280 / F 340 There is a good linear relationship between them (relatively accurate quantitative detection can be achieved within this concentration range), and the detection limit of carbon quantum dots for MLX concentration is 97nM.

[0098] On the contrary, Figure 20 and Figure 21 As shown, after carbon quantum dots are mixed with LNX, F 280 / F 340 There is a negative correlation between LNX concentration and F. 280 / F 340 The value of determines the concentration of LNX mixed in the carbon quantum dots. Among them, when the LNX concentration is in the range of 0-40μM, the LNX concentration and F 280 / F 340 There is a good linear relationship between the two, and the detection limit of carbon quantum dots at LNX concentration is 75nM.

[0099] Similar to MLX, see Figure 22 and Figure 23 After carbon quantum dots are mixed with PRX, F 280 / F 340There is a significant positive correlation between the concentration of PRX and 280 / F 340 The value of can determine the concentration of PRX mixed in carbon quantum dots. Among them, when the PRX concentration is in the range of 0-30μM, the PRX concentration and F 280 / F 340 There is a good linear relationship between the two assays, and the detection limit of carbon quantum dots for PRX concentration is 54 nM.

[0100] Similar to LNX, see Figure 24 and Figure 25 After carbon quantum dots are mixed with TNX, F 280 / F 340 There is an obvious negative correlation between the concentration of F 280 / F 340 The value of can determine the concentration of TNX mixed in carbon quantum dots. Among them, when the TNX concentration is in the range of 0-21μM, the TNX concentration and F 280 / F 340 There is a good linear relationship between the two, and the detection limit of carbon quantum dots for TNX concentration is 102 nM.

[0101] Based on this, this embodiment provides a method for detecting piroxicam, comprising the following steps:

[0102] Step 101: Before mixing the carbon quantum dots with the piroxicam, the carbon quantum dots are irradiated with 340nm excitation light to obtain the 440nm fluorescence intensity f emitted by the carbon quantum dots. 340 ;

[0103] Step 102: Before mixing the carbon quantum dots with the piroxicam, the carbon quantum dots are irradiated with 280nm excitation light to obtain the 440nm fluorescence intensity f emitted by the carbon quantum dots. 280 ;

[0104] Step 103: After mixing the carbon quantum dots with the piroxicam, the carbon quantum dots are irradiated with 340nm excitation light to obtain the 440nm fluorescence intensity F emitted by the carbon quantum dots. 340 ;

[0105] Step 104: After mixing the carbon quantum dots with the piroxicam, the carbon quantum dots are irradiated with 280nm excitation light to obtain the 440nm fluorescence intensity F emitted by the carbon quantum dots. 280 ;

[0106] Step 105: At least based on F 280 / F 340 and f 280 / f 340 , determine the concentration and type of nitroglycerin.

[0107] In order to further explore the detection mechanism of carbon quantum dots for piroxicam, Figure 26 As shown, taking MLX as an example, when MLX is mixed with carbon quantum dots, the mixture does not produce any new peak relative to MLX and carbon quantum dots alone, which proves that no new compound is produced between MLX and carbon quantum dots.

[0108] Further Figure 27 As shown in Figure 2, the PL and PLE spectra of carbon quantum dots overlap significantly with the UV-vis absorption spectrum of MLX, demonstrating that carbon quantum dots can detect MLX based on both IEE (inner filter effect) and FRET (fluorescence resonance energy transfer). Figure 28 Before and after the mixing of carbon quantum dots and MLX, under 280nm light excitation, the fluorescence lifetime of carbon quantum dots decreased from 2.98ns to 2.88ns, with a smaller decrease, indicating that the detection of MLX by carbon quantum dots was dominated by IEE at this time. Under 340nm light excitation, the fluorescence lifetime of carbon quantum dots decreased from 3.79ns to 3.06ns, with a larger decrease, indicating that the FRET degree increased in the detection process of MLX by carbon quantum dots.

[0109] Furthermore, E obsd It represents the percentage of 440nm fluorescence quenching after carbon quantum dots are mixed with piroxicam, E cor Indicates E obsd The fluorescence quenching percentage after removing IEE.

[0110] When the piroxicam is MLX and the excitation wavelength is 280 nm, E obsd =27.3%, E cor =1.9%; when the piroxicam is MLX and the excitation wavelength is 340nm, E obsd =29.1%, E cor =8.2%.

[0111] Similarly, before and after the carbon quantum dots were mixed with LNX, the fluorescence lifetime of the carbon quantum dots decreased from 2.98ns to 2.91ns under 280nm light excitation, with a smaller decrease. Under 340nm light excitation, the fluorescence lifetime of the carbon quantum dots decreased from 3.79ns to 2.99ns, with a larger decrease. When the piroxicam is LNX and the excitation wavelength is 280nm, E obsd =38.1%, E cor =0.6%; when the piroxicam is LNX and the excitation wavelength is 340nm, E obsd =24.9%, E cor =2.6%.

[0112] Before and after mixing carbon quantum dots with PRX, under 280nm light excitation, the fluorescence lifetime of carbon quantum dots decreased from 2.98ns to 2.91ns, with a smaller decrease. Under 340nm light excitation, the fluorescence lifetime of carbon quantum dots decreased from 3.79ns to 3.19ns, with a larger decrease. When the piroxicam is PRX and the excitation wavelength is 280nm, E obsd =27.6%, E cor =3.5%; when the piroxicam is PRX and the excitation wavelength is 340nm, E obsd =61%, E cor =41.9%.

[0113] Before and after the carbon quantum dots were mixed with TNX, the fluorescence lifetime of the carbon quantum dots decreased from 2.98ns to 2.89ns under 280nm light excitation, with a smaller decrease. Under 340nm light excitation, the fluorescence lifetime of the carbon quantum dots decreased from 3.79ns to 3.11ns, with a larger decrease. When the piroxicam is TNX and the excitation wavelength is 280nm, E obsd =40.8%, E cor =7.6%; when the piroxicam is TNX and the excitation wavelength is 340nm, E obsd =41.8%, E cor =6.8%.

[0114] Based on the above analysis, it can be seen that when the excitation light is 280nm, IFE plays a dominant role in the detection of piroxicam by carbon quantum dots; when the excitation light is 340nm, for MLX, LNX and TNX, IFE is still dominant, but the effect of FRET increases. Only for PRX, FRET plays a dominant role. Different types of piroxicam cause different levels of IEE and FRET, which also leads to different concentrations and FRET of different types of piroxicam. 280 / F 340 There are different corresponding relationships between the numerical values, which provides the basis for carbon quantum dots to distinguish the types of Paxicam.

[0115] Example 3:

[0116] Based on the analysis of Example 2, it can be seen that when the piroxicam is MLX and PRX, F 280 / F 340 There is a positive correlation between the concentration of piroxicam and the concentration of nivolumab. When the piroxicam is LNX and TNX, F 280 / F 340 There is a negative correlation between the concentration of MLX and the piroxicam class. Taking into account the experimental error and the influence of the setting of parameter conditions, based on the detection method provided in Example 2, manual identification alone cannot effectively distinguish MLX from PRX, nor can it effectively distinguish LNX from TNX.

[0117] Based on this, this embodiment first attempts to calculate the corresponding F when carbon quantum dots are mixed with different types of piroxicam. 280 and F 340 Perform linear discriminant analysis and try to distinguish the Paxicon class through machine learning. Figure 29 As shown in Figure 2, when the concentrations of MLX, LNX, PRX, and TNX in carbon quantum dots are all 100 μM, the spectral clustering of MLX, LNX, PRX, and TNX can be completely distinguished, as shown in Figure 2. Figure 30 As shown in the figure, when the concentration of MLX, LNX, PRX, and TNX in the carbon quantum dots is reduced to 30 μM, the spectral cluster spacing of MLX, LNX, PRX, and TNX decreases, and some eigenvalues ​​become close, making differentiation more difficult. LNX and TNX are particularly difficult to distinguish. It is not difficult to understand that when the concentration of piroxicam in the carbon quantum dots is further reduced, approaching the aforementioned detection limit of piroxicam for carbon quantum dots, linear discriminant analysis will likely be completely unable to distinguish between MLX, LNX, PRX, and TNX.

[0118] To address this issue, this example provides an application of XGBoost (eXtreme Gradient Boosting) in the identification of piroxicam-like components. Unlike other machine learning methods, XGBoost can effectively distinguish MLX, LNX, PRX, and TNX when the piroxicam-like concentration is lower than 30 μM.

[0119] In order to achieve the above effect, the first training set required by XGBoost during the training process (the training set is renamed as the first training set here to distinguish it from the subsequent examples) is constructed as follows:

[0120] Step 201: preparing a mixed solution of carbon quantum dots and different types of piroxicam at different concentrations.

[0121] Specifically, 36 first mixed solutions of MLX and carbon quantum dots with different concentrations were prepared, with the MLX concentrations in the 36 first mixed solutions being 0.1 μM, 0.2 μM, ..., 3.5 μM, respectively. 36 second mixed solutions of LNX and carbon quantum dots with different concentrations were prepared, with the LNX concentrations in the 36 second mixed solutions being 0.1 μM, 0.2 μM, ..., 3.5 μM, respectively. 36 third mixed solutions of PRX and carbon quantum dots with different concentrations were prepared, with the PRX concentrations in the 36 third mixed solutions being 0.1 μM, 0.2 μM, ..., 3.5 μM, respectively. 36 fourth mixed solutions of TNX and carbon quantum dots with different concentrations were prepared, with the TNX concentrations in the 36 fourth mixed solutions being 0.1 μM, 0.2 μM, ..., 3.5 μM, respectively. The carbon quantum dot concentration in each of the first, second, third, and fourth mixed solutions was 100 μg / nL.

[0122] Step 202: Detecting PLE spectra of at least a portion of the first mixed solution, at least a portion of the second mixed solution, at least a portion of the third mixed solution, and at least a portion of the fourth mixed solution.

[0123] Specifically, in this embodiment, when detecting PLE spectra, the excitation light wavelength scan range is 200nm-800nm, with a scanning step size of 1nm. Therefore, each PLE spectrum has 601 data points, each of which contains information about the excitation light wavelength and the intensity of the emitted light at 440nm. In this embodiment, the 601 data points contained in the same PLE spectrum are used as a whole.

[0124] Preferably, this embodiment detects the PLE spectra of all first mixed solutions, all second mixed solutions, all third mixed solutions, and all fourth mixed solutions.

[0125] Further preferably, in order to reduce experimental errors, in this embodiment, the PLE spectra of all the first mixed solutions, all the second mixed solutions, all the third mixed solutions, and all the fourth mixed solutions are detected 10 times.

[0126] Step 203: Combining each PLE spectrum and the piroxicam type corresponding to the PLE spectrum to form a first training array. The first training array does not include piroxicam concentration information corresponding to the PLE spectrum. All first training arrays are combined into the first training set.

[0127] In this embodiment, 80% of the first training arrays in the first training set are used to train XGBoost, and 20% of the first training arrays are used to test the training results of XGBoost. The test results are as follows: Figure 31As shown in the figure, XGBoost performs discrimination detection on MLX, LNX, PRX, and TNX at low concentrations (no higher than 3.5 μM), with accuracy, recall, and f1 value all being 100%.

[0128] For comparison, the same first training set is used to train and test random forest and logistic regression. The test results are as follows: Figure 32 and Figure 33 As shown in the figure, unlike XGBoost, random forest and logistic regression only have good recognition capabilities for LNX and MLX, and have very low recognition capabilities for PRX and TNX. In particular, random forest is completely unable to recognize PRX.

[0129] This proves that in order to use machine learning to distinguish MLX, LNX, PRX, and TNX under low concentration conditions, not only a specific first training set is required, but also a specific machine learning model is needed.

[0130] Example 4:

[0131] Based on the application of XGBoost in the identification of piroxicam-like components in Example 3, this example further provides an application of CNN (convolutional neural network) in the detection of piroxicam-like concentration, thereby eliminating the need for f in Example 2. 280 and f 340 Detection.

[0132] It is worth noting that since the emission wavelength of the carbon quantum dots in this embodiment is 440 nm, which belongs to visible light, this embodiment provides a method for constructing a second training set (to distinguish it from the previous embodiment, the training set is named the second training set) required for CNN training based on this characteristic, including the following steps:

[0133] Step 301: Prepare a fifth mixed solution of specific types of piroxicam and carbon quantum dots with different concentrations.

[0134] Specifically, in this embodiment, the piroxicam is MLX, the fifth mixed solution has a total of 100 portions, and the corresponding MLX concentrations are 1 μM, 2 μM, ..., 100 μM, wherein the carbon quantum dot concentration is 100 μg / nL.

[0135] Step 302: Irradiate the fifth mixed solution with 280nm excitation light and photograph the light generated by the carbon quantum dots to form a first photograph; irradiate the fifth mixed solution with 340nm excitation light and photograph the light generated by the carbon quantum dots to form a second photograph; thereby obtaining the first photograph and the second photograph corresponding to all fifth mixed solutions, and simultaneously obtaining the RGB values ​​of all pixels in all first photographs and all second photographs.

[0136] Step 303: The piroxicam concentration, the RGB values ​​of all pixels in the first photo corresponding to the concentration, and the RGB values ​​of all pixels in the second photo corresponding to the concentration are combined into a second training array.

[0137] Step 304: Preferably, step 302 and step 303 are repeated 10 times, so that each fifth mixed solution obtains 10 corresponding second training arrays.

[0138] Step 305: Combine all second training arrays into a second training set.

[0139] 80% of the second training array is used to train the CNN. During the training process, the CNN uses 16 convolutional layers, 5 average pooling layers, and 3 fully connected layers. The remaining 20% ​​of the second training array is used to test the trained CNN. The specific test results are as follows Figure 34 As shown in the figure, it can be seen that the deviation between the CNN's predicted MLX concentration and the actual concentration is very small each time. The average deviation between all the predicted results and the actual concentration is only 124 nM, which is much lower than the minimum difference of 1 μM in MLX concentration between different fifth mixed solutions. Therefore, it can be considered that the CNN trained with the second training set in this embodiment has a 100% accuracy in predicting MLX concentration.

[0140] In some other embodiments, MLX in the fifth mixed solution can be replaced with TNX, LNX or PRX, but the corresponding concentrations of the piroxicam in 100 portions of the fifth mixed solution are still 1 μM, 2 μM, ..., 100 μM. Accordingly, after the final CNN training is completed, the concentration prediction and judgment can be performed for one of TNX, LNX and PRX. In other words, after the CNN training is completed, the concentration judgment can only be performed for the specific type of piroxicam corresponding to the second training array used in its training process. Therefore, in order to perform concentration judgments for MLX, TNX, LNX and PRX respectively, four different CNNs need to be trained separately. Figure 35c As shown in Figure 2, the average deviation between the TNX concentration prediction value and the actual TNX value output by the CNN trained on TNX is 145 nM; Figure 35a As shown in Figure 2, the average deviation between the LNX concentration prediction value and the actual LNX value output by the CNN trained on LNX is 97nM; Figure 35b As shown in the figure, the average deviation between the predicted PRX concentration and the actual PRX value output by the CNN trained on PRX is 116nM. These average deviations are all much less than 1μM and can be attributed to errors in actual use. Therefore, the concentration recognition accuracy can also be considered 100%.

[0141] Based on this, this embodiment further provides a method for detecting piroxicam, comprising the following steps:

[0142] Step 401: Detect the PLE spectrum of the test solution, input the test data of the PLE spectrum into the XGBoost after training as described in Example 3, and output the types of piroxicam in the test solution by XGBoost;

[0143] Step 403: Select the trained CNN corresponding to this embodiment based on the piroxicam class output by XGBoost;

[0144] Step 404: Irradiate the test solution with 280nm and 340nm excitation light respectively and take photos. Input the RGB values ​​of all pixels in the two photos into the CNN selected in step 403, and the CNN outputs the corresponding concentration of the piroxicam.

[0145] Example 5:

[0146] This example further provides a method for preparing carbon quantum dots, comprising the following steps: dissolving 1 mmol of naphthoresorcinol and 1 mmol of tris(hydroxymethyl)aminomethane in 20 ml of ethanol, ultrasonically treating the mixture for 15 minutes, transferring the mixture to a reactor, and heating the mixture at 160°C for 6 hours. After the reaction is complete and cooled to room temperature, the mixture is filtered through a 0.22 μm pore size filter, and the filtrate is dialyzed for 24 hours using a 500 Da dialysis tubing. The filtrate is then freeze-dried to obtain the carbon quantum dots.

[0147] Specific as Figure 36 As shown, the carbon quantum dots in this embodiment have four stretching vibration peaks, located at 1067cm -1 、1476cm -1 、1595cm -1 、1719cm -1 At 2900 cm, the four stretching vibration peaks correspond to CN, CC, C=O, and C=N respectively. -1 and 3400cm -1 There is also an absorption band between them, corresponding to the stretching vibration of -NH2 / -OH. Figure 37 , the carbon content of the carbon quantum dots in this embodiment is 56.26%, the N content is 14.23%, and the O content is 29.51%. Based on this, the chemical formula of the carbon quantum dots in this embodiment is .

[0148] like Figure 38As shown, the carbon quantum dots of this embodiment have two fluorescence emission centers, the excitation wavelengths corresponding to the two fluorescence emission centers are 374nm and 470nm, and the corresponding emission wavelengths are 425nm and 533nm, respectively. For the convenience of description, the carbon quantum dots of this embodiment are irradiated with 374nm excitation light, and the 425nm fluorescence intensity emitted by the carbon quantum dots is 1 425 ; The carbon quantum dots of the embodiment were irradiated with 470nm excitation light, and the 533nm fluorescence intensity emitted by the carbon quantum dots was 1 533 In this embodiment, the gains corresponding to the 374nm excitation light and the 470nm excitation light are uniformly 550V.

[0149] Further Figure 39 As shown in the figure, after the carbon quantum dots (carbon quantum dots concentration is 50ng / μL) and different substances (concentration is uniformly 100μM) are mixed, only TNX, LNX, PRX and MLX can make I 425 / I 533 There is a significant change, which proves that the carbon quantum dots in this embodiment can also be used to detect drugs such as Paxicam. + , K + 、Ag + Mg 2+ 、Zn 2+ 、Co 2+ , Ca 2+ 、Ce 2+ , Pb 2+ 、Hg 2+ 、Cd 2+ 、Cu 2+ 、Mn 2+ 、Al 3+ 、Cl - 、SO4 2- 、NO3 - 、SO3 2- 、glucose(Glu, glucose), ascorbic acid(AA, ascorbic acid), urea(urea), uric acid(UA, uric acid), L-asparagine(L-asp, L-asparagine), L-serine(L-ser, L-serine), L-tryptophan(L-try, L-tryptophan), L-proline(L-pro, L-proline), L-alanine(L-ala, L-alanine), L-cysteine(L-cys, L-cysteine), D-alanine(D-ala, D-alanine) can not make I 425 / I 533 Obvious changes were produced, further demonstrating the specificity of the carbon quantum dots in this example for the detection of piroxicam-type drugs.

[0150] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. An application of carbon quantum dots in the detection of piroxicam, characterized in that: The preparation method of the carbon quantum dots comprises the following steps: dissolving fleroxacin in ethanol, and reacting in a reactor at 180° C.-220° C. to obtain the carbon quantum dots.

2. A method for detecting piroxicam, characterized in that: include: Before mixing the carbon quantum dots with the piroxicam, the carbon quantum dots were irradiated with 340nm and 280nm excitation light to obtain the 440nm fluorescence intensity f emitted by the carbon quantum dots. 340 and f 280 ; After the carbon quantum dots were mixed with piroxicam, the carbon quantum dots were irradiated with 340nm and 280nm excitation light to obtain the 440nm fluorescence intensity F emitted by the carbon quantum dots. 340 and F 280 ; At least based on F 280 / F 340 and f 280 / f 340 , determine the concentration and type of piroxicam; The method for preparing carbon quantum dots comprises the following steps: dissolving fleroxacin in ethanol and reacting the mixture in a reactor at 180° C.-220° C. to obtain carbon quantum dots.

3. XGBoost is applied to the identification of Paxicam-like components, characterized in that the XGBoost training set construction method includes: Preparing mixed solutions of carbon quantum dots and different types of piroxicam at different concentrations; Detect the PLE spectrum corresponding to each mixed solution; Combining the PLE spectrum and the piroxicam-type species corresponding to the PLE spectrum to form a first training array; combining at least a portion of the first training array into a training set; The preparation method of the carbon quantum dots comprises the following steps: dissolving fleroxacin in ethanol, and reacting in a reactor at 180° C.-220° C. to obtain the carbon quantum dots.

4. An application of carbon quantum dots in the detection of piroxicam, characterized in that: The preparation method of carbon quantum dots comprises the following steps: dissolving naphthalene diol and tris(hydroxymethyl)aminomethane in ethanol, and reacting the mixture in a reactor at 140°C-180°C to obtain carbon quantum dots.

Images