Metal oxide heterojunction nanomaterial, and preparation method and application thereof

Abstract

The application discloses a metal oxide heterojunction nanomaterial, which comprises cobalt oxide and copper oxide and is a binary metal oxide composite material with a porous hollow polyhedral nanocage structure. The metal oxide heterojunction nanomaterial has sufficient surface roughness, excellent ultraviolet absorption capacity and electron-hole separation efficiency, can be used for laser desorption ionization mass spectrometry detection and analysis, obtains a mass spectrum corresponding to a biological fluid metabolite, realizes high-accuracy epidural labor analgesia related parturient fever early risk prediction and real-time diagnosis discrimination, and has a wide application prospect.

Description

Technical Field

[0001] This invention belongs to the field of nanomaterials and biological detection, and relates to a metal oxide heterostructure nanomaterial, its preparation method, and its application in detecting metabolites in biological fluids. Background Technology

[0002] Metabolomics is a research approach that explores the relationship between metabolites and physiological and pathological changes. Metabolites are the end products of transcriptional-translational biochemical reaction networks, possessing a high dynamic range and capable of reflecting an individual's physiological and pathological state in real time. Biofluid-based metabolomics analysis has developed rapidly in the early diagnosis, detection, and prognosis of diseases and is considered a promising non-invasive disease screening tool. Currently, widely used biofluids include blood, urine, saliva, and sweat, among which blood is considered a reliable source for metabolite detection due to its stability, non-invasiveness, and ease of collection. Therefore, developing and establishing tools for the detection and analysis of blood metabolites holds great potential for revealing the progression of diseases.

[0003] Mass spectrometry (MS), a commonly used data acquisition tool in metabolomics research, offers higher sensitivity and greater applicability. Considering the inherent complexity of biological fluids, the timeliness of preprocessing before mass spectrometry detection determines the scale of application of this technology platform. Laser desorption / ionization mass spectrometry (LDI MS), with its advantages of high throughput, simple preprocessing, rapid analysis, ease of operation, and low sample consumption, is considered a powerful platform for large-scale clinical analysis. Studies have shown that the efficiency of LDI MS-based metabolomics analysis platforms is mainly determined by the matrix material. An ideal small molecule detection matrix should possess excellent UV absorption properties, strong chemical and thermal stability, and excellent charge transfer capabilities. Among the developed small molecule detection matrices, metal oxides are considered the most promising matrix materials for large-scale clinical applications due to their excellent semiconductor properties and cost-effectiveness. However, single metal oxides cannot meet the sufficient selectivity and ionization efficiency required for clinical applications. Constructing heterojunctions through component doping is considered a reliable strategy to improve the efficiency of LDI MS in metal oxide materials. Rationally designed binary metal oxide heterojunctions with matched band gaps can promote the separation of photogenerated carriers, thus acting as charge transfer media to facilitate analyte ionization during LDI MS. Furthermore, metal-organic frameworks (MOFs) are widely used as derivatized template materials for constructing metal oxide heterojunctions. Compared with traditional synthesis strategies, this MOF derivatization strategy can provide superior pore structures, surface properties, and more stable structures and compositions. Therefore, MOF-derived metal oxide heterojunction materials hold promise for development as ideal matrices for the detection of small molecule metabolites.

[0004] Epidural labor analgesia-related intrapartum fever (ERMF) refers to the phenomenon of significantly elevated body temperature during labor in some women receiving epidural analgesia (EA). With the increasing awareness and acceptance of EA in relieving labor pain, EA is widely accepted and implemented; however, approximately 15%-25% of women receiving EA may experience ERMF. Studies have established a clear causal relationship between EA and maternal fever (temperature ≥38℃), and ERMF may lead to adverse outcomes for both mother and fetus. Currently, there are no safe and effective interventions to prevent and treat ERMF, and its underlying pathological mechanisms remain controversial. Summary of the Invention

[0005] To develop risk prediction and diagnostic tools for ERMF to improve the accuracy and timeliness of ERMF diagnosis and avoid unnecessary obstetric interventions, thereby enabling more accurate prevention and intervention measures, our research group has developed a metal oxide heterostructure nanomaterial particularly suitable for laser desorption / ionization mass spectrometry (LDI MS) detection. After processing biological fluids with this material, high-throughput analysis of metabolites is possible. Specifically, this invention includes the following technical solutions.

[0006] A metal oxide heterostructure nanomaterial comprising cobalt oxide and copper oxide is a binary metal oxide composite material with a porous hollow polyhedral nanocage structure.

[0007] In the aforementioned metal oxide heterojunction nanomaterials, the metal oxide heterojunction has the following chemical formula: Co x Cu y -PHPNC, where x = 0.1-0.9, y = 0.9-0.1, and x+y=1, PHPNC stands for porous hollow polyhedral nanocages.

[0008] In a preferred embodiment, the above-mentioned metal oxide heterojunction includes Co. 0.9 Cu 0.1 -PHPNC, Co 0.8 Cu 0.2 -PHPNC, Co 0.7 Cu 0.3 -PHPNC, Co 0.6 Cu 0.4 -PHPNC, Co 0.5 Cu 0.5 -PHPNC, Co 0.4 Cu 0.6 -PHPNC, Co 0.3 Cu 0.7 -PHPNC, Co0.2 Cu 0.8 -PHPNC, Co 0.1 Cu 0.9 -One or more of PHPNC.

[0009] A second aspect of the present invention is to provide a method for preparing the above-mentioned metal oxide heterostructure nanomaterial, comprising the following steps:

[0010] (1) Prepare raw materials, including cobalt nitrate hexahydrate (Co(NO3)2·6H2O), copper nitrate trihydrate (Cu(NO3)2·3H2O), 2-methylimidazole, methanol and ethanol;

[0011] (2) Cobalt nitrate hexahydrate (Co(NO3)2·6H2O) is uniformly dispersed in a methanol solution to form solution A with a concentration of 0.04-0.05 M, preferably around 0.05 M;

[0012] (3) Disperse 2-methylimidazole uniformly in a methanol solution to form solution B with a concentration of 0.16-0.20 M, preferably around 0.20 M;

[0013] (4) Pour solution A into solution B and stir continuously to obtain solution C;

[0014] (5) Using chemical precipitation, solution C was aged, then centrifuged, washed, and dried to obtain intermediate a;

[0015] (6) Disperse intermediate a uniformly in an ethanol solution to obtain solution D with a concentration of 1.5-1.8 mg·mL. -1 1.6 mg / mL is preferred. -1 about;

[0016] (7) Add copper nitrate trihydrate (Cu(NO3)2·3H2O) to solution D at a concentration of 0.1-1.0 mg·mL. -1 0.9 mg·mL is preferred. -1 Left and right, reflux, centrifuge, dry, to obtain intermediate b;

[0017] (8) Heat intermediate b in air to 300-400℃ and calcine to obtain metal oxide heterostructure nanomaterials.

[0018] Preferably, in step (4) above, the volume ratio of solution A to solution B is approximately 1:1;

[0019] In step (5), the aging time is 20-24 hours;

[0020] In step (7), the reflux time is approximately 3-4 hours;

[0021] In step (8), the calcination time is about 2-3 hours.

[0022] It should be understood that in this article, when describing numerical characteristics, the terms “about,” “approximately,” or “around” refer to the fact that the expressed number may have an error range or fluctuation range of ±10%, ±9%, ±8%, ±7%, ±6%, or ±5%.

[0023] In one embodiment, the molar ratio of cobalt nitrate hexahydrate (Co(NO3)2·6H2O) to 2-methylimidazole in the above method is 1:3-6;

[0024] The molar ratio of added cobalt nitrate hexahydrate (Co(NO3)2·6H2O) to copper nitrate trihydrate (Cu(NO3)2·3H2O) is x:y, i.e., 0.1-0.9:0.9-0.1.

[0025] A third aspect of the present invention provides the use of the above-described metal oxide heterojunction nanomaterials in the preparation of biological detection reagents.

[0026] The aforementioned biological detections specifically refer to the detection of metabolites in biological fluids.

[0027] Preferably, the metabolites mentioned above refer to metabolic markers related to epidural analgesia-associated intrapartum fever (ERMF).

[0028] In a preferred embodiment, the above-mentioned biological detection reagent is used for laser desorption / ionization mass spectrometry (LDIMS) detection, such as matrix-assisted laser desorption / ionization-time of flight mass spectrometry (MALDI-TOF MS).

[0029] For example, the use of the biological detection reagent may include the following steps:

[0030] I. The biofluid was dropped onto a stainless steel target plate and allowed to dry naturally. Then, an aqueous solution of the metal oxide heterojunction nanomaterial described above was dropped onto the sample point and allowed to dry naturally. Subsequently, laser desorption / ionization mass spectrometry was performed to detect and analyze the biofluid metabolites and obtain the mass spectra corresponding to the biofluid metabolites.

[0031] II. Import the biofluid metabolic mass spectrometry obtained in step I into the orthogonal partial least squares discriminant analysis model to screen metabolic biomarkers related to epidural analgesia and intrapartum fever.

[0032] The specific conditions for laser desorption / ionization mass spectrometry analysis in step I above are as follows: a Bruker UltrafleXtreme MALDI-TOF / TOF mass spectrometer is used, with a 355 nm Nd:YAG laser source, a laser frequency of 2000 Hz, and an accelerating voltage of 20 kV; the acquisition mode is cation reflector mode, and the mass-to-charge ratio range is 100-1000 Da; metabolic mass spectrometry data are obtained from flexControl 3.4 and exported from flexAnalysis 3.4.

[0033] Preferably, the orthogonal partial least squares discriminant analysis model described in step II above is Metaboanalyst 5.0 and SIMCA.

[0034] The criteria for screening metabolic biomarkers in step II above are: VIP value greater than 1, P value less than 0.05, FC value greater than 1.5 or less than 0.67, and comparison with the human metabolome database.

[0035] The biological fluid mentioned in step I above can be whole blood, plasma, serum, urine, saliva, tears, body fluids, gastric juice, or feces, preferably plasma.

[0036] The metal oxide heterojunction nanomaterial developed in this invention is derived from metal-organic framework materials and consists of two components: cobalt oxide and copper oxide. It possesses sufficient surface roughness, excellent ultraviolet absorption capacity, and electron-hole separation efficiency. Combined with MALDI-TOF MS and machine learning algorithms, this metal oxide heterojunction nanomaterial can be successfully used for plasma metabolite profile detection and analysis in epidural analgesia-related intrapartum fever, epidural analgesia-free intrapartum fever, and non-analgesia healthy parturients. This achieves highly accurate early risk prediction and real-time diagnosis of epidural analgesia-related intrapartum fever, and screens out relevant metabolic biomarkers. It has great application potential in large-scale population screening, early risk prediction, and disease diagnosis of epidural analgesia-related intrapartum fever. Attached Figure Description

[0037] Figure 1 This is a scanning electron microscope image of the metal oxide heterojunction nanomaterial of Example 1 of the present invention.

[0038] Figure 2 This is a transmission electron microscope image of the metal oxide heterojunction nanomaterial of Example 1 of the present invention.

[0039] Figure 3 The X-ray diffraction pattern is a comparison of the metal oxide heterojunction nanomaterial of Example 1 of the present invention with single metal oxides Co3O4 and CuO.

[0040] Figure 4 This is an XPS image of the metal oxide heterojunction nanomaterial of Example 1 of the present invention.

[0041] Figure 5 The image shows the ultraviolet absorption spectra of the metal oxide heterojunction nanomaterial of Example 1 of the present invention compared with single metal oxides Co3O4 and CuO.

[0042] Figure 6 These are representative spectral diagrams of epidural analgesia-related intrapartum fever, epidural analgesia-non-fever, and non-analgesia-related healthy parturients in Embodiment 2 of the present invention.

[0043] Figure 7 This is a scatter plot of the output of the orthogonal partial least squares discriminant analysis model in Embodiment 3 of the present invention.

[0044] Figure 8 This is a violin diagram illustrating the differences in plasma metabolic markers of the present invention among three groups: febrile women undergoing epidural analgesia, non-febrile women undergoing epidural analgesia, and healthy controls without analgesia, according to Example 3 of the present invention. Detailed Implementation

[0045] The application of metal oxide nanomaterials in biological detection, such as the detection of metabolites, has become a new research hotspot, especially with the rapid development of detection techniques combined with mass spectrometry (MS). For example, patent document CN117074503A reports a nanocomposite material that can be used for time-of-flight mass spectrometry (MALDI-TOF MS) detection of biomarker samples. This nanocomposite material includes two-dimensional nanomaterials and metal oxide nanomaterials. The two-dimensional nanomaterials are selected from two-dimensional nano-Mxene, two-dimensional nano-boron nitride, two-dimensional nano-molybdenum boride, and two-dimensional nano-nitrogen carbide; the metal oxide nanomaterials are selected from nano-iron dioxide, nano-copper oxide, and nano-cobalt oxide, wherein the mass ratio of the two-dimensional nanomaterials to the metal oxide nanomaterials is 10–30:1. Patent document CN113401933A discloses a zinc oxide-supported heterometallic oxide branched nanostructure enriched with defective oxygen. The branched nanostructure contains an np heterojunction constructed by zinc oxide and heterometallic oxide. Its enrichment with defective oxygen is beneficial to increasing the interfacial barrier of the material. This ZnO / Co3O4 branched nanostructure material can be used for the detection of biomarkers such as Listeria monocytogenes, human health diagnosis and food safety monitoring.

[0046] Unlike the aforementioned nanomaterials in terms of chemical composition and microstructure, the metal oxide heterojunction nanomaterials provided by this invention contain a novel heterojunction Co. x Cu y -PHPNC enables nanomaterials to exhibit significantly different properties compared to existing metal oxide heterojunction nanomaterials.

[0047] The term "heterojunction," also known as a nanoheterojunction, refers to a nanostructure composed of different materials, possessing unique electrical, optical, and magnetic properties. It consists of two or more different materials arranged alternately, forming an interface with different band structures. This structure causes electrons to be reflected, refracted, and transmitted at the interface, resulting in a series of new physical phenomena. For example, a semiconductor heterojunction refers to the interface region formed by the contact of two different semiconductors. Based on the conductivity type of the two materials, heterojunctions can be divided into homojunctions (Pp junctions or Nn junctions) and heterojunctions (Pn or pN junctions). Multilayer heterojunctions are called heterostructures. The conditions for forming a heterojunction are usually that the two semiconductors have similar crystal structures, similar interatomic spacing, and similar coefficients of thermal expansion. Heterojunctions can be fabricated using techniques such as interface alloying, epitaxial growth, and vacuum deposition. Heterojunctions often possess superior photoelectric properties that individual PN junctions of the two semiconductors cannot achieve, making them suitable for fabricating ultra-high-speed switching devices, solar cells, and semiconductor lasers.

[0048] This invention utilizes Co(NO3)2·6H2O, Cu(NO3)2·3H2O, 2-methylimidazole, methanol, and ethanol as solvents to form a novel metal oxide heterojunction nanomaterial through a special synthesis / calcination process. This material is particularly suitable for laser desorption / ionization mass spectrometry (LDIMS) for the detection of biological markers and possesses the following characteristics: This metal oxide heterojunction nanomaterial is composed of two components: cobalt oxide and copper oxide. The doping of a suitable amount of metal components with matching bandgap structures into the single metal oxides forms a heterojunction interface that facilitates the separation of photogenerated carriers. The separation of photogenerated carriers means improved electron-hole separation efficiency, which helps to enhance the charge transfer performance of the LDIMS matrix material, thereby increasing the desorption and ionization efficiency of metabolites during LDIMS. The material is prepared using a MOFs-derived strategy, forming a stable structural composition that avoids background interference in laser desorption / ionization mass spectrometry analysis, and the matched surface roughness provides sufficient active sites to selectively capture small molecule metabolites. Because this metal oxide heterojunction nanomaterial possesses matched surface roughness, excellent ultraviolet absorption capacity, and electron-hole separation efficiency, it can be used as a matrix-assisted LDI MS process to achieve efficient ionization and desorption of small molecule metabolites in complex biofluids. The detection results show high selectivity and strong signal detection of the target signal. Therefore, this material can achieve efficient mass spectrometry detection of metabolites of intrapartum febrile biofluids related to epidural analgesia.

[0049] In an embodiment used for biological detection, the present invention uses a machine learning model to analyze the expression differences of biofluid metabolites in intrapartum fever associated with epidural analgesia, non-fever during epidural analgesia, and healthy parturients without analgesia, thereby screening biofluid metabolism biomarkers to achieve early prediction and diagnosis of intrapartum fever associated with epidural analgesia.

[0050] Based on the excellent ultraviolet absorption characteristics of this metal oxide heterostructure nanomaterial, it can be successfully used for the metabolite mass spectrometry analysis of intrapartum fever, non-fever, and non-analgesic healthy parturient biofluids related to epidural analgesia. Nine metabolites were screened as potential metabolic biomarkers for intrapartum fever related to epidural analgesia.

[0051] To make the present invention more apparent and understandable, preferred embodiments are described in detail below. Those skilled in the art should understand that the following embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0052] Example

[0053] The embodiments involve the addition amount, content and concentration of various substances. Unless otherwise specified, the "parts" mentioned therein refer to "parts by weight"; unless otherwise specified, the percentage content refers to the mass percentage content.

[0054] In the embodiments described herein, unless otherwise specified, the operating temperature is generally referred to as room temperature (15-35°C).

[0055] Example 1: Preparation of metal oxide heterostructure nanomaterials

[0056] The synthesis of metal oxide heterostructure nanomaterials includes the following steps:

[0057] (1) First, 1.245 g Co(NO3)2·6H2O is uniformly dispersed into 100 mL of methanol solution to form solution A.

[0058] 1.640 g of 2-methylimidazole was uniformly dispersed in 100 mL of methanol solution to form solution B.

[0059] Then, pour solution A into solution B and stir continuously to form a homogeneous mixed solution C.

[0060] Then, solution C was aged and allowed to stand for 20 hours. It was then washed three times with methanol, and finally the solid product was vacuum dried overnight at 50°C.

[0061] (2) Take 240 mg of the product obtained in step (1) and disperse it evenly in 150 mL of ethanol to obtain solution D.

[0062] Subsequently, 109 mg Cu(NO3)2·3H2O was added to solution D, and the mixture was refluxed for 3 hours. The solution was then washed three times with ethanol, and the solid product obtained by centrifugation was dried under vacuum at 50°C overnight.

[0063] (3) The product obtained in step (2) is calcined in air at 360°C for 2 hours at a heating rate of 2°C / min to obtain metal oxide heterostructure nanomaterials.

[0064] Material characterization: Scanning electron microscope images of metal oxide heterostructure nanomaterials, as shown in the figure. Figure 1 Transmission electron microscope images of metal oxide heterostructure nanomaterials, such as... Figure 2 X-ray diffraction patterns of metal oxide heterojunction nanomaterials compared with single metal oxides Co3O4 and CuO are shown below. Figure 3 XPS images of metal oxide heterostructure nanomaterials are shown below. Figure 4 The UV absorption spectra of metal oxide heterojunction nanomaterials compared with those of single metal oxides Co3O4 and CuO are shown below. Figure 5 These spectra differ significantly from those of existing metal oxide heterostructure nanomaterials, suggesting unique characteristics in both physical and chemical properties.

[0065] Example 2: Detection of postpartum plasma metabolite profiles

[0066] Using the metal oxide heterostructure nanomaterials obtained in Example 1, metabolite mass spectrometry was performed on plasma samples from 144 women with intrapartum fever related to epidural analgesia, 130 women without fever during epidural analgesia, and 32 healthy women without analgesia, taken from the Obstetrics and Gynecology Hospital Affiliated to Fudan University.

[0067] (1) Take 1 mg of the metal oxide heterojunction nanomaterial prepared in Example 1, disperse it in 1 mL of deionized water, and sonicate it at room temperature to obtain a uniformly dispersed metal oxide heterojunction nanomaterial suspension.

[0068] (2) Drop 1 μL of plasma sample of appropriate concentration onto a stainless steel target plate. After the sample spot dries naturally, drop the metal oxide heterojunction nanomaterial suspension obtained in step (1) onto the stainless steel target plate. After it dries naturally, perform laser desorption / ionization mass spectrometry analysis. Use a Bruker UltrafleXtreme MALDI-TOF / TOF mass spectrometer with a 355 nm Nd:YAG laser source, a laser frequency of 2000 Hz, and an accelerating voltage of 20 kV. The acquisition mode is cation reflector mode, and the mass-to-charge ratio range is 100-1000 Da. Obtain mass spectrometry data from flexControl 3.4 and export the data in flexAnalysis 3.4 to obtain plasma metabolic mass spectrometry.

[0069] Representative chromatograms of epidural analgesia-related intrapartum fever, epidural analgesia without fever, and non-epidural healthy labor are shown below. Figure 6 .

[0070] Example 3: Screening of plasma metabolic biomarkers

[0071] The plasma metabolism mass spectrometry data obtained in Example 2 were imported into an orthogonal partial least squares discriminant analysis model to screen for plasma metabolism biomarkers. The steps are as follows:

[0072] (1) The plasma mass spectrometry spectrum was preprocessed using R language based on the MALDIquant and MALDIquantForeign packages, including peak intensity conversion and normalization, peak smoothing, baseline subtraction, peak alignment, peak identification and peak grouping.

[0073] (2) Based on plasma metabolic mass spectrometry, an orthogonal partial least squares discriminant analysis model was constructed using SIMCA to select plasma metabolic biomarkers. Specifically, the P-value, FC value, and VIP value of each metabolite were calculated using Metaboanalyst 5.0 and SIMCA. Characteristic signal peaks with VIP values ​​greater than 1, P-values ​​less than 0.05, and FC values ​​greater than 1.5 or less than 0.67 were screened and compared with the human metabolome database to serve as plasma metabolic biomarkers.

[0074] The scatter plot of the output of the orthogonal partial least squares discriminant analysis model is shown below. Figure 7 The violin plot showing the differences in plasma metabolic markers among three groups—parturients with intrapartum fever associated with epidural analgesia, women without fever during epidural analgesia, and healthy controls without analgesia—is shown in [reference needed]. Figure 8 .

[0075] Based on the analysis results of the orthogonal partial least squares discriminant analysis model, nine metabolites were selected as potential metabolic biomarkers for epidural analgesia-related intrapartum fever, with m / z values ​​of 80.87, 122.98, 127.99, 138.92, 212.03, 250.11, 266.09, 279.97, and 282.04, respectively.

[0076] It should also be noted that the above analytical model can also be used to screen other disease-related biomarkers.

[0077] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. The use of a metal oxide heterojunction nanomaterial in the preparation of biological diagnostic reagents, wherein the metal oxide heterojunction nanomaterial comprises cobalt oxide and copper oxide, and is a binary metal oxide composite material with a porous hollow polyhedral nanocage structure, and the metal oxide heterojunction has the following chemical formula: Co x Cu y -PHPNC, where x = 0.1-0.9, y = 0.9-0.1, and x+y=1, PHPNC represents a porous hollow polyhedral nanocage; the metal oxide heterojunction is formed by doping two components, cobalt oxide and copper oxide, and doping a metal component with a matching bandgap structure into a single metal oxide to form a heterojunction interface that facilitates the separation of photogenerated carriers; The biological assay refers to the detection of metabolic markers related to epidural labor analgesia-associated intrapartum fever (ERMF) in biofluids.

2. The use as described in claim 1, characterized in that, The preparation method of the metal oxide heterojunction nanomaterial includes the following steps: (1) Prepare raw materials, including cobalt nitrate hexahydrate (Co(NO3)2·6H2O), copper nitrate trihydrate (Cu(NO3)2·3H2O), 2-methylimidazole, methanol and ethanol; (2) Cobalt nitrate hexahydrate (Co(NO3)2·6H2O) is uniformly dispersed in a methanol solution to form solution A with a concentration of 0.04-0.05 M; (3) Disperse 2-methylimidazole uniformly in a methanol solution to form solution B with a concentration of 0.16-0.20 M; (4) Pour solution A into solution B and stir continuously to obtain solution C; (5) Using chemical precipitation, solution C was aged, then centrifuged, washed, and dried to obtain intermediate a; (6) Disperse intermediate a uniformly in an ethanol solution to obtain solution D with a concentration of 1.5-1.8 mg·mL. -1 ; (7) Add copper nitrate trihydrate (Cu(NO3)2·3H2O) to solution D, at a concentration of 0.1-1.0 mg·mL. -1 Reflux, centrifuge, dry to obtain intermediate b; (8) Heat intermediate b in air to 300-400℃ and calcine to obtain metal oxide heterostructure nanomaterials.

3. The use as described in claim 1, characterized in that, The metal oxide heterojunction includes Co 0.9 Cu 0.1 -PHPNC, Co 0.8 Cu 0.2 -PHPNC, Co 0.7 Cu 0.3 -PHPNC, Co 0.6 Cu 0.4 -PHPNC, Co 0.5 Cu 0.5 -PHPNC, Co 0.4 Cu 0.6 -PHPNC, Co 0.3 Cu 0.7 -PHPNC, Co 0.2 Cu 0.8 -PHPNC, Co 0.1 Cu 0.9 -One or more of PHPNC.

4. The use as described in claim 1, characterized in that, The metal oxide heterojunction, as a matrix material, possesses surface roughness, ultraviolet absorption capacity, and electron-hole separation efficiency that match laser desorption / ionization mass spectrometry.

5. The use as described in claim 2, characterized in that, In step (4) of the preparation method, the volume ratio of solution A to solution B is 1:1; In step (5), the aging time is 20-24 hours; In step (7), the reflux time is 3-4 hours; In step (8), the calcination time is 2-3 hours.

6. The use as described in claim 2, characterized in that, In the preparation method, the molar ratio of cobalt nitrate hexahydrate (Co(NO3)2·6H2O) to 2-methylimidazole is 1:3-6; The molar ratio of added cobalt nitrate hexahydrate (Co(NO3)2·6H2O) to copper nitrate trihydrate (Cu(NO3)2·3H2O) is x:y, i.e., 0.1-0.9:0.9-0.

1.

7. The use as described in claim 1, characterized in that, The biological detection reagents are used for detection by laser desorption / ionization mass spectrometry or for matrix-assisted laser desorption / ionization time-of-flight mass spectrometry.

8. The use as described in claim 7, characterized in that, The use of the biological detection reagent includes the following steps: I. A biofluid is dropped onto a stainless steel target plate and dried. An aqueous solution of the metal oxide heterojunction nanomaterial as described in any one of claims 1-6 is then dropped onto the sample point, dried, and subsequently detected and analyzed by laser desorption / ionization mass spectrometry to obtain the mass spectrum corresponding to the biofluid metabolite. II. Import the biofluid metabolic mass spectrometry obtained in step I into the orthogonal partial least squares discriminant analysis model to screen metabolic biomarkers related to epidural analgesia and intrapartum fever.

9. The use as described in claim 8, characterized in that, The specific conditions for laser desorption / ionization mass spectrometry analysis in step I are as follows: a Bruker UltrafleXtreme MALDI-TOF / TOF mass spectrometer is used, with a 355 nm Nd:YAG laser source, a laser frequency of 2000 Hz, and an accelerating voltage of 20 kV; the acquisition mode is cation reflector mode, and the mass-to-charge ratio range is 100-1000 Da; metabolic mass spectrometry data are obtained from flexControl 3.4 and exported from flexAnalysis 3.

4.

10. The use as described in claim 8, characterized in that, The orthogonal partial least squares discriminant analysis model mentioned in step II is Metaboanalyst 5.0 and SIMCA.

11. The use as described in claim 8, characterized in that, The criteria for screening metabolic biomarkers in step II are: VIP value greater than 1, P value less than 0.05, FC value greater than 1.5 or less than 0.67, and comparison with the human metabolome database.

12. The use as described in claim 8, characterized in that, The biological fluid mentioned in step I is selected from whole blood, plasma, serum, urine, saliva, tears, body fluids, gastric juice, and feces.

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