A chip, a preparation method thereof and a quantitative detection method of acylcarnitine

Abstract

The application provides a preparation method of a chip for high-coverage and high-sensitivity quantitative detection of acylcarnitine in clinical samples, comprising the following steps: A) preparing silicon nanowire material; B) reducing and modifying gold nanoparticles in situ to obtain Au-SiNWs material; and C) preparing Sulfo-Au-SiNWs material through self-assembly reaction. The application introduces surface sulfonic acid groups and gold nanoparticles to synergistically enhance ionization efficiency and effectively improve the signal response of AC in a high-salt complex matrix. In terms of quantification, the full-spectrum internal standard method derived from perdeuterated ethanol uses the isotopic mass difference to avoid peak overlap, breaks through the traditional quantitative method which relies on a small number of standard samples, and for the first time realizes high-coverage and high-accuracy quantitative analysis of AC in clinical samples, significantly improving the universality and clinical operability of the method.

Description

Technical Field

[0001] This invention relates to the field of detection technology, and in particular to a chip, its preparation method, and a method for quantitative detection of acylcarnitine. Background Technology

[0002] Metabolomics is a technique for systematically studying the composition of small molecule metabolites in the body and their relationship with disease, emphasizing the dynamic reflection of metabolic characteristics on an individual's health status. Based on research strategy, it can be divided into two categories: non-targeted and targeted. The former explores potential biomarkers, while the latter targets the quantitative detection of specific molecular groups (such as acylcarnitines), typically combining MRM mass spectrometry with stable isotope internal standards to achieve highly specific analysis. Acylcarnitines (ACs) are key intermediates in fatty acid β-oxidation and are widely involved in energy metabolism. Abnormal levels of ACs are closely related to neonatal metabolic defects (IEM), insulin resistance, and other diseases, making them a key target in newborn screening (NBS). Existing AC detection methods include: LC-MS: high sensitivity but complex sample preparation and time-consuming separation, limiting throughput; FI-MS: eliminating chromatography to improve efficiency, the standard method for NBS, but still has problems such as cumbersome pretreatment, low recovery rate, and needle clogging; MALDI-MS: rapid and salt-tolerant, but quantitative stability is affected by matrix inhomogeneity and signal interference.

[0003] Current technologies mainly include LC-MS quantitative strategies based on chemical isotope labeling. Representative technical solutions are as follows: Representative technology: The chemical isotope labeling strategy based on dansyl hydrazine derivatization developed by Chen et al. (Chen, GY; Zhang, Q. Anal. Bioanal. Chem. 2020, 412, 2841−2849); Core steps: Select 13 commercially available acylcarnitine standards; Label them through chemical derivatization and isotope tagging; Use an LC-MS platform for separation and quantitative detection; Main advantages: Balances specificity and sensitivity; Main disadvantages: Quantifiable species are limited to known standards, resulting in limited coverage; The chemical labeling process is complex, requiring certain operational skills and LC separation, which is not conducive to high-throughput automated processing; It cannot be applied to unknown or low-abundance medium- to long-chain ACs that may exist in screening.

[0004] In existing SALDI-MS analyses, although attempts have been made to enhance analytical performance using silicon nanowires (SiNWs), the following challenges remain when analyzing medium- and long-chain acylcarnitines (AC) in complex biological matrices such as urine or DBS samples: (1) Limited enrichment capacity: Traditional SiNWs lack specific functional groups, making it difficult to effectively enrich positively charged AC molecules in situ. (2) Insufficient excitation efficiency: The lack of an energy regulation mechanism for the laser desorption process results in low desorption / ionization efficiency, affecting detection sensitivity. (3) Low coverage: Existing methods often rely on the addition of a small number of target compounds as internal standards for quantification, making it difficult to fully cover the AC spectrum, affecting quantitative accuracy and throughput. (4) Difficulty in balancing high throughput and accuracy: Conventional FI-MS or SALDI-MS methods have a trade-off between high-throughput rapid detection and comprehensive quantitative analysis, making it difficult to simultaneously meet the dual requirements of speed and accuracy for newborn screening.

[0005] Therefore, the aforementioned limitations restrict the application potential of this type of method in large-scale newborn metabolic disease screening (NBS) and the discovery of potential biomarkers in urine. To achieve highly sensitive detection of medium- and long-chain AC species and accurate quantification in complex biological samples, it is necessary to develop a novel mass spectrometry matrix material and construct a more universal quantitative strategy. Summary of the Invention

[0006] In view of this, the technical problem to be solved by the present invention is to provide a method for preparing a chip for quantitative detection of acylcarnitine in high-coverage and high-sensitivity clinical samples. The chip prepared by the present invention can enhance the acylcarnitine signal response.

[0007] In the quantitative analysis of acylcarnitines (ACs) in actual clinical samples, especially urine and dried blood spots (DBS), existing methods face the challenge of simultaneously achieving high sensitivity, high throughput, and broad spectral coverage. While methods such as LC-MS offer high sensitivity and quantitative accuracy, their throughput is limited by cumbersome sample pretreatment and chromatographic procedures, making it difficult to meet clinical screening needs. FI-MS, although improving detection speed, still relies on complex sample pretreatment steps and suffers from low signal recovery and limited internal standard coverage for medium- and long-chain ACs. Furthermore, existing SiNW-based SALDI platforms perform well in negative ion mode, but their detection performance is limited under positive ion conditions for positively charged AC molecules due to the lack of selective enrichment mechanisms for functional groups and ionization enhancement mechanisms.

[0008] To address the aforementioned challenges simultaneously, this invention proposes an LDI-MS platform based on Sulfo-Au-SiNWs chip-based EALDI (electrostatic adsorption-Laser desorption / ionization) technology, combined with a full-spectrum internal standard strategy. This platform achieves electrostatic enrichment of positively charged AC ions by introducing surface sulfonic acid groups, and enhances ionization efficiency through synergistic thermal desorption and charge transfer using gold nanoparticles, effectively improving the signal response of medium- and long-chain AC in high-salt complex matrices. In terms of quantification, the innovatively designed full-spectrum internal standard method derived from fully deuterated ethanol utilizes isotopic mass differences to avoid peak overlap, breaking through the traditional quantitative methods that rely on a few standards. This achieves, for the first time, high-coverage and high-accuracy quantitative analysis of AC in clinical samples, significantly improving the method's versatility and clinical operability.

[0009] In summary, this invention not only improves the desorption and enrichment efficiency of analytes, but also constructs a highly adaptable quantitative system, thereby systematically solving the problem of the difficulty in balancing throughput, coverage and sensitivity in existing AC detection methods. It is expected to provide a technical foundation with promotional value for newborn metabolic disease screening and rapid screening of metabolites in complex biological samples.

[0010] This invention provides a method for preparing a chip for the quantitative detection of acylcarnitine in high-coverage and high-sensitivity clinical samples, comprising:

[0011] A) Preparation of silicon nanowire materials;

[0012] B) The prepared silicon nanowire material was reacted with hydrofluoric acid solution, then washed, dried, and immersed in an aqueous solution containing HF, HAuCl4 and ethanol to react and obtain Au-SiNWs material.

[0013] C) The prepared Au-SiNWs material was immersed in an aqueous solution containing sodium 3-mercaptopropanesulfonate and reacted to obtain Sulfo-Au-SiNWs material.

[0014] The method for preparing a chip for quantitative detection of acylcarnitine in high-coverage and high-sensitivity clinical samples provided by the present invention first prepares silicon nanowire materials.

[0015] According to the present invention, the preparation of the silicon nanowire material specifically includes:

[0016] a) p-type silicon wafers are cut into small silicon wafers with the polished side (front side) facing up. The wafers are etched in a plastic petri dish containing HF and AgNO3 solutions to obtain the etched material.

[0017] b) The etched material is washed and then immersed in a dilute nitric acid solution; after the reaction, it is washed and dried under nitrogen conditions;

[0018] c) The above materials are immersed in HF solution for reaction. After the reaction is completed, the materials are washed and dried with nitrogen to obtain SiNWs materials.

[0019] The SiNWs provided by this invention are prepared by one-step metal-assisted chemical etching (MACE).

[0020] First, a p-type silicon wafer is cut into small silicon wafers with the polished side (front side) facing up. The wafers are then etched in a plastic petri dish containing HF and AgNO3 solutions to obtain the etched material.

[0021] In one embodiment of the present invention, a single-sided polished p-type silicon wafer with a resistivity of 5~10 Ω·cm is used, specifically 5, 6, 7, 8, 9, or 10 Ω·cm.

[0022] Preferredly, small square silicon wafers with sides of 3cm to 5cm are cut with a diamond cutter, with the polished side (front) facing up, and etched for 10 to 15 minutes at room temperature in a plastic petri dish containing 4.8 M HF and 0.02 M AgNO3 solution.

[0023] Subsequently, the etched material was washed and then immersed in a dilute nitric acid solution. After being washed three times with deionized water, the etched material was immersed in a dilute nitric acid solution (concentrated nitric acid:water = 1:1, v / v) for 1 hour to remove the Ag element produced in the previous step.

[0024] Wash after reaction and dry under nitrogen; after reaction, wash the material 2-3 times with deionized water and dry under nitrogen.

[0025] The above materials were immersed in HF solution for reaction. After the reaction was completed, the materials were washed and dried with nitrogen to obtain SiNWs materials.

[0026] That is, the above material is immersed in a 2% HF solution and reacted for 5 minutes. After the reaction, the material is washed 2-3 times with deionized water and ethanol respectively, and then dried with nitrogen to obtain SiNWs material, such as... Figure 1 As shown in A, Figure 1 This is a flowchart of the preparation process of Sulfo-Au-SiNWs.

[0027] The prepared silicon nanowire material was reacted with hydrofluoric acid solution, then washed, dried, and immersed in an aqueous solution containing HF, HAuCl4 and ethanol to react and obtain Au-SiNWs material.

[0028] The mass concentration of the hydrofluoric acid solution described in this invention is 1% to 3%; specifically, it can be 1%, 2%, or 3%. The reaction time described in this invention is 3 to 8 minutes; specifically, it can be 3 minutes, 4 minutes, 5 minutes, 6 minutes, 7 minutes, or 8 minutes; preferably, the reaction time is 5 minutes.

[0029] After the reaction is complete, wash the material 2-3 times with deionized water and ethanol respectively.

[0030] The drying process described in this invention is preferably nitrogen drying; after nitrogen drying, the material is immersed in an aqueous solution containing HF, HAuCl4, and ethanol (hereinafter referred to as the Au precursor solution) for reaction, then washed 2-3 times with deionized water, and dried under nitrogen to obtain Au-SiNWs material ( Figure 1 B).

[0031] The aqueous solution containing HF, HAuCl4 and ethanol has a concentration of 4 mmol / L, a concentration of 1 mmol / L for HAuCl4, and a volume fraction of 30% for ethanol. The reaction time is 10 min.

[0032] The prepared Au-SiNWs material was immersed in an aqueous solution containing sodium 3-mercaptopropanesulfonate and reacted to obtain Sulfo-Au-SiNWs material.

[0033] The prepared Au-SiNWs material was immersed in an aqueous solution containing sodium 3-mercaptopropane-sulfonate (MPS) and reacted for 10 min. The concentration of sodium 3-mercaptopropane-sulfonate in the aqueous solution of MPS described in this invention is 0.10 mol / L.

[0034] Then it is washed 2-3 times with deionized water and dried under nitrogen to obtain Sulfo-Au-SiNWs material. Figure 1 C). The SEM and EDS characterization analyses of the composite material are as follows: Figure 2 As shown. Figure 2 SEM and EDS characterization images of the Sulfo-Au-SiNWs material. Figures (A, B, C) and (D, E, F) show the surface SEM image and cross-sectional SEM image of the material, respectively. Among them, Figures (A) and (D) contain magnified details, Figures (B) and (E) are superimposed EDS elemental analysis maps, and Figures (C) and (F) show the corresponding EDS elemental energy spectra.

[0035] The present invention provides a chip for quantitative detection of acylcarnitine in clinical samples with high coverage and high sensitivity, prepared by the preparation method described in any one of the above technical solutions.

[0036] The specific sources of the above preparation method have been clearly described in this invention, and will not be repeated here.

[0037] This invention also provides the application of the chip described above as a surface-assisted laser desorption / ionization mass spectrometry (SALDI-MS) substrate in enhancing the acylcarnitine signal response. The detection technique using this method is hereinafter referred to as EALDI-MS.

[0038] The present invention also provides a method for quantitative detection of acylcarnitine, wherein a chip for quantitative detection of acylcarnitine in high-coverage and high-sensitivity clinical samples is prepared by any of the preparation methods described in the above technical solutions.

[0039] This invention determined the optimal concentration parameters for material preparation by plotting a bar chart of the signal-to-noise ratio (S / N) of a 1 μg / mL carnitine standard solution and Sulfo-Au-SiNWs at 40% laser energy. Based on system optimization, the optimal conditions for the gold precursor—1 mmol / L HAuCl4, 0.004 mol / L HF, and 0.10 mol / L MPS—were determined and used for all subsequent material preparations.

[0040] The quantitative detection method for acylcarnitine provided by this invention first involves sample pretreatment. In this quantitative detection method, the samples include urine and DBS samples.

[0041] The urine pretreatment includes: dilution with deionized water, centrifugation, collection of supernatant, aliquoting and storage at low temperature for subsequent analysis;

[0042] In some specific embodiments, the QC sample is diluted 25 times with deionized water, centrifuged at 8000 g for 10 min at 4°C, and the supernatant is collected, aliquoted, and stored in an ultra-low temperature freezer at -80°C for subsequent analysis.

[0043] Pretreatment of DBS samples: Prepare circular dried blood spot filter paper, add the filter paper to methanol, sonicate, shake, centrifuge, take the supernatant, dry it under nitrogen, and freeze until use.

[0044] In some specific embodiments, circular dried blood spot filter paper discs with a diameter of 3.2 mm are prepared using a punch, and then the filter paper discs are added to 100 μL of methanol, sonicated for 20 min, shaken for 20 min, centrifuged at 10000 g for 10 min, and the supernatant is dried under nitrogen and stored in a -80℃ freezer until use.

[0045] Determination of acylcarnitine concentration in quality control samples:

[0046] Urine or DBS quality control samples were subjected to targeted quantitative analysis of acylcarnitine using a detection system approved by the National Medical Products Administration (NMPA) of China (Registration Certificate No.: 20223400429). Specifically, the "Non-derived Amino Acids, Carnitine, Adenosine, Lysophosphatidylcholine and Succinylacetone Assay Kit (Tandem Mass Spectrometry)" manufactured by Suzhou Xinbo Biotechnology Co., Ltd. was used. The experiment employed a flow-through tandem mass spectrometry (FI-MS / MS) platform, strictly adhering to the testing institution's standard operating procedures for sample pretreatment and mass spectrometry detection. Three parallel assays were performed for each sample, and a formal test report was issued by the testing institution to obtain the acylcarnitine concentration information.

[0047] According to the present invention, the preparation of all internal standards in the quantitative detection method includes:

[0048] Take the quality control sample and the derivatization solution, mix them, react them, and obtain the derivatized product. The quality control sample includes the extract of urine quality control sample or DBS quality control sample. The derivatization solution includes acetyl chloride and deuterated ethanol mixed in a ratio of 1:9 (v / v).

[0049] In some specific embodiments, the preparation method uses fully deuterated ethanol as a derivatizing reagent. Specifically, an appropriate amount of the extract of the urine quality control sample or DBS quality control sample prepared above is placed in a centrifuge tube and dried in a freeze dryer.

[0050] The derivatization solution was prepared by mixing acetyl chloride and deuterated ethanol at a ratio of 1:9 (v / v), and was used immediately to ensure reactivity. The dried sample was added to the freshly prepared derivatization solution at a ratio of 1:5 (v / v), vortexed thoroughly for 30 seconds, and then transferred to a 65°C oven for 15 min. Subsequently, the sample was dried at room temperature under nitrogen to remove residual reagents. The resulting derivatized product was sealed and stored at 4°C, avoiding light and repeated freeze-thaw cycles. Before use, it was reconstituted with a 50% acetonitrile aqueous solution to the original volume, yielding the chemical isotope internal standard and the full-spectrum internal standard for acylcarnitine.

[0051] In the quantitative detection method described in this invention, a single concentration of FS IS is used to calculate the sample concentration:

[0052] The concentration of the analyte can be directly obtained by analyzing the peak intensity of acylcarnitine in the corresponding real sample and the acylcarnitine in the full-spectrum internal standard.

[0053] Establish its response factor (RF), which is the ratio of the response of the real analyte to that of the surrogate analyte:

[0054]

[0055] Once the RF is determined, the final analyte (Xs) concentration is calculated using the following formula:

[0056]

[0057] Where X represents concentration, Y represents signal intensity, and the subscripts S and A represent sample and analyte, respectively.

[0058] The RF distribution curves were plotted with the peak intensity of acylcarnitine (d-AC) derived from deuterated ethanol as the x-axis and the peak intensity of acylcarnitine (AC) derived from n-butanol as the y-axis.

[0059] Specifically, solutions containing a mixture of butanol-derived U-QC and fully deuterated ethanol-derived U-QC of equal concentration were tested in three parallel tests. The peak intensity information of the corresponding carnitine was extracted. The RF distribution curve was plotted with the peak intensity of fully deuterated ethanol-derived acylcarnitine (d-AC) as the x-axis and the peak intensity of n-butanol-derived acylcarnitine (AC) as the y-axis.

[0060] The peak intensities of the n-butanol derivative and the fully deuterated ethanol derivative of acylcarnitine showed a good correlation, and their respective RF values ​​could be replaced by the average value to simplify the quantitative calculation process. Furthermore, the data points from the three measurements exhibited good centrality, indicating that the measurement method has high stability and reproducibility. In addition, the slope of the straight line was 1.5948, indicating that the average RF of acylcarnitine on the EALDI platform was 1.5948. Therefore, equation (1-2) can be simplified to:

[0061]

[0062] make:

[0063]

[0064] Then formula (1-3) can be further simplified to:

[0065]

[0066] Where R A / IS This refers to the ratio of the peak intensity or signal-to-noise ratio of the acylcarnitine derived from n-butanol in the mass spectrometer to that of the acylcarnitine in the full-spectrum internal standard of deuterated ethanol.

[0067] And X IS Therefore, in the actual sample testing process, it is only necessary to calculate the R value for each group of acylcarnitines. A / IS The concentration of the acylcarnitine to be tested can be calculated using formula (1-5).

[0068] Quantitative detection of acylcarnitine in clinical samples:

[0069] Derivatization process: Aliquots of urine or DBS extract were transferred to microcentrifuge tubes and mixed with an equal volume of full-spectrum internal standard solution by vortexing. The mixture was evaporated to dryness under a gentle nitrogen flow, and then derivatized by adding freshly prepared n-butanol (the derivatization steps and concentration parameters are the same as those for the derivatization of deuterated ethanol described above, only the deuterated ethanol is replaced with deuterated butanol).

[0070] LDI-MS Detection: The prepared material was cut into 3 mm × 3 mm chips. The chips were then attached to an aluminum target holder using a carbon conductive adhesive. During sampling, 2 μL of liquid was dropped onto the chip surface. The samples were then allowed to air dry under controlled conditions (temperature: 23°C, humidity: 40%) before mass spectrometry analysis. LDI-TOFMS analysis was then performed using a 355 nm Nd:YAG laser combined with an autoflex maX MALDI-TOF / TOF mass spectrometer (Bruker Daltonics 31).

[0071] The laser parameters were set as follows: pulse width: 3 ns, peak power: <170 W, repetition rate: 1000 Hz, laser spot diameter: 100 μm, pulse energy: 3 μL. Relative laser energy is expressed as a percentage of pulse energy, and the measurement mode was set to reflective mode. Other instrument settings included a 200 ns extraction delay, an accelerating voltage of 19.15 kV (ion source 1), and 17.19 kV (ion source 2). Single mass spectra were obtained by randomly sampling a circular region (diameter: 2 mm) from which signals from 2500 laser irradiations were accumulated. The mass spectrometry calibrator solution consisted of AC standards derived from n-butanol. Detection was performed in positive ion mode within the m / z range of 50–500 Da. Each sample was analyzed three times to ensure reproducibility. For compound identification, metabolites were further analyzed by MALDI-TOF-MS / MS.

[0072] The chemical isotope labeling obtained by derivatization with deuterated ethanol—carnitine derived from deuterated ethanol—is preliminarily met the conditions for quantitative analysis. Furthermore, the significant difference in molecular weight between the two derivatives effectively prevents interference from isotope peaks and ion suppression effects. In addition, the molecular ion peak of the deuterated ethanol-derived acylcarnitine is of an even number, while that of the butanol-derived acylcarnitine is of an even number, preventing peak overlap. Finally, the mass numbers obtained from derivatization with deuterated ethanol and n-butanol differ by 22.9999 Da, exhibiting significant distinguishability in mass spectrometry and facilitating rapid preliminary identification of acylcarnitine peaks in complex samples.

[0073] The concentrations of various acylcarnitines in the full-spectrum internal standard solution can be directly determined using clinically established FI-ESI-MS / MS. Because this method isotopically labels all possible acylcarnitines in the sample through derivatization, it offers high coverage. Furthermore, since it uses direct derivatization of clinical quality control samples, it avoids matrix effects. Therefore, this is a novel and high-performance isotopic internal standard preparation method suitable for MALDI-TOF-MS platform analysis of clinical acylcarnitine samples.

[0074] This invention provides a sulfonic acid-modified gold nanoparticle and silicon nanowire composite material (Sulfo-Au-SiNWs) and its preparation method: a silicon nanowire array with high specific surface area is constructed based on metal-assisted chemical etching (MACE); gold nanoparticles (Au NPs) are loaded by in-situ reduction; the functionalization of the surface sulfonic acid groups is achieved by self-assembly modification; the above material is used as a surface-assisted laser desorption / ionization mass spectrometry (SALDI-MS) substrate to enhance the acylcarnitine signal response.

[0075] This invention provides a full-spectrum internal standard method derived from deuterated ethanol / n-butanol and its application in the quantitative analysis of AC class molecules: a series of stable internal standards with a mass difference of 22.9999 Da are generated through derivatization of deuterated ethanol; this strategy avoids peak overlap of natural isotopes and is compatible with acylcarnitine molecules of all carbon chain lengths; combined with a single-point calibration method, it covers multiple orders of magnitude of linear range, achieving high-coverage quantitative detection of acylcarnitine in clinical samples without the need for standards. Attached Figure Description

[0076] Figure 1 The flowchart shows the preparation process of Sulfo-Au-SiNWs.

[0077] Figure 2 SEM and EDS characterization images of Sulfo-Au-SiNWs materials. Figure 2 Images (A, B, C) and (D, E, F) show the surface SEM image and cross-sectional SEM image of the material, respectively. Figure 2 Images (A) and (D) contain enlarged details. Figure 2 In the middle (B) and (E) diagrams, the elemental analysis diagrams of the superimposed EDS are shown. Figure 2 (C) and (F) show the corresponding EDS elemental energy spectra;

[0078] Figure 3 Bar chart showing the optimization of concentration parameters for Sulfo-Au-SiNWs materials;

[0079] Figure 4 Flowchart for the preparation of the full-spectrum internal standard and the quantitative detection of acylcarnitine;

[0080] Figure 5 Full-spectrum internal standard method RF distribution curve;

[0081] Figure 6 This is a mass spectrum of urine quality control samples for quantitative detection of acylcarnitine using the full-spectrum internal standard method;

[0082] Figure 7. Linear correlation fitting diagram of free carnitine and acylcarnitine standards with different chain lengths detected by EALDI-MS combined with FSIS method;

[0083] Figure 8 Linear correlation fitting plot of free carnitine and acylcarnitine standards with different chain lengths added to U-QC was obtained by EALDI-MS combined with FSIS method.

[0084] Figure 9 is a bar chart (A) showing the recovery rates of free carnitine and acylcarnitine standards with different chain lengths (0.3 μg / mL) in water. Figure 9 The bar chart in the middle (B) shows the recovery rates of free carnitine and acylcarnitine standards with different chain lengths (0.3 μg / mL) in urine quality control samples.

[0085] Figure 10. Statistical chart of acylcarnitine subgroup quantitative detection data of U-HC1 (high quality control) samples by EALDI-MS and FI-ESI-MS / MS respectively; (A) Original data table and relative error analysis data table in Figure 10; (B) Bland-Altman test in Figure 10; (C) Passing-Bablok regression analysis in Figure 10.

[0086] Figure 11 Statistical graph of acylcarnitine subgroup quantitative detection data of U-HC2 (intermediate quality control) sample by EALDI-MS and FI-ESI-MS / MS respectively; Figure 11 (A) The original data table and the relative error analysis data table; Figure 11 (B) Bland-Altman test; Figure 11 (C) Passing-Bablok regression analysis;

[0087] Figure 12 Statistical graph of acylcarnitine subgroup quantitative detection data of U-HC3 (low quality control) sample by EALDI-MS and FI-ESI-MS / MS respectively; Figure 12 (A) Original data table and relative error analysis data table; Figure 12 (B) Bland-Altman test; Figure 12 (C) Passing-Bablok regression analysis;

[0088] Figure 13 RSD distribution of acylcarnitine peak intensity in U-QC detected by EALDI-MS platform; Figure 13 (A) and (B) in the figure show the intra-batch and inter-batch RSD distributions without using FS IS, respectively; Figure 13 (C) and (D) in the figure use the intra-batch and inter-batch RSD distributions of FS IS, respectively;

[0089] Figure 14 Stability of acylcarnitine peaks detected on different dates in Sulfo-Au-SiNWs materials. Detailed Implementation

[0090] This invention provides a chip and its preparation method, as well as a method for quantitative detection of acylcarnitine. Those skilled in the art can refer to the content of this document and appropriately modify the process parameters to achieve the same results. It should be particularly noted that all similar substitutions and modifications are obvious to those skilled in the art and fall within the scope of this invention. The methods and applications of this invention have been described through preferred embodiments. Those skilled in the art can clearly modify or appropriately change and combine the methods and applications described herein without departing from the content, spirit, and scope of this invention to implement and apply the technology of this invention.

[0091] It should be understood that the expression “one or more of…” individually includes each of the objects described after the expression, as well as various different combinations of two or more of the described objects, unless otherwise understood from the context and usage. The expression “and / or” combined with three or more described objects should be understood to have the same meaning, unless otherwise understood from the context.

[0092] The terms “including,” “having,” or “containing,” including the use of their grammatical synonyms, should generally be understood as open-ended and non-restrictive, for example, not excluding other unstated elements or steps, unless otherwise specifically stated or understood from the context.

[0093] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural.

[0094] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items.

[0095] It should be understood that the order of the steps or the order in which certain actions are performed is not important as long as the invention remains operational. Furthermore, two or more steps or actions can be performed simultaneously.

[0096] The use of any and all instances or exemplary language such as “e.g.” or “including” in this document is merely intended to better illustrate the invention and is not intended to limit the scope of the invention unless the claims are made. No language in this specification should be construed as indicating that any unclaimed element is essential to the practice of the invention.

[0097] Furthermore, the numerical ranges and parameters used to define the present invention are approximate values, and the relevant values ​​in the specific embodiments have been presented as precisely as possible. However, any value inevitably contains standard deviations due to individual test methods. Therefore, unless explicitly stated otherwise, it should be understood that all ranges, quantities, values, and percentages used in this disclosure are modified with the word "approximately". Here, "approximately" generally means that the actual value is within plus or minus 10%, 5%, 1%, or 0.5% of a specific value or range.

[0098] It should be understood that in the various embodiments of this application, the order of the above processes does not imply the order of execution. Some or all steps may be executed in parallel or sequentially. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0099] The embodiments and comparative examples of this invention describe some examples, in which the embodiments illustrate certain implementations of the invention. However, this does not mean that the effects of the invention can only be achieved in these examples.

[0100] To further illustrate the present invention, the following describes in detail, with reference to embodiments, a chip and its preparation method and a quantitative detection method for acylcarnitine provided by the present invention.

[0101] Example 1

[0102] (1) Preparation process of Sulfo-Au-SiNWs material

[0103] We have developed a novel composite material, Sulfo-Au-SiNWs, and its preparation process is shown in the following flowchart. Figure 1 As shown, the specific steps can be broken down as follows: Figure 1 Flowchart of Sulfo-Au-SiNWs preparation.

[0104] Preparation of silicon nanowires (SiNWs): SiNWs are prepared via a one-step metal-assisted chemical etching (MACE) process. The preparation procedure is as follows: A single-sided polished p-type silicon wafer with a resistivity of 5–10 Ω·cm is cut into 3 cm × 3 cm square wafers using a diamond cutter, with the polished side (front) facing upwards. The wafers are etched for 15 min at room temperature in a plastic petri dish containing 4.8 M HF and 0.02 MAgNO3 solution. (Note: The presence of hydrofluoric acid solution is extremely dangerous; the vapors are highly toxic and can harm the respiratory system. The solution can penetrate the skin and damage bone structure, causing irreversible harm. Strict protective measures are required for the reaction, and the process must be carried out with caution in a fume hood, with careful disposal of waste liquid.) Subsequently, the etched material is washed three times with deionized water and then immersed in a dilute nitric acid solution (concentrated nitric acid:water = 1:1, v / v) for 1 h to remove the Ag elemental produced in the previous step. After the reaction, the material is washed three times with deionized water and dried under nitrogen atmosphere. Subsequently, the above material was immersed in a 2% HF solution for 5 min. After the reaction, the material was washed three times with deionized water and ethanol, respectively, and then dried with nitrogen to obtain SiNWs material. Figure 1 (A)

[0105] Preparation of sulfonic acid-modified gold nanoparticles and silicon nanowire composites (Sulfo-Au-SiNWs): The prepared SiNWs material was immersed in a 2% HF solution and reacted for 5 min. After the reaction, the material was washed three times with deionized water and ethanol, respectively. After drying under nitrogen, it was immersed in an aqueous solution containing HF, HAuCl4, and ethanol (hereinafter referred to as the Au precursor solution) and reacted for 10 min. Then, it was washed three times with deionized water and dried under nitrogen to obtain the Au-SiNWs material. Figure 1 (B) The prepared Au-SiNWs material was immersed in an aqueous solution containing sodium 3-mercaptopropane-sulphonate (MPS) for 10 min, then washed three times with deionized water and dried under nitrogen to obtain Sulfo-Au-SiNWs material. Figure 1 (C). The SEM and EDS characterization analyses of this composite material are as follows: Figure 2 As shown.

[0106] Figure 2 SEM and EDS characterization images of Sulfo-Au-SiNWs materials. Figure 2 Images (A, B, C) and (D, E, F) show the surface SEM image and cross-sectional SEM image of the material, respectively. Figure 2 Images (A) and (D) contain enlarged details. Figure 2In the middle (B) and (E) diagrams, the elemental analysis diagrams of the superimposed EDS are shown. Figure 2 (C) and (F) show the corresponding EDS elemental energy spectra.

[0107] Example 2

[0108] The optimal concentration parameters for material preparation were determined by plotting the signal-to-noise ratio (S / N) histogram of 1 μg / mL carnitine standard solution and Sulfo-Au-SiNWs at 40% laser energy. Based on system optimization, the optimal conditions of 1 mmol / L HAuCl4, 0.004 mol / L HF, and 0.10 mol / L MPS in the gold precursor were identified and used for all subsequent material preparations. Figure 3 Bar chart showing the optimized concentration parameters of Sulfo-Au-SiNWs material. The standard solution was 1 μg / mL carnitine solution, and the laser energy was 40%. Figure 3 In (A), the material detects the signal intensity of the standard solution when using different concentrations of chloroauric acid solution. Figure 3 (B) The signal intensity of the material is measured when different HF solution concentrations are used. Figure 3 (C) The signal intensity of the material for detecting standard solutions when using different MPS concentrations.

[0109] (2) Preparation of full-spectrum internal standard and quantitative detection procedure of acylcarnitine

[0110] Figure 4 Flowchart for the preparation of the full-spectrum internal standard and the quantitative detection of acylcarnitine.

[0111] ① Sample pretreatment methods: The specific pretreatment method for urine is as follows: Dilute the QC sample 25 times with deionized water, centrifuge at 8000 g for 10 min at 4℃, collect the supernatant, aliquot it, and store it in an ultra-low temperature freezer at -80℃ for subsequent analysis. Pretreatment of DBS samples: Prepare circular dried blood spot filter paper with a diameter of 3.2 mm using a punch, add the filter paper to 100 μL of methanol, sonicate for 20 min, shake for 20 min, centrifuge at 10000 g for 10 min, collect the supernatant, dry it under nitrogen, and freeze it in a freezer at -80℃ until use.

[0112] ② Determination of Acylcarnitine Concentration in Quality Control Samples: Urine or DBS quality control samples were subjected to targeted quantitative analysis of acylcarnitine using a detection system approved by the National Medical Products Administration (NMPA) of China (Registration Certificate No.: 20223400429). Specifically, the "Non-Derivatized Amino Acids, Carnitine, Adenosine, Lysophosphatidylcholine and Succinylacetone Assay Kit (Tandem Mass Spectrometry)" manufactured by Suzhou Xinbo Biotechnology Co., Ltd. was used. Detailed information can be found on the NMPA website: https: / / www.nmpa.gov.cn / datasearch / home-index.html#category=ylqx. The experiment employed a flow-through tandem mass spectrometry (FI-MS / MS) platform, strictly adhering to the testing institution's standard operating procedures for sample pretreatment and mass spectrometry detection. Three parallel determinations were performed for each sample, and a formal test report was issued by the testing institution to obtain the acylcarnitine concentration information.

[0113] ③ Preparation of full-spectrum internal standard: The procedure for preparing the acylcarnitine full-spectrum internal standard is as follows. Figure 2 The preparation method used deuterated ethanol as the derivatizing reagent. Specifically, an appropriate amount of the extract from the prepared urine quality control sample or DBS quality control sample was placed in a centrifuge tube and dried in a freeze dryer. The derivatizing solution was prepared by mixing acetyl chloride and deuterated ethanol at a ratio of 1:9 (v / v), and was used immediately to ensure reactivity. The dried sample was added to the freshly prepared derivatizing solution at a ratio of 1:5 (v / v), vortexed thoroughly for 30 seconds, and then transferred to a 65°C oven for 15 min. Subsequently, the sample was dried at room temperature with nitrogen to remove residual reagents. The resulting derivatized product was sealed and stored at 4°C, avoiding light and repeated freeze-thaw cycles. When used, it was reconstituted with a 50% aqueous solution of acetonitrile to obtain the full-spectrum internal standard of acylcarnitine.

[0114] ④ Calculation of the Response Factor for Quantitative Calibration: The quantitative method established in this study uses a single concentration of FS IS to calculate the sample concentration. This single-point internal calibration method directly obtains the analyte concentration by analyzing the peak intensity of acylcarnitine in the corresponding real sample and the acylcarnitine in the full-spectrum internal standard. Therefore, it is necessary to establish its response factor (RF), which is the ratio of the response of the real analyte to that of the surrogate analyte.

[0115]

[0116] Once the RF is determined, the final analyte (Xs) concentration is calculated using the following formula:

[0117]

[0118] Where X represents concentration, Y represents signal intensity, and the subscripts S and A represent sample and analyte, respectively. Accordingly, we detected solutions containing equal concentrations of butanol-derived U-QC and fully deuterated ethanol-derived U-QC in triplicate, extracting the corresponding carnitine peak intensities. RF distribution curves were plotted with the peak intensity of fully deuterated ethanol-derived acylcarnitine (d-AC) on the x-axis and the peak intensity of n-butanol-derived acylcarnitine (AC) on the y-axis. Figure 5 Full-spectrum internal standard method RF distribution curve. For convenience, both the horizontal and vertical axes are displayed on a logarithmic scale with base 10.

[0119] Because the concentration distribution of acylcarnitine is very wide (three orders of magnitude), we used logarithmic coordinates for easier observation. The results are shown in Figure 5. After linear fitting of all points in three tests, we obtained R0. 2 The RF value of 0.9963 indicates a good correlation between the peak intensities of different acylcarnitine n-butanol derivatives and fully deuterated ethanol derivatives. The average RF value can be used to simplify the quantitative calculation process. Furthermore, the data points from the three measurements show good concentration, indicating high stability and reproducibility of the measurement method. The slope of the line is 1.5948, indicating that the average RF of acylcarnitine on the EALDI platform is 1.5948. Therefore, formula (1-2) can be simplified to:

[0120]

[0121] make:

[0122]

[0123] Then formula (1-3) can be further simplified to:

[0124]

[0125] Where R A / IS This refers to the ratio of the peak intensity or signal-to-noise ratio of the acylcarnitine derived from n-butanol in the mass spectrometer to that of the acylcarnitine in the full-spectrum internal standard of deuterated ethanol. X IS Therefore, in the actual sample testing process, it is only necessary to calculate the R value for each group of acylcarnitines. A / IS The concentration of the acylcarnitine to be tested can be calculated using formula (1-5).

[0126] Example 3

[0127] Quantitative detection of acylcarnitine in clinical samples: Derivatization process: Aliquots of urine or DBS extract were transferred to microcentrifuge tubes and mixed with an equal volume of full-spectrum internal standard solution by vortexing. The mixture was evaporated to dryness under a gentle nitrogen flow, and then derivatized by adding freshly prepared n-butanol (the derivatization steps and concentration parameters are the same as those for the derivatization of deuterated ethanol, only replacing deuterated ethanol with deuterated butanol). LDI-MS detection: Before detection and analysis, the prepared material was cut into 3 mm × 3 mm chips. The chips were then attached to an aluminum target holder using a carbon conductive adhesive. During sampling, 2 μL of liquid was dropped onto the chip surface. Then, the sample was allowed to air dry under controlled conditions (temperature: 23°C, humidity: 40%) before mass spectrometry analysis. LDI-TOFMS analysis was then performed using a 355 nm Nd:YAG laser combined with an autoflex maX MALDI-TOF / TOF mass spectrometer (Bruker Daltonics 31). Laser parameters were set as follows: pulse width: 3 ns, peak power: <170 W, repetition rate: 1000 Hz, laser spot diameter: 100 μm, pulse energy: 3 μL. Relative laser energy is expressed as a percentage of pulse energy, and the measurement mode was set to reflective mode. Other instrument settings included a 200 ns extraction delay, an accelerating voltage of 19.15 kV (ion source 1), and 17.19 kV (ion source 2). Single mass spectra were obtained by randomly sampling a circular region (diameter: 2 mm) from which signals from 2500 laser irradiations were accumulated. The mass spectrometry calibrator solution consisted of n-butanol-derived AC standards. Detection was performed in positive ion mode within the m / z range of 50–500 Da. Each sample was analyzed three times to ensure reproducibility. To identify the compounds, the metabolites were further analyzed by MALDI-TOF-MS / MS.

[0128] Figure 6This is a mass spectrum of urine quality control samples for quantitative detection of acylcarnitine using the full-spectrum internal standard method. Two peak clusters appear in the figure. The peak with the smaller m / z belongs to the deuterated ethanol derivative of acylcarnitine, while the peak with the larger m / z belongs to the n-butanol derivative of acylcarnitine. Their signal intensities are on the same order of magnitude, and their peak intensities are similar under the same concentration conditions. This indicates that the chemical isotope label obtained from deuterated ethanol derivatization—the carnitine derived from deuterated ethanol—is preliminarily suitable for quantitative analysis. Secondly, the significant difference in molecular weight between the two derivatives effectively prevents interference from isotope peaks and ion suppression effects. Furthermore, the molecular ion peak of the deuterated ethanol-derived acylcarnitine is of an even number, while that of the butanol-derived acylcarnitine is of an even number, preventing peak overlap. Finally, the mass numbers obtained from derivatization reactions with deuterated ethanol and n-butanol differ by 22.9999 Da, exhibiting significant distinguishability in mass spectrometry and facilitating rapid preliminary identification of acylcarnitine peaks in complex samples. The concentrations of various acylcarnitines in the full-spectrum internal standard solution can be directly determined using clinically established FI-ESI-MS / MS. Because this method isotopically labels all possible acylcarnitines in the sample through derivatization, it offers high coverage. Furthermore, since it uses direct derivatization of clinical quality control samples, it avoids matrix effects. Therefore, this is a novel and high-performance isotopic internal standard preparation method suitable for MALDI-TOF-MS platform analysis of clinical acylcarnitine samples. Figure 6 Mass spectrum of urine quality control samples for quantitative detection of acylcarnitine using the full-spectrum internal standard method.

[0129] Example 4 Detection performance:

[0130] Table 1. Summary of Acylcarnitines Detected by the Platform

[0131]

[0132] The quantitative and stability properties are as follows:

[0133] (1) Evaluation of quantitative detection performance of standard products

[0134] We first selected free carnitine (C0), acetylcarnitine (C2, short-chain acylcarnitine), capryloylcarnitine (C8, medium-chain acylcarnitine), and palmitoylcarnitine (C16, long-chain acylcarnitine) as representative compounds. Standard curves for the standards (Figure 7) and for the urine spiked samples (Figure 8) were established using EALDI-MS combined with FSIS. The experimental results showed that all standard curves exhibited good linearity (R² > 0.99) within the concentration range of 0.02–0.5 μg / mL, and the relative standard deviation (RSD) at each concentration point was less than 15%, indicating that the method has excellent linear range, precision, and quantitative reliability.

[0135] Figure 7. Linear correlation fitting diagram of free carnitine and acylcarnitine standards with different chain lengths detected by EALDI-MS combined with FSIS method. The analytes are (A) carnitine, (B) acetylcarnitine, (C) capryloylcarnitine, and (D) palmitoylcarnitine.

[0136] Furthermore, this study systematically determined the limits of detection (LODs) of free carnitine (C0) and short-chain (C2), medium-chain (C8), and long-chain (C16) acylcarnitines using standard curves established in the U-QC. The calculations showed that the LOD for free carnitine was 0.037 μmol / L, while the LODs for all types of acylcarnitines were below 0.01 μmol / L, specifically 0.0086 μmol / L for acetylcarnitine (C2), 0.0057 μmol / L for capryloylcarnitine (C8), and 0.0095 μmol / L for palmitoylcarnitine (C16). These LOD values ​​are all lower than the physiological concentration range of acylcarnitines in the blood and urine of healthy individuals and the detection limit (0.01 μmol / L) of the FI-ESI-MS / MS method, indicating that this method has sufficient sensitivity for accurate quantitative analysis of acylcarnitines in clinical samples.

[0137] Figure 8 The linear correlation fitting plot of free carnitine and acylcarnitine standards with different chain lengths added to U-QC was determined by EALDI-MS combined with FSIS method. The analytes were (A) carnitine, (B) acetylcarnitine, (C) capryloylcarnitine, and (D) palmitoylcarnitine.

[0138] Subsequently, we conducted spiked recovery experiments on acylcarnitine standards in water and U-QC. As shown in Figure 9, when 0.3 μg / mL of free carnitine and various acylcarnitine standards were added to the aqueous matrix and urine quality control samples, respectively, the spiked recoveries remained stably within the ideal range of 96.0%–112.0%. This result confirms that the detection method established in this study has excellent quantitative analytical capabilities for acylcarnitine.

[0139] Figure 9 is a bar chart (A) showing the recovery rates of free carnitine and acylcarnitine standards with different chain lengths (0.3 μg / mL) in water. Figure 9 The middle (B) is a bar chart showing the recovery rates of free carnitine and acylcarnitine standards with different chain lengths (0.3 μg / mL) in urine quality control samples;

[0140] (2) Performance evaluation of quantitative detection of healthy urine samples

[0141] Finally, we used the developed EALDI-MS platform-based method combined with FS IS for the quantitative detection of acyl groups in three real urine samples: U-HC1, U-HC2, and U-HC3.

[0142] Figure 10. Statistical chart of acylcarnitine subgroup quantitative detection data of U-HC1 (high quality control) samples by EALDI-MS and FI-ESI-MS / MS respectively; (A) Original data table and relative error analysis data table in Figure 10; (B) Bland-Altman test in Figure 10; (C) Passing-Bablok regression analysis in Figure 10.

[0143] The quantitative results were compared with the absolute concentration of acylcarnitine in the test report obtained by the Department of Genetics and Metabolism of the Children's Hospital Affiliated to Zhejiang University School of Medicine using the FI-ESI-MS / MS method to evaluate the quantitative accuracy and consistency of the method.

[0144] Based on the acylcarnitine concentration reports of the three samples U-HC1, U-HC2, and U-HC3 obtained by FI-ESI-MS / MS, it was found that only 25 acylcarnitines could be detected. According to the average concentration, sample U-HC1 had the highest concentration, U-HC2 had a medium concentration, and U-HC3 had the lowest concentration; therefore, they were designated as high controls, medium controls, and low controls, respectively.

[0145] We compared the concentrations of acylcarnitine detected by the EALDI-MS platform with those detected by the FI-ESI-MS / MS method, calculated the relative error, and performed Bland-Altman test and Passing-Bablok regression analysis using MedCalc software. The data analysis results for the three samples U-HC1, U-HC2, and U-HC3 are shown in Figures 10, 11, and 12, respectively.

[0146] Figure 11 Statistical graph of acylcarnitine subgroup quantitative detection data of U-HC2 (intermediate quality control) sample by EALDI-MS and FI-ESI-MS / MS respectively; Figure 11 (A) The original data table and the relative error analysis data table; Figure 11 (B) Bland-Altman test; Figure 11 (C) Passing-Bablok regression analysis;

[0147] Figure 12 Statistical graph of acylcarnitine subgroup quantitative detection data of U-HC3 (low quality control) sample by EALDI-MS and FI-ESI-MS / MS respectively; Figure 12(A) Original data table and relative error analysis data table; Figure 12 (B) Bland-Altman test; Figure 12 (C) Passing-Bablok regression analysis;

[0148] The results showed that, regardless of whether it was a high-quality control, medium-quality control, or low-quality control, the relative errors in the concentrations of acylcarnitine detected by the two methods were mostly controlled within 25%, except for a few species with extremely low abundance. Furthermore, the Bland-Altman test showed that, except for one acylcarnitine in the high-quality control and low-quality control samples that showed an abnormality, the signal differences for all other acylcarnitines were distributed within the 95% confidence interval (± 1.96σ). This result indicates a high degree of consistency between the two detection methods. Simultaneously, Passing-Bablok regression analysis showed that the acylcarnitine data detected by the high-quality control, medium-quality control, and low-quality control samples using the two mass spectrometry platforms were all distributed within the 95% confidence interval, with Spearman correlation coefficients (ρ) reaching 0.981, 0.984, and 0.987, respectively (P < 0.0001), confirming a high degree of statistical consistency and significant correlation between the two analytical methods.

[0149] 3.3.4 Methodological Stability Testing

[0150] When applied to large-scale clinical testing, the stability and reproducibility of acylcarnitine assays are crucial, as they directly affect the reliability of test results and the accuracy of clinical diagnosis.

[0151] To further verify the stability of the testing platform, the study used triple-replica experiments to systematically test U-QC samples and evaluated the consistency between in-batch and inter-batch samples.

[0152] Statistical analysis of the relative standard deviations of the different acylcarnitine peaks extracted (Figure 13, C, D) specifically shows that the FSIS method for quantitative detection of acylcarnitine subgroups in urine meets the clinical standard requirement of less than 20% in both intra-assay precision (median RSD = 10.3%) and inter-assay reproducibility (median RSD = 12.2%). Furthermore, comparison with the method without FSIS (Figure 13, A, B) reveals that the addition of an internal standard simultaneously reduces the RSD of the detection signal. For intra-assay stability, the addition of an internal standard reduces the median RSD from 12.3% to 10.3%. For inter-assay stability, the effect of the internal standard is even more significant, reducing the median RSD from 20.68% to 12.2%. Therefore, full-spectrum internal standard quantification is crucial for achieving inter-assay stability.

[0153] Figure 13 RSD distribution of acylcarnitine peak intensity in U-QC detected by EALDI-MS platform; Figure 13 (A) and (B) in the figure show the intra-batch and inter-batch RSD distributions without using FS IS, respectively; Figure 13 (C) and (D) in the figure use the intra-batch and inter-batch RSD distributions of FS IS, respectively;

[0154] Finally, to comprehensively examine the long-term stability of the material, we conducted long-term storage stability tests on the prepared Sulfo-Au-SiNWs material under strictly controlled conditions (sealed, light-proof, and dry environment). The stability of the material was assessed by periodically detecting changes in the acylcarnitine content in urine quality control samples (U-QC). We prepared a sufficient quantity of Sulfo-Au-SiNWs material at once, aliquoted into different components, and performed acylcarnitine subgroup quantitative detection on U-QC on days 1 (prepared and used immediately), 7, 14, and 30. The acylcarnitine peaks were compared with the signal on day 1, and the logarithm of the signal ratio (base 2) was calculated and plotted as a box plot. As shown in Figure 14, even after a storage period of up to one month, the material maintained stable surface-enhanced laser desorption / ionization performance, and its detection sensitivity, specificity, and repeatability did not show significant attenuation. These data strongly demonstrate that the EALDI-MS detection platform based on Sulfo-Au-SiNWs materials has excellent long-term stability and clinical application potential. Figure 14 Stability of acylcarnitine peaks detected on different dates in Sulfo-Au-SiNWs materials.

[0155] 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. A method for quantitative detection of acylcarnitine, characterized in that, A chip for the quantitative detection of acylcarnitine in high-coverage, high-sensitivity clinical samples is used; the method for preparing the chip for the quantitative detection of acylcarnitine in high-coverage, high-sensitivity clinical samples includes: A) Preparation of silicon nanowire materials; B) The prepared silicon nanowire material was reacted with hydrofluoric acid solution, then washed, dried, and immersed in an aqueous solution containing HF, HAuCl4 and ethanol to react and obtain Au-SiNWs material. C) The prepared Au-SiNWs material was immersed in an aqueous solution containing sodium 3-mercaptopropanesulfonate and reacted to obtain Sulfo-Au-SiNWs material; S1) Quantitative detection of acylcarnitine concentration in quality control samples after pretreatment: S2) Preparation of full-spectrum internal standard: The quality control sample and the derivatization solution were mixed and reacted to obtain the derivatized product; the derivatization solution consisted of acetyl chloride and deuterated ethanol mixed at a ratio of 1:9 v / v. The quality control samples include extracts of urine quality control samples or DBS quality control samples; S3) Calculation of the response factor for quantitative calibration: In quantitative detection methods, the sample concentration is calculated using a single concentration of FS IS. The concentration of the analyte can be directly obtained by analyzing the peak intensity of acylcarnitine in the corresponding real sample and the acylcarnitine in the full-spectrum internal standard. Establish its response factor RF, which is the ratio of the response of the real analyte to that of the substitute analyte: 1-1 After determining the RF, the final formula for calculating the concentration of analyte Xs is: 1-2 Where X represents concentration and Y represents signal strength. S4) Quantitative detection of acylcarnitine in the sample: LDI-MS detection was performed after derivatization. The sample to be tested and the derivatized solution are mixed and reacted to obtain the test solution, which is then dropped onto the chip surface and detected by LDI-MS. The concentration of acylcarnitine in the sample to be tested can be calculated by formula 1-2.

2. The detection method according to claim 1, characterized in that, Step A) The preparation of the silicon nanowire material specifically includes: a) p-type silicon wafers are cut into small silicon wafers with the polished side facing up, and etched in a plastic petri dish containing HF and AgNO3 solutions to obtain the etched material; b) The etched material is washed and then immersed in a dilute nitric acid solution; after the reaction, it is washed and dried under nitrogen conditions; c) The above materials are immersed in HF solution for reaction. After the reaction is completed, the materials are washed and dried with nitrogen to obtain SiNWs materials.

3. The detection method according to claim 1, characterized in that, Step B) The concentration of the hydrofluoric acid solution is 2%; the reaction time is 5 min; the washing is performed with deionized water and ethanol, and the number of washings is 2-3 times; the drying is performed with nitrogen. The aqueous solution containing HF, HAuCl4 and ethanol has a concentration of 4 mmol / L, a concentration of 1 mmol / L for HAuCl4, and a volume fraction of 30% for ethanol. The reaction time is 10 min.

4. The detection method according to claim 1, characterized in that, In step C), the concentration of sodium mercaptopropanesulfonate in the aqueous solution containing sodium 3-mercaptopropanesulfonate is 0.1 mol / L, and the reaction time is 10 min.

5. The detection method according to claim 1, characterized in that, In the quantitative detection method, the quality control samples include urine and DBS samples; The urine pretreatment includes: dilution with deionized water, centrifugation, collection of supernatant, aliquoting and storage at low temperature for subsequent analysis; Pretreatment of DBS samples: Prepare circular dried blood spot filter paper, add the filter paper to methanol, sonicate, shake, centrifuge, take the supernatant, dry it under nitrogen, and freeze until use.

6. The detection method according to claim 1, characterized in that, The RF distribution curves were plotted with the peak intensity of acylcarnitine derived from deuterated ethanol as the x-axis and the peak intensity of acylcarnitine derived from n-butanol as the y-axis.

7. A chip for quantitative detection of acylcarnitine in clinical samples with high coverage and high sensitivity, prepared by the method of claim 1.

8. The application of the chip according to claim 7 as a surface-assisted laser desorption / ionization mass spectrometry substrate in enhancing the signal response of acylcarnitine.

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