Computer-implemented method for detecting at least one analyte in sample using laser desorption mass spectrometer

Abstract

A computer-implemented method for detecting at least one analyte in a sample with a laser desorption mass spectrometer (220) is disclosed. The method comprises: a) at least one imaging step comprising imaging at least one reflective target (128) by using at least one imaging device (235) wherein the sample comprising the at least one analyte is applied to the reflective target (128); b) at least one sample identification step comprising positioning at least one sample region on the reflective target (128); and c) at least one analyte detection step comprising detecting the at least one analyte in the sample using surface assisted laser desorption ionization mass spectrometry (SALDI-MS) with the laser desorption mass spectrometer (220) wherein laser radiation is applied to the reflective target (128) using at least one laser source (222) of the laser desorption mass spectrometer (220), the laser desorption mass spectrometer (220) is configured such that at least one ion of the at least one analyte is generated, the at least one ion being detected by using at least one of a mass analysis unit (224) or an ion mobility spectrometry device of the laser desorption mass spectrometer (220), wherein the laser radiation is directed on the positioned sample region by using at least one control device (237).

Description

Technical Field

[0001] The present invention relates to a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer, including a system having at least one laser desorption mass spectrometer and a computer program. The method and apparatus can be applied to measure the mass of an analyte or the mass of a fragment of an analyte for the purpose of identifying the analyte and quantitatively determining the analyte. Specifically, the apparatus and method can be applied to the quantitative analysis of biomolecules such as proteins, peptides, oligonucleotides, and small molecule compounds. However, other applications are also feasible. Background Art

[0002] Matrix-assisted laser desorption / ionization (MALDI) mass spectrometry is an ionization technique that combines small organic matrix molecules that absorb radiation with the corresponding target analytes. Since the ionization process itself is often gentle, it is now a well-established analytical method, especially for the analysis of biomolecules such as proteins or peptides.

[0003] A variant of this technique is the surface-assisted laser desorption ionization (SALDI) process. Compared with MALDI-MS, no further organic matrix material is mixed in excess with the target analyte. Instead, a functional solid surface is used for desorbing and ionizing the analyte. Depending on the element composition, most of the reported functional SALDI materials in the literature can generally be classified into three main types: carbon-based, semiconductor-based, and metal-based. A review of surface-assisted laser desorption ionization for mass spectrometry analysis is provided in G. Eppe, Surface-assisted laser desorption / ionization mass spectrometry imaging: A review, Mass Spec Rev. 2022; 41:373–420 (DOI: 10.1002 / mas.21670).

[0004] In principle, the goal of SALDI is to input the mass-to-charge ratio m / z of small molecules, especially small molecules with a molar mass less than 1000 Da. Traditional MALDI methods usually hide or suppress such molecules through interference signals from the matrix. In addition, SALDI is usually advantageous to avoid certain matrix application processing steps. Generally, if quantitative accuracy is required, the co-crystallization process with the analyte may cause problems.

[0005] Classical MALDI methods that aim to perform controlled detection and laser irradiation of perfect matrix-analyte-crystals to generate optimal MALDI-MS spectra have been demonstrated. For a descriptive work in the field of MALDI-MS, the following literature can be referred to:

[0006] JP5504282B2 describes a MALDI mass analysis method by which a high-quality MS spectrum can be effectively obtained in a short period of time by accurately predicting a sweet spot where a large number of ions are generated. A sweet spot prediction method is described, in which a mixed crystal of a matrix and a sample containing a molecule to be measured is separated, and then local analysis of the mixed crystal is performed using an analysis method other than mass spectrometry. Thereafter, MALDI mass analysis is performed to predetermine the analysis results of portions in the mixed crystal that will and / or will not become sweet spots. Next, the mixed crystal of the matrix and the sample containing the molecule to be measured is separated, and then local analysis of the mixed crystal is performed using the analysis method other than mass spectrometry. A portion of the mixed crystal showing the analysis results of becoming and / or not becoming a sweet spot is detected, and a prediction is made as to whether or not this portion is a sweet spot. A MALDI mass analysis method using the sweet spot prediction method is also described.

[0007] US7359574B2 describes a mass spectrometer that uses image processing of the output signal of a camera in the mass spectrometer to provide feedback for guiding a laser. Determining the actual position where a sample is deposited on a plate during a cycle period of the mass spectrometer and selecting different points for aiming the laser for each sample according to the structure of each sample are described. Such feedback information increases the likelihood that the laser hits the sample and provides useful data.

[0008] WO2006116166A2 describes a method and apparatus for image analysis of a sample target area on a MALDI sample plate to select a laser impact position for optimal mass spectrometry acquisition. An image of the target area is captured and analyzed to determine the incident distribution of image element values (representing luminance and / or chrominance information). A dynamic threshold can be determined by constructing a virtual histogram and then identifying the value at which a local minimum occurs between the modes of a bimodal distribution. The threshold is applied to the image elements to locate regions within the target area having desired visual characteristics, such as high luminance indicating a crystalline structure. Mass spectrometry acquisition can be optimized by directing the laser beam to hit only those regions having the required visual characteristics. By coupling the image analysis process with an automatic spectrum filtering technique, the performance of the mass spectrometer can be further improved, whereby the laser beam is selectively held at or moved away from the area of a sample spot based on whether the resulting mass spectrum meets a predetermined performance criterion.

[0009] US6956208B2 describes a MALDI mass spectrometer that directs a laser emission onto a MALDI sample to generate a sample spectrum, analyzes the sample spectrum to determine whether the sample spectrum meets a predetermined criterion. If so, subsequent laser emissions are directed to a predetermined location on the MALDI sample. Substantially, if the analysis of a previous laser emission indicates that the "sweet spot" of the MALDI sample has been located, subsequent laser emissions can be directed to an area adjacent to the previous emission, thereby allowing thorough sampling of the sweet spot. Methods of operating the MALDI mass spectrometer are also described.

[0010] Despite the advantages of the above-described apparatus, there are still several technical challenges.

[0011] Quantitative methods using SALDI are generally highly regarded because of its potential for ultrafast analysis times to obtain spectra of dried spots of analytes on a SALDI target. So far, there is no known algorithm that directs laser stimulation only onto the dried spots of a corresponding SALDI target. Generally, after identifying the spots, dedicated laser stimulation can be performed while excluding the stimulation of blank spot areas. In the absence of automatic identification, there is usually a rather long acquisition time resulting from running a pre-programmed laser path.

[0012] Problems to be Solved

[0013] Accordingly, it is desirable to provide a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer, a system comprising at least one laser desorption mass spectrometer, and a computer program that at least partially address the above technical challenges. Specifically, rapid measurement of analyte spots should be provided. Summary of the Invention

[0014] This problem is solved by a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer, a system comprising at least one laser desorption mass spectrometer, and a computer program having the features of the independent claims. Advantageous embodiments that can be implemented individually or in any combination are listed in the dependent claims and throughout the specification.

[0015] As used herein, the terms "having", "including", or "comprising" or any grammatical variations thereof are used in a non-exclusive manner. Thus, these terms can either refer to a situation where no other features are present in the entity described in this context except for the features introduced by these terms, or to a situation where one or more other features are present. As an example, the statements "A has B", "A includes B", and "A comprises B" can either refer to a situation where no other elements are present in A except for B (i.e., a situation where A consists of B alone and uniquely); or to a situation where one or more other elements (such as element C, elements C and D, or even other elements) are also present in entity A in addition to B.

[0016] Further, it should be noted that the terms "at least one", "one or more", or similar expressions indicating that a feature or element may be present once or more than once are generally used only once when introducing the corresponding feature or element. Hereinafter, in most cases, when referring to the corresponding feature or element, although the corresponding feature or element may be present only once or multiple times, the expressions "at least one" or "one or more" will not be reused.

[0017] Further, as used herein, the terms "preferably", "more preferably", "particularly", "more particularly", "specifically", "more specifically", or similar terms are used in conjunction with optional features without restricting the possibilities of alternatives. Thus, the features introduced by these terms are optional features and are not intended to limit the scope of the claims in any way. As those skilled in the art will recognize, the present invention can be implemented by using alternative features. Similarly, the features introduced by "in one embodiment of the present invention" or similar expressions are intended to be optional features, without any limitation to alternative embodiments of the present invention, without any limitation to the scope of the present invention, and without any limitation to the possibility of combining the features introduced in this way with other optional or non-optional features of the present invention.

[0018] In a first aspect of the present invention, a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer is disclosed.

[0019] The method includes the following steps, which can be specifically performed in a given order. However, it should be noted that different orders are also possible. Further, one or more method steps can also be performed once or repeatedly. Further, two or more method steps can be performed simultaneously or in a timely overlapping manner. The method can include other method steps not listed.

[0020] The method includes the following steps:

[0021] a) At least one imaging step, including imaging at least one reflective target by using at least one imaging device, wherein a sample containing at least one analyte is applied to the reflective target;

[0022] b) At least one sample identification step, which includes positioning at least one sample area on the reflective target; and

[0023] c) At least one analyte detection step, which includes using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) with a laser desorption mass spectrometer to detect at least one analyte in the sample, wherein laser irradiation is applied to the reflective target by using at least one laser source of the laser desorption mass spectrometer, such that at least one ion of at least one analyte is generated, and the at least one ion is detected by using at least one of a mass analysis unit or an ion mobility spectrometry device of the laser desorption mass spectrometer, wherein the laser irradiation is guided onto the positioned sample area by using at least one control device.

[0024] As used herein, the term "computer-implemented" is a broad term and should be given its ordinary and customary meaning to a person of ordinary skill in the art and should not be limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, a method involving at least one computer and / or at least one computer network. The computer and / or computer network can include at least one processor configured to perform at least one of the method steps of the method according to the present invention. Preferably, each method step is performed by the computer and / or computer network. The method can be performed completely automatically (such as, without user interaction). As used herein, the term "automatically" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, a process performed entirely by means of at least one computer and / or at least one computer network and / or at least one machine, in particular, without manual operation and / or interaction with the user.

[0025] A computer-implemented method for detecting at least one analyte in a sample by using a laser desorption mass spectrometer can be performed at least partially automatically. Specifically, at least one of steps a) and c) can be performed automatically.

[0026] A computer-implemented method for detecting at least one analyte in a sample by using a laser desorption mass spectrometer can be performed completely automatically (specifically from sample preparation to the analyte detection step). Specifically, at least steps a), b), and c) can be performed automatically. As will be further outlined in detail below, the computer-implemented method for detecting at least one analyte can further include at least one sample preparation step. The sample preparation step can also be performed at least partially or completely automatically.

[0027] This method can be carried out completely automatically. Steps a) to c), for example, and further optional method steps can be carried out completely automatically. Steps a) and b) (such as image processing and image recognition) can be carried out completely automatically. The system (such as the system proposed in another aspect of this article) can carry out this method completely automatically. The system can be configured to carry out this method completely automatically, starting from sample preparation to the detection of analytes using SALDI-MS. Automatically carrying out this method can allow for an increase in sample throughput.

[0028] As used herein, the term "sample" is a broad term and is given the ordinary and customary meaning to those of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, this term can refer to, but is not limited to, any sample, for example, a biological sample (also referred to as a test sample), a quality control sample, an internal standard sample. The sample can include one or more relevant analytes. The sample can specifically be a liquid sample, especially a liquid sample comprising at least one biological material. In addition, the analyte can be provided in the sample, specifically in a tissue sample or in a processed serum sample. Specifically, the tissue sample can have a section thickness of less than 500 μm. For example, the sample can be selected from the group consisting of: physiological fluids, including blood, serum, plasma, saliva, aqueous humor, cerebrospinal fluid, sweat, urine, milk, ascites, mucus, synovial fluid, peritoneal fluid, amniotic fluid, tissue, cells, etc. The sample can be used directly when obtained from the corresponding source, or can be subjected to a pretreatment and / or sample preparation workflow. For example, the sample can be pretreated by adding an internal standard and / or by diluting with another solution and / or by mixing with reagents, etc. The quality control sample can be a mock test sample and include a sample of one or more quality control substances with known values. The quality control substance can be the same as the target analyte, or can be an analyte generated by the reaction or derivatization of an analyte identical to the target analyte, and / or can be an analyte with a known concentration, and / or can be a substance that mimics the target analyte or is otherwise related to a certain target analyte. The internal standard sample can be a sample comprising at least one internal standard substance with a known concentration.

[0029] As used herein, the term "analyte" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, any chemical or biological substance or species to be detected and / or measured, such as a molecule or chemical compound. Specifically, the presence, absence, concentration, and / or amount of an analyte in a sample can be detected or measured. Specifically, the analyte can be a biomolecule or macromolecule. The analyte is selected from the group consisting of: steroids; specifically ketosteroids, specifically secosteroids (such as vitamin D); therapeutically active substances; detergents; glycosides; peptides; proteins; dyes; ions; nucleic acids; amino acids; metabolites; hormones; fatty acids; lipids; carbohydrates. In addition, the analyte can be a modified molecular feature of another molecule or a substance internalized in an organism or a metabolite of such a substance or a combination thereof. However, other species of analytes are also feasible. The steroids can be selected from the group consisting of: progesterone, testosterone, estradiol, androstenedione, cortisol, cortisone, 21-deoxycortisol. However, other steroids are also feasible. The therapeutically active substances can be selected from the group consisting of: digitoxin, mycophenolic acid, theophylline, lidocaine, digoxin, voriconazole, 4-hydroxyalprazolam, cyclosporine A. However, other therapeutically active substances can also be feasible. The analyte can include permanently positively charged molecules or permanently negatively charged molecules. In addition, the analyte can have an isotopic pattern. The analyte can have a molar mass of 6 daltons to 10,000 daltons (preferably 50 daltons to 3,000 daltons, most preferably 100 daltons to 2,000 daltons). However, in principle, all types of analytes that can be applied to the reflector target are feasible.

[0030] As used herein, the term "mass spectrometer" is a broad term and will be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, any analytical device configured to determine or measure the mass-to-charge ratio of ions. The measurement results can specifically be presented as a mass spectrum, for example, a plot of intensity versus mass-to-charge ratio.

[0031] As used herein, the term "laser desorption mass spectrometer" is a broad term and will be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, any mass spectrometer based on a laser-based ionization technique. Specifically, the term can refer to a mass spectrometer that uses a medium and a laser to desorb and ionize a sample or a portion of the sample. Specifically, the medium can absorb energy from the laser and then can transfer the energy to the sample or a portion thereof. The ionization technique can also be referred to as a soft ionization technique. The laser desorption mass spectrometer can specifically be configured for surface-assisted laser desorption / ionization (SALDI) techniques. SALDI techniques can include at least three different stages. In the first stage, a sample can be applied to a target. In the second stage, a laser pulse of a laser can be applied to the target, and the target can absorb the laser energy and transfer the laser energy to the molecules of the sample. In the third stage, desorption and ionization can occur, and a potential difference can accelerate the generated ions into a mass analyzer. Laser desorption mass spectrometry can include the process of analyzing a sample by using a laser desorption mass spectrometer. Detection can specifically refer to the identification of an analyte of a sample. The detection can be qualitative and / or quantitative detection.

[0032] As outlined above, step a) corresponds to at least one imaging step, which includes imaging at least one reflective target by using at least one imaging device, wherein a sample containing at least one analyte is applied to the reflective target.

[0033] As used herein, the term "imaging step" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, a method step that includes at least one imaging process. As used herein, the term "imaging" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, providing a two-dimensional or three-dimensional representation of a reflective target. Imaging can include recording or capturing one or more of optical information (e.g., spatially resolved two-dimensional or even three-dimensional optical information). Imaging can include generating at least one image of a reflective target. As used herein, the term "image" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, data recorded by using an imaging device, such as multiple electronic readings from an imaging device, such as pixels of a camera chip.

[0034] As used herein, the term "imaging device" is a broad term and shall be given its ordinary and customary meaning to a person of ordinary skill in the art, and shall not be limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, a device having at least one imaging element configured to record or capture spatially resolved one-dimensional, two-dimensional or even three-dimensional optical information. The imaging device can be at least one device selected from the group consisting of: at least one camera, at least one CCD camera, at least one CMOS camera, at least one RGB camera, at least one digital camera, at least one camera of a microscope, at least one camera of a reflection microscope. The imaging device generally can include an image sensor such as a one-dimensional or two-dimensional array of pixels. In addition to at least one camera chip or imaging chip, the imaging device can also include other elements, such as one or more optical elements, for example one or more lenses. As an example, the imaging device can be a fixed-focus camera having at least one lens adjusted fixedly relative to the camera. However, alternatively, the imaging device can also include one or more variable lenses that can be adjusted automatically or manually.

[0035] The method can include loading a reflection target into a laser desorption mass spectrometer. The imaging step can be performed before and / or after loading the reflection target into the laser desorption mass spectrometer.

[0036] The term "target" as used herein is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, any article, device or element exposed to or exposable to a light beam (especially a laser beam). As an example, the target can be configured as a solid target having a predetermined shape, such as a flat target surface and (for example) a flat target disk or wafer having a circular, elliptical or polygonal shape. Specifically, the target can be exposed to or exposable to the laser beam of a laser of a mass spectrometer (especially a laser desorption mass spectrometer). The target can specifically be a reusable target. The term "reusable target" as used herein is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, any target that can be configured for multiple uses. As will be outlined in further detail below, the preparation of the last sample for analysis in a laser desorption mass spectrometer can include applying at least one sample to the target. After performing at least one measurement, the target can be cleaned, especially the surface of the target (for example, the sample may be removed). Thereafter, another sample can be applied to the target and further measurements can be performed.

[0037] As used herein, the term "reflective target" is a broad term and is given the ordinary and customary meaning to those of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, this term can refer to, but is not limited to, any target having at least one reflective interface, specifically at least one reflective surface. The reflective interface or reflective surface can be configured to change the direction of a wavefront between two different media such that the wavefront returns to the medium from which it originated. Reflection can specifically refer to the reflection of light. The reflective target can have a specular reflection of ≥ 45%. Specular reflection can refer to the reflection phenomenon of parallel light beams falling on a surface at equal angles. Specular reflection generally follows all three laws of reflection, i.e., the angle of reflection is equal to the angle of incidence, and the normal beam, incident beam, and reflected beam are all in the same plane. The incident ray and the reflected beam are on the other side of the normal beam.

[0038] Specifically, the reflective target can have a smooth surface. The reflective target (specifically the surface of the reflective target) can specifically have an R a nominal arithmetic roughness of ≤ 2 μm.

[0039] Specifically, the thickness of the reflective target can be from 0.2 mm to 1 cm, preferably from 0.5 mm to 3 mm. In addition, the thickness of the reflective target can be less than 1 cm, preferably less than 3 mm. However, other dimensions may also be feasible.

[0040] Below, examples of reflective targets are described. However, other types of reflective targets may also be feasible, such as different types of materials and / or coatings for the reflective target.

[0041] The reflective target can have at least one surface. The surface can be at least partially covered with at least one layer. The layer can be a hydrogen-containing, silicon-doped amorphous carbon (a-C:H:Si) layer. The a-C:H:Si layer can include:

[0042] ● 40 at.% to 80 at.% carbon;

[0043] ● 1 at.% to 20 at.% hydrogen; and

[0044] ● 10 at.% to 40 at.% silicon.

[0045] The sum of carbon, hydrogen, and silicon can be at most 100%, specifically 100%. However, the a-C:H:Si layer can also include additional elements. Therefore, the sum of carbon, hydrogen, and silicon can be less than 100%. Specifically, the sum of carbon, hydrogen, and silicon can be at least 51%, specifically at least 55%, specifically at least 60%, specifically at least 65%, specifically at least 70%, specifically at least 75%, specifically at least 80%, specifically at least 85%, specifically at least 90%, specifically at least 95%, specifically at least 98%.

[0046] As used herein, the term "surface" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, the entire area that externally delimits any object. Thus, a body can have multiple surfaces. As used herein, the term "layer" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, the amount of material deposited on the surface of any element. A layer can specifically be a coating. A layer can completely cover an object or can cover only one or more portions of an object. A layer can specifically have a lateral extent that is at least 2 times, at least 5 times, at least 10 times, or even at least 20 times or greater than its thickness. Specifically, the thickness of an a-C:H:Si layer can be from 100 nm to 10 nm, preferably from 500 nm to 1.5 μm. However, other dimensions are also possible.

[0047] As used herein, the term "at least partially covers" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, the property of any element that is completely or partially covered by something. Specifically, the surface of any element can be completely or partially covered by something. In the case where the surface is partially covered by something, the covered surface can also be referred to as a surface section. As further used herein, the term "surface section" can refer to a part of a surface, specifically different parts of a surface. Exemplarily, the term surface section can refer to at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95% of a representative surface. However, other embodiments may also be possible. The layer can specifically form a continuous layer covering a surface section or even the entire surface of a reflective target (specifically the substrate of the reflective target).

[0048] As used herein, the term "hydrogen-containing, silicon-doped amorphous carbon (a-C:H:Si) layer" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, an amorphous carbon layer containing hydrogen and silicon. Specifically, hydrogen and / or silicon can be embedded or dispersed in the carbon layer but are not covalently bonded to carbon. An a-C:H:Si layer can specifically be a diamond-like carbon layer doped with amorphous silicon. Diamond-like carbon doped with amorphous silicon can have structural, mechanical, electrical, optical, chemical, and / or acoustic properties similar to diamond. Specifically, diamond-like carbon doped with amorphous silicon can be a layer including sp 3Metastable forms of amorphous carbon with hybridized carbon atoms. More specifically, in diamond-like carbon doped with amorphous silicon, carbon can exist in three hybridizations: sp 3 、sp 2 and sp 1 . The physical properties of diamond-like carbon doped with amorphous silicon as described above can stem from its mixture of carbon bonds. Specifically, the sp 3 hybridization in diamond may have strong σ bonds, which may result in high mechanical hardness and chemical inertness. The sp 2 hybridization in graphite may have strong in-plane σ bonds and weak interlayer van der Waals bonds. The physical properties can specifically depend on the ratio of sp 2 bonds to sp 3 bonds.

[0049] The a-C:H:Si layer can specifically be a hydrogen-containing, heteroatom-modified, silicon-doped amorphous carbon (a-C:H:Si:X) layer. The heteroatom X can be selected from the group consisting of oxygen, nitrogen, fluorine, and boron, and the a-C:H:Si:X layer can further include:

[0050] · Up to 15 at. % oxygen;

[0051] · Up to 10 at. % nitrogen;

[0052] · Up to 10 at. % boron; and

[0053] · Up to 5 at. % fluorine;

[0054] The sum of oxygen, nitrogen, fluorine, and boron can be at least 1 at. %, specifically at least 1.5 at. %, specifically at least 2 at. %.

[0055] The sum of carbon, hydrogen, silicon, oxygen, nitrogen, fluorine, and boron can specifically be 100 at.%. However, the a-C:H:Si:X layer can also include additional elements. Thus, the sum of carbon, hydrogen, silicon, oxygen, nitrogen, fluorine, and boron can specifically be less than 100 at.%. Thus, the sum of carbon, hydrogen, silicon, oxygen, nitrogen, fluorine, and boron can be at least 52 at.%, specifically at least 55 at.%, specifically at least 60 at.%, specifically at least 65 at.%, specifically at least 70 at.%, specifically at least 75 at.%, specifically at least 80 at.%, specifically at least 85 at.%, specifically at least 90 at.%, specifically at least 95 at.%, specifically at least 98 at.%. Other heteroatoms are also feasible. The heteroatoms can specifically be selected from the group consisting of: metalloids, specifically germanium, specifically antimony, specifically selenium, specifically tellurium; post-transition metals, specifically aluminum; transition metals, specifically titanium, specifically vanadium, specifically niobium, specifically tantalum, specifically chromium, specifically molybdenum, specifically tungsten, specifically iron, specifically cobalt, specifically copper, specifically silver; non-metals, specifically phosphorus, specifically sulfur, specifically chlorine, specifically bromine, specifically iodine.

[0056] As used herein, the term "hydrogen-containing, silicon-incorporated, heteroatom-modified amorphous carbon (a-C:H:Si:X) layer" is a broad term and is given the ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. This term can specifically refer to, but is not limited to, an amorphous carbon layer that contains hydrogen and silicon and further contains one or more heteroatoms in addition to hydrogen and silicon. Specifically, hydrogen, silicon, and the heteroatoms can be embedded or dispersed in the carbon layer but are not covalently bonded to carbon. The a-C:H:Si:X layer can specifically be an amorphous heteroatom-modified silicon-incorporated diamond-like carbon layer. The term "heteroatom" can refer to any atom other than carbon or hydrogen. As described above, the heteroatoms are selected from the group consisting of: oxygen, nitrogen, fluorine, boron. However, other heteroatoms are also feasible. The heteroatoms can specifically be selected from the group consisting of: metalloids, specifically germanium, specifically antimony, specifically selenium, specifically tellurium; post-transition metals, specifically aluminum; transition metals, specifically titanium, specifically vanadium, specifically niobium, specifically tantalum, specifically chromium, specifically molybdenum, specifically tungsten, specifically iron, specifically cobalt, specifically copper, specifically silver; non-metals, specifically phosphorus, specifically sulfur, specifically chlorine, specifically bromine, specifically iodine.

[0057] The expression "at.%" can specifically refer to an indication of the percentage of atoms in a chemical substance. The percentage of atoms can be calculated by dividing the number of all atoms of an element by the number of all atoms within the chemical substance. Thereafter, the result can be multiplied by 100.

[0058] The reflective target may specifically include at least one substrate. As used herein, the term "substrate" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term may specifically refer to, but is not limited to, any flat element, such as a flat element that laterally extends at least 2 times, at least 5 times, at least 10 times, or even at least 20 times or more than its thickness. The substrate may have any shape. Specifically, the substrate may have a circular, oval, or polygonal shape, such as a rectangular or circular shape. Additionally, as will be described in further detail below, the substrate may have a strip shape. However, other shapes may also be feasible.

[0059] The substrate may be made of at least one conductive material or may include at least one layer of the at least one conductive material. The conductive material may specifically have a sheet resistance of less than or equal to 100 Ω / sq (preferably less than or equal to 60 Ω / sq). Thus, by way of example, the substrate may be made of at least one conductive material, and an a-C:H:Si layer may be deposited on the surface of the substrate.

[0060] Furthermore, by way of example, the substrate may be made of at least one electrically insulating material or at least one conductive material, and at least one layer of the at least one conductive material may be deposited on the substrate. In the case where at least one surface of the reflective target is at least partially covered by at least one layer of a-C:H.Si layer, the a-C:H:Si layer may be deposited on the surface of the at least one layer of the conductive material. Thus, the a-C:H:Si layer may form the outermost layer of the reflective target. The at least one layer of the conductive material may form the intermediate layer of the reflective target. Additionally, the reflective target may include a layer structure having at least one layer of a-C:H:Si layer and at least one layer of the at least one conductive material. Specifically, the layer structure may include multiple layers of the at least one conductive material. The multiple layers of the at least one conductive material may form the intermediate layer of the reflective target. Additionally, the layer structure may include one or more layers of at least one electrically insulating material. The at least one layer of the conductive material may also be referred to as a conductive contact layer. The surface of the substrate or the surface of the at least one layer of the conductive material on which the a-C:H:Si layer may be deposited may be such that the a-C:H:Si layer can be well-bonded to the surface of the substrate or to the surface of the at least one layer of the conductive material. By way of example, the substrate may be made of glass, and the conductive material may be indium tin oxide (ITO). Thus, the substrate made of glass may include at least one ITO layer and the a-C:H:Si layer may be deposited on the surface of the ITO layer. Additionally, prior to depositing the a-C:H:Si layer, a pretreatment (specifically, plasma treatment) may be performed on the surface of the substrate and / or the intermediate layer, specifically to increase the adhesion of the a-C:H:Si layer on the substrate.

[0061] The substrate of the reflection target can be made at least in part of at least one material or can include at least one material selected from the group consisting of: glass; steel, specifically stainless steel; aluminum; silicon; germanium titanium; copper; cobalt; chromium; molybdenum; nickel; tungsten; tantalum; graphite; polymeric materials, specifically polyethylene, specifically polypropylene, specifically polycarbonate, specifically polystyrene, specifically polyacrylate. Additionally, the polymeric material can be a conductive polymeric material, specifically polyaniline, specifically poly(3,4-ethylenedioxythiophene) polystyrene sulfonate, specifically polypyrrole, specifically polythiophene. Other materials are also feasible, such as alloys comprising at least one metal as described above and at least one additional element.

[0062] A substrate having a surface at least partially covered by at least one layer (comprising hydrogen, silicon-doped amorphous carbon (a-C:H:Si)) is commercially available, for example, from CeWOTec GmbH (Chemnitzer Werkstoff-und Chemnitz, Germany). CeWOTec GmbH provides the "Technical Data Sheet for Our XLC-PURA Coating", which includes the information in Table 1 below. The Technical Data Sheet dates from January 21, 2016, and the information is provided in German. The table below includes an English translation of the text.

[0063]

[0064]

[0065] As described above, the elemental composition of the a-C:H:Si:X layer can specifically be 40 at.% to 80 at.% carbon; 1 at.% to 20 at.% hydrogen; 10 at.% to 40 at.% silicon; up to 15 at.% oxygen; up to 10 at.% nitrogen; up to 10 at.% boron; and up to 5 at.% fluorine. As described above, the sum of oxygen, nitrogen, fluorine, and boron is at least 1 at.%. Thus, the a-C:H:Si:X layer can include one or some or all of the heteroatoms at least 1 at.%. Specifically, the sum of oxygen, nitrogen, fluorine, and boron can be at least 5 at.%, preferably at least 10 at.%.

[0066] As outlined above, the a-C:H:Si layer comprises up to 15 at. % oxygen. Specifically, the percentage of oxygen within the a-C:H:Si layer can vary. The closer the region of the a-C:H:Si layer is to the surface of the reflective target, the lower the percentage of oxygen can be. Thus, within the a-C:H:Si layer, the percentage of oxygen can decrease continuously or discontinuously in a direction perpendicular to the surface of the reflective target (i.e., the surface exposed to laser irradiation). In the bulk region of the a-C:H:Si layer, the percentage of oxygen can be less than 1 at. %, specifically less than 0.1 at. %, and more specifically less than 0.01 at. %.

[0067] As described above, the a-C:H:Si layer can be an amorphous layer. As used herein, the term "amorphous layer" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, any layer made of at least one material lacking long-range order. Thus, the atoms of the material can form an irregular pattern and can only have short-range order. However, the material can also have an internal structure made of interconnected structural blocks. The interconnected structural blocks can correspond to the crystalline phases of the material.

[0068] Specifically, the a-C:H:Si layer can form the outermost layer of the reflective target, which can specifically face the external environment of the reflective target. Further, the a-C:H:Si layer can form a continuous layer on the surface of the reflective target. Further, the structural shape of the surface of the a-C:H:Si layer can be similar to the shape of the surface of the substrate. Specifically, on a smooth substrate, the a-C:H:Si layer can also form a continuous and smooth surface with only a small number of defect sites.

[0069] Specifically, the a-C:H:Si layer can be deposited on the surface of the reflective target by a plasma-supported surface coating process. Specifically, the plasma-supported surface coating process can be a plasma-assisted chemical vapor deposition process (PA-CVD). PA-CVD can be carried out at a process temperature of 100 °C to 200 °C. The term "plasma-assisted chemical vapor deposition" generally can refer to a deposition method in which a substrate is exposed to one or more volatile precursors that react and / or decompose on the surface of the substrate to produce the desired deposit. However, other deposition methods are also feasible.

[0070] As described above, step b) corresponds to at least one sample identification step, which includes positioning at least one sample region on the reflective target.

[0071] As used herein, the term "sample identification step" is a broad term and will be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, a method step of positioning a sample area on a reflection target. As used herein, the term "sample area" is a broad term and will be given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, at least one area on the reflection target that includes the sample. The reflection target can include at least one area on which the sample is located, for example, at least one area on which the sample is applied. The reflection target can include at least one other area without a sample. As used herein, the term "positioning at least one sample area" is a broad term and is given its ordinary and customary meaning to one of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, identifying the sample area on the reflection target.

[0072] For example, the sample identification step can include manually positioning the sample area on the reflection target. For example, the positioning can include the user determining the sample area on the image of the reflection target imaged in step a).

[0073] For example, step b) can be performed automatically, for example, without user interaction. The sample area can be located on the reflection target by using at least one image evaluation algorithm on the image of the reflection target imaged in step a) by using at least one processing device. As used herein, the term "processing device" is a broad term and is given the ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term can refer to, but is not limited to, any logic circuitry configured to perform the basic operations of a computer or system; and / or, generally, a device configured to perform computational or logical operations. The processing device can be configured to process the basic instructions that drive the computer or system. As an example, the processing device can include at least one arithmetic logic unit (ALU), at least one floating-point unit (FPU) (such as a math coprocessor or a numeric coprocessor), a plurality of registers (specifically, registers configured to provide operands to the ALU and store the operation results), and a memory (such as L1 and L2 caches). The processing device can be a multi-core processor. The processing device can be or can include a central processing unit (CPU). Additionally or alternatively, the processing device can be or can include a microprocessor, and thus, specifically, the elements of the processor can be included in a single integrated circuit (IC) chip. Additionally or alternatively, the processing device can be or can include one or more application-specific integrated circuits (ASICs) and / or one or more field-programmable gate arrays (FPGAs) and / or one or more tensor processing units (TPUs) and / or one or more chips, such as a dedicated machine learning optimization chip, etc. The processing device can be configured (such as by software programming) to perform one or more evaluation operations. The processing device can be configured to perform a specified method step. Thus, as an example, the processing device can include software code stored thereon that includes a plurality of computer instructions. The processing device can provide one or more hardware elements for performing one or more of the indicated operations, and / or can provide software for running on one or more processors for performing one or more method steps.

[0074] As used herein, the term "image evaluation algorithm" is a broad term and will be given the ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, an algorithm designed to perform at least one image analysis and / or image processing to localize a sample area. The image evaluation algorithm can include one or more of the following: aligning an image via a reference structural element; applying at least one image filter; image inversion; selecting at least one target area; background correction; decomposition into color channels; segmenting an image, such as a watershed transform or K-means clustering. The target area can be determined manually by a user or can be determined automatically, such as by identifying an object within the image. The image evaluation algorithm can include at least one image correction. The image correction can include at least one background subtraction.

[0075] As an example, the image evaluation algorithm can utilize image recognition, such as software-based automatic image recognition and / or image recognition via a machine learning process. For example, the method can include applying at least one trained model to the image, such as an object classification and / or detection model. The object classification and / or detection model can include at least one machine learning and / or deep learning architecture configured for object recognition and / or identification of an object in an image and classifying the detected object (specifically, assigning a class label to the detected object). The object classification and / or detection model can include at least one convolutional neural network. The object classification and / or detection model can include at least one convolutional neural network selected from the group consisting of: AlexNet; Visual Geometry Group ("VGG") network; Residual Neural Network ("ResNet"); You Only Look Once ("YOLO"); Convolutional Neural Network ("CNN"), such as a Convolutional Neural Network for Spot Detection ("detectSpot"), GoogLeNet Convolutional Neural Network, Region-based Convolutional Neural Network Method ("R-CNN"), Region-based Fully Convolutional Network ("R-FCN"), Single Shot Detector ("SSD"), Spatial Pyramid Pooling (SPP-Net); classical classification machine learning algorithms, such as the k-Nearest Neighbor algorithm ("KNN"); Support Vector Machine ("SVM").

[0076] The image evaluation algorithm can include identifying at least one pattern in the image that indicates a sample. As used herein, the term "pattern" is a broad term and will be given the ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, an image area that includes at least one arbitrary feature.

[0077] The reflection target may include at least one predefined reference structure element. The image evaluation algorithm may include considering information about the predefined reference structure element to localize the sample region in the image. As used herein, the term "predefined reference structure element" is a broad term and will be given its ordinary and customary meaning to a person of ordinary skill in the art, and should not be limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, a predefined reference structure element having known features (e.g., due to the structure of the reflection target). Specifically, the ideal path of laser irradiation can be calculated based on the reference structure element. The predefined reference structure element may include at least one geometric structure. The geometric structure includes at least one element selected from the group consisting of: circle, hexagon, square, polygon, reference cross, point, line. Additionally, the predefined reference structure element may be selected from two-dimensional designs such as a grid (specifically a polygon grid), a lattice. However, other elements may also be feasible. The predefined reference structure element may be or may include a mark and / or engraving on the reflection target. Specifically, the reflection target may include a plurality of predefined reference structure elements. Thus, by way of example, the predefined reference structure elements may be arranged concentrically. However, other arrangements may also be feasible. Specifically, at least one predefined reference structure element may substantially cover the entire surface of the reflection target. Alternatively, at least one predefined reference structure element may cover an area or section of the surface of the reflection target.

[0078] The image evaluation algorithm may include at least one pattern recognition algorithm that uses information about the predefined reference structure element to identify the pattern in the image that indicates the sample. As used herein, the term "pattern recognition algorithm" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, an object classification and / or detection model designed to identify at least one pattern in an image. As used herein, the term "identify the pattern in the image that indicates the sample" is a broad term and will be given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, the process of determining the pattern in the image that indicates the sample.

[0079] Information about predefined reference structure elements can be used to define a target region in an image. As used herein, the term "target region" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, a region or area of any shape in the image. The target region can be the entire image or a part of the image. The target region can be a region of the image that includes or is suspected of including at least one feature. The image can be a pixelated image including a plurality of pixels, such as arranged in a pixel array, such as a rectangular array, having m rows and n columns, where m and n are independently positive integers. The region of interest can be or can include a group of pixels, which includes any number of pixels. The region of interest can include a plurality of sub-regions, such as a plurality of pixels. As used herein, the term "sub-region" is a broad term and will be given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term can specifically refer to, but is not limited to, any part or element of the region of interest that includes at least one pixel or group of pixels, particularly an image element. The sub-region can be a square region of the region of interest. Specifically, the target region in the image can correspond to the part inside or around the predefined reference structure element of the image. First, at least one reference structure element can be identified. Second, the pattern indicating the sample in the image can be located. Specifically, the information about the target region can be transferred to a control device. The laser irradiation can be guided onto the region of the reflection target corresponding to the target region by using the control device.

[0080] Before performing step c), the image of the reflection target imaged in step a) can be additionally transferred to a structure element. First, at least one image evaluation algorithm can be used for the image of the reflection target. Specifically, a processed image of the reflection target can be obtained. The processed image can exemplarily refer to a black / white image. Second, specifically as an additional step, the image of the reflection target, specifically the processed image of the reflection target, can be transferred to the structure element. The structure element can specifically be selected from the group consisting of: a grid, specifically a polygonal grid; a lattice. Specifically, in step c), at least one of the following can be calculated based on the structure element: the path of the laser irradiation, the movement path of the reflection target, the movement path of the holder of the reflection target, and optionally at least one of the laser power and the laser focus. Thus, the guided laser path or the movement of the reflection target can be calculated in combination with a statically aligned laser beam. Specifically, in the case of automatic processing, the calculation of the laser power and / or the laser focus can be optional.

[0081] The method may further include at least one fail-safe step. If the sampling area is not positioned on the reflection target in step b), the reflection target, specifically the target area, may be scanned. A portion or section of the applied sample of the reflection target may be reconstructed based on at least one reference structural element. Then, essentially only the target area may be scanned. As used herein, the term "fail-safe step" is a broad term and should be given its ordinary and customary meaning to a person of ordinary skill in the art and should not be limited to a special or custom meaning. The term may specifically refer to, but is not limited to, at least one step that ensures prevention of generation and / or determination and / or display of unreliable or even false measurement values.

[0082] As described above, step c) corresponds to at least one analyte detection step, which includes using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) with a laser desorption mass spectrometer to detect at least one analyte in a sample, wherein a laser irradiation is applied to the reflection target by using at least one laser source of the laser desorption mass spectrometer, such that at least one ion of at least one analyte is generated, and the at least one ion is detected by using at least one of a mass analysis unit or an ion mobility spectrometry device of the laser desorption mass spectrometer, wherein the laser irradiation is guided onto the positioned sample area by using at least one control device.

[0083] As used herein, the term "analyte detection step" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term may specifically refer to, but is not limited to, any method step that includes quantitative and / or qualitative determination of at least one analyte in any sample. The quantitative and / or qualitative determination of the analyte in the sample may be the result or an intermediate result of a detection process that may include at least one measurement step and other steps, such as at least one preparation step and / or at least one analysis step. As part of the detection process, at least one measurement value may be generated, specifically a measurement value regarding the presence, absence, relative concentration, or amount of the analyte in the sample.

[0084] As used herein, the term "laser irradiation" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term may specifically refer to, but is not limited to, the process of exposing an object (specifically the surface of the object) to a laser. Specifically, a first portion of the object, particularly a first portion of the surface of the object, may be irradiated with at least one laser beam, and preferably a second portion of the object, particularly a second portion of the surface of the object, may not be irradiated with at least one laser beam. Specifically, the reflection target may absorb the laser energy and transfer the laser energy to the molecules of the sample, and desorption and ionization may occur.

[0085] As used herein, the term "laser source" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, a device configured to emit light through an optical amplification process based on stimulated emission of electromagnetic radiation. Specifically, the laser may include a pulsed laser. The energy of the pulse may be in the range of less than 60 μJ, specifically in the range of less than 35 μJ. In addition, the laser may have a laser repetition rate in the range of 500 Hz to 5 kHz, specifically 1 kHz to 3 kHz. For example, the laser may be configured to generate a laser beam in the UV spectral range. Specifically, the laser wavelength may be in the range between 300 nm and 400 nm. More specifically, the laser may be a neodymium-doped yttrium aluminum garnet laser (Nd:YAG laser) with a wavelength of 355 nm. Other types of laser sources may also be feasible. In addition, the laser source may include one or more additional optical elements, such as variable mirrors, lenses, polarizers, and / or shutters.

[0086] As used herein, the term "mass analysis unit" is a broad term and will be given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, a device configured to detect input ions. The mass analysis unit may be configured to detect charged particles. The mass analysis unit may be or may include at least one electron multiplier. The mass analysis unit may be configured to determine at least one mass spectrum of the detected ions. As used herein, the term "mass spectrogram" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, a two-dimensional representation of signal intensity versus mass-to-charge ratio m / z, where the signal intensity corresponds to the abundance of the corresponding ions. The mass-to-charge ratio may refer to the reciprocal of a specific charge. The mass spectrogram may be a pixelated image. To determine the resulting intensity of a mass spectrometry pixel, the signals detected by the mass analysis unit within a certain m / z range may be integrated. The mass analysis unit may include at least one evaluation device. The analyte in the sample may be identified by the at least one evaluation device. Specifically, the evaluation device may be configured to correlate known masses with the identified masses or to configure them through characteristic fragmentation patterns.

[0087] As used herein, the term "ion mobility spectrometry device" is a broad term and should be given its ordinary and customary meaning to a person of ordinary skill in the art, and should not be limited to a special or customized meaning. Specifically, the term can refer to, but is not limited to, any analytical technique that is configured to separate and identify ionized molecules in the gas phase based on their mobility in a carrier gas buffer gas and in the presence of an electric field. The ion mobility spectrometry device can be specifically coupled to a laser desorption mass spectrometer, specifically to achieve multi-dimensional separation. The ion mobility spectrometry device can be configured to detect at least one drift time of ions through an ion mobility mass spectrometry cell.

[0088] The method can further include at least one sample preparation step. As used herein, the term "sample preparation step" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art, and is not limited to a special or customized meaning. Specifically, the term can refer to, but is not limited to, at least one process of preparing a sample for subsequent measurement. The sample preparation step can include at least one workflow. The workflow can include a single step or multiple subsequent and / or parallel steps. Sample preparation can include sample purification and / or sample dilution and / or sample concentration. The sample can undergo one or more pre-treatments and / or sample preparation steps. The sample can be pre-treated by physical and / or chemical methods, such as by centrifugation, filtration, mixing, homogenization, chromatography, purification precipitation, dilution, concentration, contact with binding and / or detection reagents, and / or any other method considered suitable by a person skilled in the art.

[0089] The sample preparation step can include applying the sample to at least one reflection target, where the sample contains at least one analyte. Specifically, the sample, which is a fluid sample, can be applied to at least one reflection target. Optionally, the sample preparation step can include drying the sample on the reflection target. Drying can refer to allowing the sample to dry naturally, such as drying in the open air. As part of the drying process, part or all of the liquid of the sample may evaporate.

[0090] Specifically, a volume of 0.01 μl to 10 μl, preferably 0.05 μl to 5 μl, and most preferably 0.75 μl to 2 μl can be applied to the reflection target. However, other volumes may also be feasible.

[0091] Specifically, the amount of analyte on one sample spot can be less than 35 nmol, specifically less than 3.5 nmol, specifically less than 350 pmol, specifically less than 35 pmol, specifically less than 3.5 pmol, specifically less than 350 fmol. However, other amounts may also be feasible.

[0092] In another aspect of the present invention, a system including at least one laser desorption mass spectrometer is disclosed.

[0093] The laser desorption mass spectrometer includes at least one reflection target. At least one sample can be applied to the reflection target. The sample contains at least one analyte. The laser desorption mass spectrometer is configured to detect at least one analyte in the sample using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS). The laser desorption mass spectrometer includes at least one laser source. The laser source is configured to apply a laser irradiation to the reflection target such that at least one ion of at least one analyte is generated. Specifically, applying the laser irradiation to the reflection target may include adjusting at least one of the following: the path of the laser irradiation, the movement path of the reflection target, the movement path of the holder of the reflection target, and optionally at least one of the laser power and the laser focus. The laser desorption mass spectrometer includes at least one of a mass analysis unit or an ion mobility spectrometry device configured to detect the ions. The system includes at least one imaging device configured to image the reflection target. The laser desorption mass spectrometer includes at least one control device configured to direct the laser irradiation onto the positioned sample area.

[0094] As used herein, the term "system" is a broad term and will be given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. The term may specifically refer to, but is not limited to, a group consisting of at least two elements that can interact with each other to achieve at least one common function. The at least two components may be disposed independently, or may be coupled, connected, or integrated to form a common component.

[0095] The system may be configured to perform a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer as described above or further described in more detail below.

[0096] The system may include at least one processing device configured to use at least one image evaluation algorithm on at least one image of the reflection target imaged by the imaging device, thereby positioning at least one sample area on the reflection target. Further details regarding the processing device are referred to the description above.

[0097] The reflection target can be provided in the form of a material tape or a stack of microplates. In the case where the reflection target is provided as a material tape, the reflection target can be specifically provided in a coiled manner. The material tape can be configured to be unrolled before applying one or more samples to the material tape, specifically to the surface of the material tape. The material tape can be configured to pass through the system. Specifically, the material tape can be configured to pass through different stations of the system. The different stations can include a laser desorption mass spectrometer and can further include one or more liquid handling systems and one or more vacuum regions. Further details regarding the liquid handling systems and the vacuum regions can be provided in more detail below. The material tape can be specifically made of steel or aluminum. However, other materials are also feasible. The material tape can have a width of 0.5 cm to 10 cm (preferably 1 cm to 3 cm). In addition, the material tape can have a thickness of 0.2 mm to 2 mm (preferably 0.5 mm to 1 mm). In addition, the length of the material tape can be 5 m to 100 m. However, other dimensions are also feasible. Specifically, the length of the material tape can be unrestricted. Specifically, the material tape can be manufactured by coating a substrate during a winding process. Thus, exemplarily, an a-C:H:Si layer can be formed on the surface of the substrate during the winding process. This manufacturing process can also be exemplarily referred to as a roll-to-roll PA-CVD coating process.

[0098] In addition, as outlined above, the reflection target can be provided as a stack of microplates. The microplates can specifically have a rectangular shape, such as a square shape. However, other shapes are also feasible, such as a circular shape. The microplates can specifically have a thickness of 0.2 mm to 1 cm (preferably 0.5 mm to 3 mm). In addition, the microplates can have a width in the range of 1 cm to 10 cm (preferably 1 cm to 8 cm, most preferably 1 cm to 5 cm). In addition, the microplates can have a length in the range of 1 cm to 15 cm (preferably 1 cm to 12 cm, most preferably 1 cm to 7 cm).

[0099] The microplates can be provided stacked on top of each other. Specifically, the system can include at least one microplate holder configured to receive the stack of microplates. The microplate holder can be configured to continuously release the microplates. Specifically, the system can include at least one conveyor belt. The microplate holder can be configured to continuously release the microplates onto the conveyor belt. Specifically, the conveyor belt can be configured to continuously move the microplates through the system. Specifically, the conveyor belt can be configured to continuously move the microplates through different stations of the system.

[0100] The system may further include at least one vacuum system. The system may be configured to pass a material tape or a microplate through the vacuum system. As used herein, the term "vacuum system" is a broad term and is given its ordinary and customary meaning to a person of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, this term may refer to, but is not limited to, any device configured to generate a vacuum, such as a region having a pressure below atmospheric pressure in a defined space (e.g., a chamber). For this purpose, the vacuum system may include at least one vacuum pump. Further details regarding the vacuum pump may be seen in the description of the vacuum pump above. Specifically, the vacuum system may include at least one vacuum zone, preferably at least two vacuum zones. The term "vacuum zone" may refer to a defined space, such as a chamber having a pressure below atmospheric pressure. At least two vacuum zones may be arranged continuously. The material tape or the microplate stack may be configured to pass through the vacuum system (specifically one or more vacuum zones) before passing through the laser desorption mass spectrometer. The vacuum zone may be configured to provide a negative pressure below 1500 mbar, such as below 1000 mbar, below 900 mbar, below 800 mbar, below 700 mbar, below 600 mbar, below 500 mbar, below 400 mbar, below 300 mbar, below 200 mbar, below 100 mbar, below 90 mbar, below 80 mbar, below 70 mbar, below 60 mbar, below 50 mbar, below 40 mbar, below 30 mbar, below 20 mbar, below 10 mbar, below 1 mbar or even lower. Specifically, at least two vacuum zones may be configured to provide different negative pressures from each other. Other parameters are also feasible. The vacuum system (specifically the vacuum zone) may be configured to dry the sample on the reflection target.

[0101] In addition, the system may include at least one liquid handling system. The liquid handling system may be configured to apply at least one sample having at least one analyte onto a reflective target, specifically onto a material tape or one of the microplates. As used herein, the term "liquid handling system" is a broad term and is given the ordinary and customary meaning to those of ordinary skill in the art and is not limited to a special or custom meaning. Specifically, the term may refer to, but is not limited to, any device configured to apply a liquid (specifically a limited or desired amount of liquid) onto another object. The amount of liquid can be adjusted. The liquid handling system may specifically include one or more pipetting units. The pipetting unit may include at least one chamber configured to hold or receive at least one liquid. The pipetting unit may be configured to create a partial vacuum above the chamber and to selectively release the partial vacuum to aspirate and dispense the liquid. Additionally or alternatively, the liquid handling system may include at least one acoustic droplet ejection unit. The acoustic droplet ejection unit may be configured to move a large amount of fluid using ultrasonic pulses without any physical contact. However, other embodiments may also be feasible.

[0102] The present invention further discloses and presents a computer program including instructions, which when executed by the system as described above or further described in more detail below, cause the system to perform the methods as described above or to be further described in more detail below. Specifically, the computer program may be stored on a computer-readable data carrier. Thus, specifically, the method steps a), b), and c) of the method as indicated above may be performed by using a computer or a computer network, preferably by using the computer program. Specifically, a scan parameter table may be provided to the instrument software.

[0103] The present invention further discloses and presents a computer program product having program code means for, when the program is executed on a computer or a computer network, performing more than one or even all of the method steps a), b), and c) of the method as indicated above according to the present invention in one or more of the embodiments appended hereto. Specifically, the program code means may be stored on a computer-readable data carrier.

[0104] The present invention further discloses and presents a computer-readable storage medium including instructions, which when executed by the system as described above or further described in more detail below, cause the system to perform the methods as described above or to be further described in more detail below.

[0105] The present invention further discloses and presents a non-transitory computer-readable medium including instructions, which when executed by one or more processors, cause the one or more processors to perform as described above or to be further described in more detail below.

[0106] Furthermore, the present invention discloses and provides a data carrier having a data structure stored thereon, which, after being loaded into a computer or a computer network, such as after being loaded into the working memory or main memory of a computer or a computer network, can perform more than one or even all of method steps a), b), and c) of the method as indicated above according to one or more of the embodiments disclosed herein.

[0107] The present invention further provides and discloses a computer program product having program code means stored on a machine-readable carrier for performing, when the program is executed on a computer or a computer network, more than one or even all of method steps a), b), and c) of the method as indicated above according to one or more of the embodiments disclosed herein. As used herein, a computer program product refers to a program as a tradable product. The product can generally exist in any format (such as in a paper format) or on a computer-readable data carrier. Specifically, the computer program product can be distributed over a data network.

[0108] Finally, the present invention provides and discloses a modulated data signal containing instructions readable by a computer system or a computer network for performing more than one or even all of method steps a), b), and c) of the method as indicated above according to one or more of the embodiments disclosed herein.

[0109] Preferably, with reference to the computer-implemented aspects of the present invention, more than one or even all of method steps a), b), and c) of the method as indicated above can be performed according to one or more of the embodiments disclosed herein by using a computer or a computer network. Thus, generally speaking, any method step including providing and / or manipulating data can be performed by using a computer or a computer network. Generally speaking, these method steps can include any method steps other than those method steps that usually require manual operations (such as providing samples and / or performing certain aspects of actual measurements).

[0110] Specifically, the present invention further discloses:

[0111] - A computer or a computer network comprising at least one processor, wherein the processor is adapted to perform more than one or even all of method steps a), b), and c) of the method according to one embodiment of the embodiments described in this specification.

[0112] - A computer-loadable data structure, which is adapted to perform more than one or even all of method steps a), b), and c) of the method according to one embodiment among the embodiments described in this specification when the data structure is executed on a computer.

[0113] - A computer program, which is adapted to perform more than one or even all of method steps a), b), and c) of the method according to one embodiment among the embodiments described in this specification when the program is executed on a computer.

[0114] - A computer program including program means, which are used to perform more than one or even all of method steps a), b), and c) of the method according to one embodiment among the embodiments described in this specification when the computer program is executed on a computer or on a computer network.

[0115] - A computer program, which includes program means according to the foregoing embodiment, wherein the program means are stored on a computer-readable storage medium.

[0116] - A storage medium, on which a data structure is stored and which is adapted to perform more than one or even all of method steps a), b), and c) of the method according to one embodiment among the embodiments described in this specification after the data structure has been loaded into the main memory and / or working memory of a computer or a computer network.

[0117] And

[0118] - A computer program product having program code means, wherein the program code means can be stored or are stored on a storage medium for performing more than one or even all of method steps a), b), and c) of the method according to one embodiment among the embodiments described in this specification in the case where the program code means are executed on a computer or on a computer network.

[0119] Compared with known methods and apparatuses, the method and apparatus according to the present invention provide a number of advantages.

[0120] Image-based sample identification can be coupled to a SALDI target, which is used to direct the laser irradiation of the SALDI process only onto the spots where the dried analyte is present. This allows for rapid measurement of analyte spots and supports quantitative analysis, while also reducing the data file size, specifically compared to classical measurement methods such as MALDI imaging of predefined sample areas. Specifically, classical MALDI methods cannot be coupled with such ideas because of the fact that a large amount of matrix compound (>>10 pg) is usually used to ionize the analyte components and thus covers the entire spot. Therefore, in classical MALDI methods, it is usually impossible to distinguish between the matrix and the analyte.

[0121] Summarizing and without excluding other possible embodiments, the following embodiments can be envisaged:

[0122] Embodiment 1: A computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer, wherein the method comprises:

[0123] a) At least one imaging step, including imaging at least one reflective target by using at least one imaging device, wherein a sample containing at least one analyte is applied to the reflective target;

[0124] b) At least one sample identification step, which includes positioning at least one sample area on the reflective target; and

[0125] c) At least one analyte detection step, which includes using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) with a laser desorption mass spectrometer to detect at least one analyte in the sample, wherein laser irradiation is applied to the reflective target by using at least one laser source of the laser desorption mass spectrometer such that at least one ion of at least one analyte is generated, and the at least one ion is detected by using at least one of a mass analysis unit or an ion mobility spectrometry device of the laser desorption mass spectrometer, wherein the laser irradiation is directed onto the positioned sample area by using at least one control device.

[0126] Embodiment 2: The method according to the foregoing embodiment, wherein the method further comprises at least one sample preparation step, wherein the sample preparation step includes applying the sample to the at least one reflective target, and the sample contains the at least one analyte.

[0127] Embodiment 3: The method according to the foregoing embodiment, wherein the sample preparation step includes drying the sample on the reflective target.

[0128] Embodiment 4: The method according to any one of the foregoing embodiments, wherein the sample area is positioned on the reflective target by using at least one image evaluation algorithm for the image of the reflective target imaged in step a) by using at least one processing device.

[0129] Example 5: The method according to the foregoing embodiment, wherein before performing step c), the image of the reflection target imaged in step a) is transferred to a structural element.

[0130] Example 6: The method according to the foregoing embodiment, wherein in step c), at least one of the following items is calculated based on the structural element: the path of the laser irradiation, the movement path of the reflection target, the movement path of the holder of the reflection target, and optionally at least one of the laser power and the laser focus.

[0131] Example 7: The method according to any one of the foregoing three embodiments, wherein the image evaluation algorithm includes identifying at least one pattern in the image that indicates the sample.

[0132] Example 8: The method according to the foregoing embodiment, wherein the reflection target includes at least one predefined reference structural element, and the image evaluation algorithm includes considering information about the predefined reference structural element for locating the sample region in the image.

[0133] Example 9: The method according to the foregoing embodiment, wherein the predefined reference structural element includes at least one geometric structure, and the geometric structure includes at least one element selected from the group consisting of: circle, hexagon, square, polygon, reference cross, point, line.

[0134] Example 10: The method according to any one of the foregoing two embodiments, wherein the predefined reference structural element: grid, lattice.

[0135] Example 11: The method according to any one of the foregoing two embodiments, wherein the image evaluation algorithm includes at least one pattern recognition algorithm, and the pattern recognition algorithm uses the information about the predefined reference structural element to identify the pattern in the image that indicates the sample.

[0136] Example 12: The method according to any one of the foregoing three embodiments, wherein the information about the predefined reference structural element is used to define a target region in the image.

[0137] Example 13: The method according to any one of the foregoing embodiments, wherein the sample identification step includes manually positioning the sample region on the reflection target.

[0138] Example 14: The method according to any one of the foregoing embodiments, wherein the computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer is performed at least partially automatically.

[0139] Example 15: The method according to the foregoing example, wherein at least steps a) and c) are carried out automatically.

[0140] Example 16: The method according to any one of the foregoing examples, wherein the computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer is carried out completely automatically, specifically from sample preparation to the analyte detection step.

[0141] Example 17: The method according to the foregoing example, wherein at least steps a), b) and c) are carried out automatically.

[0142] Example 18: The method according to any one of the foregoing examples, wherein the reflection target has a specular reflection of ≥ 45%.

[0143] Example 19: The method according to any one of the foregoing examples, wherein the reflection target has an R a nominal arithmetic roughness of ≤ 2 μm.

[0144] Example 20: The method according to any one of the foregoing examples, wherein the reflection target has at least one surface, wherein the surface is at least partially covered with at least one layer, wherein the layer is a hydrogen-containing, silicon-doped amorphous carbon (a-C:H:Si) layer, wherein the a-C:H:Si layer comprises:

[0145] · 40 at.% to 80 at.% carbon;

[0146] · 1 at.% to 20 at.% hydrogen; and

[0147] · 10 at.% to 40 at.% silicon.

[0148] Example 21: The method according to the foregoing example, wherein the a-C:H:Si layer is a hydrogen-containing, heteroatom-modified, silicon-doped amorphous carbon (a-C:H:Si:X) layer, wherein the heteroatom X is selected from the group consisting of oxygen, nitrogen, fluorine, boron, wherein the a-C:H:Si:X layer further comprises:

[0149] · up to 15 at.% oxygen;

[0150] · up to 10 at.% nitrogen;

[0151] · up to 10 at.% boron; and

[0152] · up to 5 at.% fluorine;

[0153] wherein the sum of oxygen, nitrogen, fluorine and boron is at least 1 at.%.

[0154] Example 22: The method according to any one of the two preceding examples, wherein the a-C:H:Si layer is deposited on the surface of the target by a plasma-supported surface coating process.

[0155] Example 23: The method according to any one of the preceding examples, wherein the reflective target comprises at least one substrate, and the substrate is made of at least one material selected from the group consisting of: glass; steel, specifically stainless steel; aluminum; silicon; germanium; titanium; copper; cobalt; chromium; molybdenum, nickel; tungsten; tantalum; graphite; polymer materials, specifically polyethylene, specifically polypropylene, specifically polycarbonate, specifically polystyrene, specifically polyacrylate, specifically polyaniline, specifically poly(3,4-ethylenedioxythiophene) polysulfonate, specifically polypyrrole, specifically polythiophene.

[0156] Example 24: The method according to any one of the preceding examples, wherein the imaging device is at least one device selected from the group consisting of: at least one camera, at least one CCD camera, at least one CMOS camera, at least one RGB camera, at least one digital camera, at least one camera of a microscope, at least one camera of a reflecting microscope.

[0157] Example 25: The method according to any one of the preceding examples, wherein the analyte is at least one analyte selected from the group consisting of: steroids; specifically ketosteroids, specifically secosteroids; therapeutically active substances; detergents; glycosides; peptides; proteins; dyes; ions; nucleic acids; amino acids; metabolites; hormones; fatty acids; lipids; carbohydrates.

[0158] Example 26: The method according to any one of the preceding examples, wherein the analyte has a molar mass of 6 daltons to 10,000 daltons, preferably 50 daltons to 3,000 daltons.

[0159] Example 27: The method according to any one of the five preceding examples, wherein the analyte comprises permanently positively charged molecules or permanently negatively charged molecules.

[0160] Example 28: The method according to any one of the preceding examples, wherein the amount of the analyte on one sample spot is less than 35 nmol, specifically less than 3.5 nmol, specifically less than 350 pmol, specifically less than 35 pmol, specifically less than 3.5 pmol, specifically less than 350 fmol.

[0161] Example 29: The method according to any one of the preceding examples, wherein a volume of 0.01 μl to 10 μl, preferably 0.05 μl to 5 μl and most preferably 0.75 μl to 2 μl is applied to the reflective target.

[0162] Example 30: The method according to any one of the preceding examples, wherein the analyte is provided in a sample, and the sample is selected from the group consisting of: physiological fluids, including blood, serum, plasma, saliva, aqueous humor, cerebrospinal fluid, sweat, urine, milk, ascites, mucus, synovial fluid, peritoneal fluid, amniotic fluid, tissues or cells.

[0163] Example 31: The method according to any one of the preceding examples, wherein the method comprises loading the reflector target into the laser desorption mass spectrometer, and the imaging step is performed before and / or after loading the reflector target into the laser desorption mass spectrometer.

[0164] Example 32: The method according to any one of the preceding examples, wherein the method comprises at least one fail-safe step, and in the case where the sampling area is not located on the reflector target in step b), the reflector target is scanned.

[0165] Example 33: A system comprising at least one laser desorption mass spectrometer, wherein the laser desorption mass spectrometer comprises at least one reflector target, at least one sample can be applied to the reflector target, and the sample contains at least one analyte,

[0166] wherein the laser desorption mass spectrometer is configured to detect the at least one analyte in the sample using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS), the laser desorption mass spectrometer comprises at least one laser source, and the laser source is configured to apply a laser irradiation to the reflector target such that at least one ion of the at least one analyte is generated, and the laser desorption mass spectrometer comprises at least one of a mass analysis unit or an ion mobility spectrometry device configured to detect the ions,

[0167] wherein the system comprises at least one imaging device configured to image the reflector target, and the laser desorption mass spectrometer comprises at least one control device configured to direct the laser irradiation onto a positioned sample area.

[0168] Example 34: The system according to the preceding example, wherein the system comprises at least one processing device configured to use at least one image evaluation algorithm for at least one image of the reflector target imaged by the imaging device, thereby positioning at least one sample area on the reflector target.

[0169] Example 35: The system according to any one of the preceding two examples, wherein the system is configured to perform the method for detecting at least one analyte according to any one of the preceding claims.

[0170] Example 36: A system according to any one of the preceding three examples, wherein the target is provided in the form of a material tape or a stack of microplates, and wherein the system further comprises at least one vacuum system, and wherein the system is configured to pass the material tape or the stack of microplates through the vacuum system.

[0171] Example 37: A computer program comprising instructions which, when the program is executed by a system according to any one of the preceding examples relating to a system, cause the system to perform a method according to any one of the preceding claims relating to a method.

[0172] Example 38: A computer-readable storage medium comprising instructions which, when the instructions are executed by a system according to any one of the preceding claims relating to a system, cause the system to perform a method according to any one of the preceding examples relating to a method.

[0173] Example 39: A non-transitory computer-readable medium comprising instructions which, when executed by one or more processors, cause the one or more processors to perform a method according to any one of the preceding examples relating to a method. Description of the Drawings

[0174] Other optional features and examples will be disclosed in more detail in the following description of the examples, preferably in combination with the dependent claims. Wherein, as will be appreciated by those skilled in the art, the various optional features can be implemented separately and in any feasible combination. The scope of the present invention is not limited by the preferred examples. The examples are schematically depicted in the drawings. Wherein, the same reference numerals in these drawings refer to the same or functionally equivalent elements.

[0175] In the drawings:

[0176] Figures 1A to 1B Two exemplary embodiments of a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer according to the present invention are shown in a schematic flowchart;

[0177] Figures 2A to 2B Low-resolution microscope images of the dried sample on the reflection target are shown respectively;

[0178] Figures 3A to 3B Mass spectra obtained using a laser desorption mass spectrometer are shown respectively;

[0179] Figure 4 Further low-resolution microscope images of the dried sample are shown;

[0180] Figure 5Shows an exemplary embodiment of a laser desorption mass spectrometer according to the present invention; and

[0181] Figure 6 Shows a further exemplary embodiment of the system according to the present invention; Detailed Description

[0182] Figure 1A and 1B Illustrates two exemplary embodiments of a computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer according to the present invention in a schematic flowchart.

[0183] The computer-implemented method for detecting at least one analyte in a sample may include at least one sample preparation step. The sample preparation step may include applying the sample to at least one reflector target. The sample may include at least one analyte. The applied sample may also be referred to as a sample spot. This step is shown in Figure 1A the flowchart by block 112.

[0184] In addition, the sample on the reflector target may be dried. This step is shown in Figure 1A the flowchart by block 114. Drying of the sample on the reflector target may also be part of the sample preparation step.

[0185] In addition, the computer-implemented method for detecting at least one analyte in a sample includes at least one imaging step, which includes imaging the reflector target by using at least one imaging device. This step is shown in Figure 1A the flowchart by block 116.

[0186] In addition, the computer-implemented method for detecting at least one analyte in a sample includes at least one sample identification step, which includes positioning at least one sample area on the reflector target. This step is shown in Figure 1A the flowchart by block 118. This step may include data processing and image digitization. Specifically, the sample area may be positioned on the reflector target by using at least one image evaluation algorithm on the image of the reflector target by using at least one processing device. In addition, specifically, the image evaluation algorithm may include identifying at least one pattern in the image that indicates the sample.

[0187] Thereafter, the reflector target with the sample may be loaded onto the laser desorption mass spectrometer. This step is shown in Figure 1A the flowchart by block 120.

[0188] In addition, a computer-implemented method for detecting at least one analyte in a sample includes at least one analyte detection step, which includes using a laser desorption mass spectrometer to detect at least one analyte in the sample using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS). The detection step includes applying a laser irradiation to a reflection target by using at least one laser source of the laser desorption mass spectrometer, such that at least one ion of at least one analyte is generated. The laser irradiation is guided onto the positioned sample area by using at least one control device. This step is shown in Figure 1A by box 122 in the flowchart of. In addition, the detection step includes detecting at least one ion of at least one analyte by using at least one of a mass analysis unit or an ion mobility spectrometry device of the laser desorption mass spectrometer. This step may also be referred to as a sample measurement step and is shown in Figure 1A by box 124 in the flowchart of.

[0189] As Figure 1B shown, the computer-implemented method for detecting at least one analyte in a sample largely corresponds to the computer-implemented method for detecting at least one analyte in a sample as Figure 1A shown. Therefore, refer to the description above Figure 1A .

[0190] Contrary to the method as Figure 1A shown, in the method as Figure 1B shown, the order of the steps is reversed. Therefore, loading the reflection target with the sample onto the laser desorption mass spectrometer (shown by box 120 in the flowchart) can be performed before imaging the reflection target by using at least one imaging device and before positioning at least one sample area on the reflection target. These steps are shown by boxes 116 and 118 in the flowchart.

[0191] Figure 2A and 2B show low-resolution microscopic images of the dry sample 126 on the reflection target 128, respectively.

[0192] Specifically, Figure 2A shows a low-resolution microscopic image 123 of 100 ng of cortisol dried from an 80% MeOH solution. The reflection target 128 may specifically include a predefined reference structure element 130. The predefined reference structure element 130 may specifically include a plurality of circles 132. In the low-resolution microscope image, a ring 134 is visible within one of the circles 132. The ring 134 corresponds to the dry sample 126. The ring 134 may specifically exhibit the dry sample 126 with a typical coffee ring effect.

[0193] In addition, Figure 2BShows a low-resolution microscopic image 123 (black / white image) of 100 ng of cortisol dried from an 80% MeOH solution after binarization. The circle 132 is still visible and can be used for calibration of the laser position. The ring 134 may correspond to the measurement range of the laser. Only the black spots within the circle 132 are vulnerable to laser stimulation. The white area 136 corresponds to the area without sample.

[0194] Figures 3A to 3B Respectively show mass spectra obtained by a laser desorption mass spectrometer. As Figure 2A and 2B shown, the mass spectra are obtained from the reflection target 128.

[0195] The mass spectra show the relative abundance ra (%) depending on the mass-to-charge ratio m / z.

[0196] Figure 3A Shows the spectrum outside the ring 134 corresponding to the dried sample 126. Therefore, there is no analyte. Figure 3B Shows the spectrum inside the ring 134 corresponding to the dried sample 126. Cortisol ([M+H] + and [M+Na] + ) analyte signals are clearly visible.

[0197] Figure 4 Shows a further low-resolution microscopic image of the dried sample 126. The sample 126 corresponds to a mixture of 500 pg of testosterone and 500 pg of progesterone. The reflection target 128 may specifically include a predefined reference structural element 130. The predefined reference structural element 130 may specifically include a plurality of circles 132. In the low-resolution microscopic image, the ring 134 within one of the circles 132 is visible. The ring 134 corresponds to the dried sample 126.

[0198] Figure 5 Shows an exemplary embodiment of a system 218 including a laser desorption mass spectrometer 220 according to the present invention.

[0199] The laser desorption mass spectrometer 220 includes at least one reflection target 128. The reflection target 128 may at least partially correspond to the reflection target 128 depicted as Figure 2A above. Therefore, referring to the above Figure 2ADescription. Further, the laser desorption mass spectrometer 220 includes at least one laser source 222. The laser source 222 is configured to apply a laser irradiation to the reflection target 128 such that at least one ion of at least one analyte is generated. Further, the laser desorption mass spectrometer 220 includes at least one of the mass analysis units 224. Additionally or alternatively, the laser desorption mass spectrometer 220 may include an ion mobility spectrometry device configured to detect the ions. Specifically, the mass analysis unit 224 may be configured to detect at least one mass-to-charge ratio of at least one ion emitted from the target 118.

[0200] The laser desorption mass spectrometer 220 may include at least one chamber 226. Further, the laser desorption mass spectrometer 220 may include at least one high-vacuum chamber 228, at least one low-vacuum chamber 227, and at least one sample loading chamber 229. At least one ion inlet 231 may be arranged between the high-vacuum chamber 228 and the chamber 226.

[0201] The laser source 222 may specifically be a pulsed laser 232. The laser source 222 may be configured to generate a laser beam in the UV spectral range. The laser source 222 may be arranged relative to the reflection target 128 such that the laser beam schematically depicted by the arrow 234 impinges on the reflection target 128 at an angle of 10° to 90° (preferably 30° to 70°). Specifically, the reflection target 128 may absorb the laser energy and transfer the laser energy to the molecules of the sample, and desorption and ionization may occur. Further, the system 218 may include at least one imaging device 235. The imaging device 235 may be arranged relative to the reflection target 128 at an angle of 10° to 90°, preferably 30° to 80°, as shown by the arrow 233. Specifically, the imaging device 235 may be arranged relative to the reflection target 128 at an angle of substantially 90°.

[0202] Further, the laser desorption mass spectrometer 320 may include at least one mass separation module 236. The arrangement of the mass separation module 236 may depend on the applied mass spectrometry technique.

[0203] The mass analysis unit 224 having the readout electronics 238 may be received within the chamber 226. Further, the mass analysis unit 224 may be arranged at a certain distance from the reflection target 128. The mass analysis unit 224 may be configured to detect or determine at least one mass-to-charge ratio of at least one ion emitted from the reflection target 128. Additionally, the laser desorption mass spectrometer 220 includes at least one control device 237, which is configured to direct the laser irradiation onto a local sample area.

[0204] Figure 6 Shows a further exemplary embodiment of the system 218 according to the present invention.

[0205] According toFigure 6 The system 218 includes at least one laser desorption mass spectrometer 220. The laser desorption mass spectrometer 220 at least partially corresponds to the laser desorption mass spectrometer 220 as shown in Figure 5 Therefore, refer to the description above Figure 5 .

[0206] Figure 6 Figure 218 shows the system 218, in which the reflection target 128 is provided as a stack 164 of microplates 266. The microplates 266 may specifically have a rectangular shape, such as a square shape. The microplates 266 may be provided stacked on top of each other. Specifically, the microplates 266 may be stored in a microplate holder 270. The microplate holder 270 may be configured to continuously release the microplates 266. Specifically, the system 218 may include at least one conveyor belt (not shown). The microplate holder 270 may be configured to continuously release the microplates 266 onto the conveyor belt. The conveyor belt may be configured to continuously move the microplates 266 through different stations 248 of the system 218.

[0207] The different stations 248 may include the laser desorption mass spectrometer 220 and may further include one or more liquid handling systems 250 and / or vacuum systems 252.

[0208] The liquid handling system 250 may be configured to apply at least one sample 268 having at least one analyte onto the reflection target 128, specifically onto the microplates 266. The liquid handling system 250 may specifically include one or more pipetting units 254. Specifically, the conveyor belt may be configured to continuously move the microplates 166 through the liquid handling system 150. After individually collecting the microplates 166 from the stack 164, the sample 268 including the analyte solution may be loaded onto the microplates 166 by using the pipetting unit 254. The sample 268 may be pipetted onto the surface 272 of the microplates 266.

[0209] Further, the conveyor belt can be configured to continuously pass the microplate 266 through the vacuum system 252 and the laser desorption mass spectrometer 220. The vacuum system 252 can include one or more vacuum zones 258. The vacuum zones 258 can be arranged continuously. The microplate 266 can be configured to pass through the vacuum system 252 (specifically, one or more vacuum zones 258) before passing through the laser desorption mass spectrometer 220. Specifically, the microplate 266 can be configured to pass through at least one first vacuum zone 260 and at least one second vacuum zone 262 before passing through the laser desorption mass spectrometer 220. The first vacuum zone 260 can be configured to provide a first negative pressure, and the second vacuum zone 262 can be configured to provide a second negative pressure. The first negative pressure can be higher than the second negative pressure, or vice versa. The first negative pressure and the second negative pressure can be lower than 1500 mbar. The vacuum system 252 (specifically, the vacuum zone 258) can be configured to dry the sample on the reflection target 128. In addition, the vacuum system 252 can include at least one third vacuum zone 184 and at least one fourth vacuum zone 186. Specifically, the microplate 266 can be configured to pass through at least one third vacuum zone 284 and at least one fourth vacuum zone 286 after passing through the laser desorption mass spectrometer 220. The third vacuum zone 284 and the fourth vacuum zone 286 can be configured to ensure continuous outward conveyance and, at the same time, keep the vacuum in the laser region as low as technically possible, specifically to ensure reliable measurement.

[0210] The laser desorption mass spectrometer 220 can exemplarily include quadrupoles, and subsequently ion trapping, isobar separation via ion mobility, fragmentation in a collision cell, and subsequently quadrupole or time-of-flight (ToF) mass analysis can be performed. Other ion manipulation techniques (such as sector magnets or ion traps) and different combinations of corresponding units are also possible.

[0211] List of Reference Numerals

[0212] 112 box

[0213] 114 box

[0214] 116 box

[0215] 118 box

[0216] 120 box

[0217] 122 box

[0218] 123 Low-resolution microscope image

[0219] 124 box

[0220] 126 Dry sample

[0221] 128 Reflective target

[0222] 130 Predefined reference structure element

[0223] 132 Circle

[0224] 134 Ring

[0225] 136 White area

[0226] 218 System

[0227] 220 Laser desorption mass spectrometer

[0228] 222 Laser source

[0229] 224 Mass analysis unit

[0230] 226 Chamber

[0231] 227 Low vacuum chamber

[0232] 228 High vacuum chamber

[0233] 229 Sample loading chamber

[0234] 230 Arrow

[0235] 231 Ion inlet

[0236] 232 Pulsed laser

[0237] 233 Arrow

[0238] 234 Arrow

[0239] 235 Imaging device

[0240] 236 Mass separation module

[0241] 237 Control device

[0242] 238 Readout electronics

[0243] 248 Station

[0244] 250 Liquid handling system

[0245] 252 Vacuum system

[0246] 254 Pipetting unit

[0247] 256 Region

[0248] 258 Vacuum zone

[0249] 260 First vacuum zone

[0250] 262 Second vacuum zone

[0251] 264 stacks

[0252] 266 microplates

[0253] 268 samples

[0254] 270 microplate holders

[0255] 272 surfaces

Claims

1. A computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer (220), wherein the method comprises: a) at least one imaging step, which includes imaging at least one reflection target (128) by using at least one imaging device (235), wherein the sample containing the at least one analyte is applied to the reflection target (128); b) at least one sample identification step, which includes positioning at least one sample area on the reflection target (128); and c) at least one analyte detection step, which includes using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) with the laser desorption mass spectrometer (220) to detect the at least one analyte in the sample, wherein laser irradiation is applied to the reflection target (128) by using at least one laser source (222) of the laser desorption mass spectrometer (220), so as to generate at least one ion of the at least one analyte, and the at least one ion is detected by using at least one of a mass analysis unit (224) or an ion mobility spectrometry device of the laser desorption mass spectrometer (220), wherein the laser irradiation is guided onto the positioned sample area by using at least one control device (237).

2. The method according to the preceding claim, wherein the method further comprises at least one sample preparation step, and the sample preparation step includes applying the sample to the at least one reflection target (128), and the sample contains the at least one analyte.

3. The method according to any one of the preceding claims, wherein the sample area is positioned on the reflection target (128) by using at least one image evaluation algorithm for the image of the reflection target (128) imaged in step a) by using at least one processing device.

4. The method according to the preceding claim, wherein before performing step c), the image of the reflection target (128) imaged in step a) is transferred to a structuring element.

5. The method according to the preceding claim, wherein in step c), at least one of the following is calculated based on the structuring element: the path of the laser irradiation, the movement path of the reflection target, the movement path of the holder of the reflection target, the laser power, and the laser focus.

6. The method according to any one of the preceding three claims, wherein the image evaluation algorithm includes identifying at least one pattern in the image indicating the sample.

7. The method according to the preceding claim, wherein the reflection target (128) includes at least one predefined reference structuring element (130), and the image evaluation algorithm includes considering information about the predefined reference structuring element (130) for positioning the sample area in the image.

8. The method according to the preceding claim, wherein the image evaluation algorithm comprises at least one pattern recognition algorithm which uses the information about the predefined reference structural element (130) for identifying the pattern in the image indicative of the sample.

9. The method according to any one of the preceding two claims, wherein the information about the predefined reference structural element (130) is used for defining a target region in the image.

10. The method according to any one of the preceding claims, wherein the computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer (220) is performed at least partially automatically.

11. The method according to any one of the preceding claims, wherein the computer-implemented method for detecting at least one analyte in a sample using a laser desorption mass spectrometer (220) is performed fully automatically.

12. The method according to any one of the preceding claims, wherein the reflection target (128) has a specular reflection of ≥ 45%.

13. The method according to any one of the preceding claims, wherein the reflection target (128) has a nominal arithmetic roughness R a ≤ 2 μm.

14. A system (218) comprising at least one laser desorption mass spectrometer (220), wherein the laser desorption mass spectrometer (220) comprises at least one reflection target (128), wherein at least one sample can be applied to the reflection target (128), and wherein the sample contains at least one analyte, wherein the laser desorption mass spectrometer (220) is configured to detect the at least one analyte in the sample using surface-assisted laser desorption ionization mass spectrometry (SALDI-MS), wherein the laser desorption mass spectrometer (220) comprises at least one laser source (222), wherein the laser source (222) is configured to apply a laser irradiation to the reflection target (128) such that at least one ion of the at least one analyte is generated, wherein the laser desorption mass spectrometer (220) comprises at least one of a mass analysis unit (224) configured to detect the ions or an ion mobility spectrometry device, and wherein the system (218) comprises at least one imaging device (235) configured to image the reflection target (128), wherein the laser desorption mass spectrometer (220) comprises at least one control device (237) configured to direct the laser irradiation onto the positioned sample area.

15. A computer program comprising instructions which, when the program is executed by a system (218) according to any one of the preceding claims relating to the system (218), cause the system (218) to perform the method according to any one of the preceding claims relating to the method.

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