564 results about "Serum samples" patented technology

The invention relates to a construction method of a metabolic syndrome phlegm syndrome lipid metabolism characteristic diagnosis model. The construction method comprises the following steps: S1, acquiring a serum sample; s2, carrying out lipid metabolite analysis through a full-quantitative lipidomics formula; s3, carrying out primary screening on differential metabolites; s4, optimizing the characteristic indexes by using a random forest algorithm and stepwise regression; and S5, constructing a differential metabolite diagnosis model through Logistic regression analysis. By analyzing differential lipid metabolites of patients with MetS phlegm syndromes and non-phlegm syndromes, the invention reveals that abnormal accumulation of lipid and lipid metabolites may be the core pathological parenchyma of MetS phlegm syndromes. By integrating lipid metabonomics data, using a random forest algorithm, stepwise regression and other methods to screen feature difference lipid metabolites and construct a MetS phlegm syndrome specific diagnosis model, a novel combined biomarker and evidence-based basis are provided for early diagnosis of MetS phlegm syndromes, and a scientific basis can also be provided for objective diagnosis of traditional Chinese medicine phlegm syndromes.

The invention discloses an African swine fever virus p30 protein antibody and application thereof. When the African swine fever virus p30 protein antibody is used for a competitive ELISA method, a serum sample with the p30 antibody after African swine fever virus infection can be rapidly and accurately detected, the detection time is shortened, the detection steps are simplified, the African swine fever virus p30 protein antibody has the characteristics of rapidness and high-throughput detection, and a reliable immunological technology is provided for rapidly and efficiently detecting African swine fever virus infection.

The invention relates to a method for acquiring a biomarker for assisting CRLM early diagnosis. The method comprises the following steps: acquiring sequencing data, clinical information and metabonomics characteristics of a CRC sample; evaluating and determining a plurality of differentiated machine learning models; performing classification according to the determined machine learning model, and constructing a CRLM biomarker prediction model; screening candidate biomarkers according to the prediction model; and verifying the candidate biomarker at least according to the tissue slice and the serum sample, and determining a final biomarker.

The invention belongs to the technical field of liquid chromatography-mass spectrometry detection pretreatment, and particularly relates to a pretreatment method for liquid chromatography-tandem mass spectrometry analysis of pesticide and veterinary drug residues in serum, which comprises the following steps: (S1) carrying out heating reaction on Sc (III) salt, Cu (II) salt and 1H-pyrazole-4-formic acid (H2PyC) in a polar aprotic solvent, and cooling to obtain a green crystal, namely MOF-919; the chemical formula of the MOF-919 is [Sc < 3 > (mu3-O) (OH) < 3 >] [Cu3 (mu3-O) (mu-PyC) < 3 > (H2O) < 6 >] < 2 >; (S2) mixing the serum sample with an acetonitrile solution containing formic acid, carrying out ultrasonic treatment, vortex oscillation and centrifugation, taking supernate, and diluting the supernate with an aqueous solution containing formic acid to obtain a to-be-purified solution; and (S3) adding MOF-919 into the to-be-purified liquid, mixing, performing ultrasonic treatment, performing vortex oscillation, centrifuging, and taking supernate, thereby completing the pretreatment of the to-be-purified liquid. According to the method, the MOF-919 is used for adsorbing chemical pollutant residues in serum, especially phospholipids, so that the purpose of removing the chemical pollutant residues in blood is achieved. The method is simple and convenient to operate, small in organic solvent consumption and good in purification effect, and can be widely applied to residue analysis of chemical pollutants in serum.

An exemplary machine learning-based system and method are disclosed for a clinical tool that can provide a comprehensive prediction of ovarian cancer propensity using metabolite and metabolomic profiles acquired from ultra-performance liquid chromatography, high-resolution mass spectrometry (UPLC-MS) analysis. Each serum sample may be independently processed through two different columns (HILIC and C18 reversed phase). Different ionization modes (negative and positive) may be used. The clinical tool can validated to provide successful prediction of ovarian cancer by over 90%. Ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS / MS) and the like can be used.

The invention discloses a method and equipment for detecting oxidized low-density lipoprotein based on immunoturbidimetry, and the method comprises the following steps: preparing a macroinitiator by active esterification reaction, and preparing a block graft copolymer by atom transfer radical polymerization and radical grafting reaction; the preparation method comprises the following steps: carrying out surface modification on latex microspheres with different particle sizes by using a grafted copolymer, and then respectively coupling the microspheres with different particle sizes with different OxLDL monoclonal antibodies so as to prepare a double-particle-size latex microsphere marker; and mixing the serum sample with the double-particle-size latex microsphere marker, measuring an absorbance value, and calculating the concentration of the oxidized low-density lipoprotein in the serum sample according to a standard curve established on the basis of the standard substance solution. According to the scheme, the stability of the latex microsphere marker can be enhanced, and the binding efficiency of the latex microsphere marker and ox-LDL can be improved.

The invention provides a method for detecting an external vesicle marker through high-flux nano plasma exciting light immune color development, and belongs to the technical field of human extracellular vesicles. After a serum sample is subjected to centrifugal treatment, the serum sample and a CD81 capture antibody substrate are incubated, and the particle size distribution of the vesicles is monitored in real time; a zwitterionic polymer modified gold nanoparticle LAM detection probe and a polyethylene glycol modified silver nanoparticle LprG detection probe are prepared to be specifically combined with a vesicle surface antigen, a chromogenic enhancement solution is adopted to induce a plasma resonance signal, and full-hole scanning imaging is carried out; and constructing a double-layer game optimization model to cooperatively optimize the detection sensitivity and the signal stability, carrying out weighted summation on normalized signals of the particle size subgroups to obtain comprehensive detection signal intensity, comparing the comprehensive detection signal intensity with a threshold value, and outputting a final judgment result. The technical problem that quantitative accuracy is affected by signal intensity deviation caused by vesicle particle size difference in outer vesicle marker detection is solved.

The invention provides a metabolite qualitative annotation quality evaluation method based on high-resolution mass spectrum simulation. The metabolite qualitative annotation quality evaluation method comprises the following steps: collecting human serum sample mgf data measured by different instrument platforms; determining the distribution characteristic and the intensity mode of the mass-to-charge ratio; constructing a high-resolution mass spectrum data model based on mass spectrum characteristic quantity, adjacent m / z difference and intensity distribution; constructing a high-resolution mass spectrum simulation database of hundreds of thousands of metabolites with similarity and difference; constructing a strong interference strategy and a weak interference strategy, and simulating mass spectrum data change possibly encountered in an actual experiment; searching and evaluating an undetermined property spectrum under the interference model by adopting eight similarity evaluation methods; factor level analysis and range analysis are adopted to deeply discuss the internal relation between the scoring algorithm and the mass spectrum characteristics.

The present invention relates to a method for quantitatively analyzing the concentration of lencanezumab in blood based on liquid chromatography-tandem mass spectrometry, wherein a serum sample is pretreated to obtain a characteristic peptide segment, and the characteristic peptide segment is quantified by an internal standard method combined with liquid chromatography-tandem mass spectrometry technology, thereby quantifying the content of lencanezumab in blood. The method of the present invention detects the concentration of lencanezumab with high sensitivity and high specificity, and the accuracy and precision meet the requirements. It can be used for the quantitative analysis of lencanezumab in serum, and provides a reliable detection method for monitoring the concentration of lencanezumab, thereby guiding its clinical use.

The invention relates to a serum liquid chromatography-tandem mass spectrometry pretreatment method, which comprises: (S1) mixing a serum sample and a formic acid-containing acetonitrile solution, carrying out ultrasonic treatment, vortex oscillation and centrifugation, taking the supernatant, and diluting with a formic acid-containing aqueous solution to obtain a liquid to be purified; (S2) mixing the to-be-purified liquid with PCN-777, performing ultrasonic treatment, vortex oscillation and centrifugation, and taking supernate to obtain to-be-detected liquid; the PCN-777 is a C24H23N3O16Zr3 phospholipid removal material, and the PCN-777 is a C24H23N3O16Zr3 phospholipid removal material, and the PCN-777 is a C24H23N3O16Zr3 phospholipid removal material. According to the present invention, the serum ultra-high performance liquid chromatography-tandem mass spectrometry pretreatment method is developed by using the known MOFs material PCN-777, such that different types of phospholipids in the serum can be specifically, rapidly and effectively removed, the efficient recovery and detection of pesticide and veterinary drugs can be achieved, and the interference of phospholipids can be avoided.

The invention discloses an indirect ELISA (Enzyme-Linked Immunosorbent Assay) detection kit for distinguishing host infected Listeria monocytogenes and / or Listeria ivanovii. The coating antigens are respectively a recombinant listeria monocytogenes surface protein ActA, a serotype 4h listeria monocytogenes and listeria ivanovii common outer membrane protein SmcL and a listeria ivanovii specific outer membrane protein I-inlH, indirect ELISA methods are respectively established based on the three antigens, the three detection methods are combined to detect the content of the listeria monocytogenes, and the content of the listeria ivanovii can be detected. The levels of the ActA antibody, the SmcL antibody and the I-inlH antibody in a clinical serum sample can be effectively monitored, and the detection on the listeria monocytogenes caused by the listeria monocytogenes and / or the listeria ivanovii is realized. The kit is relatively high in sensitivity, strong in specificity and good in stability, and an effective method is provided for epidemiological investigation and diagnosis of listeria monocytogenes.

The invention belongs to the technical field of immunology, and particularly relates to an anti-mandarin fish immune globulin D (IgD) monoclonal antibody as well as a preparation method and application thereof. The invention provides a hybridoma cell strain 5C7 capable of secreting an anti-fish IgD monoclonal antibody or an antigen binding fragment thereof for the first time, the hybridoma cell strain 5C7 is preserved in China Center for Type Culture Collection on January 16, 2025, and the preservation number is CCTCC NO: C202550. The anti-mandarin fish IgD monoclonal antibody or the antigen binding fragment thereof can be subjected to specific reaction with mandarin fish secreting type IgD protein and B cell surface film type IgD, can be applied to detection of IgD in a mandarin fish serum sample, and can also be applied to detection of IgD + B cell surface markers.

The invention discloses an application method of a serum Raman spectrum as a biomarker in cognitive impairment diagnosis, a cognitive impairment diagnosis system is used for diagnosis, the cognitive impairment diagnosis system comprises a Raman spectrum detection and preprocessing module, a database module and a cognitive diagnosis module, and the application method comprises the following steps: step 1, collecting a sample; step 2, pre-treating a sample; 3, collecting and preprocessing a serum sample by using a Raman spectrum detection and preprocessing module; 4, performing model construction and optimization by utilizing a database module; step 5, performing efficiency evaluation; and 6, performing cognitive grading diagnosis on the new sample by using a cognitive diagnosis module. The method has remarkable technical progress, no cognitive impairment diagnosis blood test method suitable for the whole crowd exists clinically at present, cognitive impairment can be diagnosed through the Raman spectrum of serum, detailed cognitive function grading can be carried out, and the cost of a single sample is less than 100 yuan.

The invention provides a lactic acid electrochemical sensor LDHamp; the invention relates to construction of BiNPs (at) MWCNTs / GCE and a serum lactic acid detection method, and belongs to the technical field of biosensors, the method comprises the following steps: taking sodium citrate, Bi (NO3) 35H2O and NaBH4 as raw materials, synthesizing BiNPs through a multi-step reaction, compounding the BiNPs with MWCNTs, carrying out carboxyl activation and loading LDH, and finally modifying on a glassy carbon electrode to obtain the sensor. During detection, the sensor is placed in a PBS system containing 5mM of NAD, a serum sample is added, and the concentration of lactic acid is measured by electrochemical scanning according to current response change. According to the method, the detection linear range is 0-200 [mu] M, the detection limit is as low as 0.03 [mu] M, the detection difference of different batches of sensors is small, the method shows the advantages of high sensitivity and good stability, meanwhile, efficient and accurate detection of lactic acid in serum is achieved, and powerful support is provided for clinical diagnosis and disease research.

The invention relates to the technical field of spectral analysis and biomedical detection, and discloses an SERS (Surface Enhanced Raman Scattering) spectrum quantitative detection method and system based on interpretable stacked ensemble learning. The method comprises the following steps: acquiring SERS spectral data of serum tumor marker standard substances with different concentration gradients; performing baseline correction and normalization preprocessing on the data, performing sparse feature selection by using an LASSO algorithm, and screening out key spectral features to construct a sample data set; constructing an interpretable stacking integration model, wherein the model adopts a base learner layer and a meta learner layer; training the model by using the training set, optimizing model hyper-parameters by using a cross validation strategy, and establishing a mapping relationship between spectral features and tumor marker concentrations; and collecting SERS spectral data of a to-be-detected serum sample, extracting key spectral features, inputting the key spectral features into the trained interpretable stacked integrated model, and outputting a concentration predicted value of the tumor marker in the to-be-detected serum sample. The method has the advantages of high precision, universality and molecular level interpretability.

The invention discloses a method for detecting L-cysteine in serum based on N, S co-doped carbon nanodots, and belongs to the field of analysis and detection. The method comprises the following steps: (1) preparing carbon dots by taking beta-mercaptoethylamine and p-phenylenediamine as precursors; (2) after Fe < 3 + > is added into the carbon dot solution, a carbon dot fluorescence quenching phenomenon occurs, and a carbon dot-Fe < 3 + > mixed system is obtained; then adding L-cysteine into the carbon dot-Fe < 3 + > mixed system to gradually recover the fluorescence of the system; and (3) constructing a linear relationship between the concentration of the L-cysteine and the fluorescence recovery degree to obtain the quantitative detection model for the L-cysteine in the serum sample. According to the method, the carbon dots are prepared by taking beta-mercaptoethylamine and p-phenylenediamine as precursors for the first time, quantitative detection of L-cysteine is realized, and the method is low in cost, high in sensitivity, suitable for field rapid detection and relatively high in practical value and popularization prospect.

The invention provides a gouty arthritis diagnosis and detection kit prepared based on ceRNA, and relates to the field of nucleic acid determination kits, the gouty arthritis diagnosis and detection kit comprises a water bath tank, a mixing mechanism, an anti-blocking structure and a flow guide assembly, a top plate is inserted in the top of the water bath tank, a cover plate is hinged to the other side of the top of the water bath tank, a water injection pipeline is inserted in the bottom of the side edge of the water bath tank, and the water injection pipeline is hinged to the other side of the top of the water bath tank. According to the present invention, with the help of the two mixing sleeves in the mixing structure, the diluent and the serum sample are subjected to reciprocating flow, and the diluent and the serum sample are subjected to heat transfer with the synchronously stirred warm water during the flowing process, such that the diluent and the serum sample can be subjected to heat transfer so as to achieve the rapid detection; therefore, the water temperature of each part in the water bath tank can be ensured to be consistent, a large amount of diluted serum samples can be quickly heated, the pretreatment efficiency is improved, the number of detection test tubes for injection can be flexibly controlled, the water bath tank and the mixing mechanism part can be repeatedly utilized, and the equipment cost is reduced.

The invention belongs to the technical field of biological detection, and particularly relates to a method for synchronously and quantitatively detecting various folic acid metabolism related substances in trace plasma or serum, which comprises the following steps of: detecting a pretreated trace plasma or serum sample by adopting a liquid chromatography-tandem mass spectrometry method; the following nine folic acid metabolism related substances are synchronously and quantitatively detected: 5-formyl tetrahydrofolic acid, folic acid, 5-methyl tetrahydrofolic acid, S-adenosine-L-methionine, S-adenosine-L-homocysteine, vitamin B12, pyridoxamine, pyridoxine and pyridoxal. The invention further relates to application of the detection method in related detection of child neurodevelopment. According to the detection method, only trace plasma or serum is used, methotrexate is used for replacing an expensive isotope internal standard for more economical detection, and nine folate metabolism related substances can be accurately quantified at the same time. Therefore, the detection method disclosed by the invention has important clinical significance and wide market application prospect.

The invention provides a construction method and system of a chronic hepatitis B liver tissue inflammation grading prediction model and application. The construction method of the chronic hepatitis B liver tissue inflammation grading prediction model comprises the following steps: S1, screening out a plurality of patients which are diagnosed as chronic hepatitis B through liver tissue biopsy pathology and have clear liver tissue inflammation grading according to inclusion and exclusion standards, and collecting clinical data and serum samples of the patients; s2, performing serum protein N-carbohydrate chain fingerprint spectrum difference analysis on the serum samples of the patients with different ALT levels by adopting an N-carbohydrate fingerprint spectrum technology; s3, on the basis of conventional biochemical indexes and / or N-sugar markers, constructing liver tissue inflammation grading evaluation models under different ALT levels by adopting a binary logistic regression analysis method; and S4, respectively evaluating and selecting the model with the optimal efficiency as a chronic hepatitis B liver tissue inflammation grading prediction model. The chronic hepatitis B liver tissue inflammation grading method can be used for quickly, accurately and noninvasively grading the chronic hepatitis B liver tissue inflammation.

The present invention relates to a pretreatment method for serum liquid chromatography-tandem mass spectrometry analysis, comprising the following steps: (S1) mixing a serum sample with an acetonitrile solution containing formic acid, ultrasonicating, vortexing, and centrifuging, taking the supernatant and diluting it with an aqueous solution containing formic acid to obtain a liquid to be purified; (S2) mixing the liquid to be purified with PCN-777, ultrasonicating, vortexing, and centrifuging, taking the supernatant and obtaining a liquid to be tested; the PCN-777 is C 24 H 23 N3O 16 Zr3 phospholipid removal material, the PCN-777 is C 24 H 23 N3O 16 Zr3. The present invention uses a known MOFs material PCN-777 to develop a pretreatment method for serum ultra-high performance liquid chromatography-tandem mass spectrometry analysis, which can specifically, quickly and effectively remove different types of phospholipids in serum, and achieve efficient recovery and detection of pesticides and veterinary drugs, avoiding interference from phospholipids.

The invention discloses a terahertz metamaterial sensing device and a blood glucose concentration detection method, and belongs to the field of terahertz science and technology. The terahertz metamaterial sensing device comprises an upper-layer asymmetric arc-shaped silicon column array and a lower-layer silicon substrate; the asymmetric arc-shaped silicon column array is composed of a plurality of arc-shaped silicon column unit structures with one long arc-shaped silicon column unit structure and one short arc-shaped silicon column unit structure. The long arc-shaped silicon column and the short arc-shaped silicon column have the same circle center and radius, and the arc length of the long arc-shaped silicon column is longer than that of the short arc-shaped silicon column; 3-aminopropyltriethoxysilane and glucose oxidase are used for carrying out surface functional modification on the asymmetric arc-shaped silicon column array and the silicon substrate. The device can be used for sensing and detecting blood glucose in a clinical serum sample, the concentration information of the blood glucose in the sample is obtained through the frequency shift of the resonance peak of the device, and the real-time, label-free and nondestructive detection of the sample is realized while the detection sensitivity is improved.

The invention relates to the field of biological detection, in particular to application of IGSF1 protein as a cardiac function recovery marker. The invention provides application of protein as a marker in preparation of a product for detecting and / or diagnosing heart failure with improved ejection fraction. The protein comprises one or more of IGSF1, LIMS1, MPP1, PTX3, SLC2A3, FERMT3, ARPC1B, IGHG1, PTGS1, ACTN1 and RTN4, and is characterized in that the protein comprises one or more of the IGSF1, the LIMS1, the MPP1, the PTX3, the SLC2A3, the FERMT3, the ARPC1B, the IGHG1 The invention provides a novel serum marker, the expression level of the novel serum marker can predict heart failure patients with reduced ejection fraction and heart function recovery potential with high precision, and the change of the novel serum marker is earlier than the change of ejection fraction. According to the invention, a non-invasive standardized detection process based on a serum sample is established, all levels of medical institutions are adapted, and early and non-invasive prediction of the heart function recovery potential of the heart failure patient is realized.

The invention discloses a stem cell metabolism marker omics analysis method, device, equipment and medium, relates to the technical field of biomedicine, is applied to a computer device, and comprises the following steps: carrying out non-targeted detection on a to-be-detected sample of a target object to obtain an original mass spectrum; wherein the sample to be detected is a serum sample or a cell sample; preprocessing the original mass spectrogram to obtain a metabolite matrix in a standardized format; performing principal component analysis and partial least square discriminant analysis on the metabolite matrix, and determining a metabolic marker from the metabolite matrix according to an obtained analysis result; obtaining fragment information of the metabolic marker based on a collision-induced dissociation mode, and searching for a structural annotation of the metabolic marker from a human metabolome database based on the fragment information; and constructing a metabolic pathway map of the metabolic marker according to the structural annotation of the metabolic marker. The accuracy of omics analysis of the stem cell metabolism marker is improved.

The present invention provides a homocysteine ​​electrochemical sensor, and its preparation method and application. The preparation method of the homocysteine ​​electrochemical sensor of the present invention comprises the following steps: adding a dispersion containing carbon nanomaterials to the surface of a glassy carbon electrode, baking and drying, to obtain a carbon nanomaterial-modified electrode; then placing the carbon nanomaterial-modified electrode in a gold salt aqueous solution, and using an electroplating method to deposit nanogold on the surface of the carbon nanomaterial-modified electrode, to obtain a homocysteine ​​electrochemical sensor; the high conductivity of gold nanoparticles is of great significance for improving the electrocatalytic performance of the composite material for homocysteine. The homocysteine ​​electrochemical sensor prepared by the present application has low cost, low detection limit, and good stability. In addition, the spiked recovery rate of homocysteine ​​in serum samples is good, which provides potential application value for the reliable determination of homocysteine ​​in biological systems and the study of homocysteine-related diseases.

The invention discloses a kit for detecting Abeta1-40 protein as well as a preparation method and application of the kit. The invention provides a reagent for detecting Abeta1-40 protein. The reagent contains magnetic beads coupled with a capture antibody and / or a detection antibody labeled with fluorescent microspheres, the magnetic bead coupled with the capture antibody contains an A beta 1-40 protein capture antibody and a magnetic bead, and the diameter of the magnetic bead is 1.0-3.0 [mu] m; the detection antibody marked with the fluorescent microspheres contains an A beta 1-40 protein detection antibody and the fluorescent microspheres, and the diameter of the fluorescent microspheres is 190-400 nm. According to the present invention, the Abeta1-40 in the serum sample can be rapidly detected, the sensitivity is high, the repeatability is good, the sensitivity can achieve 0.12 pg / mL, and the data dispersion degree CV value can achieve 3.2%; the serum can be used as a sample for detection, the sample source is simple and easy to obtain, detection can be performed without living body puncture, and the use process is simple and convenient.

The present invention relates to the technical field of serum image analysis, and in particular to a serum abnormal state identification method, system and storage medium based on image analysis, comprising the following steps: using OCT technology to image the serum sample to be analyzed, and obtaining multi-level serum image data; performing hierarchical image segmentation on the collected multi-level serum sample image; establishing a mathematical model to analyze and standardize the optical and biochemical properties of the serum sample, and then extracting key features; based on the extracted key features, applying pattern recognition technology to distinguish normal and abnormal biochemical indicators, thereby identifying abnormal states in serum; and displaying the identified abnormal state in a graphical user interface, including information on the abnormal type and severity. The present invention, by combining the analysis of spectral characteristics and scattering characteristics, can comprehensively consider a variety of physical and chemical information in the serum sample, and enhance the sensitivity and recognition ability to abnormal states.

The invention discloses an active tuberculosis diagnosis method based on proteomics and metabonomics. The method comprises the following steps: collecting a serum sample of a suspected active tuberculosis patient; detecting specific proteins in the serum sample by using a proteomics technology; detecting specific amino acids in the serum sample by using a metabonomics technology; carrying out standardization treatment on the obtained protein, amino acid and bile acid data; establishing a diagnosis model by using a machine learning algorithm; inputting data of a to-be-diagnosed sample into the model, and calculating a probability value of the to-be-diagnosed sample suffering from active tuberculosis; according to a preset threshold value, whether the sample provider suffers from the active tuberculosis or not is judged. By comprehensively analyzing multiple omics data, the sensitivity and specificity of diagnosis are greatly improved; by utilizing a machine learning algorithm, the disease risk can be objectively and quantitatively evaluated, and human misjudgment is reduced; the detection process is simple and fast, the sample demand is small, and clinical popularization and application are facilitated.

The invention provides a method for detecting the blood concentration of elacycline in serum. The method comprises the following steps: pretreating a human serum sample; then detecting by adopting liquid chromatography-mass spectrometry, wherein a liquid chromatography condition mobile phase comprises ultrapure water (a mobile phase A) containing 0.1% of formic acid and acetonitrile (a mobile phase B); the temperature of the chromatographic column is kept at 45 DEG C, and the sample size is 2L; the flow velocity of the mobile phase is set to be 0.3 mL / min, and the total operation time is 4.5 minutes; in mass spectrum conditions, a positive electrospray ionization mode is adopted, multiple reaction monitoring (MRM) is adopted, and multi-reaction monitoring is adopted as a scanning mode. The method is high in sensitivity, the lowest quantitative concentration can reach 50 ng / mL, and accurate, rapid and sensitive determination of the elacycline in the human serum can be realized.

The invention discloses a cadmium ion and lead ion detection system and method based on CRISPR and deoxyribozyme, and the method comprises the following steps: forming active deoxyribozyme by using target ions and a recognition probe, cutting a redundant sequence in a substrate probe, releasing a semi-activator, and cooperatively activating the activity of CRISPR-Cas12a with the other semi-activator in the system. According to the system, the signal-to-noise ratio and the sensitivity of detection are improved by utilizing the effect of inhibiting cooperative activation by redundant fragments in semi-activators. According to the detection method, nano material modification on the substrate probe is not needed, magnetic separation is not needed, and the detection cost is reduced. The detection process only needs two steps of room temperature incubation reaction, and the two steps are carried out in one reaction tube, so that cross contamination possibly caused by multi-tube reaction is avoided, and the detection process is simplified. The method can be applied to detection of cadmium ions and lead ions in rice or serum samples, and has wide application prospects in the fields of food safety, medical detection and the like.

The invention relates to the technical field of pathogen detection, in particular to a rapid pathogen detection system based on nanopore sequencing, which comprises an acquisition and pretreatment module, which is used for precipitating and centrifuging serum, carrying out layered monitoring, carrying out supernate separation and concentration, and measuring pH value and temperature. According to the invention, the serum is precipitated and centrifuged, and layered monitoring is combined, so that the layered state of the serum sample in the centrifugation process is visualized, and the stability of precipitated particles and the separation precision of supernate are improved. And in the supernatant concentration link, the dynamic monitoring and optimization of the sample purity are realized by measuring the pH value and the temperature and combining the recording of the protein concentration and the turbidity value. Absorbance and viscosity measurement are combined, so that the change of liquid properties can be captured in real time and compared with a pathogen directory range threshold value, and an abnormal sample can be recognized in an early stage.