679 results about "Blood specimen" patented technology

The invention discloses a sugar chain marker combination for predicting prognosis of liver cancer transarterial chemoembolization and application of the sugar chain marker combination. The invention discovers and verifies that the combination composed of NA3Fb, NA4Fb and NA4F2b can be used as a novel marker for evaluating TACE treatment reaction and prognosis by analyzing a serum sugar chain map of a liver cancer patient for the first time. Based on the marker combination, a TACE-GT prognosis scoring model and system are established, and the progression risk of a patient within 12 months after a TACE operation can be effectively distinguished by noninvasively detecting the expression levels of three carbohydrate chains in serum of the patient and calculating a specific score. The detection method provided by the invention is based on a blood sample, and has the advantages of noninvasiveness and convenience, and a risk assessment system can provide individualized curative effect prediction and decision support for clinicians before and after TACE treatment, and has important values for realizing precise treatment of liver cancer and improving prognosis of patients.

In some embodiments, a method for classifying elements of a blood sample is provided, the method including: digitally staining an image of the blood sample using a trained machine learning model to generate a digitally stained image; extracting one or more intermediate features generated by the trained machine learning model during the digital staining of the image; providing the one or more extracted intermediate features to a trained multi-class classifier; and employing the trained multi-class classifier to classify at least one element in the blood sample based on the one or more extracted intermediate features. Many other embodiments are also provided.

Analyzers and methods of use are disclosed, including a blood analyzer comprising a light source to transmit an optical signal; a detector to generate data indicative of optical signal intensity; a transparent sample vessel between the light source and the detector; a dispensing device to pass a first portion of the blood sample comprising whole blood or lysed blood into the vessel at a first instance of time, and to pass a plasma portion of the blood sample into the vessel at a second instance of time; a controller to cause a processor to obtain first and second data generated by the detector, the first data indicative of the optical signal passing through the first portion of the blood sample and the second data indicative of the optical signal passing through the plasma, to determine a total absorbance spectrum in which the first data is adjusted by the second data.

A blood cell analyzer (100) and a blood cell analysis method (300). The blood cell analysis method (300) comprises: sucking a blood sample to be tested; preparing a first determination sample and obtaining first optical information; preparing a second determination sample and obtaining second optical information; generating a first leukocyte classification scatter diagram and a second leukocyte classification scatter diagram; determining a first counting result of neutrophils of the to-be-detected blood sample based on the first leukocyte classification scatter diagram and the second leukocyte classification scatter diagram; determining an actual distribution area of neutrophils from the first leukocyte classification scatter diagram; based on a reference distribution region of neutrophils of a reference leukocyte classification scatter diagram of the normal blood sample, determining a leaf-division nucleophore distribution region from the actual distribution region; determining a second counting result of the cells falling into the leaf-separating nucleogranulocyte distribution area; and based on the first counting result and the second counting result, determining a counting result of the rod-shaped nuclear granulocytes in the to-be-detected blood sample.

The invention discloses a prediction marker and a prediction method for acute upper respiratory infection susceptibility. The prediction marker and the prediction method are used for solving the problem that current acute upper respiratory infection susceptibility risk prediction is low in accuracy. The method comprises the following steps: firstly, providing a prediction marker for acute upper respiratory infection susceptibility, wherein the prediction marker is a prediction feature combination obtained by comprehensively considering human health state blood routine data and baseline blood transcriptome data and carrying out feature processing; secondly, providing a prediction method, and obtaining a to-be-detected blood sample; and performing blood analysis based on a to-be-detected blood sample, inputting the obtained blood routine sample and the gene expression sample into a susceptibility prediction model pre-trained based on a prediction marker for susceptibility risk judgment, and obtaining a susceptibility risk assessment result of acute upper respiratory infection of a human body corresponding to the to-be-detected blood sample in a future period of time, therefore, the acute upper respiratory infection susceptibility risk of the human body in a period of time in the future can be simply, quickly and accurately predicted.

Provided are a method for diagnosing cancer, a diagnosis kit and compositions useful for measurement of NK cell activity. The incidence of cancer may be diagnosed by monitoring changes in the in vivo immune system through measurement of NK cell activity in blood. Thus, the incidence of cancer may be readily predicted as described herein using a blood sample from a subject.

The invention relates to the field of drug concentration detection, in particular to a rapid tacrolimus drug concentration detection device based on a micro-fluidic chip. The detection device comprises a blood sampling area, a separation area, a liquid medicine storage area, a waste liquid storage area and a spectrograph, the separation area is used for separating a tacrolimus medicine in a blood sample solution, and a liquid medicine sample and a waste liquid sample are obtained; the spectrograph is used for collecting liquid medicine spectral data of the liquid medicine sample in the liquid medicine storage area and waste liquid spectral data of the waste liquid sample in the waste liquid storage area, and detecting the concentration of the tacrolimus medicine in the blood sample solution according to the liquid medicine spectral data and the waste liquid spectral data. According to the invention, the accuracy of detecting the concentration of the tacrolimus drug in the blood can be improved.

This invention discloses a blood purification device and medical system. The blood purification device includes: a device housing; a blood purifier; a blood tubing assembly, the blood tubing assembly including a first blood tubing connecting a human blood vessel to the inlet of the blood purifier and a second blood tubing connecting the outlet of the blood purifier to the human blood vessel; a power assembly including a blood pump for driving blood flow within the blood tubing assembly, a first replenishment pump for allowing anticoagulant solution to flow into the first blood tubing, and / or a second replenishment pump for allowing calcium solution to flow into the second blood tubing; and a blood component analysis component disposed within the device housing, the blood component analysis component being used to detect collected blood samples. This design facilitates the appropriate adjustment of anticoagulant drugs and calcium ions in the blood purification circuit.

The invention discloses an active tuberculosis diagnostic marker, a kit and application thereof. In particular to application of a reagent for detecting a diagnostic marker in preparation of a kit for diagnosing active tuberculosis, the diagnostic marker is a biomarker TRIM22 in a blood sample, and the sequence of the TRIM22 is as shown in SEQ ID NO: 1. According to the invention, TRIM22 in a blood sample is used as a biomarker for detecting active tuberculosis for the first time. Results of ROC curve analysis show that the expression level of TRIM22 in whole blood has good sensitivity and specificity for active tuberculosis diagnosis. Therefore, the invention overcomes the defects of low detection rate, long time consumption and the like of the existing active tuberculosis diagnosis, has the characteristics of good specificity and high sensitivity, and has good clinical application value for the auxiliary diagnosis of the active tuberculosis.

The invention discloses a method for identifying Yushan black pigs by adopting an SNP (Single Nucleotide Polymorphism) molecular marker technology, and particularly relates to the technical field of molecular detection.The method comprises the following steps: S1, sample preparation: collecting any one of ear tissues, tail tips or blood samples of to-be-detected pig individuals, and extracting to obtain genome DNA (Deoxyribose Nucleic Acid); the genome DNA is used as a template, amplification detection is conducted through a first primer pair, a second primer pair, a third primer pair and a fourth primer pair corresponding to the first SNP site, the second SNP site and the fourth SNP site, and the nucleotide sequences of the first primer pair, the second primer pair and the fourth primer pair are sequentially SEQ ID NO.5-SEQ ID NO.12. By detecting the specific single nucleotide polymorphic sites in the Yushan black pig genome and carrying out genetic typing comparison, the Yushan black pigs and the filial generation thereof can be quickly and accurately identified.

The invention belongs to the field of medical examination equipment, and provides a medical examination sampling device and a use method.The medical examination sampling device comprises a sampling table, a fixed baffle is fixedly installed on the edge of the upper surface of the sampling table, an operation window is formed in the bottom of one end of the fixed baffle, and a fixed groove is formed in the middle of the top end of the sampling table; the conveying mechanism comprises supporting rollers, the supporting rollers are symmetrically and rotationally installed on the two side edges of the inner wall of the fixing groove, the outer surfaces of the supporting rollers are sleeved with a conveying belt, a stepping motor is installed in the middle of one end of each supporting roller, positioning assemblies are arranged on the outer surface of the conveying belt at certain intervals, and limiting clamping pipes are installed on the portions, in the positioning assemblies, of the outer surface of the conveying belt. By means of the automatic separating and collecting structure (the connecting rotary disc, the fixing clamping sleeve and the collecting box), non-contact recycling of blood sampling parts is achieved, direct contact between medical workers and blood samples and sharp tools is reduced, and occupational exposure risks are remarkably reduced.

The invention relates to the technical field of infectious disease detection, and discloses a new respiratory infectious disease early warning method, which comprises the following steps: S1, specimen collection and data collection: collecting biological samples of new respiratory infectious disease virus infected individuals and other respiratory infectious disease virus infected individuals, the biological sample comprises a blood sample and a swab sample; meanwhile, basic information of the individuals is collected, wherein the basic information comprises gender, age and respiratory symptom duration; s2, quantitative detection: the biological sample is subjected to quantitative detection by adopting reagents of various respiratory infectious disease viruses, the detection content comprises antigens and antibodies, and the antibodies comprise an I gM antibody, an I gG antibody and an I gA antibody; according to the invention, basic information of individuals and antigen-antibody detection reagent resources of various respiratory infectious disease viruses are deeply integrated, so that the recognition capability of new respiratory infectious disease virus infected individuals is effectively improved.

The invention discloses a gastric cancer biomarker composition as well as a screening method and application thereof, and belongs to the technical field of bioinformatics. The screening method of the gastric cancer biomarker composition comprises the following steps: firstly, collecting blood specimens of a gastric cancer patient and a healthy control, carrying out high-throughput plasma proteomics detection, and screening out differential expression proteins; and verifying the candidate protein markers by using a prospective queue in the British biological sample library, and finally determining 17 core proteins to obtain the gastric cancer biomarker composition. A gastric cancer risk prediction model is constructed by combining clinical risk factors and protein expression levels of gastric cancer biomarkers. The gastric cancer risk prediction model constructed by the invention can realize accurate layering of gastric cancer risks, decision curve analysis shows that the net benefit of the model is obviously superior to that of a traditional screening method, and an efficient tool is provided for early warning and personalized intervention of gastric cancer.

The invention provides a pathogenic microorganism detection method and system based on a blood sample, and relates to the field of microorganism detection.The pathogenic microorganism detection method comprises the steps that the blood sample is obtained and preprocessed to obtain the preprocessed blood sample; carrying out pathogen separation on the pretreated blood sample through an alternating electromagnetic field to obtain captured pathogens; performing partition amplification on the captured pathogens to obtain amplification products; performing fusion detection on the amplification product through a multi-modal sensor to obtain a detection signal; extracting sequence features from the detection signals, and converting the sequence features into graph nodes; and according to the hypergraph structure, calculating sequence similarity, and performing clustering analysis to obtain an analysis result. The method is used for overcoming the defect of contradiction between the detection flux and the coverage range in the prior art.

The invention relates to a full-automatic blood sample pretreatment experiment device, and relates to the technical field of pretreatment experiment devices, and the full-automatic blood sample pretreatment experiment device comprises a tube rack module which comprises a blood collection tube rack, a centrifugal tube rack, a suction head plate and a reagent bottle rack; the mechanical arm module comprises a carrying mechanical arm and a pipetting mechanical arm which can move in the X, Y and Z directions; the reverse cover pulling module comprises a reverse assembly and a cover pulling assembly; the reversing assembly is used for driving the blood collection tube to rotate in the vertical direction; the cover pulling assembly is used for clamping a blood collection tube; the cap screwing module comprises a cap screwing air bag and a driving assembly, the cap screwing air bag is used for clamping the centrifugal tube, and the driving assembly is used for driving the cap screwing air bag to rotate in the horizontal direction; the vortex module is used for carrying out vortex uniform mixing operation; the centrifugal module is used for conducting centrifugal operation. By arranging the experimental device capable of automatically pretreating the blood sample, the problem that errors are easy to introduce in the prior art is effectively solved, the treatment efficiency is improved, and the experimental requirements of a large number of samples are met.

The invention provides a method and a system for predicting early gastric cancer prognosis by a circulating marker, and relates to the technical field of auxiliary diagnosis. The method comprises the following steps: performing multi-omics detection on a blood sample based on a preset sampling time sequence to obtain a multi-dimensional time sequence characteristic data set containing three groups of heterogeneous data of circulating tumor DNA, exosomes and protein markers; calculating a change slope and a fluctuation variance of the heterogeneous data in adjacent time sequence intervals, constructing a dynamic variation feature matrix in combination with a standard attenuation weighting factor, and deeply mining spatial cross-correlation and sequence dependence features of the matrix to generate a multi-modal fusion feature fingerprint; and performing regression operation on the feature fingerprints by using an integrated learning stack model to obtain a dynamic prognosis risk score, and further retrieving a risk hierarchical mapping table to generate a prognosis evaluation result containing a survival curve. According to the method, multi-modal heterogeneous data can be effectively fused, the biological dynamic characteristics in the tumor postoperative recovery phase are captured, and the accuracy and timeliness of early gastric cancer prognosis prediction are remarkably improved.

The invention discloses a newborn rare disease intelligent screening and diagnosis system based on multi-omics data fusion, relates to the technical field of medical data processing, and aims to solve the technical problems that a traditional diagnosis method is long in time consumption and low in accuracy and cannot meet the requirement for rapid and accurate diagnosis of newborn rare diseases. The data acquisition module is used for acquiring clinical omics data from a doctor's advice database through a neonatal medical record, and acquiring blood samples to acquire gene data and metabonomics data and marking when the medical record records that the neonatal suffers from a rare disease; the data processing module is used for preprocessing the clinical omics data according to the neonatal medical record to obtain a training set and a test set, and preprocessing the gene data and the metabonomics data according to the blood sample; and the diagnosis module is connected with the data processing module. By constructing a three-level modular architecture, the problem of missed diagnosis caused by traditional multi-source data isolated analysis is effectively solved, and the accuracy rate of newborn rare disease diagnosis is remarkably improved.

The invention relates to the field of medical imaging and clinical data machine learning, and discloses an ICAS stroke risk prediction method and system, and the method comprises the steps: carrying out the preprocessing of image data; clinical data such as past medical history, clinical symptoms and family history of the patient are collected; analyzing related biomarkers of the blood sample to obtain biomarker data, and selecting variables closely related to the stroke risk; then carrying out feature splicing to form a multi-modal fusion feature vector; and finally, training, verifying and testing by adopting a machine learning algorithm, and constructing to obtain an ICAS stroke risk prediction model. And based on the ICAS stroke risk prediction model, generating a stroke risk score for each patient, and generating a clinical decision support strategy. The performance of the stroke risk prediction method and system can be improved continuously, accurate risk prediction can be provided in different clinical environments, and accurate stroke risk assessment and targeted treatment schemes can be provided for ICAS patients.

The present invention relates to methods for determining a blood gas parameter and / or a basic metabolic panel parameter in a blood sample comprising combining the blood sample with an anti-coagulant and an anti-platelet agent, and determining said blood gas parameter and / or parameter in the sample. In some aspects, the invention relates to determining said parameters in samples that have been subjected to pre-analytical stress.

A microneedle device comprises a device structure, insertable to a living body and being formed with an opened niche at least partially surrounded by walls of micrometric heights above a base of the niche for allowing the niche to be filled with a blood sample upon the insertion. The device also comprises a biosensor configured to sense a bioanalyte in the blood sample and having a sensing element formed on the base. The thickness of the sensing element is less than the micrometric heights of the walls.

To provide a specimen measurement device and a specimen measurement method that readily confirms the suitability of a sample as platelet-rich plasma.SOLUTION: A specimen measurement device 1 comprises a test section 13 for measuring optical information of platelet-rich plasma and platelet-poor plasma prepared from a blood specimen, a control sections 210 and 213 for acquiring information regarding platelet aggregation of the blood specimen based on the optical information of the platelet-rich plasma and platelet-poor plasma, and a display 4 for displaying information regarding platelet aggregation. The control sections 210 and 213 acquire evaluation information regarding the suitability of the platelet-rich plasma as a sample based on the measurement results of the platelet-rich plasma by the test section 13, and make the display 4 display the information.SELECTED DRAWING: Figure 15

The invention discloses an anticoagulant sample agglutination detection device for hemoglobin analysis, and relates to the technical field of biomedical detection.The anticoagulant sample agglutination detection device comprises a machine shell, a blood collection tube and a machine cover rotationally installed on the machine shell, and further comprises a plurality of laser receiving plates rotationally installed on the machine cover and a light blocking cylinder fixedly installed in the machine shell; a support is installed in the machine shell through a damping support, a motor is fixedly installed on the support, a rotating disc is rotatably installed on the support, a storage disc is fixedly installed on the rotating disc, and a plurality of sets of tube frame stations used for storing blood collection tubes are installed on the storage disc. The method has the advantages that the centrifugal light transmittance is adopted to detect the agglutination condition in the blood sample, multiple batches of samples can be detected at a time, the detection efficiency is higher, the detection has higher real-time performance, the detection result is more accurate, the horizontal position of agglutination can be judged, and the type of agglutination can be judged according to the agglutination position.

The invention discloses a tacrolimus detection kit and application thereof. The tacrolimus detection kit comprises a reagent R1, a reagent R2, a reagent R3, a standard substance, a reagent tube A, a reagent tube B, a reagent tube C and a freeze-drying bottle, wherein the reagent tube A, the reagent tube B, the reagent tube C and the freeze-drying bottle are respectively used for the reagent R1, the reagent R2, the reagent R3 and the standard substance; the reagent R1 is a magnetic bead antibody working solution; the reagent R2 is an enzyme-labeled antigen working solution; the reagent R3 is a blood sample treatment solution, which is a TBS buffer solution containing EDTA-2Na (Ethylene Diamine Tetraacetic Acid), a zinc sulfate solution, Triton X-100 and ProClin300; the standard substance is a freeze-dried whole blood standard substance containing tacrolimus. According to the tacrolimus detection kit and the application thereof, the general blood sample treating fluid is adopted, so that the reliability and the stability of a detection result of tacrolimus in a blood sample are improved.

The invention relates to the technical field of biological detection, and discloses a method for double-ring detection of lung cancer L858R mutation based on CRISPR / Cas9 and DNA, and the method comprises the following steps: enriching circulating tumor cells CTC from a blood sample; extracting genomic DNA (deoxyribonucleic acid) of the enriched CTC; carrying out amplification on the DNA fragment containing the L858R mutation by adopting recombinase polymerase amplification RPA (recombinase polymerase amplification); the amplified DNA fragment is hybridized with a recognition ring in a DNA double-ring structure, a DNA double ring is composed of the recognition ring and a report ring, and a part of region of the recognition ring is hybridized with a corresponding fragment of the report ring to form a staggered double-chain region; when L858R mutation exists, the mutated DNA and a recognition ring are hybridized to activate a CRISPR / Cas9 system, and under the guidance of sgRNA, Cas9 cuts hybrid double strands and releases a report ring; carrying out rolling circle amplification RCA under the action of DNA polymerase by taking the released report ring as a template; a fluorescent probe is used for detecting an RCA amplification product, and whether L858R mutation exists or not is judged according to a fluorescence signal. The CRISPR / Cas9 system is combined with a DNA double-ring structure, so that the ultra-sensitive and specific detection on the lung cancer L858R mutation is realized.

In the blood spherical red blood cell parameter, the detection method and the identification AI training method thereof, a blood sample is preprocessed to obtain a microscopic examination sample, and the microscopic examination sample is tiled; a tiled microscopic examination sample image is shot, normal red blood cells and spherical red blood cells are recognized and labeled, labeled pictures are obtained and subjected to AI training, and an obtained AI feature data set A comprises normal red blood cell features and an obtained AI feature data set A comprises spherical red blood cell features. Identifying the microscopic examination sample image by using an AI identification algorithm, identifying spherical red blood cells in the blood sample in a selected area S1 of the image, and obtaining the total number NUMS1 of the spherical red blood cells in the blood sample in the selected image; the AI recognition algorithm recognizes the spherical red blood cells in the blood sample according to the feature data set including the spherical red blood cells. The AI training data collection efficiency is improved through diversified means, and the AI evolution efficiency is improved. Spherical red blood cell recognition is completed through advanced AI computing power, analysis is more efficient, and accuracy is higher.

The invention discloses a thrombelastogram calibration method, device, system and equipment and a storage medium, and the method comprises the steps: generating an initial thrombelastogram in a process that a blood sample rotates along with a container, through a mechanical torsion signal which drives a suspension wire to move in and after a process that the blood sample forms a blood clot, and collecting the initial thrombelastogram through a mechanical sensor; the method comprises the following steps: generating a light intensity time change chart through near-infrared light signals collected by a spectrograph, and extracting an attenuation rising rate representing a blood sample coagulation rate, an attenuation value representing blood sample coagulation intensity and an attenuation recovery rate representing fibrinolysis after blood sample coagulation, so as to calibrate an initial thromboelastogram and obtain a calibrated thromboelastogram. Therefore, on the basis of the thrombelastogram measured on the basis of the mechanics principle, the attenuation signal measured by the near-infrared optical principle is utilized to calibrate the thrombelastogram, the influence of non-coagulation factor interference on only mechanical signals is reduced, and the accuracy and the reliability of generating the thrombelastogram are improved.

The application discloses application of a product for detecting metabolite levels in serum in preparation of a preparation for diagnosing systemic lupus erythematosus (SLE) and SLE patients with different organ involvement phenotypes and a reagent. The application first uses specific serum biomarkers to assist in screening SLE, SLE with different disease activity and SLE patients with different organ phenotypes, including only kidney involvement systemic lupus erythematosus (KI), only skin involvement systemic lupus erythematosus (SI), only blood system involvement systemic lupus erythematosus (BI) and multi-system involvement systemic lupus erythematosus (MI), thereby opening up a new way for the diagnosis of the field and helping to more accurately diagnose and evaluate the disease progression of SLE. The blood specimen required is small, easy to carry out and has a good application prospect.

The application discloses a blood sample image intelligent recognition and classification system based on computer vision, relates to the technical field of pathological image analysis and computer vision, and comprises the following steps: acquiring an original collected image and performing nonlinear concentration mapping to generate a biochemical layered image containing measured concentration data; locking a cell center and dividing an initial jurisdiction through center response calculation to construct an ideal simulation single-cell layer; calculating a difference image of a simulation superimposed image and a measured image, iteratively correcting the simulation layer in a reverse direction by using concentration difference data until an independent single-cell layer containing recovered texture is obtained; and finally generating an overlapping complexity weight map based on the difference image, constructing a multi-dimensional feature data packet and inputting the multi-dimensional feature data packet into a convolutional neural network to output a classification result; the application effectively solves the recognition problem caused by cell overlapping in high-density samples by combining physical model decoupling with deep learning.

The invention provides a computer-implemented method and system for non-invasive and step-by-step prediction of cancer risks and a storage medium. The method comprises the following steps: (1) determining a cancer signal score based on the level of a biomarker in a blood sample of a subject; (2) comparing the cancer signal score with a preset threshold value, and determining a primary screening positive subject; (3) further performing cancer risk determination and cancer species prediction by adopting an NGS method on the basis of the primarily screened positive subjects; wherein the biomarker is selected from at least one of AFP (Alpha Fetal Protein), CA125, CA15-3, CA19-9, CA72-4, CEA (Carcino Embryonic Acid), CYFRA (Cytochrome Factor Receptor Amplification) 21-1, ProGRP (Proso-Growth Radical Polymerase Chain Reaction), SCCA (Sequence