10 results about "Plasma samples" patented technology

The application discloses a combined filter for separating plasma from whole blood, comprising a whole blood sample adding chamber, a first combined filter membrane, an intermediate chamber, a second combined filter membrane and a plasma collecting chamber arranged in sequence along a filtering direction of a whole blood sample flow; and the whole blood sample is filtered multiple times through the first combined filter membrane and the second combined filter membrane to obtain a plasma sample. The application further provides a combined filter device and a method for separating plasma from whole blood. The combined filter provided by the application can further improve the recovery rate, recovery quality and recovery efficiency of the whole blood separation plasma, and meets the demand of in-vitro diagnosis on the pretreatment of the whole blood sample.

This invention relates to the field of medical technology, specifically to a method for preoperative risk assessment and prediction in liver transplant patients with hepatocellular carcinoma, comprising the following steps: Sample collection: selecting plasma samples and corresponding clinicopathological information from liver transplant recipients of hepatocellular carcinoma, and clarifying the inclusion and exclusion criteria for samples; Plasma cell-free DNA extraction and whole-genome sequencing: extracting and quality-controlling cell-free DNA from the plasma samples collected in step S1, constructing a sequencing library, and performing low-coverage whole-genome sequencing. This invention utilizes plasma-extracted cfDNA for whole-genome sequencing, combined with clinical testing information, to construct a preoperative risk assessment and prediction model for postoperative recurrence in liver transplant recipients of hepatocellular carcinoma based on non-invasive testing. This model can be used to predict the probability of recurrence-free survival before liver transplantation. The model derivation cohort integrates clinical records and circulating tumor DNA data for preoperative recurrence risk prediction.

The present invention relates to a method for determining whether an unknown blood sample is a serum sample, a citrated plasma sample, or an EDTA-treated plasma sample. The invention also relates to a method for the diagnosis and / or monitoring of a patient suffering from a hemostasis disorder.

The invention discloses a plasma near-infrared spectrum mode recognition method for detecting latent hepatitis B. The method comprises the following steps: S1, collecting spectral data of a plasma sample to be tested in a near-infrared band; s2, acquiring multi-repetition near infrared spectrum data of each sample, and constructing a spectrum data set; s3, grouping samples of a latent hepatitis B infection group and a normal control group in the spectral data set; s4, constructing an OBI-normal control spectrum discrimination model of the plasma sample based on a classifier primitive algorithm; s5, preprocessing parameters are optimized based on the discriminant performance of the classifier; s6, constructing an optimal wavelength combination; and S7, checking the optimal model. Compared with the prior art, the plasma near infrared spectrum mode recognition method for detecting the latent hepatitis B has the advantage that a solution can be provided for developing a small special blood analyzer for detecting latent hepatitis B infection.

The present disclosure relates to an application of gene markers in multi-cancer early detection, a method for constructing an early detection model, and a detection device. In the present disclosure, low-coverage whole-genome sequencing is conducted on cell-free DNAs (cfDNAs) from a plasma sample, and according to high-throughput sequencing results, six differential features of the cfDNA fragments are analyzed for each cancer. Then the training and modeling are conducted with a convolutional neural network to allow the early detection of a plurality of cancers at a low sequencing depth. Then the training and modeling are conducted with a generalized linear model (GLM), a gradient boosting machine, a random forest model, a deep learning model, and an extreme gradient boosting model, and staking is conducted with a GLM to construct a multi-feature algorithm, to allow the tissue-of-origin-based detection of cancers.

The disclosure discloses a method for treating a plasma sample containing (7aS,2′S)-2-oxo-clopidogrel and a method for determining the same, which belongs to the technical field of pharmaceutical analysis and solves the problem in the prior art that there is not yet a method for determining the concentration of (7aS,2′S)-2-oxo-clopidogrel in plasma. The method for treating a plasma sample containing (7aS,2′S)-2-oxo-clopidogrel comprises: taking whole blood containing (7aS,2′S)-2-oxo-clopidogrel, adding a reducing agent solution and collecting plasma. The method for determining (7aS,2′S)-2-oxo-clopidogrel in plasma according to the disclosure uses the treatment method as described above to treat a sample to be determined, and includes the following steps: S1. Whole blood treatment: taking whole blood, adding a reducing agent solution, centrifuging, and collecting plasma; S2. Plasma sample pre-treatment: adding a protein precipitant and an internal standard working solution to the plasma, vortexing and then centrifuging, and taking the supernatant; S3. LC / MS / MS determination. The method of the disclosure is simple, easy to operate, and has good stability, specificity and sensitivity, and accurate determination results.

Disclosed is a method for diagnosing a cancer health state, or a change in cancer health state in a patient, or for diagnosing a risk of the change or presence of a cancer in a patient, comprising determining, in a plasma sample from said patient, one or more biomarker values that correspond to complement protein C8 gamma-containing complex structures, and assigning the patient as having or not having cancer, or having or not having a change in cancer health state, or having or not having a risk of cancer based on said biomarker values, wherein said cancer is preferably lung cancer (LC).

In an aspect, a method comprises obtaining cell-free ribonucleic acid (RNA) from a plasma sample of a subject; converting the cell-free RNA into complementary deoxyribonucleic acid (cDNA), thereby producing sample cDNA; and sequencing the sample eDNA to determine a level of the sample cDNA that corresponds to a set of RNA transcripts.

The application discloses a caliper structure ratio type double-aptamer probe and application thereof, and relates to the field of biomedical technology.The ratio type double-aptamer probe provided by the application realizes oligomer state resolution through a ratio type caliper structure;the probe adopts double-affinity aptamer design, and forms a "caliper structure" through spatial arrangement, can recognize TCR-CD3 monomers and dimers respectively, simultaneously outputs two kinds of fluorescence signals, realizes label-free discrimination of the oligomer state of EVs surface proteins through ratio change, the method is unique, the discrimination ability is strong, the proportion of TCR-CD3 monomers / dimers in complex biological samples can be quickly and effectively detected, has high sensitivity and specificity, can be directly applied to plasma samples, fluorescence ratio signal is read through a microwell plate reader, standardization and batch popularization are facilitated, meanwhile, has high modular compatibility with other aptamers and markers, is suitable for constructing a multi-index joint analysis platform, and has extremely high application potential.