24 results about "Protein abundance" patented technology

The present disclosure relates to compositions and methods to modulate the level of expression of a protein in a deliberate manner (i.e., tunable regulation of expression) with only a minimal change to the genetic sequence of the gene of interest. The present disclosure therefore also provides compositions and methods to predictably alter protein abundance.

The present application provides a base model processing method and device for single-cell proteome detection data, which comprises: obtaining single-cell proteome detection data, uniformly processing protein identification information, and standardizing protein abundance data according to detection technology types to obtain uniformly distributed protein expression data; mapping relevant information into identification and abundance embedding vectors respectively and fusing them, adding a special marker vector to construct cell sequence data; inputting the cell sequence data into a base model for pre-training, optimizing parameters through a mask reconstruction and global prediction task to obtain a pre-training model; and fine-tuning the model for a target analysis task, analyzing and processing to-be-processed data to obtain downstream results. The present application can integrate single-cell proteome data of different detection technologies and batches, effectively remove batch effects, extract stable cell low-dimensional representations, support multi-downstream task fine-tuning, realize undetected protein inference and cell trajectory analysis, and improve data utilization efficiency and task adaptability.

This invention discloses a polypeptide that specifically binds to the RNA-binding domain of the PRMT5 protein and its applications, belonging to the field of biomedical technology. The polypeptide specifically binds to the RNA-binding domain of the PRMT5 protein, and its amino acid sequence includes sequence A or sequence B. Sequence A is: LTNKKGFPVLSK; sequence B is: PGMFSWFPILFP. This polypeptide can precisely interfere with PRMT5-RNA interaction without affecting PRMT5 protein abundance, thereby specifically disrupting a key pathway for maintaining tumor protein translation. This polypeptide therapeutic agent has been shown to effectively inhibit tumor growth in preclinical models, validating the therapeutic feasibility of the "PRMT5-RBD targeting" strategy and providing a novel potential treatment option for patients (including those insensitive to or resistant to existing methylation inhibitors).

The application relates to a detection device for resolving proteins based on magnetophoresis and a detection method thereof, and relates to the technical field of protein abundance and molecular weight detection. The detection device comprises a magnetophoresis preparation part and a protein magnetophoresis part which are sequentially communicated. The magnetophoresis preparation part comprises a mixing container containing SDS solution, the SDS solution is used to eliminate the charge difference between protein molecules, a pipeline is connected to the outlet end of the mixing container, the pipeline sequentially passes through a stirring area provided with an ultrasonic stirrer and a uniform electric field area provided with a uniform electric field generator, the protein magnetophoresis part comprises a separation chamber arranged in the uniform magnetic field area, different protein molecules are separated according to the difference in molecular weight, and the separated protein molecules are detected by a detector, analyzed by an analysis device and displayed, and the relative sizes of the abundance and molecular weight of the proteins are reflected. The detection device has the advantages of simple structure, convenient operation and the like, and provides a new detection method for detecting the relative sizes of the abundance and molecular weight of proteins.

The invention discloses application of FUT2 in improvement of cancer radiotherapy sensitivity, and belongs to the technical field of biological medicine. The invention provides an application of an FUT2 gene / protein as a target spot in any one of the following items: (1) an application in preparation of a product for improving cancer radiotherapy sensitivity; (2) application in preparation of a product for predicting the cancer radiotherapy effect; and (3) application in preparation of a product for predicting the prognosis effect of cancer radiotherapy. It is found for the first time that FUT2 reprograms a tumor immune microenvironment in vivo and promotes pancreatic ductal adenocarcinoma cell death in a mode independent of the metabolic activity of FUT2, FUT2 can enhance the effect of cancer radiotherapy, and the effect of FUT2 in enhancing anti-tumor immunity during radiotherapy depends on protein abundance of FUT2. The tumor immune microenvironment is reprogrammed by regulating and controlling tumor progression through an unconventional metabolic function, the action range of FUT2 in cancers is widened, effective support is provided for cancer radiotherapy sensitization, and good clinical value is achieved.

The invention relates to the technical field of high-resolution mass spectrum determination, and discloses a complete 15N stable isotope labeled protein abundance determination method based on high-resolution mass spectrometry, which comprises the following steps: collecting and calculating a mass spectrum signal of a sample to be detected to obtain the actually measured relative isotope peak intensity of the sample at m / z = i; calculating to obtain predicted relative isotope peak intensity of m / z = i under different 15N isotope abundance; according to a formula 1, respectively calculating correlation coefficients r under different 15N isotope abundance; the correlation coefficients r calculated under different 15N isotope abundance are compared, and the r value closest to 1 is the 15N stable isotope labeled protein abundance value. The use amount of required samples is small, pretreatment such as derivatization is not needed, and operation is easy and convenient; the method is high in resolution, small in calculation workload, and good in stability and accuracy.

The present disclosure relates to compositions and methods to modulate the level of expression of a protein in a deliberate manner (i.e., tunable regulation of expression) with only a minimal change to the genetic sequence of the gene of interest. The present disclosure therefore also provides compositions and methods to predictably alter protein abundance.

The application relates to the technical field of high-resolution mass spectrometry, and discloses a complete N stable isotope labeling protein abundance determination method based on high-resolution mass spectrometry 15 A method for determining the abundance of N stable isotope labeled protein comprises the following steps: collecting and calculating the mass spectrum signal of a sample to be measured to obtain the actual measured relative isotope peak intensity of the sample at m / z=i; calculating the predicted relative isotope peak intensity of m / z=i under different N isotope abundances; calculating the correlation coefficient r under different N isotope abundances according to formula 1; and comparing the correlation coefficients r calculated under different N isotope abundances, wherein the r value closest to 1 is the N stable isotope labeling protein abundance value. 15 15 15 15 The application has the advantages of small sample consumption, no need for pretreatment such as derivatization, simple operation, high resolution, small calculation workload, good stability and accuracy.​​​

The present invention relates of an ex vivo method for determining a reference proteomic profile of extrahepatic cholangiocarcinoma in the presence of bile duct stricture in a subject, comprising steps of : a) quantification of the protein abundances of all proteins identified in at least one bile duct cytological sample from at least one subject for which a diagnosis of extrahepatic cholangiocarcinoma has been previously established, or having benign stricture, b) quantification of the protein abundances of all proteins identified in human bile duct cells standard reference, c) determining the proteomic profile of each of said at least one sample by comparing protein abundances of each protein in the at least one sample with respect to the standard reference, d) determining a reference proteomic profile for extrahepatic cholangiocarcinoma condition, by means of a statistical test established with the proteomic profiles determined in step c). The present invention also relates to a reference proteomic profile of extrahepatic cholangiocarcinoma in the presence of bile duct stricture, and to an ex vivo method for differential diagnosis of extrahepatic cholangiocarcinoma in the presence of bile duct stricture of a subject.

The application provides a mass spectrum processing method and system based on digestive tract tissues, and is applied to the technical field of mass spectrum data processing. By acquiring mass spectrum of each digestive tract tissue; the retention time and mass-to-charge ratio information of each main peak in the mass spectrum are automatically extracted to obtain a core feature vector representing the protein abundance of the digestive tract tissue; and the protein identity information associated with the index of the core feature vector is determined; according to the core feature vector of the healthy digestive tract tissue, a first protein abundance is determined; and according to the core feature vector of each of the multiple diseased digestive tract tissues, multiple second protein abundances are determined; the fold change and the significant difference value are calculated according to the first protein abundance and the multiple second protein abundances; the target protein abundance corresponding to the fold change and the significant difference value satisfying the preset condition is determined; and according to the protein identity information corresponding to the target protein abundance, a protein differential quantification list is output. It has high credibility and data traceability.

The invention discloses an application of AHCY protein in pig intramuscular fat content character assisted breeding, and belongs to the technical field of biology. Intramuscular fat contents of longissimus dorsi muscles of ZYH and DLL pigs are detected, a proteomics technology is adopted, longissimus dorsi muscle differential protein is screened, and the characteristic of the longissimus dorsi muscle is obtained. And calculating a correlation coefficient and a P value of the IMF content, the differential protein expression quantity and the intramuscular fat content so as to identify the protein marker significantly related to the intramuscular fat content of the pig. It is found that AHCY protein abundance is positively correlated with pig intramuscular fat content, and a pig sample with high AHCY protein abundance is selected to have higher pig intramuscular fat content. The protein can be used as a marker related to the intramuscular fat content of pigs, and plays a role in assisted breeding.

The invention discloses a method for enhancing gene expression through gene editing, and relates to the technical field of biological gene editing. According to the method, a known PE precise gene editing technology developed based on a CRISPR / Cas9 system is utilized, a specific translation enhancer is inserted in front of an initiation codon of a target gene, and a specific transcription enhancer is inserted in front of a 5UTR of the target gene, so that the transcription level and the protein abundance of the target gene are improved; the nucleotide sequence of the translation enhancer is as shown in SEQ ID NO.2, and the nucleotide sequence of the transcription enhancer is as shown in SEQ ID NO.25. The method is a universal gene editing and knocking-up method, gene expression can be effectively enhanced through insertion of double enhancers, the gene transcription level is increased by 2-3 times, and the protein abundance is increased by 80%.

Described herein are compositions and methods for modulating protein abundance in a target-specific manner via degron tags.

The invention discloses a ligand target protein analysis method based on protein sequential denaturation. The method comprises the following steps: sequentially denaturing and centrifuging proteins of a ligand group and a control group respectively, and taking supernate; the sequential denaturation comprises at least two of high-temperature treatment, acidic reagent treatment, organic solvent treatment, oxidant treatment, high-ion strength treatment and mechanical oscillation force treatment; and performing guanidine denaturation, reduction, alkylation and enzymolysis on the supernate, detecting protein abundance by mass spectrometry, comparing the protein abundance difference of a ligand group and a control group, and determining the ligand target protein. According to the invention, the coverage and sensitivity of target protein identification are improved; the sample consumption is low; the solubility displacement induced by the ligand is increased; by performing multi-step continuous treatment under different denaturation conditions on the sample, the solubility difference generated by ligand induction is accumulated and amplified under the continuous different denaturation conditions, and the solubility difference generated by ligand induction only responding to one denaturation condition is not diluted and averaged.

The present invention provides a computer-implemented method for determining if a pancreatic cyst of a subject is pre-malignant / malignant or benign, the method comprising a) providing protein abundance data obtained from a liquid sample from the subject ("sample data"); b) providing the sample data as input to a machine learning model trained on a training data set comprising a protein abundance profile of at least three pancreatic carcinomas and at least three presumed benign pancreatic cysts, the protein abundance profile comprising the abundance level of at least 15 proteins selected from Table 1 ("training data"), wherein each pancreatic carcinoma is a distinct pancreatic carcinoma subtype and each presumed benign pancreatic cyst is a distinct presumed benign pancreatic cyst subtype; c) receiving an output from the machine learning model, the output indicative of a pre-malignant / malignant classification or a benign pancreatic cyst classification for the sample data; and d) determining if the pancreatic cyst of the subject is pre-malignant / malignant or benign based on the output received in step c). Related methods and systems for use in performing the methods are also provided.

The present invention provides a pharmaceutical composition for use in modifying scalp or skin, promoting wound healing, or modifying hair, comprising a secretion from adipose stem cells as an active ingredient, wherein 0.3 to 0.6 μg of the secretion in terms of protein abundance per site in scalp or skin is administered.

Disclosed herein are a system and method for detecting the interaction between active probes and proteins, suitable for screening candidate ligands of target proteins (biomolecules) in the context of living cells, which overcome the disadvantages of traditional ligand screening methods that require modification or purification of target proteins, representing an in situ quantitative screening technology. Additionally, the method of the present invention exhibits high versatility, being applicable to the screening of inhibitors, agonists, synergistic ligands, and degraders capable of altering protein abundance. By combining detection methods such as ELISA and qPCR, it can sensitively and quantitatively reflect interactions between proteins and ligands or changes in protein levels. This method is broadly applicable to drug lead compound screening, protein functional studies, and other biomedical research fields. Further disclosed herein use of the method of the present disclosure in detecting antigens by a combination of a specific probe and antibody in in vitro diagnostics (IVD), and in screening specific probes as reagents for use in IVD.

The present application relates to a method for inhibiting PRRSV infection in vitro by honokiol and application thereof, and experiments show that honokiol can be used for preparing a medicine for inhibiting PRRSV infection. In the process of PRRSV infection in MARC-145 cells in vitro, honokiol with a concentration of 2.5, 5 and 10 micromoles / L is added, and compared with a control group without honokiol, the PRRSV RNA content, protein abundance and titer of the treatment group with honokiol are obviously reduced in a dose-dependent manner, indicating that honokiol can be used for inhibiting PRRSV infection in vitro.

Analysis devices, storage media, and methods relating to prediction of phenotypic traits from proteomic data and correlation of the phenotypic traits to genomic data. The proteomic data includes information regarding protein abundance for a plurality of distinct proteins for a plurality of individuals. The genomic data includes information regarding presence of a plurality of distinct genetic variants for each individual. The methods include applying a predictive model to the proteomic data to predict at least one predicted phenotypic trait that is correlated to the proteomic data for at least one individual. The applying includes correlating the protein abundance of at least two proteins to the predicted phenotypic trait for the at least one individual. The methods also include identifying, from the genomic data for the at least one individual, at least one genetic variant that is correlated to the at least one predicted phenotypic trait.

The invention provides a peripheral blood protein-based diagnostic product for hepatocellular carcinoma molecular typing, belongs to the field of tumor clinical medicine, and comprises a kit for detecting the abundance of proteins in peripheral blood serum, calculating a single sample gene set enrichment analysis score and predicting hepatocellular carcinoma molecular typing. By detecting the abundance of protein in peripheral blood serum, rapid molecular typing is carried out on hepatocellular carcinoma, and different treatment effects of liver cancer patients can be predicted while high accuracy is achieved.

The invention relates to the field of biological information, and discloses a protein phosphorylation site function evaluation method based on a kinetic model in combination with an artificial intelligence algorithm. Comprising the following steps: S1, acquiring intracellular omics data of cells under N conditions; s2, taking the omics data under each condition as a reference one by one, substituting the data in the S1 into a kinetic model, and estimating model parameters by introducing a Bayesian algorithm; meanwhile, whether a certain protein phosphorylation site has functions or not under the current reference condition is evaluated through likelihood ratio test; and S3, repeating the step S2 for N times until each condition serves as a reference, summarizing the results of a certain protein phosphorylation site under N iterations, and estimating the probability that the potential protein phosphorylation site has a regulation function under N conditions by adopting a maximum likelihood estimation method. According to the method, the model parameter estimation capability of an artificial intelligence algorithm is fully utilized, protein abundance data are integrated, phosphorylation abundance data are also integrated, model solving is more accurate, and false positive occurrence is reduced.

The present application relates to the fields of biological medicine and data analysis, and particularly relates to a screening method and system of Alzheimer's disease diagnostic markers. The present application provides a screening method and system of Alzheimer's disease diagnostic markers, based on Mendelian randomization (SMR) analysis of aggregated data, combined with multi-omics (risk gene methylation, expression and protein abundance information) research methods, to find key genes in AD pathology, and to reveal their regulatory mechanisms in AD pathogenesis. The method and system provided by the present application further refine the AD diagnostic markers and therapeutic targets, deepen the understanding of the molecular mechanisms in AD disease, find new therapeutic targets, provide innovative strategies and tools for individualized treatment, and ultimately improve the quality of life of patients.

The application discloses application of a reagent for detecting LGALS3BP protein abundance in preparation of a tear liquid diagnostic reagent for gestational diabetes mellitus. The application provides a new diagnostic marker for gestational diabetes mellitus diagnosis, and also provides a new diagnostic method for gestational diabetes mellitus diagnosis. Since the diagnosis is performed through tears, the method has the advantages of non-invasiveness, simple operation and rapidness.

The invention discloses a protein abundance screening and ladder characterization method and device, and the method comprises the steps: constructing a multi-modal data integration and dynamic knowledge base, obtaining sample data from the multi-modal data integration and dynamic knowledge base, processing the sample data, obtaining a standardized abundance matrix, constructing the standardized abundance matrix as an ASSM matrix, performing logarithmic differential compression processing and adaptive normalization processing on the ASSM matrix; inputting the processed ASSM matrix and the sample label into an improved penalty logistic regression model to obtain an optimized weight, and inputting the optimized weight and the normalized ASSM matrix into a ten-layer deep neural network model to obtain an abundance difference probability; and inputting the abundance difference probability into a digital graph conversion engine for dynamic mapping to obtain a gradient probability density ladder atlas. According to the method provided by the invention, the memory overflow risk faced by a traditional spectrogram library searching method is solved, dynamic mapping from the protein abundance difference probability to the gradient ladder atlas is further realized, and a new technical support is provided for disease mechanism research and precise diagnosis and treatment.