Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

285 results about "Pulmonary adenocarcinoma" patented technology

N-alkyl-1,2,3,4,5,6-hexahydro-1,1,5,5-tetramethyl-7H-2,4 alpha-methanonaphthalene-7-amine compound as well as synthetic method and application thereof

The invention discloses an N-alkyl-1,2,3,4,5,6-hexahydro-1,1,5,5-tetramethyl-7H-2,4 alpha-methanonaphthalene-7-amine compound as well as a synthetic method and an application thereof. Longifolene serving as a heavy oil main component is relatively rich terpenoid in numerous natural extracts. The synthetic method comprises the following steps: obtaining isolongifolene through longifolene isomerization, obtaining isolongifolenone through allylic oxidation of the isolongifolene, carrying out dehydration condensation on the isolongifolenone and primary amine so as to obtain imine and obtaining the chiral N-alkyl-1,2,3,4,5,6-hexahydro-1,1,5,5-tetramethyl-7H-2,4 alpha-methanonaphthalene-7-amine compound after reduction. The compound has vey good inhibition activity on candida albicans, aspergillus niger, candida tropicalis, escherichia coli, staphylococcus aureus, pseudomonas fluorescens, bacillus subtilis and the like, a part of compound has good cancer cell proliferation inhibition activity on human breast cancer cells MCF-7, human lung adenocarcinoma cells A549, hepatoma cells HepG2 and SMMC-7721, and the N-alkyl-1,2,3,4,5,6-hexahydro-1,1,5,5-tetramethyl-7H-2,4 alpha-methanonaphthalene-7-amine compound is a potential antibacterial and bactericidal and anti-tumor compound.
Owner:NANJING FORESTRY UNIV

Non-small cell lung cancer pathological section identification method based on deep convolutional neural network

The invention discloses a non-small cell lung cancer pathological section identification method based on a deep convolutional neural network. The method comprises the following steps: acquiring pathological sections of non-small cell lung cancer in a public data set from TCGA; constructing a deep learning model for training; inputting the training data set into a convolutional neural network for training to obtain a learned convolutional neural network model; and inputting the training data set into a convolutional neural network for training to obtain a learned convolutional neural network model. According to the method, the Inception-v3 model and the CBAM attention mechanism are fused together, so that the classification of the non-small cell lung cancer is realized, and the network precision is improved through the attention mechanism; meanwhile, a deep convolutional neural network Inception-v3 experimental result shows that the non-small cell lung cancer pathological section identification method based on deep learning provided by the invention can effectively classify lung adenocarcinoma and lung squamous cell carcinoma, reduces the burden of doctors to a certain extent, and realizes very good performance in the field of medical image identification.
Owner:LIAONING TECHNICAL UNIVERSITY

Auxiliary identification system and method for lung adenocarcinoma subtypes

The invention discloses an auxiliary identification system and method for lung adenocarcinoma subtypes, and relates to a neural network. The system comprises an acquisition module for acquiring a digital pathological image and labeling to obtain a labeled image; wherein the features include lesion areas and real pathological image features; the processing module is used for processing the annotated image to obtain a processed image and storing the processed image into a database; the classification module divides the processed images into a training set, a verification set and a test set; thetraining module is used for training the training set to obtain an auxiliary identification model of the lung adenocarcinoma subtype; the verification module is used for inputting the verification setinto the auxiliary identification model for optimization to obtain an optimization model; the test module is used for inputting the test set into the optimization model to obtain a result and obtaintest accuracy; the comparison module is used for comparing the test accuracy with a test threshold value and retraining when the test accuracy is smaller than the test threshold value; and if not, storing the auxiliary identification optimization model. The kit has the beneficial effect of assisting a clinician in identifying the lung adenocarcinoma subtype.
Owner:SHANGHAI PULMONARY HOSPITAL

Chinese lung adenocarcinoma cell line with high metastases potentiality of bone, lever and adrenal gland

The invention belongs to the filed of microorganism animal cell lines and provides a Chinese lung adenocarcinoma cell line with high metastases potentiality of bone, lever and adrenal gland. According to the invention, hydrothorax of an adenocarcinoma first-diagnosis patient is used as primary culture of cells; the human adenocarcinoma cell has the preservation number of CGMCC No.3137 and classified name as human lung adenocarcinoma cell line CPA-Yang3, can grow adhered to the wall and has the tumorigenesis rate up to 100 percent; the human lung adenocarcinoma cell can grow quickly and metabolize vigorously; the expression levels of cancer genes EMS1, VEGF-C, IL-6, IL-8, SVIL and AR gene are higher than the expression level of SPC-A-1 cell; and the lung adenocarcinoma cancel cell has the biological characteristics of mainly transferring the bone and having high transfer potential of the lever and the adrenal gland, high growth speed of bone transfer cells and complete cell morphology. The invention can be used for providing reference data to early diagnosis for transferring the human lung adenocarcinoma bone, further establishing the relevant gene chip technology and assessing and exploring the curative effects of various medicaments and the like by comprehensively applying the gene chip, quantifying PCR (Polymerase Chain Reaction), western blot in real time and other technologies.
Owner:SHANGHAI CHEST HOSPITAL

Diterpenoid compounds, and preparation method and application thereof

The invention discloses diterpenoid compounds, and a preparation method and application thereof. The diterpenoid compounds are prepared by the following steps: by using Aralia melanocarpa root as a raw material, carrying out extract leaching, organic solvent extraction, silica gel column chromatography and high pressure liquid chromatography separation. The molecular formula of the compounds is C20H28O2 which is named ent-pimar-6,8(14),15-trien-19-oic acid disclosed as the structural formula in the specification. The preparation method comprises the following steps: by using the Aralia melanocarpa root as the raw material, carrying out extract leaching, organic solvent extraction, silica gel column chromatography and high pressure liquid chromatography separation. The invention also discloses application of the diterpenoid compounds in preparing drugs for preventing and / or treating tumor and in preparing drugs for preventing and / or treating human lung adenocarcinoma, human prostatic cancer or human acute medullary system leukaemia. The diterpenoid compounds have obvious inhibiting actions when being applied to drugs for human lung adenocarcinoma, human prostatic cancer or human acute medullary system leukaemia, which indicates that the diterpenoid compounds have favorable anticancer activity and can be used as an anticancer active component or lead compound.
Owner:YUNNAN MINZU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products