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48 results about "Thyroid gland cancer" patented technology

In addition to a group of tumorous cancers which attack the thyroid gland, a form of lymphoma which focuses on the thyroid is also sometimes seen in medical practice. There are four types of thyroid cancer in addition to thyroid lymphoma: medullary, follicular, papillary, and anaplastic.

Genetic amplification of IQGAP1 in cancer

ActiveUS9157123B2Diminish invasivenessReduce spreadOrganic active ingredientsSugar derivativesCell invasionFollicular thyroid cancer
We examined IQGAP1 copy gain and its relationship with clinicopathologic outcomes of thyroid cancer and investigated its role in cell invasion and molecules involved in the process. We found IQGAP1 copy number (CN) gain ?3 in 1 of 30 (3%) of benign thyroid tumor, 24 of 74 (32%) follicular variant papillary thyroid cancer (FVPTC), 44 of 107 (41%) follicular thyroid cancer (FTC), 8 of 16 (50%) tall cell papillary thyroid cancer (PTC), and 27 of 41 (66%) anaplastic thyroid cancer, in increasing order of invasiveness of these tumors. A similar tumor distribution trend of CN ?4 was also seen. IQGAP1 copy gain was positively correlated with IQGAP1 protein expression. It was significantly associated with extrathyroidal and vascular invasion of FVPTC and FTC and, remarkably, a 50%-60% rate of multifocality and recurrence of BRAF mutation-positive PTC (P=0.01 and 0.02, respectively). The siRNA knock-down of IQGAP1 dramatically inhibited thyroid cancer cell invasion and colony formation. Co-immunoprecipitation assay showed direct interaction of IQGAP1 with E-cadherin, a known invasion-suppressing molecule, which was upregulated when IQGAP1 was knocked down. IQGAP1, through genetic copy gain, plays an important role in the invasiveness of thyroid cancer and represents a useful prognostic marker and therapeutic target for this and other cancers.
Owner:THE JOHN HOPKINS UNIV SCHOOL OF MEDICINE

Preparation of 131I-thyroid stimulating hormone (TSH) and application thereof

InactiveCN101787077ASimple preparation processStable markerRadioactive preparation carriersDepsipeptidesTyrosineUndifferentiated Thyroid Tumor
The invention relates to the preparation of 131I-thyroid stimulating hormone (TSH) and an application thereof, belonging to the field of radionuclide therapeutic drugs. The compound 131I-thyroid stimulating hormone is a radioiodine marker for thyroid stimulating hormone with pathoclisis in vivo acting on thyrocyte. A preparation method of the 131I-thyroid stimulating hormone comprises the following steps of: carrying out iodine 131 marking on the thyroid stimulating hormone by utilizing a chloramine-T method, a peroxide oxidation method or an iodogen method, and introducing radionuclide iodine 131 for treatment into tyrosine residues in thyroid stimulating hormone molecules. The marking rate of the prepared 131I-TSH is 85.9 percent, the radiochemical purity after purification achieves more than 90 percent, and the prepared 131I-TSH can be stored stably for more than one week at room temperature; the 131I-TSH is mainly metabolized through the liver and excreted through the kidneys; the percentage of ID/g of the 131I-TSH in the thyroid gland is not obviously reduced in four hours; and the 131I-TSH can be concentrated in thyroid gland issues sealed by an iodine solution. Concerning low/undifferentiated thyroid tumours incapable of iodine uptake, the 131I-TSH can increase the radioiodine uptake of thyroid gland cancer cells, and the radioiodine 131 can be chosen for treatment.
Owner:JIANGSU INST OF NUCLEAR MEDICINE

Implant agent treating for solid tumor

The invention relates to a sustained-release implant for treating a solid tumor, which is characterized in that: the sustained-release implant contains an effective anticancer amount of bortezomib and sustained-release excipients. The solid tumor includes brain tumor, liver cancer, lung cancer, oesophagus cancer, gastric cancer, breast cancer, pancreatic cancer, thyroid cancer, nasopharyngeal cancer, ovarian cancer, endometrial cancer, cervical cancer, renal cancer, prostate cancer, bladder cancer, colon cancer, rectal cancer, skin cancer, head and neck cancer and primary or secondary cancer, caruncle or carcinosarcoma rooted at a peripheral nervous system, mucosa, glands, blood vessels, bone tissues and lymph nodes. The sustained-release excipients are mainly a biological polymer which is dissoluble and can be degraded and absorbed, in the degradation and absorption process of which carmustine is sustainedly released to part of the tumor, thus the entire toxicity of the carmustine is significantly reduced while an effective medicine consistency is maintained on part of the tumor. That the sustained-release implant is implanted inside part of the tumor can not only reduce the entire toxicity of the carmustine but also enhance the medicine consistency on part of the tumor, thereby increasing the curing effect of non-operative therapeutics such as chemotherapeutic drugs and radiotherapy.
Owner:JINAN SHUAIHUA PHARMA TECH

Thyroid cancer pathological image classification method based on deep learning

ActiveCN112364920AEasy to classifySolve the problem of losing a large number of featuresCharacter and pattern recognitionNeural architecturesThyroid gland cancerThyroid pathology
The invention discloses a thyroid cancer pathological image classification method based on deep learning, and mainly solves the problem of poor thyroid cancer pathological image classification effectof an existing method. According to the implementation scheme, the method comprises the following steps: reading a thyroid pathology image database, extracting low-level convolution and pooling features by a receptive field network, and fusing the features to obtain fused low-level features; extracting high-level features, namely predicted category vectors, from the fused low-level features through a capsule network; updating the category vector through a dynamic routing algorithm to obtain a final category vector, and calculating the modulus of the category vector through a compression activation function; carrying out image reconstruction on the vector with the maximum modulus value through a decoding reconstruction network; iteratively updating weights in the receptive field network andthe capsule network to complete model training; and finally, inputting a thyroid pathological image to be classified into the trained model to obtain a final classification result. The invention improves the classification accuracy of the thyroid cancer pathological images and can be used for computer-aided diagnosis.
Owner:XIDIAN UNIV
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