14 results about "Merokeratin" patented technology

The invention provides an automatic tumor budding identification method fusing pathological staining migration and YOLO target detection. The method comprises the following steps: training Hamp by using a CUT model; a staining migration model is established from the E image to the immunohistochemical image, and the staining migration model is utilized to carry out Hamp; e, converting the dyed full-width pathological section into a cytokeratin dyed full-width pathological section; and performing tumor budding detection on the generated full-width pathological section dyed by the cytokeratin by using a TB-YOLO model improved on the basis of YOLOv10. According to the method, the CUT is combined for pathological image staining migration, the IHC image generated through TB-YOLO analysis is used for tumor budding detection, meanwhile, accurate translation and detection of positive signals are ensured, richer diagnosis information is provided for pathologists, the diagnosis accuracy is improved, the pathological examination cost of patients is reduced, and the purpose that only Hamp is used for diagnosis is achieved. And E, the tumor budding is accurately detected by the dyed image, so that the comparability of medical images in different dyeing modes and the applicability of a cross-dyeing method are improved.

The invention relates to a 177Lu-DOTATATE peptide receptor radionuclide curative effect prediction model and application thereof, the model is used for performing multicolor immunofluorescent staining on tissue slices of a neuroendocrine tumor (NET) patient, and the model at least comprises specific staining antibodies of cytokeratin (CK +) cells, CD8 cells and TIM-3 molecules; then carrying out image acquisition and analysis, and identifying two positive cells, namely CK < + > and CD8 < + > TIM-3 < + >; calculating an under-curve area difference AUC (CK) (CD8 + TIM-3 +) between an observation curve of a nearest neighbor distance accumulation function (G function) between CK + and CD8 + TIM-3 + and a Poisson distribution curve according to an R language software package, determining a response scoring formula and threshold division based on single-factor logistic regression of PRRT response degree of case data, and substituting the difference into the response scoring formula, and the response score can be used for curative effect prediction.

The present invention relates to the use of the use of a blend of sugars comprising psicose, mannose, fructose and glucose to increase the expression of cytokeratin-1 in skin to strengthen skin's self-defense mechanisms and maintain skin integrity.

The application relates to the technical field of biology, and discloses a method for inducing a cell line of immortalized musk deer scent glands to synthesize dihydrotestosterone, wherein the cell line is obtained by transfecting a primary musk deer scent gland epithelial cell with a lentivirus carrying an SV40 Large T antigen and performing resistance screening; the cell line is in an epithelial cell form and stably expresses keratin 18, cholesterol side chain cleavage enzyme, 17 alpha-hydroxylase and 3 beta-hydroxysteroid dehydrogenase. Through lentivirus-mediated SV40 Large T antigen transfection, the primary musk deer scent gland epithelial cell breaks through the limit of replicative senescence and obtains unlimited proliferation capacity, effectively overcomes the defects that the primary cell is prone to fibrosis and rapidly loses metabolic function during in-vitro culture, provides a standardized cell model with a clear genetic background and persistent metabolic activity for biological manufacturing of dihydrotestosterone, and relieves the dependence on endangered animal live resources.

The present invention relates inter alia to the development of monoclonal antibodies against Loricrin and methods for determining whether a subject with melanoma has an increased risk of metastasis using said antibodies.

The invention provides a lung cancer early screening method and system based on biomarker in-vitro detection, and relates to the technical field of biomarker research, and the lung cancer early screening method comprises the following steps: collecting a peripheral blood sample of a subject, identifying a target biomarker in the peripheral blood sample, and detecting the concentration information of the target biomarker; the target biomarker comprises a carcino-embryonic antigen, a cytokeratin 19 fragment and a squamous epithelial cell carcinoma antigen; obtaining an optical signal through a surface plasma resonance detection device; noise reduction processing is carried out on the optical signal to obtain core characteristic parameters, and the core characteristic parameters comprise a binding rate, a dissociation rate and a resonance angle deviation amplitude; utilizing an edge computing technology to obtain a corresponding risk score; through a cross comparison mode, obtaining verified risk data; the verified risk data and concentration information are integrated and analyzed to obtain an early screening result of the lung cancer, so that high-sensitivity and high-specificity early screening of the non-invasive lung cancer is realized.

A TPS CLIA kit comprises an immunoconjugate comprising an alkaline phosphatase conjugated to a monoclonal antibody, or an antigen-binding fragment thereof, binding specifically to one of the M3 and M21 epitopes of cytokeratin 18, a monoclonal antibody, or an antigen-binding fragment thereof, binding specifically to other of the M3 and M21 epitopes, a substrate of alkaline phosphatase and a solid support. The monoclonal antibody, or the antigen-binding fragment thereof, binding specifically to other of the M3 and M21 epitopes is immobilized or is intended to be immobilized to the solid support. The invention also relates to a method for detecting TPS in a sample using the TPS CLIA kit.

The present invention is in the fields of diagnostics and treatment of cancer. The present invention provides, inter alia, means and methods for detecting and / or isolating metastasis founder cells based on the expression or expression level of the marker(s) c-KIT and / or MUC1, and, preferably, at least one additional disseminated cancer cell (DCC) marker such as EpCAM and / or (a) cytokeratin(s). Corresponding isolated cells or cell populations, and uses thereof, are provided as well. In one aspect, the invention relates to a method for detecting metastasis founder cells in a sample, comprising measuring in single cells in a sample the expression or expression level of (i) a first marker which is c-KIT and (ii) at least one disseminated cancer cell (DCC) marker, wherein expression of c-KIT and at least one DCC marker in a cell is indicative of the cell being a metastasis founder cell, or wherein expression levels of c-KIT and at least one DCC marker in a cell above respective thresholds are indicative of the cell being a metastasis founder cell. Furthermore, the invention relates to methods for prognosing the development of metastases and / or the relapse, progression or outcome of a cancer, as well as to methods for measuring the success of an anti-cancer treatment and / or for stratifying subjects for treatment with (an) anti-cancer drug(s), based on the expression or expression level of said marker(s) in single cells. In addition, the present invention relates to one or more anti-cancer drugs for use in treating a patient having metastasis founder cells according to the invention. Further provided are therapeutics for targeting metastasis founder cells such as antibodies or fragments thereof binding both, c-KIT and EpCAM, or CAR-T cells targeting both, c-KIT and EpCAM.

Abstract A method for detecting a biological marker in a sample, preferably a biological marker on a cancer cell, the method comprising: (i) contacting the sample with at least one DNA aptamer coupled to a first reagent and wherein the aptamer specifically binds to a first biological marker in the sample to form a first complex; (ii) contacting the first complex of (i) with a second binding agent that specifically binds to the first reagent such that a second complex is formed, wherein the second binding agent is coupled to a reporter molecule; (iii) contacting the second complex (ii) with a substrate for the reporter molecule of the at least one second binding agent; and (iv) detecting the substrate reaction by formation of a reaction product thereby detecting the biological marker in the sample. Biological markers include cytokeratin 8 (CK8), cytokeratin 18 (CK18), human epidermal growth factor receptor 2 (HER2) and epithelial cell adhesion molecule (EpCAM). Abstract 41 / 50 FIGURE 40 Frozen section preparation 4 Sample fixation + Wash (10 dips in PBS) DNA aptamer staining DAB Substrate DAB substrate HRP FAM Anti-FITC conjugated with HRP FAM DNA Aptamer conjugated with FAM HRP Frozen section slide / Touch imprint slide / Cytology slide / Direct smear slide Anti-FITC-HRP Wash (10 dips in PBS) DAB Wash (10 dips in PBS) Hematoxylin counter-staining Wash under tap water Cove rs lip DAB brown precipitate at the location of the aptamer B o min 1 min 15 sec 5 min 15 sec 5 min 15 sec 5 min 15 sec 10 sec 1 min 1 min A + Wash (10 dips in PBS) Total time for aptamer-DAB staining: —18 min 4 1 / 5 0 A B 1 0 m i n 1 m i n D A B s u b s t r a t e 1 5 s e c H R P A n t i - F I T C 5 m i n D N A a p t a m e r s t a i n i n g H R P 1 5 s e c 5 m i n 1 5 s e c D N A A p t a m e r c o n j u g a t e d w i t h F A M 5 m i n D A B W a s h ( 1 0 d i p s i n P B S ) F r o z e n s e c t i o n s l i d e / T o u c h i m p r i n t s l i d e / C y t o l o g y s l i d e / D i r e c t s m e a r s l i d e c o u n t e r - s t a i n i n g 1 m i n W a s h u n d e r t a p w a t e r 1 m i n C o v e r s l i p F I G U R E 4 020 25 28 36 33 19 D ec 2 02 5 1 9 D e c 2 0 2 5 A B 1 0 m i n F r o z e n s e c t i o n p r e p a r a t i o n 1 m i n S a m p l e f i x a t i o n D A B 2 0 2 5 2 8 3 6 3 3 s u b s t r a t e 1 5 s e c W a s h ( 1 0 d i p s i n P B S ) H R P A n t i - F I T C 5 m i n D N A a p t a m e r s t a i n i n g H R P 1 5 s e c 5 m i n A n t i - F I T C - H R P T o t a l t i m e f o r 1 5 s e c D N A A p t a m e r W a s h ( 1 0 d i p s i n P B S ) c o n j u g a t e d w i t h F A M 5 m i n D A B s t a i n i n g : ~ 1 8 m i n W a s h ( 1 0 d i p s i n P B S ) F r o z e n s e c t i o n s l i d e / T o u c h i m p r i n t s l i d e / 1 0 s e c H e m a t o x y l i n C y t o l o g y s l i d e / D i r e c t s m e a r s l i d e c o u n t e r - s t a i n i n g 1 m i n W a s h u n d e r t a p w a t e r 1 m i n C o v e r s l i p F I G U R E 4 0

The application discloses an anti-cellular keratin 18 antibody and a preparation method and application thereof. The anti-cellular keratin 18 antibody or antigen binding fragment thereof has a heavy chain variable region and / or a light chain variable region shown in the amino acid sequences of SEQ ID NO.: 1-6. The preparation scheme of the CK18 antibody in the application uses a prokaryotic recombinant CK18 full-length antigen, has more CK18 dominant epitopes, and avoids the problem of less epitope exposure caused by the filamentous helical structure of natural CK18. In addition, the immunogen used in the application has strong immunogenicity and more dominant epitope exposure, so that the affinity of the prepared monoclonal antibody is greatly improved. Meanwhile, the CK18 polypeptide with a specific sequence is selected to further screen and prepare the antibody, so that the problem of missed detection caused by individual mutation difference can be avoided, and the problem of reduced antibody affinity caused by the phosphorylation modification of the CK18 protein can be avoided.

A lateral flow immunometer 10 includes a sample accommodation portion 20 configured to accommodate a sample; a SERS active particle configured to bind to cytokeratin-18 (K18) in the sample, and a test portion 40 configured to immobilize the SERS active particle that has bound to K18.

This tumor microenvironment prediction method using a deep learning model comprises steps in which an analysis device: generates a cytokeratin (CK) staining image from a hematoxylin and eosin (H&E) staining image with respect to a region of interest of a sample; generates a leukocyte common antigen (LCA) staining image from the H&E staining image; generates a desmin staining image from the H&E staining image; and calculates a tumor microenvironment index for the region of interest on the basis of the CK staining image, the LCA staining image, and the desmin staining image.

Conventional, manual identification and scoring of a whole slide image (WSI) to detect Cytokeratin 17 (K17) expression has limitations in terms of lower accuracy in the medium grade cases, slower turn-around time, and high inter and intra-observer variability. Each WSI can take a pathologist six to ten minutes to examine. This is because the brown color staining indicating the presence of K17 may be one of thousands or tens of thousands or other expressions present on the slide. Apparatus and methods are provided for an artificial intelligence (AI) solution that identifies and quantifies positively stained urothelial cells in WSI of urine cytology to aid the diagnosis of urinary bladder carcinoma. An illustrative AI solution may include one or computer models that are programmed to run one more machine learning (ML) models. The ML models may be trained to recognize subtle and complex patterns and features associated with specific diseases.