Abstract: Present invention is related to a tumor microenvironment on chip or a biochip for cell therapy having a carrier, a first cell or tissue culture area and a second cell or tissue area imbedded within the carrier. The present invention provides a biochip successfully cooperating micro fluidic technology and cell culture achieving the goal for detecting or testing the function of cell therapy for cancer or tumor.

Abstract: A method for predicting an immunogenic and/or therapeutic response to adalimumab 5 from a sample extracted from a rheumatoid arthritis patient by testing the sample for the presence of biomarkers, the biomarkers being autoantibodies to antigens comprising SSB, TROVE2 and ZHX2.

Abstract: The present disclosure provides an anti-T-cell nanobody that specifically binds to CD3 ?. The present disclosure also provides the nucleic acid sequence of the anti-T-cell nanobody, use of the anti-T-cell nanobody for treating cancer, immunoregulation and activating immune cells, and a method for detecting expression levels of CD3 ?.

Abstract: A method for producing exosomes in a large-scale by using a cyclic tensile bioreactor to stimulate cells to release exosomes. In addition, the exosome having an anti-HLA-G protein specific for cancer is used as a delivery vehicle to deliver therapeutic agents for treating cancer.

Abstract: The present disclosure provides an anti-immune-checkpoint nanobody that specifically binds to a programmed cell death ligand 1. The present disclosure also provides the nucleic acid sequence of the anti-immune-checkpoint nanobody, use of the anti-immune-checkpoint nanobody for treating cancer and immune-related disorders, and a method for detecting expression levels of PD-L1.

Abstract: The present disclosure relates to a chimeric antigen receptor, a nucleic acid, a chimeric antigen receptor expression plasmid, a chimeric antigen receptor expressing cell, a pharmaceutical composition for treating cancer, and use of the chimeric antigen receptor expressing cell. The chimeric antigen receptor is specific to human leukocyte antigen G. The nucleic acid encodes the chimeric antigen receptor. The chimeric antigen receptor expression plasmid expresses the chimeric antigen receptor. The chimeric antigen receptor expressing cell is obtained by transducing the chimeric antigen receptor into an immune cell. The pharmaceutical composition for treating cancer includes the chimeric antigen receptor expressing cell and a pharmaceutically acceptable carrier.

Abstract: A system of deep learning neural network in prostate cancer bone metastasis identification based on whole body bone scan images includes a pre-processing module for receiving input whole body bone scan images, and a neural network module for detecting whether there is a prostate cancer bone metastasis. The neural network module includes: a chest portion network module for establishing first stage faster R-CNN and segmenting training images of chest portion according to the input whole body bone scan images, and using the training images to train second stage faster R-CNN and categorizing the lesions of cancerous bone metastasis; and a pelvis portion network module for establishing first stage faster R-CNN and segmenting training images of pelvis portion according to the input whole body bone scan images, and using the training images to train the convolutional neural network to categorize whether it is a bone metastasis image.

Abstract: The present disclosure relates to a HLA-G specific chimeric antigen receptor, a nucleic acid, a HLA-G specific chimeric antigen receptor expression plasmid, a HLA-G specific chimeric antigen receptor expressing cell, a pharmaceutical composition for treating cancer, and use of the HLA-G specific chimeric antigen receptor expressing cell. The chimeric antigen receptor specifically binds to human leukocyte antigen G. The nucleic acid encodes the HLA-G specific chimeric antigen receptor. The HLA-G specific chimeric antigen receptor expression plasmid expresses the HLA-G specific chimeric antigen receptor. The HLA-G specific chimeric antigen receptor expressing cell is obtained by transducing the HLA-G specific chimeric antigen receptor into an immune cell. The pharmaceutical composition for treating cancer includes the HLA-G specific chimeric antigen receptor expressing cell and a pharmaceutically acceptable carrier.

Abstract: An atrial fibrillation prediction system is provided. The atrial fibrillation prediction system includes an electrocardiogram obtaining unit and a non-transitory machine-readable medium. The non-transitory machine-readable medium is configured for storing a program which is executed by a processing unit to obtain a prediction result. The program includes a reference database obtaining module, a reference feature selecting module, a training module, a target feature selecting module and a comparing module.

Abstract: Disclosed is a method for identifying methicillin-resistant Staphylococcus aureus through detection a mass signal at m/z of 6580-6600 in the MALDI-TOF mass spectrum. Also disclosed is a novel peptide biomarker, which consists of SEQ NO ID:5 and the use thereof for detection and/or identification of methicillin-resistant Staphylococcus aureus.

Abstract: Disclosed is a method for identifying methicillin-resistant Staphylococcus aureus through detection a mass signal at m/z of 6580-6600 in the MALDI-TOF mass spectrum. Also disclosed is a novel peptide biomarker, which consists of SEQ NO ID:5 and the use thereof for detection and/or identification of methicillin-resistant Staphylococcus aureus.

Abstract: A computer-aided recognition system for treatment response of rectal cancer is provided to predict the probability of a pathological complete response (pCR) of a rectal cancer patient after preoperative neoadjuvant chemoradiotherapy. The system includes a random forest model having several decision trees. Each decision tree has at least a feature node. Each feature node generates two branches according to a feature threshold, wherein each branch connects to another feature node or corresponds to an elementary pCR predicting probability. The random forest model integrates the elementary pCR probability of each decision tree, so as to generate a final pCR probability.

Abstract: The present disclosure provides a bone age assessment and height prediction system including an image capturing unit and a non-transitory machine readable medium. The image capturing unit is for obtaining a target x-ray image data of a subject. The non-transitory machine-readable medium is for storing a program for assessing the development of the bones of a hand and the bone age of the subject, and predicting the adult height of the subject when executed by a processing unit. Therefore, the bone age assessment and height prediction system of the present disclosure can effectively improve the accuracy and sensitivity of the bone age assessment and the height prediction, and the time for assessing the bone age and predicting the height can be further shorten.

Abstract: The present disclosure relates to a HLA-G specific chimeric antigen receptor, a nucleic acid, a HLA-G specific chimeric antigen receptor expression plasmid, a HLA-G specific chimeric antigen receptor expressing cell, a pharmaceutical composition for treating cancer, and use of the HLA-G specific chimeric antigen receptor expressing cell. The chimeric antigen receptor specifically binds to human leukocyte antigen G. The nucleic acid encodes the HLA-G specific chimeric antigen receptor. The HLA-G specific chimeric antigen receptor expression plasmid expresses the HLA-G specific chimeric antigen receptor. The HLA-G specific chimeric antigen receptor expressing cell is obtained by transducing the HLA-G specific chimeric antigen receptor into an immune cell. The pharmaceutical composition for treating cancer includes the HLA-G specific chimeric antigen receptor expressing cell and a pharmaceutically acceptable carrier.

Abstract: An implant surface mapping and unwrapping method provided by the present invention selects or defines a mesh implant geometry, and places and rotates it in a specific spatial position according to a mesh. Vertex space coordinates, which are interpolated in medical images such as computed tomography, magnetic resonance imaging, or ultrasound to calculate the gray scale values of these spatial coordinate points, and map them on the surface of the implant. In addition, the implant is irregular. The surface can be further unwrapped through the planar image to help understand its contact with the anatomy. If the medical image is pre-converted to other anatomical, physiological, pathological, and functional parameters, the mapping and unwrapping results will also be displayed with these parameters. Learn more about the relationship between implants and these parameters.

Abstract: A prediction system of tumor image-aided prediction of prognosis for patients with uterine cervical cancer is provided. The prediction system includes a data augmentation module and a deep convolution neural network model. The data augmentation module is used to apply a data expansion process of the image data, so as to generate a plurality of slice sets of the uterine cervical cancer tumor. The deep convolution neural network model is used to apply a feature analysis to the slices, so as to predict the prognosis of a patient after chemoradiotherapy.

Abstract: A simulated method and system for surgical instrument based on tomography are provided. The method includes obtaining a biological stereoscopic image and inputting a parameter set of an implant to be implanted, denoting a target position and an initial position in the biological stereoscopic image, estimating a dimensional coordinate of a contact area of the implant and a living organism when the implant has been implanted into the living organism based on the parameter set, the target position and the initial position in the biological stereoscopic image, and obtaining a physiological data set by re-sampling corresponding to the dimensional coordinate of the implant in the living organism for evaluating the effect after the implant has been implanted into the living organism. Surgeons may evaluate the effect after implantation of implant into the living organism by using the simulated method, enhancing the overall quality and result of the surgery.

Abstract: A liver fibrosis assessment model includes following establishing steps. A reference database is obtained, wherein the reference database includes a plurality of reference blood test data. A preprocessing step of the blood test data is performed. A feature extracting step is performed, wherein the feature extracting step is for extracting at least one eigenvalue according to the reference database. A normalizing step of the blood test data is performed. A classifying step is performed, wherein the classifying step is for achieving a convergence of the normalized reference blood test data by using a gradient boosting algorithm so as to obtain the liver fibrosis assessment model. The liver fibrosis assessment model is used to assess whether a subject suffers from liver fibrosis and predict a degree of liver fibrosis of the subject.

Abstract: An assisted detection system of breast tumor includes an image capturing unit and a non-transitory machine readable medium. The non-transitory machine readable medium storing a program which, when executed by at least one processing unit, determines a breast tumor type of the subject and predicts a probability of a tumor location of the subject. The program includes a reference database obtaining module, a first image preprocessing module, an autoencoder module, a classifying module, a second image preprocessing module and a comparing module.

Abstract: A method of evaluating if a glioblastoma multiforme (GBM) patient is applicable to be treated with an immunotherapy based on dendritic cell tumor vaccines includes a sample obtaining step to obtain a sample from the GBM patient, a detecting step to detect an expression level of a biomarker, and a comparing step to compare the expression level of the biomarker to a threshold, wherein the GBM patient is applicable to treat with the immunotherapy based on dendritic cell tumor vaccines when the expression level of the biomarker is lower than the threshold. A method of prognosticating a survival rate in the GBM patient after a treatment includes a sample obtaining step, a detecting step, and a comparing step, wherein the GBM patient is determined to have a good prognosis after the treatment when the expression level of the sample from the GBM is lower than the threshold.