Abstract: The present application relates to a bispecific antibody and a use thereof, and also to an immunoconjugate and a pharmaceutical composition comprising the bispecific antibody. The present application further relates to uses of the bispecific antibody and immunoconjugate and pharmaceutical composition comprising the bispecific antibody. The bispecific antibody prepared in the present application can recognize or bind a cell expressing Claudin 18.2 and/or recognize or bind a cell expressing 4-1BB. Moreover, tumors can be prevented and/or treated in a subject.

Abstract: Disclosed is a high-contrast minimum variance imaging method based on deep learning. For the problem of the poor performance of a traditional minimum variance imaging method in terms of ultrasonic image contrast, a deep neural network is applied in order to suppress an off-axis scattering signal in channel data received by an ultrasonic transducer, and after the deep neural network is combined with a minimum variance beamforming method, an ultrasonic image with a higher contrast can be obtained while the resolution performance of the minimum variance imaging method is maintained. In the present method, compared with the traditional minimum variance imaging method, after an apodization weight is calculated, channel data is first processed by using a deep neural network, and weighted stacking of the channel data is then carried out, so that the pixel value of a target imaging point is obtained, thereby forming a complete ultrasonic image.

Abstract: The present invention discloses a method for automatic segmentation of a fuzzy boundary image based on active contour and deep learning. In the method, firstly, a fuzzy boundary image is segmented using a deep convolutional neural network model to obtain an initial segmentation result; then, a contour of a region inside the image segmented using the deep convolutional neural network model is used as an initialized contour and a contour constraint of an active contour model; and the active contour model drives, through image characteristics of a surrounding region of each contour point, the contour to move towards a target edge to derive an accurate segmentation line between a target region and other background regions.

Abstract: The present invention discloses a method for automatic segmentation of a fuzzy boundary image based on active contour and deep learning. In the method, firstly, a fuzzy boundary image is segmented using a deep convolutional neural network model to obtain an initial segmentation result; then, a contour of a region inside the image segmented using the deep convolutional neural network model is used as an initialized contour and a contour constraint of an active contour model; and the active contour model drives, through image characteristics of a surrounding region of each contour point, the contour to move towards a target edge to derive an accurate segmentation line between a target region and other background regions.

Abstract: Disclosed is a high-contrast minimum variance imaging method based on deep learning. For the problem of the poor performance of a traditional minimum variance imaging method in terms of ultrasonic image contrast, a deep neural network is applied in order to suppress an off-axis scattering signal in channel data received by an ultrasonic transducer, and after the deep neural network is combined with a minimum variance beamforming method, an ultrasonic image with a higher contrast can be obtained while the resolution performance of the minimum variance imaging method is maintained. In the present method, compared with the traditional minimum variance imaging method, after an apodization weight is calculated, channel data is first processed by using a deep neural network, and weighted stacking of the channel data is then carried out, so that the pixel value of a target imaging point is obtained, thereby forming a complete ultrasonic image.

Abstract: An ordered macroporous metal-organic framework single crystals and a preparation method therefor. In the method, a three-dimensional structure constructed by polymer microspheres is used as a template; 2-methylimidazole and zinc nitrate, precursors of MOFs, are firstly deposited in the three-dimensional template; the three-dimensional template containing the precursors is soaked in a mixed solution of ammonia water and methanol subsequently, and the three-dimensional template is taken out after crystallization; the three-dimensional template is soaked in an organic solvent to remove the macromolecular three-dimensional template, and the ordered macroporous MOF single crystals is obtained through centrifugal separation. The ordered macroporous MOF single crystals have a basic framework of zeolitic imidazolate framework-8, and structurally include highly-ordered macro-pores whose pore size may be controlled to be between 50 and 2000 nm based on a size of the used template.

Abstract: An ordered macroporous metal-organic framework single crystals and a preparation method therefor. In the method, a three-dimensional structure constructed by polymer microspheres is used as a template; 2-methylimidazole and zinc nitrate, precursors of MOFs, are firstly deposited in the three-dimensional template; the three-dimensional template containing the precursors is soaked in a mixed solution of ammonia water and methanol subsequently, and the three-dimensional template is taken out after crystallization; the three-dimensional template is soaked in an organic solvent to remove the macromolecular three-dimensional template, and the ordered macroporous MOF single crystals is obtained through centrifugal separation. The ordered macroporous MOF single crystals have a basic framework of zeolitic imidazolate framework-8, and structurally include highly-ordered macro-pores whose pore size may be controlled to be between 50 and 2000 nm based on a size of the used template.

Abstract: Degradable pure iron stent or iron alloy stent is provided. The stent is made containing 0.01 to 0.5 atom % of La, Ce or Sr. The stent is surface modified using ion implantation or plasma ion implantation to implant oxygen, nitrogen, La, Ce or Sr into the stent surface. The stent may also be manufactured by depositing a thin film of La, Ce, Sr, lanthana, ceria, strontia, iron or iron oxide onto the stent surface. The thickness of the deposited films is from 10 to 1000 nanometers with the grain size from 10 to 200 nanometers. The corrosion resistance of these stents is significantly increased, and the stents have good biocompatibility. The degradation of the stents is controllable. The stents can also provide sufficient support in blood vessel in 3-6 months after intervention and be degraded after 6 months.

Abstract: The present invention discloses at least one to omnidirectionally modify surfaces of organic or inorganic materials by means of plasma immersion ion implantation process to produce TiO2-x films of the materials surfaces (x is about 0˜0.35). The method includes using oxygen which exists as plasma in the PIII vacuum chamber as the environment, creating and introducing titanium and other metallic plasmas which deposit on the materials surfaces, into the vacuum chamber by means of metal arc source, and apply a negative pulse potential of 500˜50,00 Hz and 0.1˜10 kV amplitude on the workpiece. And also the method to by means of implanting H, Ta or Nb into the TiO2-x films to produce TiO2-x films containing H, Ta or Nb. The materials with surface films fabricated by the present invention, when implanted into human body and contacting blood, have obvious improved blood compatibilities.