6results about How to "Effective way" patented technology

The invention discloses a closed-loop training device and a closed-loop training method for an in-vitro neural chip to control obstacle avoidance of a trolley, and belongs to the field of neurobiology and in-vitro brain-computer interfaces, and the closed-loop training device shapes a biological neural network structure and regulates and controls a discharge mode in a closed-loop training mode, so that the device makes a correct decision in different obstacle situations to control obstacle avoidance of the trolley. According to the device, by means of sensory electrical stimulation coding, the neuron culture can'sense 'the obstacle condition faced by the trolley in the environment, and then motion control over the external trolley is achieved by collecting and decoding the discharge signals of the neuron. According to the method, training electrical stimulation is adopted to provide feedback for a neural network, a system applies reward or punishment electrical stimulation to the neural network according to whether a trolley successfully avoids an obstacle or not, a synaptic structure and a discharge mode of the neural network are adaptively shaped and optimized, and the safety of the trolley is improved. And a network structure capable of autonomously controlling the trolley to avoid obstacles in different obstacle environments is gradually formed.

This invention discloses a transgenic recombinant immune cell that specifically targets tumors. The recombinant immune cell comprises a chimeric polypeptide and a chimeric antigen receptor; the chimeric polypeptide includes a first extracellular region, a first transmembrane region, and a first intracellular region with HLA-G protein binding activity, wherein the N-terminus of the first transmembrane region is connected to the C-terminus of the first extracellular region, and the N-terminus of the first intracellular region is connected to the C-terminus of the first transmembrane region; the first transmembrane region includes the transmembrane region of the Notch receptor protein from Xenopus laevis; the antigen-chimeric receptor does not have HLA-G protein binding activity. This recombinant immune cell significantly improves the precise recognition of tumor cells by immune cells, reduces off-target effects of cell therapy, and accurately and effectively distinguishes tumor cells from normal cells, providing an effective target and targeting method for the treatment of broad-spectrum tumors (especially solid tumors).

The application relates to application of L-selenomethionine oligopeptide in preparation of an antitumor drug, and L-selenomethionine oligopeptide (III) is further prepared by using synthesized L-selenomethionine (II). The L-selenomethionine oligopeptide has good antitumor activity, and (II-1) to (II-10) in the application have good inhibitory activity on cervical cancer cells. The results obtained by the application show that the L-selenomethionine oligopeptide has wide application prospects in a drug development system, a new and wider idea is provided for synthesizing and screening the L-selenomethionine oligopeptide, and a more effective way is provided for treating related diseases.

The application discloses a strain for significantly improving HSAF yield under iron limitation and application thereof, and the genetically engineered bacterium is obtained by knocking out or silencing an iron response transcription factor Fur gene of L.enzymogenes OH11, and the nucleotide sequence of the Fur gene is shown as SEQ ID NO.1.Compared with a wild type strain, the mutant strain has no significant difference in growth in an iron deficiency or low-iron culture medium, and the HSAF synthesis capacity is greatly improved.The HSAF yield of the mutant strain in the iron deficiency culture medium reaches 162.34+5.84 mg / L, which is 3.60 times of that of the wild type strain.Therefore, the technical scheme of the application provides a more direct and effective way for improving the HSAF yield of L.enzymogenes OH11 in the iron deficiency or low-iron environment.

This invention discloses a transgenic recombinant immune cell that specifically targets tumors. The recombinant immune cell comprises a chimeric polypeptide and a chimeric antigen receptor; the chimeric polypeptide includes a first extracellular region, a first transmembrane region, and a first intracellular region with HLA-G protein binding activity, wherein the N-terminus of the first transmembrane region is connected to the C-terminus of the first extracellular region, and the N-terminus of the first intracellular region is connected to the C-terminus of the first transmembrane region; the first transmembrane region includes the transmembrane region of the Notch receptor protein from Xenopus laevis; the antigen-chimeric receptor does not have HLA-G protein binding activity. This recombinant immune cell significantly improves the precise recognition of tumor cells by immune cells, reduces off-target effects of cell therapy, and accurately and effectively distinguishes tumor cells from normal cells, providing an effective target and targeting method for the treatment of broad-spectrum tumors (especially solid tumors).

The application discloses a tendering and purchasing process optimization method and system based on self-optimization instruction engineering, and relates to the fields of artificial intelligence and browser automation. The method comprises the following steps: deploying an agent basic model and a browser execution environment, and establishing a memory bank and an instruction bank; recording user browser interaction events and context data, mapping the events and data into a tendering and purchasing business intention, and generating a structured operation instruction; generating a candidate positioning method for the same business intention; generating an anti-forgetting instruction to maintain business constraints and process states; constructing a preference pair based on operation results, user corrections and business rule satisfaction conditions, optimizing a strategy model by using a direct preference optimization algorithm, and updating instruction priorities; and executing a process according to the updated instruction bank and using execution feedback for continuous optimization. The application can improve the stability, accuracy and adaptability of tendering and purchasing automation execution in the case of page changes and long processes.