Abstract: Provided are transaminase mutants and uses thereof. The transaminase mutant is obtained by one or more amino acid mutations occurring in SEQ ID NO: 2 or is a mutant with a conserved amino acid mutation obtained by taking the sequence SEQ ID NO: 1 of a wild-type CvTA transaminase as a reference. Compared with wild-type transaminases, the catalytic activity of the mutant is improved to different degrees, so that the production efficiency of chiral amine compound synthesis may be improved.

Abstract: Provided is a method for synthesizing a chiral amine compound. A transaminase is used to transaminate a ketone substrate under the action of an amino donor, to obtain the chiral amine compound; and the conserved amino acid sequence region of the transaminase at least includes a region 1 (MAGLWCVN) and a region 2 (YNTFFKT). With the transaminase with the specific conserved amino acid sequence region to synthesize a large sterically hindered chiral amine, the enzyme catalytic reaction volume is small, the synthesizing route is short, the product yield is high, a high-cost noble metal is not required for catalysis under the synthesizing conditions, three wastes are reduced, and the production cost is saved.

Abstract: A low-heat-loss operation method of a line-focusing heat collection system and the line-focusing heat collection system are provided. The method includes the following steps. Solar energy is utilized to preheat a collector tube in an empty tube state, so that the collector tube is in a preheating mode. After a set preheating temperature is reached, a heat transfer working medium is injected into the collector tube. In the injection process of the heat transfer working medium, an injection section of the collector tube is converted into a focusing mode from a preheating mode. After heat collection is finished, the circulation of the heat transfer working medium is stopped, and the focusing mode of the collector tube is kept. In the drainage process of the heat transfer working medium, an emptying section of the collector tube is converted into a light heat-tracing mode from a focusing mode.

Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.

Abstract: A battery unit includes an electrode assembly and a support component. The electrode assembly includes a positive electrode plate and a negative electrode plate that have opposite polarities, and a separator separating the positive electrode plate and the negative electrode plate. The electrode assembly is wound around an outer periphery of the support component. An outer peripheral wall surface of the support component includes a first arc surface and a second arc surface. A first end of the first arc surface is connected to a first end of the second arc surface, and a second end of the first arc surface is spaced apart from a second end of the second arc surface so as to form a step region on the outer peripheral wall surface. The step region is configured to accommodate at least part of the electrode assembly.

Abstract: This application discloses methods of designing a treatment protocol for a human patient with ovarian cancer, as well as methods of treatment of ovarian cancer. This application also includes methods of characterizing an ovarian cancer in a human patient by the type of tumor.

Abstract: The present disclosure provides a semiconductor structure and a storage circuit that implements the storage structure of a magnetoresistive random access memory (MRAM) based on a dynamic random access memory (DRAM) fabrication platform.

Abstract: The present application makes public a magnetic memory and a reading/writing method thereof, which magnetic memory comprises at least one cell layer, and the cell layer includes a plurality of parallel second wires that are disposed in a second plane, the first plane being parallel to the second plane, and projections of the second wires onto the first plane intercrossing the first wires; a plurality of storage elements that are disposed between the first plane and the second plane, the storage elements including magnetic tunnel junctions and bi-directional gating components connected in series along a direction perpendicular to the first plane, the magnetic tunnel junctions being connected to the first wires, the bi-directional gating components being connected to the second wires, and the bi-directional gating components being configured to be conductive upon application of a threshold voltage and/or a threshold current.

Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.

Abstract: The present invention provides diagnostic methods, therapeutic methods, and compositions for the treatment of cancer (e.g., a bladder cancer (e.g., UC, e.g., mUC), a kidney cancer, a lung cancer, a liver cancer, an ovarian cancer, a pancreatic cancer, a colorectal cancer, or a breast cancer). The invention is based, at least in part, on the discovery that expression levels of one or more biomarkers described herein in a sample from an individual having cancer can be used in methods of identifying an individual having a cancer who may benefit with an anti-cancer therapy that includes an immunotherapy (e.g., a PD-L1 axis binding antagonist such as an anti-PD-L1 antibody (e.g., atezolizumab)) and a suppressive stromal antagonist (e.g.

Abstract: The present invention relates to methods and kits or articles of manufacture related thereto that may find use, inter alia, in assessing responsiveness of cancers to MUC16 antagonists by monitoring HE4 expression. In some embodiments, the methods include measuring the level of expression of HE4 in a sample from a subject; comparing the level of expression of HE4 in the sample with the level of expression of HE4 in a sample previously obtained from the subject; and, optionally, administering to the subject a therapeutically effective amount of a MUC16 antagonist.

Abstract: The present invention provides diagnostic methods, therapeutic methods, and compositions for the treatment of cancer (e.g., a bladder cancer (e.g., UC, e.g., mUC), a kidney cancer, a lung cancer, a liver cancer, an ovarian cancer, a pancreatic cancer, a colorectal cancer, or a breast cancer). The invention is based, at least in part, on the discovery that expression levels of one or more biomarkers described herein in a sample from an individual having cancer can be used in methods of identifying an individual having a cancer who may benefit with an anti-cancer therapy that includes an immunotherapy (e.g., a PD-L1 axis binding antagonist such as an anti-PD-L1 antibody (e.g., atezolizumab)) and a suppressive stromal antagonist (e.g.

Abstract: The present invention relates to methods and kits or articles of manufacture related thereto that may find use, inter alia, in assessing responsiveness of cancers to MUC16 antagonists by monitoring HE4 expression. In some embodiments, the methods include measuring the level of expression of HE4 in a sample from a subject; comparing the level of expression of HE4 in the sample with the level of expression of HE4 in a sample previously obtained from the subject; and, optionally, administering to the subject a therapeutically effective amount of a MUC16 antagonist.

Abstract: Example embodiments are directed to systems and methods for providing end of route navigation. In example embodiments, a network system identifies a destination of a route and retrieves a display template based on the destination. The display template provides guidelines for display of end of route content, whereby the display of the end of the route content is different than display of content during a middle of the route. The network system identifies, based on the display template, a display time to trigger the display of the end of the route content. The display time may be associated with a threshold distance to the destination. The network system monitors a location of a vehicle along the route and accesses end of route content. Responsive to detecting that the location of the vehicle is at the threshold distance to the destination, the network system causes presentation of the end of the route content on a device associated with the vehicle.

Abstract: The present invention relates to methods, uses, and compositions for the treatment of cancer (e.g., a lung cancer; a cervical cancer; a breast cancer; a head and neck cancer; a liver cancer; a bladder cancer; a gastric cancer; an esophageal cancer; a pancreatic cancer; a kidney or renal cancer; a melanoma; an ovarian cancer; or a colorectal cancer). More specifically, the invention concerns the treatment of patients having cancer with an anti-TIGIT antagonist antibody, including treatment with an anti-TIGIT antagonist antibody in a combination therapy.

Abstract: This application discloses methods and compositions for use in treating cancer, including breast cancer (such as metastatic triple negative breast cancer, mTNBC), urothelial carcinoma, renal cell carcinoma, and liver cancer (hepatocellular carcinoma, HCC) with the combination of a PD-1 axis binding antagonist (e.g., a PD-L1 binding antibody such as atezolizumab) and an IL6 antagonist (e.g. an anti-IL6 receptor antibody such as tocilizumab), optionally further comprising a VEGF antagonist (e.g. an anti-VEGF antibody such as bevacizumab). Optionally, the patient has C-reactive protein (CRP) and/or IL-6 level(s) above the upper limit of normal. Optionally, the cancer is PD-L1 positive.

Abstract: A machine-learning model (e.g., a clustering model) may be used to predict a phenotype of a tumor based on expression levels of a set of genes. The set of genes may have been identified using a same or different machine-learning model. The phenotype may include an immune-excluded, immune-desert or an inflamed/infiltrated phenotype. A treatment strategy and/or treatment recommendation may be identified based on the predicted phenotype.

Abstract: The present invention provides diagnostic methods, therapeutic methods, and compositions for the treatment of cancer (e.g., a bladder cancer (e.g., UC, e.g., mUC), a kidney cancer, a lung cancer, a liver cancer, an ovarian cancer, a pancreatic cancer, a colorectal cancer, or a breast cancer). The invention is based, at least in part, on the discovery that expression levels of one or more biomarkers described herein in a sample from an individual having cancer can be used in methods of identifying an individual having a cancer who may benefit with an anti-cancer therapy that includes an immunotherapy (e.g., a PD-L1 axis binding antagonist such as an anti-PD-L1 antibody (e.g., atezolizumab)) and a suppressive stromal antagonist (e.g.