Abstract: The present disclosure provides a compound having a STING agonistic activity, which may be expected to be useful as an agent for the prophylaxis or treatment of STING-related diseases. The present disclosure relates to a compound represented by the formula (I): wherein each symbol is as defined in the description, or a salt thereof.

Abstract: It is aimed to properly correct the various types of distortion without a reduction in observation throughput.

Abstract: A non-transitory computer-readable program, an information processing method, an information processing device, and a model generation method that can predict a time and a fee required for catheter treatment. According to the program, a computer obtains patient information related to a patient for whom catheter treatment is performed, and treatment information related to the catheter treatment to be performed on the patient. Furthermore, the computer outputs a treatment time and a fee required for the catheter treatment based on the obtained patient information and treatment information.

Abstract: A non-transitory computer-readable medium storing a computer program executed by a computer processor to execute a process including: acquiring a medical image generated based on a signal detected by a catheter inserted into a luminal organ; deriving determination information for determining whether to detect an object region from the medical image based on the acquired medical image; determining whether to detect an object region from the medical image based on the derived determination information; and detecting an object region included in the medical image by inputting the acquired medical image into a first model trained for detecting an object region included in the medical image when a medical image is input when the object region is determined to be detected from the medical image.

Abstract: A dielectric microscopic observation is possible, which suppresses image flow regardless of scanning speed.

Abstract: A program and the like that make a catheter system relatively easy to use. The program including a non-transitory computer-readable medium (CRM) storing computer program code executed by a computer processor that executes a process comprising: acquiring a tomographic image generated using a diagnostic imaging catheter inserted into a lumen organ; and inputting the acquired tomographic image to a first model configured to output types of a plurality of objects included in the tomographic image and ranges of the respective objects in association with each other when the tomographic image is input, and outputting the types and ranges of the objects output from the first model.

Abstract: A non-transitory computer-readable medium (CRM) storing computer program code executed by a computer processor that executes a process, an information processing apparatus, and model generation method that generates an image of a lumen organ. The process includes acquiring a first image obtained by imaging a lumen organ of a patient based on an ultrasound signal of a first frequency; and generating a second image by inputting the acquired first image into a model, the model being learned to generate, when the first image is input, the second image in which the lumen organ is imaged based on an ultrasound signal of a second frequency. Preferably, the second image, in which a part of an image region of the first image is converted into the second frequency, is generated using the model, and a synthesis image is generated in which the second image is superimposed to the first image.

Abstract: A non-transitory computer-readable medium (CRM) storing computer program code executed by a computer processor that executes a process, an information processing apparatus, and a model generation method that outputs complication information for a medical treatment. The process includes acquiring a medical image obtained by imaging a lumen organ of a patient before treatment, inputting the acquired medical image into a trained model so as to output complication information on a complication that is likely to occur after the treatment when the medical image is received, and outputting the complication information. Preferably, complication information including a type of the complication that is likely to occur and a probability value indicating an occurrence probability of the complication of the type is output.

Abstract: A non-transitory computer-readable medium (CRM) storing computer program code executed by a computer processor that executes a process of acquiring a medical image generated based on a signal detected by a catheter inserted to a lumen organ, estimating a position of an object at least included in the acquired medical image by inputting the medical image to a first learning model for estimating a position of an object included in the medical image, extracting from the medical image an image portion by using the estimated position of the object as a reference, and recognizing the object included in the extracted image portion by inputting the image portion to a second learning model for recognizing an object included in the image portion.

Abstract: A computer is caused to perform processing of: acquiring a plurality of medical images generated based on signals detected by a catheter inserted into a lumen organ while the catheter is moving a sensor along a longitudinal direction of the lumen organ, the lumen organ including a main trunk, a side branch branched from the main trunk, and a bifurcated portion of the main trunk and the side branch; and recognizing a main trunk cross-section, a side branch cross-section, and a bifurcated portion cross-section by inputting the acquired medical images into a learning model configured to recognize the main trunk cross-section, the side branch cross-section, and the bifurcated portion cross-section.

Abstract: A non-transitory computer-readable medium storing computer program code executed by a computer processor that executes an imaging process comprising: acquiring a medical image generated based on a signal detected by a catheter insertable into a body lumen; estimating a cause of an image defect by inputting the acquired medical image to a model learned to output the cause of the image defect when the medical image in which the image defect occurs is input; and outputting introduction information for introducing a countermeasure for removing the estimated cause of the image defect.

Abstract: The accuracy of an intervention site in surgery is predicted and the predicted intervention site is presented to a surgeon. A surgery support apparatus includes a prediction data generation unit that generates prediction data predicting an intervention site based on data before an intervention using an artificial intelligence algorithm. The artificial intelligence algorithm is an artificial intelligence algorithm learning an intervention site by analyzing data before the intervention and intervention site data for an object, and outputs coordinates, a region, or a shape of one point of the intervention site as prediction data. Data before the intervention used for learning of the artificial intelligence algorithm and input data input to the artificial intelligence algorithm to generate prediction data correspond to image data, a segment image, a feature point, etc. The prediction data is displayed on a display apparatus together with an image of a patient acquired in advance.

Abstract: A highly sensitive allergen measurement method is provided. A method for detecting an allergen in a sample, comprising: treating a sample with a protease; and detecting presence or absence of an allergen marker in the enzyme-treated sample by analysis that utilizes chromatographic separation. The allergen comprises buckwheat and wheat.

Abstract: A clamp is provided, which has a simple structure capable of holding linear members of various sizes. The clamp includes a supporting member, a movable arm, and a fixed arm. The movable arm is swingably connected to the supporting member. The fixed arm has a base end portion fixed to the supporting member. The movable arm can swing between a closed position, where a tip end portion of the movable arm is adjacent to a tip end portion of the fixed arm, and an open position, where the tip end portion of the movable arm is placed farther from the tip end portion of the fixed arm. Both the movable arm and the fixed arm can elastically deform to displace their respective tip end portions relative to each other.

Abstract: An aluminum member includes: a substrate formed of aluminum or an aluminum alloy that contains 0 to 10% by mass of magnesium, 0.1% by mass or less of iron, and 0.1% by mass or less of silicon and a balance of which is aluminum and unavoidable impurities; and an anodic oxide coating formed on a surface of the substrate. A surface of the substrate on the anodic oxide coating side has an arithmetical mean height Sa of 0.1 to 0.5 ?m, a maximum height Sz of 0.2 to 5 ?m, and an mean width of roughness profile elements Rsm of 0.5 to 10 ?m, where the arithmetical mean height Sa, the maximum height Sz, and the mean width of roughness profile elements Rsm are measured after the anodic oxide coating is removed.

Abstract: A highly-sensitive-allergen-measurement method is provided. A method for detecting an allergen in a sample comprises treating the sample with a protease, and detecting the presence or absence of an allergen-derived polypeptide in the enzymatically treated sample by a chromatographic separation analysis, wherein the allergen is one or more members selected from the group consisting of buckwheat, crustacean, milk, egg and peanut.

Abstract: The accuracy of an intervention site in surgery is predicted and the predicted intervention site is presented to a surgeon. A surgery support apparatus includes a prediction data generation unit that generates prediction data predicting an intervention site based on data before an intervention using an artificial intelligence algorithm. The artificial intelligence algorithm is an artificial intelligence algorithm learning an intervention site by analyzing data before the intervention and intervention site data for an object, and outputs coordinates, a region, or a shape of one point of the intervention site as prediction data. Data before the intervention used for learning of the artificial intelligence algorithm and input data input to the artificial intelligence algorithm to generate prediction data correspond to image data, a segment image, a feature point, etc. The prediction data is displayed on a display apparatus together with an image of a patient acquired in advance.

Abstract: An aluminum member includes: a substrate formed of aluminum or an aluminum alloy that contains 0 to 10% by mass of magnesium, 0.1% by mass or less of iron, and 0.1% by mass or less of silicon and a balance of which is aluminum and unavoidable impurities; and an anodic oxide coating formed on a surface of the substrate. A surface of the substrate on the anodic oxide coating side has an arithmetical mean height Sa of 0.1 to 0.5 ?m, a maximum height Sz of 0.2 to 5 ?m, and an mean width of roughness profile elements Rsm of 0.5 to 10 ?m, where the arithmetical mean height Sa, the maximum height Sz, and the mean width of roughness profile elements Rsm are measured after the anodic oxide coating is removed.

Abstract: To predict the movement and the deformation of an organ before and after an intervention, and improve the accuracy of position information on a surgical instrument or the like to be presented to an operator. Provided is a surgical support device that is provided with a storage device that stores therein, by analyzing data before and after an intervention to an object, an artificial intelligence algorithm having learned a deformational rule of the object that deforms due to the intervention, and a prediction data generation unit that generates, using the artificial intelligence algorithm, prediction data in which a shape of the object after the intervention is predicted on the basis of the data before the intervention.

Abstract: A highly-sensitive-allergen-measurement method is provided. A method for detecting an allergen in a sample comprises treating the sample with a protease, and detecting the presence or absence of an allergen-derived polypeptide in the enzymatically treated sample by a chromatographic separation analysis, wherein the allergen is one or more members selected from the group consisting of buckwheat, crustacean, milk, egg and peanut.