Grund Intellectual Property Group

The present invention provides a genetically-modified T cell comprising in its genome a modified human T cell receptor alpha gene. The modified T cell receptor alpha gene comprises an exogenous sequence of interest inserted into an intron within the T cell receptor alpha gene that is positioned 5' upstream of TRAC exon 1. The exogenous sequence of interest can comprise an exogenous splice acceptor site and/or a poly A signal, which disrupts expression of the T cell receptor alpha subunit. The sequence of interest can also include a coding sequence for a polypeptide, such as a chimeric antigen receptor. Additionally, the endogenous splice donor site and the endogenous splice acceptor site flanking the intron are unmodified and/or remain functional. The invention further provides compositions and methods for producing the genetically-modified cell, and populations of the cell, and methods for the treatment of a disease, such as cancer, using such cells.

The present invention relates to genetically modified Clostridia strains that provide an improved combination of replication and physiological characteristics useful for a variety of clinical and industrial applications. In particular, clinical grade spores generated from the Clostridia strains described herein can be efficiently stored, formulated, and advantageously used in the prevention and/or treatment of medical conditions, such as cancer.

This application describes, amongst other things, example methods and systems using machine-learning components having knowledge of a plurality of numerical embeddings corresponding to a plurality of documents, where the plurality of numerical embeddings relates to a set of similarity clusters. An example method includes obtaining a constraint indicating a period of time and a type of subject matter and, using the constraint, obtaining a set of documents and corresponding metadata. A set of numerical embeddings are generated for the set of documents. A set of updated similarity clusters are generated by updating the set of similarity clusters to incorporate the set of numerical embeddings. A set of potential actions are identified based on links between entity information and the set of updated similarity clusters. The set of potential actions are ranked, and a notification is provided indicating top-ranked actions.

This application describes, amongst other things, an example method for responding to user queries. The method includes receiving, via a user interface, a user query from a user and categorizing the user query using a first task-specific orchestration. The method also includes providing information about the user query to a destination task-specific orchestration, including, in accordance with categorizing the user query in a first category, assigning a second task-specific orchestration as the destination task-specific orchestration; and, in accordance with categorizing the user query in a second category, assigning a third task-specific orchestration as the destination task-specific orchestration. The method further includes, in response to providing the information about the user query, receiving an output from the destination task-specific orchestration; and providing a response to the user query via the user interface based on the output from the destination task-specific orchestration.

Methods, systems, and software are provided for determining a microsatellite instability (MSI) status of a subject. Nucleotide sequences are obtained for cell-free DNA molecules from a liquid biopsy sample of the subject. The nucleotide sequences are used to determine, for each respective microsatellite locus in a plurality of predetermined microsatellite loci, one or more independent corresponding metrics, where each metric in the one or more metrics is determined at least in part by the distribution of the number of repeat units at the respective microsatellite locus. The one or more metrics are input into a classifier trained to distinguish between stable and unstable microsatellite loci, in order to classify the MSI status of the subject. In certain aspects, microsatellite stability metrics are compared against metrics from solid tumor samples and/or normal tissues. In certain aspects, the microsatellite stability metrics are determined relative to a subject-specific standard for microsatellite stability.

Disclosed herein are recombinant meganucleases engineered to recognize and cleave a recognition sequence present in the human mitochondrial DNA (mtDNA). The disclosure further relates to the use of such recombinant meganucleases in methods for producing genetically-modified eukaryotic cells, and to a population of genetically-modified eukaryotic cells wherein the mtDNA has been having modified or edited.

Computer systems and methods are provided for compiling a computer program to run on a quantum processor or system comprising a plurality of qubits, qudits or quantum continuous variables. A compiler obtains the program in a unified language, that is effectively a classical language, as opposed to a quantum language, and performs code refactoring on all or a portion of the program to form a refactored code and sequentially converts the refactored code into a plurality of instances of a compiled code including a first instance in the sequential plurality of instances of the compiled code and a final instance in the sequential plurality of instances of the compiled code. The final instance in the sequential plurality of instances of the compiled code is expressed in a quantum gate-level language in accordance with an instruction set and gate locality constraints of the target quantum processor or system.

Systems and methods for tissue classification are provided. An image of tissue on a substrate is obtained as a plurality of pixels. Fiducial markers are on the substrate boundary. Pixels are assigned to a first class, indicating tissue sample, or a second class, indicating background. The assigning uses the fiducial markers to define a bounding box within the image and disregards pixels outside the box. Then, heuristic classifiers are applied to the pixels: for each respective pixel in the plurality of pixels, each heuristic classifier votes for the respective pixel between the first and second class, thereby forming an aggregated score for each pixel that in one of first class, likely first class, likely second class, and obvious second class. The aggregated score and intensity of each pixel is applied to a segmentation algorithm to assign a probability to each pixel of being tissue sample or background.

Methods, systems, and software are provided for using organoid cultures, e.g., patient-derived tumor organoid cultures, to improve treatment predictions and outcomes.

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