Abstract: Provided herein are compositions and methods for gene therapy for disorders of arterial calcification as well as Generalized Arterial Calcification of Infancy (GACI). The methods include a gene addition strategy to deliver a DNA construct to target tissues (such as liver and smooth muscle cells) to express soluble recombinant ENPP1 (srENPP1) or transmembrane full-length recombinant ENPP1 (rENPP1).

Abstract: The invention provides a system and method for generating biologically optimized codon sequences corresponding to a given protein sequence using a generative language model and reinforcement learning. A codon generation model receives an amino acid sequence and outputs a synonymous nucleotide sequence constrained by a codon masking mechanism to ensure translational fidelity. A composite reward function incorporating biologically relevant metrics, such as codon adaptation index (CAI), GC content, and mRNA folding stability, guides the optimization process. The model is fine-tuned using reinforcement learning to maximize the reward signal and produce codon sequences suitable for enhanced expression in specified host organisms. The system supports software-based deployment as an API or cloud interface and is applicable to synthetic biology, mRNA therapeutics, gene therapy, and protein manufacturing.

Abstract: Technologies are disclosed for quantitatively predicting whether or not a deterioration in their health status is likely within a future time interval subsequent to computing a prediction. In one embodiment, serial medical data of a particular patient is received from a plurality of inputs. Based on a transformation of the received data, a predicted probability of acute deterioration (PPOD) score is determined. The PPOD score is provided to clinicians, to ensure that timely and effective measures may be taken to mitigate the patient's chances of acute deterioration.

Abstract: The present invention relates to a method for selecting cancer neoantigens for use in a personalized vaccine. This invention relates as well to a method for constructing a vector or collection of vectors carrying the neoantigens for a personalized vaccine. This invention further relates to vector and collection of vectors comprising the personalized genetic vaccine and the use of said vectors in cancer treatment.

Abstract: Expression constructs and methods for recombinant parvovirus production are disclosed. In some embodiments, the expression construct encodes (1) adenovirus E4 and E2a proteins, (2) parvovirus proteins necessary for the production of the recombinant parvovirus, and (3) a recombinant parvovirus genome, thus allowing production of the recombinant parvovirus by transfecting a host cell with a single expression construct.

Abstract: Methods and systems for designing phage therapy cocktails. A candidate phage selector module may be configured to predict lytic activity of phages using a first trained machine learning algorithm, and select candidate phages based at least in part on predicted lytic activity. A cocktail generator module may be configured to generate a set of phage cocktails using a second trained machine learning algorithm, based at least in part on predicted lytic activity. A feedback panel module may be configured to receive feedback information associated with phage cocktails, and use the feedback information to train the first and/or second trained machine learning algorithms.

Abstract: Disclosed are a method and device for fixed-point editing of a nucleotide sequence stored with data.

Abstract: This disclosure relates generally to a computational model for personalizing defibrillation mechanism of wearable cardiac defibrillator (WCD). Cardiac defibrillators are lifesaving therapeutic device with potentially harming capacity if not tuned properly. Hence creation of a personalized energy distribution model based on subject's anatomy, rather than a ‘one size fits all’ approach is preferred. The disclosed model compares the efficiency of standard and nonstandard WCD electrode placement in the torso vest, demonstrating significant differences in defibrillation efficacy associated with different strategies. A new measure is presented for performing such a comparison which combines the DFT and extent of myocardial damage.

Abstract: Gene expression vectors of two samples in a gene expression space can be transformed into gene feature vectors in a gene feature space. Gaussian densities and associated weights can be determined for each sample using the corresponding gene feature vectors. Gaussian densities of one samples can be aligned to Gaussian densities of the other sample. A difference between a pair of aligned Gaussian densities of the two samples can be determined, which indicates a difference between subpopulation of cells of the two samples represented by the Gaussian densities of the pair of aligned Gaussian densities.

Abstract: The present disclosure provides methods and systems of identifying an inflammatory disease or condition, e.g., an inflammatory bowel disease in a subject using a DeepLearning model. The DeepLearning model may be used to predict, treat, monitor, and/or prevent the inflammatory disease or condition in the subject, as well as to characterize a subtype of the inflammatory disease or condition.

Abstract: The present disclosure relates to methods for expanding populations of hematopoietic stem cells (HSCs) using a genetically engineered human fetal liver niche and compositions of purified ex vivo expanded HSCs. Also provided herein are methods of using such expanded HSC cell populations for clinical applications including allogeneic hematopoietic stem cell transplantation and for drug discovery and modeling human liver development.

Abstract: A method for analyzing sequences performed by one or more processors is provided, including aligning first sequence data generated at a first time point based on reference sequence data, in which the first time point is a time point after reading of a first read of a pair of paired-end reads is completed and at which a second read of the pair of paired-end reads is partially read, identifying a structural variant from the aligned first sequence data, and before reading the second read is completed, generating a first report including information on the identified structural variant.

Abstract: Mechanisms for molecule design using machine learning include: forming a first training set for a neural network using, for each of a first plurality of known molecules, a plurality of input values that represent the structure of the known molecule and a plurality of functional property values for the known molecule; training the neural network using the first training set; proposing a first plurality of proposed molecules, and predicting first predicted functional property values of the first plurality of proposed molecules that have the desired function property values; causing the first plurality of proposed molecules to be synthesized to form a first plurality of synthesized molecules; receiving first measured functional property values of the first plurality of synthesized molecules; and adding data regarding the first plurality of synthesized molecules to the first training set to form a second training set and retrain the neural network using the second training set.

Abstract: A method is described for real-time detecting and classifying of a characteristic signal, such as a neural spike, and forwarding information for further processing if it meets certain criteria. A system (e.g., an on-chip system implanted in a subject's cranium) receives an electrical biological signal. The system filters the signal to generate a filtered signal and fits the filtered signal to a model. The system identifies a set of fit values based on the model, the set of fit values comprising a plurality of sample amplitude values and a respective plurality of time values. Based on the fit values, the system computes a set of characteristic values. The system compares the characteristic values to a corresponding set of threshold values. Based on the comparison, the system determines whether the received biological signal corresponds to a neural spike and, if a spike is detected, forwards on information.

Abstract: Artificial expression constructs for modulating gene expression in targeted central nervous system cell types are described. The artificial expression constructs can be used to express synthetic genes or modify gene expression in chandelier cells. Chandelier cells are a subtype of GABAergic interneurons that that have been implicated in disorders such as epilepsy and schizophrenia.

Abstract: The present invention features a dual vector system for disrupting and replacing a target gene comprising a mutation (e.g., dominant, recessive mutation). Embodiments of the invention may also provide compositions comprising the dual vector system, and methods of using the dual vector system, including but not limited to methods of modifying the genome of a cell, methods of genomic editing, and methods of treating cells or a subject suffering from a genetic disease comprising a mutation.

Abstract: The present invention provides a recombinant adeno-associated virus (rAAV) particle of 6.2 serotype comprising a recombinant nucleic acid comprising a lung-specific SpB promoter and a therapeutic gene, wherein the lung-specific promoter comprises SEQ ID NO: 1, and wherein said promoter is operably linked to and regulates the expression of the therapeutic gene.

Abstract: Technologies are described related to determining protein structure and properties based on sequences of proteins. In various implementations, a first model can be generated to determine structural features of proteins based on amino acid sequences of the proteins. Additionally, a second model can be generated to determine biophysical properties of proteins based on structural features of the proteins. In particular implementations, an amino acid sequence of a particular protein can be utilized by the first model to determine one or more structural features of the protein. The one or more structural features of the protein generated by the first model can be utilized by the second model to determine at least one biophysical property of the protein.

Abstract: A chimeric non-human mammal disease model, wherein (1) at least 30% of all the glial cells in the corpus callosum of the chimeric non-human mammal are human glial cells, and/or (2) at least 5% of all of the glial cells in the white matter of the brain and/or brain stem of the chimeric non-human mammal are human glial cells, and wherein the human glial cells comprise a combination of a first group of human glial cells tagged with a first label and a second group of human glial cells tagged with a second label that is distinguishable from the first label.

Abstract: The present invention provides transgenic animals (e.g., transgenic porcine animals), organs, tissues, and cells derived from the transgenic animals that are particularly useful for xenotransplantation therapies. In particular, the present invention provides transgenic porcine animals, as well as organs, tissues and cells derived from the transgenic porcine animals, which lack any expression of a functional alpha 1,3 galactosyltransferase (GTKO) gene and comprise at least six transgenes under the control of at least three promoters within a single multi-gene expression vector, and further comprise at least four additional genetic modifications. Also provided are methods of making the transgenic animals (e.g., transgenic porcine animals), and methods of using the transgenic animals, organs, tissues, and cells derived from the transgenic animals for xenotransplantation therapies and treating a disease or condition.