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.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that a implement a framework for active learning to discover pairwise interactions via representation learning. Indeed, in one or more implementations, the disclosed systems generate a first individual perturbation embedding from a first representation of a first cell exposed to a first perturbation and a second individual perturbation embedding, from a second representation of a second cell exposed to a second perturbation. For instance, the disclosed systems combine the first individual perturbation embedding and the second individual perturbation embedding to determine a predicted pairwise embedding. Moreover, in some instances, the disclosed systems generate a pairwise embedding from a representation of a cell exposed to both the first and second perturbation.

Abstract: The invention provides a method of diagnosing overactive bladder disorder (OAB), the method comprising: measuring the concentrations of one or more of adenosine triphosphate (ATP), acetylcholine (ACh), nitric oxide (NO) and interleukin 5 (IL-5) in a sample obtained from a subject; normalising the concentrations to the concentration of creatinine (Cr) in the sample; range standardising the normalised concentrations and subject's age to the following values: Age to 120 years old; ATP/Cr to 0.000001; ACh/Cr to 0.1; NO to 20000; IL-5/Cr to 100; wherein the likelihood of having OAB (pOAB)=1/1+e?x, where X=one or more of the following: (a) (?2.688±1.050)+5.472±2.098×subject's age+1.356±0.559×Gender (Female=1, Male=0)+(?7.998±40.273)×[IL-5/Cr]; (b) (?2.141±0.966)+4.506±1.902×subject's age+1.034±0.519×Gender (Female=1, Male=0)+(?5294.063±9075.456)×[ACh/Cr]; (c) (?2.825±1.072)+5.964±2.167×subject's age+1.312±0.562×Gender (Female=1, Male=0)+17.790±58.762×[IL-5/Cr]+(?9180.821±12700.057)×[ACh/Cr]; (d) (?2.993±1.197)+5.

Abstract: A predictive system may access a set of physical structures corresponding to a physical system. Each physical structure representative of a configuration. The predictive system may encode the accessed physical structures to produce a set of encoded physical structures by encoding, for each accessed physical structure, a position of each constituent unit of the physical system within the accessed physical structure. The predictive system may train a machine-learned model using the encoded physical structures. The predictive system may retrain the machine-learned model by iteratively: accessing a set of two or more candidate physical structures, determining a first energy difference among the set of candidate physical structures, obtaining a second energy difference between a set of physical structures corresponding to the set of candidate physical structures using a method to calculate reference energy values.

Abstract: Virus-Like Particles derived from the subfamilies, Parahepevirinae, which infect trout and salmon, and the Orthohepevirinae, which infect mammals and birds, particularly those of the species Paslahepevirus balayani, which can cause acute hepatitis in humans and several mammalian species, and chronic conditions in immunocompromised patients are also disclosed. Major aspects of the invention relate to compositions of Virus-Like Particles comprising viral capsid proteins capable of assembly in cultured cells that may be purified, disassembled, and reassembled in the presence of other molecules suitable for use as therapeutic drug products to facilitate the targeting and delivery of cargo molecules to specific cells or tissues, or as antigenic agents designed to stimulate responses to heterologous epitopes exposed on the surfaces of Virus-Like Particles.

Abstract: The present invention relates to a phage or a composition that comprises it, wherein said phage expresses at least one specific recognition element and is furthermore conjugated with at least 300 molecules of a sonosensitiser. The invention further relates to the use of said phage in a sonodynamic therapy.

Abstract: The present disclosure provides, in part, nucleic acid loaded flowable hydrogels and compositions, systems and methods related thereto, to effectively deliver nucleic acids to cells that contact the flowable hydrogels.

Abstract: A method and a system of molecular typing and subtyping classifier for immune-related diseases are provided. The method includes: conducting molecular typing via a clustering algorithm in a training set to obtain a plurality of subtypes stably appearing in the training set and a marker gene for each subtype; conducting enrichment analysis on marker genes for the plurality of subtypes, conducting immune cell infiltration evaluation on the plurality of subtypes, and dividing the plurality of subtypes into a plurality of subtype classes according to results of the analysis and the evaluation; comparing treatment response rates of different subtype classes through a comparison set to determine a subtype class to be identified; constructing a support vector machine model with feature genes screened and an optimal parameter combination; and determining whether immune-related disease data to be classified is the subtype class to be identified.

Abstract: The present invention relates to ex vivo methods for obtaining populations of human keratinocytes derived from human pluripotent stem cells (hPSCs). More particularly, the present invention relates to an automated method that combines in a sequential manner automated differentiation and amplification of a population of hPSC-derived keratinocytes.