Abstract: Systems, methods and/or devices for treating diabetes mellitus by alleviating glucotoxicity and restoring pancreatic beta-cell function, comprising at least a first memory for storing data inputs corresponding at least to one or more components in a patient's present insulin dosage regimen, and data inputs corresponding at least to the patient's blood-glucose-level measurements determined at a plurality of times, and a processor operatively connected to the at least first memory. The processor is programmed at least to determine from the data inputs corresponding to the patient's blood-glucose-level measurements determined at a plurality of times whether and by how much to vary at least one of the components of the patient's present insulin dosage regimen.

Abstract: Computer based methods, systems, and computer readable media for intelligently accessing various types of pharmaceutical information in a content repository and ranking drugs at the variant level, gene level, and pathway level. In some cases, drugs that target the same gene, gene variant, or biological pathway may be ranked based upon in vitro, pre-clinical, clinical, or post-clinical evidence. To determine ranking of a plurality of drugs, information pertaining to drug administration is analyzed for the drugs. For a plurality of drugs, attributes corresponding to the drug are determined, wherein the attributes include a variant or a gene targeted by the drug, and a biological pathway comprising the targeted variant or gene. The plurality of drugs are ranked according to a drug effectiveness score based on one or more of a determined efficacy, potency, or toxicity.

Abstract: Provided are a method of detecting chromosomal aneuploidy of a targeted fetal chromosome, and a computer-readable medium having recorded thereon a program to be applied to performing the method. According to the present disclosure, fetal chromosomal aneuploidy may be non-invasively and prenatally diagnosed with excellent sensitivity and specificity.

Abstract: Disclosed is a computer-implemented method of screening a patient for end organ damage due to infection. The method entails receiving patient data relating to an identified patient in a computing system including a processor and memory coupled to the processor, wherein the memory stores programmable instructions executable by the processor. The presence of Systemic Inflammatory Response Syndrome is determined and then the presence or absence of a high probability of end organ damage due to infection. Each of the determining steps includes receiving, on a graphical user interface, one or more user selections presented on the graphical user interface and executing programmable instructions based on received user selections.

Abstract: Fisher discriminant analysis is performed on data sets of typically developing (TD) individuals and data sets of autism spectrum disorder (ASD) individuals to produce a model that classifies TD individuals from ASD individuals. The ASD data sets include pre-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data and post-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data for patients receiving one or more ASD treatments. Changes in adaptive behavior are predicted by utilizing regression of changes in adaptive behavior and changes in biochemical measurements observed in the data sets. Thus, the system can be used to predict the effectiveness of a given course of treatment for an ASD patient based on measured metabolite data of that patient, or to predict the overall effectiveness of a clinical trial based on metabolite data for the trial participants.

Abstract: The present disclosure provides computing device implemented methods, computing device readable media, and systems for adjustment of tooth position in a virtual dental model. Virtual dental modeling can include detecting space and/or collision between posterior teeth of an upper jaw and posterior teeth of a lower jaw in a virtual dental model that has been set in a preliminary target position. An energy function can be defined including the space and/or collision, tooth root movement, and align points. Weights can be assigned for each variable in the energy function. A position of the posterior teeth of the upper jaw and the posterior teeth of the lower jaw can be adjusted in six degrees of freedom to minimize the energy function. The detection, definition, assignment, and adjustment can be repeated until the energy function converges. The weights can be adjusted to reduce the space and/or collision.

Abstract: The present specification provides a method of calculating a diagnostic score for prostate cancer by combining at least two values. The method comprises preparing a sample, obtaining a first value, obtaining a second value, and calculating a diagnostic score. The sample is a urine sample from a subject, and the first value corresponds to an amount of a hsa-miR-3659 or hsa-miR-3679-5p derived from extracellular vesicles in the sample, and the second value corresponds to a miRNA derived from the extracellular vesicles in the sample. Both the first and second values include information on whether the subject has developed prostate cancer, and the second value corresponds to a normalization factor specialized for the first value. The diagnostic score for prostate cancer calculated according to the method is characterized by being capable of diagnosing prostate cancer. The present specification provides a use of the diagnostic score for prostate cancer.

Abstract: Systems and methods for providing a clotting factor VIII (CFVIII) dosing regimen include collecting two blood samples from a patient after an infusion of CFVIII and determining a CFVIII clearance based on the two blood samples, and determining if a patient has a half-life greater than a predetermined threshold. A pharmacokinetic (PK) profile of the patient is determined using a Bayesian model of pharmacokinetic profiles of sampled patients having similar body weight or age of the patient. A first weight is applied to the Bayesian model of pharmacokinetic profiles of sampled patients if the half-life of the patient is greater than the predetermined threshold, and a second weight, less than the first weight, is applied to the Bayesian model of pharmacokinetic profiles of sampled patients if the half-life of the patient is less than the predetermined threshold. A dosing regimen is determined for the patient based on the PK profile.

Abstract: The present invention relates to a method of predicting a performance characteristic of a plant or yeast hydrolysate, wherein a plant or yeast hydrolysate sample is measured with 2D fluorescence spectroscopy in powder form. Said method comprises the steps for providing a model based on a predetermined value of a manufacturing parameter of interest. For this purpose a training set consisting of predetermined manufacturing parameter of interest (e.g volumetric productivity parameter, virus titer or cell number) and fluorescence spectroscopic data is used. The fluorescence spectroscopic data is correlated to the values of the manufacturing parameter of interest to obtain a calibration model/model parameters by applying multivariate data analysis. This calibration model is being used to predict the manufacturing parameter of interest for new samples dedicated for the manufacturing process.

Abstract: A neural network model is generated for drug efficacy prediction in treatment of genetic disease from a dataset correlating biomolecular data for disease-cell samples with drug efficacy values for a plurality of drugs, including defining training data pairs each including biomolecular data for a sample represented in the dataset and a string representation of a drug represented in the dataset; and using the training data pairs and the drug efficacy values corresponding to respective pairs to train weights of the model including a first attention-based encoder which encodes the biomolecular data of each pair, to produce encoded biomolecular data, a second attention-based encoder which encodes the string representation of each pair, to produce encoded string data, and a set of neural network layers which process the encoded biomolecular and string data for each pair, to produce a model output corresponding to drug efficacy.

Abstract: A method of evaluating gastrointestinal cancer risk. The method comprises generating a set of features comprising a plurality of current blood test results from a blood collected from a target individual, providing at least one classifier generated according to an analysis of a plurality of respective historical blood test results of each of another of a plurality of sampled individuals, and evaluating, using a processor, a gastrointestinal cancer risk of the target individual by classifying the set of features using the at least one classifier.

Abstract: Provide a reinforcement learning model including an agent and a critic; the critic includes a neural network pre-trained to generate, from input biomolecular data characterizing tissue cells and input compound data defining a compound molecule, a property value for said biomolecular action of that molecule on those tissue cells. The agent includes a neural network adapted to generate the compound data in dependence on input biomolecular data. Supply biomolecular data characterizing patient tissue cells to the agent and supply that data, and the compound data generated therefrom, to the critic to obtain a property value in an iterative training process in which reward values, dependent on the property values, are used to progressively train the agent to optimize the reward value. After training the agent, supply target biomolecular data, characterizing the target tissue cells, to the agent to generate compound data corresponding to a set of drug compounds.

Abstract: Systems and methods for detecting and reporting patterns in analyte concentration data are provided. According to some implementations, an implantable device for continuous measurement of an analyte concentration is disclosed. The implantable device includes a sensor configured to generate a signal indicative of a concentration of an analyte in a host, a memory configured to store data corresponding at least one of the generated signal and user information, a processor configured to receive data from at least one of the memory and the sensor, wherein the processor is configured to generate pattern data based on the received information, and an output module configured to output the generated pattern data. The pattern data can be based on detecting frequency and severity of analyte data in clinically risky ranges.

Abstract: There is provided a blood condition analyzing device including: an extraction unit configured to use temporal change data of an electrical characteristic of blood at an arbitrary frequency to extract a feature of the data; and a blood condition evaluation unit configured to evaluate a condition change of blood from a feature extracted in the extraction unit.

Abstract: The present disclosure provides methods for determining a probability that after any of a number of therapeutic interventions, an initial state of a subject, such as somatic cell mutational status of a subject with cancer, will develop a subsequent state. Such probabilities can be used to inform a health care provider as to particular courses of treatment to maximize probability of a desired outcome for the subject.

Abstract: Factors affecting the fragmentation pattern of cell-free DNA (e.g., plasma DNA) and the applications, including those in molecular diagnostics, of the analysis of cell-free DNA fragmentation patterns are described. Various applications can use a property of a fragmentation pattern to determine a proportional contribution of a particular tissue type, to determine a genotype of a particular tissue type (e.g., fetal tissue in a maternal sample or tumor tissue in a sample from a cancer patient), and/or to identify preferred ending positions for a particular tissue type, which may then be used to determine a proportional contribution of a particular tissue type.

Abstract: Methods, non-transitory computer-implemented methods and systems for identifying compound heterozygous mutations (CHMs) and de novo mutations (DNMs) in populations are provided. Also provided are methods for phasing genetic variants in a population by leveraging the population's relatedness. Further provided is a prediction model of relatedness in a human population.

Abstract: Factors affecting the fragmentation pattern of cell-free DNA (e.g., plasma DNA) and the applications, including those in molecular diagnostics, of the analysis of cell-free DNA fragmentation patterns are described. Various applications can use a property of a fragmentation pattern to determine a proportional contribution of a particular tissue type, to determine a genotype of a particular tissue type (e.g., fetal tissue in a maternal sample or tumor tissue in a sample from a cancer patient), and/or to identify preferred ending positions for a particular tissue type, which may then be used to determine a proportional contribution of a particular tissue type.

Abstract: Factors affecting the fragmentation pattern of cell-free DNA (e.g., plasma DNA) and the applications, including those in molecular diagnostics, of the analysis of cell-free DNA fragmentation patterns are described. Various applications can use a property of a fragmentation pattern to determine a proportional contribution of a particular tissue type, to determine a genotype of a particular tissue type (e.g., fetal tissue in a maternal sample or tumor tissue in a sample from a cancer patient), and/or to identify preferred ending positions for a particular tissue type, which may then be used to determine a proportional contribution of a particular tissue type.

Abstract: According to some embodiments, a system for performing secure data exchange in a digital ecosystem is disclosed. The system includes a plurality of progeny VDAXs, wherein each respective progeny VDAX is configured with a respective ecosystem security platform that is executed by a respective device and has a respective genomic data set assigned thereto. The respective ecosystem security platform is configured to: establish engagement eligibility with another progeny VDAXs of the plurality of progeny VDAXs based on its genomic data set, generate a spawned link that includes encoded regulation instructions and is sent to the other progeny VDAX, and decode VBLS objects that are encoded by the other progeny VDAX based on the unique genomic regulation instructions that were included in the spawned link and the genomic data set assigned to the respective progeny VDAX to obtain decoded digital objects.