Abstract: This invention describes an allogenomics mismatch scoring method that estimates the genomic incompatibility between potential organ donors and a transplant recipient. The allogenomics method addresses immunological concerns and compares genotype information from matched, or potential, donors and recipients. The allogenomics method uses genomic data available before transplantation and predicts kidney graft function for greater than three years after transplantation. The strength of the inverse correlation between pre-transplantation genomic mismatches and transplant organ function increases with the time after transplantation: a low allogenomics mismatch score correlates with better acceptance and function of a donor transplant over time.

Abstract: Systems, methods, and apparatuses can determine and use methylation profiles of various tissues and samples. Examples are provided. A methylation profile can be deduced for fetal/tumor tissue based on a comparison of plasma methylation (or other sample with cell-free DNA) to a methylation profile of the mother/patient. A methylation profile can be determined for fetal/tumor tissue using tissue-specific alleles to identify DNA from the fetus/tumor when the sample has a mixture of DNA. A methylation profile can be used to determine copy number variations in genome of a fetus/tumor. Methylation markers for a fetus have been identified via various techniques. The methylation profile can be determined by determining a size parameter of a size distribution of DNA fragments, where reference values for the size parameter can be used to determine methylation levels. Additionally, a methylation level can be used to determine a level of cancer.

Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.

Abstract: Embodiments of the invention are directed to methods of determining the prognosis of a breast cancer patient by evaluating a specified set of genes. Specifically, methods may comprise calculating a prognosis score based on a particular algorithm. Also disclosed are compositions, kits and methods for treating cancer in a subject in need thereof are disclosed involving one or more upstream activators and/or downstream effectors of TET1.

Abstract: A training apparatus includes: a controller. The controller is configured to: (a) while a subject is performing a behavior, acquire time-series myoelectric potentials of each of muscles of the subject; (b) calculate a muscle synergy matrix W, a control matrix C and an error matrix E from a myoelectric potential matrix M so that the relationship M=WC+E is satisfied, row vectors each expressing the acquired time-series myoelectric potentials of a corresponding one of the muscles, m being arranged in rows in the myoelectric potential matrix, n unit column vectors being arranged in columns in the muscle synergy matrix W, n row vectors being arranged in rows in the control matrix; (c) calculate a feature quantity indicating consistency among the unit column vectors included in the calculated muscle synergy matrix W; and (d) output the calculated feature quantity.

Abstract: The methods herein can allow for the optimised selection and isolation, within a respective population, of elements of interest and/or utility for a series of subsequent operations. A method can include the phases of: a) identifying, for each particle, at least one of a plurality of characteristic parameters; b) selecting the particles of interest, comparing for each of these the at least one parameter with a respective reference parameter. It can furthermore include the phases of c) storing, for each of the particles, the at least one parameter identified; d) processing the value of a function of the stored parameter, associating the function with a criterion for selection of the particles of interest chosen from a group of possible selection criteria; e) establishing for each particle a threshold criterion to be used as reference parameter. The threshold criterion is established on a time by time basis according to the result of the above processing.

Abstract: The present disclosure provides methods for profiling a microbiome and therapeutic compositions for treatment. Additionally, the methods, systems, compositions and kits provided herein are directed to assessing or predicting health status in a subject. Some of the embodiments include generating a report.

Abstract: Techniques for biochemcally-enabled security/authentication mechanisms are described herein. In an example embodiment, a security system receives a biological sample from a key. The biological sample includes a set of deoxyribonucleic acid (DNA) oligos that represent a code assigned to the key. The set of DNA oligos is sequenced to obtain a set of read sequences. The set of read sequences is then filtered to identify a set of filtered sequences. The set of filtered sequences is matched to sets of expected sequences, where the sets of expected sequences are assigned to respective keys issued for the security system. Access to a resource is then granted or denied based on whether the set of filtered sequences matches with any set from the sets of expected sequences.

Abstract: Methods and systems for identifying causal genetic mechanisms of antibiotic resistance in pathogens. In accordance with at least one embodiment, the system includes a gene resistance module to identify genes present in an antibiotic resistant pathogen, a single nucleotide polymorphism module to identify mutations present in an antibiotic resistant pathogen, and an antibiotic resistance module configured to output the causation of antibiotic resistance based on the identified genes and mutations.

Abstract: Omics patient data are analyzed using sequences or diff objects of tumor and matched normal tissue to identify patient and disease specific mutations, using transcriptomic data to identify expression levels of the mutated genes, and pathway analysis based on the so obtained omic data to identify specific pathway characteristics for the diseased tissue. Most notably, many different tumors have shared pathway characteristics, and identification of a pathway characteristic of a tumor may thus indicate effective treatment options ordinarily not considered when tumor analysis is based on anatomical tumor type only.

Abstract: Refusal-based methods of establishing a cat or dog food preference, which can include methods of selecting a preferred cat or dog food among multiple foods as well as methods of determining palatability are provided. The methods can include presenting a cat or dog with one or more small samples of a test food and observing for refusal behavior, which can include refusing to eat a food sample. Higher numbers of instances of refusal of a particular food can be correlated with lower palatability.

Abstract: Methods, systems, and apparatus for determining probabilistic measures of seizure activity (PMSA) values based on a plurality of seizure detection algorithms and/or body signals used as inputs by the seizure detection algorithms. Use of the PMSA values to detect seizure activity based on a consensus of the algorithms and/or body signals, and/or warn, log, administer a therapy, or assess the efficacy of a therapy.

Abstract: Systems and methods for performing genomic information compression, transmission, and decompression are provided. A system for compression, transmission, and decompression of genomic information includes a first computer associated with a first index and a second computer associated with a second index, each index containing reference permutations of nucleic acid sequence portions, each permutation associated with a reference number. The first computer uses input genomic information and the first index to produce a compressed representation of the genomic information, and transmits the compressed representation to the second computer. The second computer uses the compressed representation and the second index to assemble a data representation of the genomic information. The compressed representation comprises references to permutations, indications of locations of each permutation in the input information, indications of variations to permutations, and/or indications of sequence length.

Abstract: An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation f ? ( m ) = pN ? ( m ? ? , ? ) pN ? ( m ? ? , ? ) + ( 1 - p ) ? N ? ( m ? ? _ , ? _ ) where: m is the distance calculated for the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range fr

Abstract: A method of identifying a microorganism by mass spectrometry, including acquiring at least one mass spectrum of said microorganism; for each acquired mass spectrum: detecting peaks of the spectrum in a predetermined mass range; generating a list of peaks identifying at most one peak in each interval of a predetermined subdivision of the range of mass-to-charge ratios, the width of the intervals of the subdivision logarithmically increasing along with the mass-to-charge ratio, and analyzing the list(s) of peaks obtained according to a knowledge base of previously-identified microorganisms and/or types of microorganisms.

Abstract: A method of determining the risk of metastasis of prostate cancer in a human subject who has or had prostate cancer is disclosed herein. The method is based on detecting in a prostate sample from the subject the number of copies per cell of genes and/or genomic regions of a metastatic gene signature set disclosed herein, and determining alternations in the number of copies per cell of the genes and/or genomic regions in the signature set, as compared to the number of copies per cell in non-cancer cells, thereby determining the risk of prostate cancer metastasis.

Abstract: Provided is a method, system and/or apparatus for determining prospective heart failure event risk. Acquired from a device memory are a heart failure patient's current and preceding risk assessment periods. Counting detected data observations in the current risk assessment period for a current risk assessment total amount and counting detected data observations in the preceding risk assessment period for a preceding risk assessment period total amount. Associating the current risk assessment and preceding risk assessment total amounts with a lookup table to acquire prospective risk of heart failure (HF) event for the preceding risk assessment period and the current risk assessment period. Employing weighted sums of the prospective risk of the HF event for the preceding risk assessment period and the current risk assessment period to calculate a weighted prospective risk of the HF event for a patient. Displaying on a graphical user interface the weighted prospective risk of the HF event for the patient.

Abstract: Disclosed is a system and a method for determining an injectable amount of bile required for a patient after gallbladder removal. The system comprises a receiving module, a creating module, and a determining module. The receiving module may receive a bile-flow rate, physiological parameters of a patient, and amount of fatty food in an alimentary tract of the patient. Based on these data received, the creating module may create a graph. Further, the determining module may determine a correlation between the bile-flow rate and the amount of fatty food in the alimentary tract based on the graph created. The correlation may be determined corresponding to a normal person and the patient which may be seen by two separate curves on the graph. Further, the determining module may determine an injectable amount of bile required for the patient based on the correlation.

Abstract: Described herein are methods of identifying tumor-specific epitopes from the cancer tissue DNA of cancer patients using both DNA sequencing and bioinformatics techniques. The identification of tumor-specific epitopes provides pharmaceutical compositions with a limited number of tumor-specific peptides suitable for personalized genomics-driven immunotherapy of human cancer. Specifically disclosed herein is a novel index called the Differential Agretopic Index (DAI) for the epitope which allows prediction of whether immunization with a particular epitope will be protective against the tumor. Pharmaceutical compositions and methods of administration are also included.

Abstract: A method of determining an ESA dose, which allows a hemoglobin concentration in the blood to be stably maintained at a target value, and which can decrease a range of fluctuation of the hemoglobin concentration with respect to the target value. The method comprises the steps of: setting the target value of the hemoglobin concentration in the blood; calculating a target value of a hemoglobin production rate which allows the hemoglobin concentration to reach the target value; calculating a serum ESA concentration which allows the hemoglobin production rate to reach the target value, from a relationship between the hemoglobin production rate and the ESA concentration; and calculating an amount of administration of an ESA which gives the serum ESA concentration, from a relationship between the ESA concentration and the amount of administration of the ESA, to determine an ESA dose which allows the hemoglobin concentration to reach the target value.