C12Q1/6809

METHOD AND SYSTEM OF DIAGNOSING AND TREATING NEURODEGENERATIVE DISEASE AND SEIZURES
20230010690 · 2023-01-12 ·

A method of distinguishing a subject with pre-clinical Alzheimer's disease from those with similar symptoms but other forms of dementia such as mild cognitive impairment. The blood RNA whole transcriptome profile of a subject with suspected pre-clinical Alzheimer's disease is obtained and analyzed against a reference blood RNA whole transcriptome profile from a subject with another form of dementia such as frontal temporal dementia, CADASIL or mild cognitive impairment (MCI). The blood RNA whole transcriptome profile includes the presence and quantitation of ncRNA. Methods to enhance treatment of epileptic seizures are also discussed.

Methods for biological sample processing and analysis

Provided are methods for biological sample processing and analysis. A method can comprise providing a substrate configured to rotate. The substrate can comprise an array having immobilized thereto a biological analyte. A solution comprising a plurality of probes may be directed, via centrifugal force, across the substrate during rotation of the substrate, to couple at least one of the plurality of probes with the biological analyte. A detector can be configured to detect a signal from the at least one probe coupled to the biological analyte, thereby analyzing the biological analyte.

Methods for biological sample processing and analysis

Provided are methods for biological sample processing and analysis. A method can comprise providing a substrate configured to rotate. The substrate can comprise an array having immobilized thereto a biological analyte. A solution comprising a plurality of probes may be directed, via centrifugal force, across the substrate during rotation of the substrate, to couple at least one of the plurality of probes with the biological analyte. A detector can be configured to detect a signal from the at least one probe coupled to the biological analyte, thereby analyzing the biological analyte.

EFFICIENT ARRAYS OF AMPLIFIED POLYNUCLEOTIDES

The present invention is related generally to analysis of polynucleotides, particularly polynucleotides derived from genomic DNA. The invention provides methods, compositions and systems for such analysis. Encompassed by the invention are arrays of polynucleotides in which the polynucleotides have undergone multiple rounds of amplification in order to increase the strength of signals associated with single polynucleotide molecules.

EFFICIENT ARRAYS OF AMPLIFIED POLYNUCLEOTIDES

The present invention is related generally to analysis of polynucleotides, particularly polynucleotides derived from genomic DNA. The invention provides methods, compositions and systems for such analysis. Encompassed by the invention are arrays of polynucleotides in which the polynucleotides have undergone multiple rounds of amplification in order to increase the strength of signals associated with single polynucleotide molecules.

Assays and methods for determining microbial resistance

Assays and methods for detecting resistance to beta-lactam antibiotics including detection of multiple β-lactamase family specific gene targets by polymerase chain reaction or microarray. One or more kits including primers and/or probes for identification of β-lactamase genes selected from the group consisting of one or more of the following: MOX-like, FOX-like, ACC-like, ACT/MIR-like, CMY-2-like, DHA-like, CTX-M-14-like, CTX-M-15-like, VIM-like, NDM-like, IMP-like, KPC-like, and OXA-48-like, OXA-51-like, OXA-143-like, OXA-58-like, OXA-23-like, OXA-24/40-like, TEM-like, and SHV-like. A kit may also include one or more primers and/or probes for the identification a non-beta lactamase gene family which confers antibiotic resistance, such as the MCR-1 gene.

Assays and methods for determining microbial resistance

Assays and methods for detecting resistance to beta-lactam antibiotics including detection of multiple β-lactamase family specific gene targets by polymerase chain reaction or microarray. One or more kits including primers and/or probes for identification of β-lactamase genes selected from the group consisting of one or more of the following: MOX-like, FOX-like, ACC-like, ACT/MIR-like, CMY-2-like, DHA-like, CTX-M-14-like, CTX-M-15-like, VIM-like, NDM-like, IMP-like, KPC-like, and OXA-48-like, OXA-51-like, OXA-143-like, OXA-58-like, OXA-23-like, OXA-24/40-like, TEM-like, and SHV-like. A kit may also include one or more primers and/or probes for the identification a non-beta lactamase gene family which confers antibiotic resistance, such as the MCR-1 gene.

Long non-coding RNA gene expression signatures in disease diagnosis
11708600 · 2023-07-25 · ·

Differential expression of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) are used to diagnose diseases including neurological diseases, inflammatory diseases, rheumatic diseases, and autoimmune diseases. Machine learning systems are used to identify lncRNAs or eRNAs having differential expression correlated with certain disease states.

Long non-coding RNA gene expression signatures in disease diagnosis
11708600 · 2023-07-25 · ·

Differential expression of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) are used to diagnose diseases including neurological diseases, inflammatory diseases, rheumatic diseases, and autoimmune diseases. Machine learning systems are used to identify lncRNAs or eRNAs having differential expression correlated with certain disease states.

Methods and systems for identifying target genes

The present disclosure provides methods and systems for identification of genomic regions for therapeutic targeting. A method for identifying one or more genomic regions for therapeutic targeting, which may facilitate re-programming of a cell from one phenotypic state to another, may comprise: providing single-cell RNA-seq data for a plurality of diseased cells and a plurality of normal cells of a cell type; mapping the single-cell RNA-seq data for the plurality of diseased cells and the plurality of normal cells into a latent space corresponding to a plurality of phenotypic states of the cell type; identifying, based at least in part on a topology of the latent space, the one or more genomic regions for therapeutic targeting; and electronically outputting the one or more genomic regions for therapeutic targeting.