The invention relates to the use of an iron-score based on the expression level of at least 2 genes, in particular at least 5, preferably at least 10, and even preferably 11 genes selected in the group consisting of ALAS1, HIF1A, LRP2, HMOX1, HMOX2, HFE, ISCA1, SLC25A37, PPOX, STEAP1 and TMPRSS6 involved in the iron metabolism, as a prognosis marker in subjects having DLBCL, in particular for identifying subjects with a poor outcome such as a relapse and/or death.

A method for providing a diagnosis and/or prognosis for a mitochondrial DNA (mtDNA) disorder or determining the risk of a mtDNA disorder developing in a subject, the method comprising the steps of assaying a stool sample from the subject to measure the level of mutated mtDNA molecules is provided. Methods for monitoring the progression of a mtDNA disorder, evaluating therapeutic effect of a treatment for a mtDNA disorder, and determining a subjects compliance with a prescribed treatment for a mtDNA disorder using a stool sample are also provided. Further, methods of treating a mtDNA disorder and uses of a stool sample in the methods described herein are also provided.

An in vitro or ex vivo method for determining the risk of incidence of a healthcare-associated infection includes a step of measuring the expression of TAP2 in a biological sample from said patient.

The present invention relates to a method of diagnosing or predicting the prognosis of colorectal cancer by measuring the methylation level in the intragenic region of PDXJ, EN2 and/or MSXJ. The present invention provides highly reliable biomarkers for colorectal cancer by identifying CpG regions in genes that are hypermethylated specifically in colorectal cancer patients, and also provides optimized methylation-specific PCR (MSP) primers capable of efficiently detecting the identified CpG regions. Accordingly, the present invention may provide important clinical information that makes it possible to accurately predict not only the onset of colorectal cancer, but also overall prognosis including the degree of invasion of cancer tissue, the likelihood of metastasis, and the survival rate of the patient, thereby establishing a treatment strategy early and significantly improving the survival rate of colorectal cancer patients. The present invention also provides, as guidelines for the design of primers capable of accurately detecting DNA methylation, optimal parameters for the amplicon length, the total number of CpGs in target gene-binding regions of the primers, and the range of Tm values.

Provided herein are systems and methods for determining a subject's risk of spontaneous coronary artery dissection (SCAD) and myocardial infarction (MI) and systems and methods of using SCAD and/or MI risk for treatment thereof.

Systems, methods, and apparatuses for generating and using machine learning models using genetic data. A set of input features for training the machine learning model can be identified and used to train the model based on training samples, e.g., for which one or more labels are known. As examples, the input features can include aligned variables (e.g., derived from sequences aligned to a population level or individual references) and/or non-aligned variables (e.g., sequence content). The features can be classified into different groups based on the underlying genetic data or intermediate values resulting from a processing of the underlying genetic data. Features can be selected from a feature space for creating a feature vector for training a model. The selection and creation of feature vectors can be performed iteratively to train many models as part of a search for optimal features and an optimal model.

The majority of glioblastomas can be classified into molecular subgroups based on mutations in the TERT promoter (TERTp) and isocitrate dehydrogenase 1 or 2 (IDH). These molecular subgroups utilize distinct genetic mechanisms of telomere maintenance, either TERTp mutation leading to telomerase activation or ATRX-mutation leading to an alternative lengthening of telomeres phenotype (ALT). However, about 20% of glioblastomas lack alterations in TERTp and IDH. These tumors, designated TERTp.sup.WT-IDH.sup.WT glioblastomas, did not have well-established genetic biomarkers or defined mechanisms of telomere maintenance. The genetic landscape of TERTp.sup.WT-IDH.sup.WT glioblastoma includes tumors that have chromosomal rearrangements upstream of TERT. These rearrangements define a novel molecular subgroup of glioblastoma, that is a telomerase-positive subgroup driven by TERT-structural rearrangements (IDH.sup.WT-TERT.sup.SV).

Disclosed herein is a combination of genomic sequences whose methylation patterns have utility for the improved detection and differentiation between colorectal neoplasms. Further disclosed herein are methods, nucleic acids and kits for detecting or differentiating between colorectal neoplasms.

Disclosed herein is a system and method for increasing the fidelity of measured genetic data, for making allele calls, and for determining the state of aneuploidy, in one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available. Poorly or incorrectly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related individuals. In accordance with one embodiment, incomplete genetic data from an embryonic cell are reconstructed at a plurality of loci using the more complete genetic data from a larger sample of diploid cells from one or both parents, with or without haploid genetic data from one or both parents. In another embodiment, the chromosome copy number can be determined from the measured genetic data, with or without genetic information from one or both parents.

The present disclosure discloses an in-vitro and non-invasive method for detecting a medical condition in a subject. The method involves enriching very small embryonic like stem cells from the sample, to obtain a mixture comprising said very small embryonic like stem cells; obtaining nucleic acid from the mixture of step; performing an assay with the nucleic acid for analysing expression level of Oct4A in the very small embryonic like stem cells from the sample; and comparing the expression level of Oct4A in the very small embryonic like stem cells from the sample with an expression level of Oct4A in a control sample. The present disclosure also provides a method for predicting the onset of cancer and for predicting the presence of cancer. A method of treating cancer is also disclosed herein. Moreover, a reagent kit and a detection kit are also disclosed.