The disclosure relates to electrochemical sensors for measuring creatinine and creatine in a patient's blood. More particularly, the disclosure relates to compositions and methods for improving measurement accuracy of electrochemical sensors used for measuring creatinine and creatine.

Disclosed are multi-enzyme biosensors that are stable at ambient temperature, and methods of making thereof.

Disclosed are multi-enzyme biosensors that are stable at ambient temperature, and methods of making thereof.

This application provides methods and systems for determining transplant status. In some embodiments, the method comprises obtaining a biological sample from hematopoietic stem cell transplant (HSCT) recipient; measuring the amount of one or more identified recipient-specific nucleic acids or donor-specific nucleic acids in the sample; and (c) determining transplant status by monitoring the amount of the one or more identified recipient-specific nucleic acids or donor-specific nucleic acids after transplantation. In some approaches, the one or more recipient-specific or the donor-specific nucleic acids are identified based on the amount of one or more polymorphic nucleic acid targets, which can be used to determine the transplant status. Optionally, the biological sample is blood or bone marrow. Optionally the nucleic acid is genomic DNA.

Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. There have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy or polynucleotide sequencing applications.

Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. There have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy or polynucleotide sequencing applications.

The present disclosure provides systems and methods for analyzing circulating hormone receptor transcripts to provide diagnoses, prognoses, and treatment suggestions for patients afflicted with breast cancer. Circulating transcripts can be obtained from patient samples, including blood samples, without the need for invasive tissue biopsies. This may include expression transcripts obtained from extracellular vesicles. Analysis of hormone receptor expression transcripts may include comparison with expression transcripts of patients with known clinical outcomes.

This disclosure relates to systems and methods for providing individualized assessments of breast cancer. The assessments are provided in the format of index scores that are prognostic to disease severity and progression. Methods involve measuring gene expression from a patient sample to create a gene expression signature. The gene expression signature is compared with expression signatures from tumors that are associated with known outcomes. The comparison is used to generate an index score that assigns a risk status to the patient. The index score may indicate, for example, risk of distant metastasis or benefit of chemotherapy.

The present disclosure provides methods and systems using machine learning to assess one or more of a patient's biomarkers to analyze various conditions, including cancers, such as breast cancer. The present systems and methods can be trained to analyze patient's biomarker data to form prognoses, diagnoses, and treatment suggestions. Further, the present systems and methods can use biomarker feature data and clinical feature data to create novel correlations in order to provide more accurate, patient-specific diagnoses, prognoses, and treatment suggestions.

Cell-based sensor devices, systems, and methods for the detection and identification of volatile compounds, and for the determination of the location of the source of the volatile compounds in an enclosed space are described.