The invention provides a method for classifying tumors by their collagen expression patterns into groups associated with high and low overall survival.

Biomarkers, methods, devices, reagents, systems, and kits used to assess an individual for the prediction of risk of developing a primary or secondary Cardiovascular (CV) event over a 4 year period are provided.

This disclosure relates to compositions and methods of diagnosing neurodegenerative disease by analyzing protein expression profiles in a subject.

A method for predicting whether an early stage (IA, IB) non-small-cell lung cancer (NSCLC) patient is at a high risk of recurrence of the cancer following surgery involves subjecting a blood-based sample from the patient (obtained prior to, at, or after the surgery) to mass spectrometry and classification with a computer implementing a classifier. If the patients blood sample is classified as “high risk”, highest risk“or the equivalent, the patient can be guided to more aggressive treatment post-surgery. The classifier, or combination of classifiers, can be arranged in a hierarchical manner to make intermediate classifications, such as intermediate/high or intermediate/low, as well as low risk” or “lowest risk” classifications. Such additional classifications may guide clinical decisions as well.

The present invention provides methods for using surgical drainage waste fluid as a means for diagnosing disease, assessing disease progression, predicting metastatic disease, assessing cancer metastasis, disease staging, molecular staging, and assessing metastatic disease. During surgery, suction is used to drain fluids such as blood, tissue fluids, and other bodily fluids away from the surgery site. The suction drainage fluid waste, also called drain fluid, is removed from the patient during the surgical procedure. Because surgical drain fluid is typically viewed as something that is not useful, it is disregarded and thrown away during the surgery. Instead, the invention provides that drain fluid, which is mostly lymphatic fluid and interstitial fluid, is diagnostically rich and contains important information for assessing, diagnosing, and treating disease. The methods of the invention use this waste fluid for the valuable data it contains. Therefore, while a patient is already undergoing surgery for a medical condition, the waste drain fluid is sampled and analyzed for biomarkers or other molecular indicia of disease.

Systemic Lupus Erythematosus is marked by altered immune regulation linked to waxing and waning clinical disease. Embodiments described herein identify sets of biomarkers/mediators and their use for informing and/or predicting a future SLE disease activity event such as an impending SLE flare or SLE-related organ inflammation. Such an approach can be beneficial in the management of lupus.

The present disclosure relates generally to discovery of novel compounds involved in the treatment and prevention of suicidality by bioinformatics drug repurposing using novel genes expression biomarkers involved in suicidality. Disclosed are methods for assessing severity, determining future risk, matching with a drug treatment, and measuring response to treatment, for suicidality. Also disclosed are new methods of use for drugs and natural compounds repurposed for use in preventing and treating suicidality. These methods include computer-assisted methods analyzing the expression of panels of genes, clinical measures, and drug databases. Detailed herein are methods using a universal approach, in everybody, as well as personalized approaches by gender, and by diagnosis. The discovery describes compounds for use in everybody (universal), as well as personalized by gender (males, females), diagnosis (bipolar, depression), gender and diagnosis combined (male bipolar, male depression), male PTSD, male SZ/SZA), and subtypes of suicidality (high anxiety, low mood, combined (affective), and high psychosis (non-affective). Also disclosed are methods for identifying which subjects should be receiving which treatment, using genes expression biomarkers for patient stratification and measuring response to treatment. The disclosure also relates to algorithms, universal and personalized by gender and diagnosis. The algorithms combine biomarkers as well as clinical measures for suicidality and for mental state, in order to identify subjects who are at risk of committing suicide, as well as to track responses to treatments. The disclosure further relates to determining subtypes of suicidality. Such subtypes may delineate groups of individuals that are more homogenous in terms of biology, behavior, and response to treatment.

Disclosed herein are automated processes and systems for determining an underlying cause of anemia. Also disclosed herein are processes and systems for determining an underlying cause of microcytic anemia, normocytic anemia, and macrocytic anemia. Additionally disclosed herein are methods of treating the underlying cause of anemia in an individual in need thereof.

Provided herein are methods for reducing risk of severe symptoms and outcomes associated with Coronavirus Disease 2019 (COVID-19) and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection by measuring levels of interleukin 6 (IL-6), IL-8, IL-22, and serum ferritin in a subject. Also provided are methods for treating a subject exposed to or at elevated risk of expose to SARS-CoV-2 based on levels of IL-6, IL-8, IL-22, and ferritin in the serum of the subject.

Disclosed is a non-invasive method for assessing in a subject the presence and severity of a liver lesion, or the risk of death or liver-related events, including: 1) performing at least three binary logistic regressions on at least one variable, performed on the same variable(s) but each directed to a different single diagnostic target, thereby obtaining at least three scores; 2) combining the scores from step 1) in a multiple linear regression to obtain a new multi-targeted score; 3) optionally sorting the multi-targeted score obtained in step 2) in a classification of liver lesion stages or grades, thereby determining to which liver lesion stage or grade the subject belongs based on his/her multi-targeted score. Also disclosed is a single multi-targeted non-invasive test obtained by the combination of single-targeted non-invasive tests providing a unique score and a unique classification with improved accuracy compared to single-targeted diagnostic tests.