Abstract: Compounds are provided that antagonize the kappa-opioid receptor (KOR) and products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope or salt thereof: wherein X, Y, R1, R2, R4, R5, R6, R7, R8 and R11 are as defined herein.

Abstract: The method for evaluating mental health of a patient includes displaying a series of inquiries from mental health questionnaires on a display device. Each inquiry of the series of inquiries includes text and a set of answers. A series of selections is received from a user interface. Each selection of the series of selections is representative of an answer of the set of answers for each corresponding inquiry in the series of inquiries. Unprocessed MRI data are received. The unprocessed MRI data correspond to a set of MRI images of a biological structure associated with a patient. Using a machine learning model, the series of selections and the unprocessed MRI data are processed. The series of selections being processed corresponds to the series of inquiries. A symptom severity indicator for a mental health category of the patient is outputted.

Abstract: A system for evaluating mental health of patients includes a memory and a control system. The memory contains executable code storing instructions for performing a method. The control system is coupled to the memory and includes one or more processors. The control system is configured to execute the machine executable code to cause the control system to perform the method: A selection of answers associated with a patient is received. The selection of answers corresponds to each question in a series of questions from mental health questionnaires. Unprocessed MRI data are received. The unprocessed MRI data correspond to a set of MRI images of a biological structure associated with the patient. The unprocessed MRI data is processed to output a set of MRI features. Using a machine learning model, the selection of answers and the set of MRI features are processed to output a mental health indication of the patient.

Abstract: Compounds are provided that antagonize vasopressin receptors, particularly the V1a receptor products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope, or salt thereof: wherein A, B, G, R1, R1b, R1c, R2 and X are as defined herein.

Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.

Abstract: Compounds are provided that antagonize the kappa-opioid receptor (KOR) and products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope or salt thereof: wherein X, Y, R1, R2, R4, R5 R6, R7, R8 and R11 are as defined herein.

Abstract: The present tools and methods for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject. These tools and methods relates to a genotype and neurophenotype topography-based approach for analyzing brain neuroimaging and gene expression maps to identify drug targets associated with neurobehavioral phenotypes and, conversely, neurobehavioral phenotypes associated with potential drug targets, to develop rational design and application of pharmacological therapeutics for brain disorders, and to provide methods and tools for treatment of subjects in need of neurological therapy.

Abstract: Compounds are provided that antagonize the kappa-opioid receptor (KOR) and products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope or salt thereof: wherein X, Y, R1, R2, R4, R5 R6, R7, R8 and R11 are as defined herein.

Abstract: A system includes a display device, a user interface, a memory, and a control system. The memory contains machine readable medium including machine executable code storing instructions for performing a method. The control system is coupled to the memory, and includes one or more processors. The control system is configured to execute the machine executable code to cause the control system to display, on the display device, a series of questions from mental health questionnaires. The series of questions includes text and answers for each question. From the user interface, a selection of answers of each of the displayed series of questions is received from a patient. Using a Bayesian Decision List, the received selection of answers is processed to output an indication of mental health of the patient. The indication of mental health identifies a kappa opioid receptor antagonist to which the patient would likely be a higher responder.

Abstract: Compounds are provided that antagonize vasopressin receptors, particularly the V1a receptor products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope, or salt thereof: wherein Q1, Q2, Q3, R2a, R2b, R3 and X are as defined herein.

Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.