Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.

As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings.

Applications of artificial intelligence in clinical laboratory genomics.

The transition from analog to digital technologies in clinical laboratory genomics is ushering in an era of "big data" in ways that will exceed human capacity to rapidly and reproducibly analyze those data using conventional approaches. Accurately evaluating complex molecular data to facilitate timely diagnosis and management of genomic disorders will require supportive artificial intelligence methods. These are already being introduced into clinical laboratory genomics to identify variants in DNA sequencing data, predict the effects of DNA variants on protein structure and function to inform clinical interpretation of pathogenicity, link phenotype ontologies to genetic variants identified through exome or genome sequencing to help clinicians reach diagnostic answers faster, correlate genomic data with tumor staging and treatment approaches, utilize natural language processing to identify critical published medical literature during analysis of genomic data, and use interactive chatbots to identify individuals who qualify for genetic testing or to provide pre-test and post-test education.

Chronic pain induces generalized enhancement of aversion.

A hallmark feature of chronic pain is its ability to impact other sensory and affective experiences. It is notably associated with hypersensitivity at the site of tissue injury. It is less clear, however, if chronic pain can also induce a generalized site-nonspecific enhancement in the aversive response to nociceptive inputs.

Deciphering neuronal population codes for acute thermal pain.

Objective: Pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage. Current pain research mostly focuses on molecular and synaptic changes at the spinal and peripheral levels. However, a complete understanding of pain mechanisms requires the physiological study of the neocortex.

Persistent neuropathic pain increases synaptic GluA1 subunit levels in core and shell subregions of the nucleus accumbens.

The nucleus accumbens (NAc) is a key component of the brain reward system, and it is composed of core and shell subregions. Glutamate transmission through AMPA-type receptors in both core and shell of the NAc has been shown to regulate reward- and aversion-type behaviors. Previous studies have additionally demonstrated a role for AMPA receptor signaling in the NAc in chronic pain states.

Persistent pain alters AMPA receptor subunit levels in the nucleus accumbens.

Background: A variety of pain conditions have been found to be associated with depressed mood in clinical studies. Depression-like behaviors have also been described in animal models of persistent or chronic pain. In rodent chronic neuropathic pain models, elevated levels of GluA1 subunits of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors in the nucleus accumbens (NAc) have been found to inhibit depressive symptoms.

Activation of corticostriatal circuitry relieves chronic neuropathic pain.

Neural circuits that determine the perception and modulation of pain remain poorly understood. The prefrontal cortex (PFC) provides top-down control of sensory and affective processes. While animal and human imaging studies have shown that the PFC is involved in pain regulation, its exact role in pain states remains incompletely understood.

Neuroplasticity underlying the comorbidity of pain and depression.

Acute pain induces depressed mood, and chronic pain is known to cause depression. Depression, meanwhile, can also adversely affect pain behaviors ranging from symptomology to treatment response. Pain and depression independently induce long-term plasticity in the central nervous system (CNS).

Differential effects of natural rewards and pain on vesicular glutamate transporter expression in the nucleus accumbens.

Background: Pain and natural rewards such as food elicit different behavioral effects. Both pain and rewards, however, have been shown to alter synaptic activities in the nucleus accumbens (NAc), a key component of the brain reward system. Mechanisms by which external stimuli regulate plasticity at NAc synapses are largely unexplored.

Development of a humanized in vitro blood-brain barrier model to screen for brain penetration of antiepileptic drugs.

Purpose: A biotechnologic breakthrough for the study of drug permeability across the blood-brain barrier (BBB) would be the use of a reproducible in vitro model that recapitulates the functional, structural, and pathologic properties of the BBB in situ. We developed a humanized dynamic in vitro BBB model (DIV-BBB) based on cocultures of human microvascular endothelial cells (HBMECs) from "normal" and drug-resistant epileptic brain tissue with human brain astrocytes (HAs) from epilepsy patients or controls.

Methods: HBMECs and HAs were cocultured for 28 days in polypropylene capillaries.