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Maddox, S.

Publications and source records attributed to Maddox, S..

2 recordsLinked to original sources

A Clinically Aligned Murine Model of Electroconvulsive Stimulation Reverses Social Aversion and Displays Fear Memory Impairment After Chronic Social Defeat Stress

Electroconvulsive therapy (ECT) is the most effective treatment for patients with major depression, bipolar depression, mania, catatonia, and schizophrenia. Nonetheless, the mechanisms underlying its therapeutic effects largely remain unknown. While previous preclinical studies have noted a role for neurotropic signaling, neurogenesis, and alterations in monoamine neurotransmitter systems, these models were largely conducted using procedures that deviate from clinical practice. Therefore, we sought to develop a clinically relevant murine model of ECT, referred to as electroconvulsive stimulation (ECS) in animals, which more closely aligns with current clinical approaches to better explore its mechanisms. Using the well-established chronic social defeat stress (CSDS) paradigm, known to negatively impact reward processes, we investigated whether the behavioral changes after CSDS could be reversed following a clinically related course of ECS. Additionally, we observed induction of plasticity-related genes in the nucleus accumbens (NAcc) and amygdala, regions responsible for reward and fear-related memory, respectively. Lastly, we investigated ECS-related changes in the NAcc with bulk RNA-sequencing. Pathway analysis demonstrated cellular changes primarily involved in neuroplasticity and regulating cell migration and differentiation. Therefore, utilizing our novel and clinically relevant model of ECS, we have begun to elucidate mechanisms that contribute to ECTs therapeutic outcomes by examining murine behavior and RNA from brain regions associated with stress-induced states that model anxiety and depression and the effects of ECS.

neuroscience↗

Small Cell Lung Cancer subtypes identified by systems-level modeling of transcription factor networks

Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes, while the fourth is a previously undescribed neuroendocrine variant (NEv2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.

systems biology↗