Publications by authors named "Kevin J Pollard"

Respiratory syncytial virus (RSV) primarily infects the respiratory epithelium, but growing evidence suggests that it may also be responsible for neurologic sequelae. In 3-dimensional microphysiologic peripheral nerve cultures, RSV infected neurons, macrophages, and dendritic cells along 2 distinct trajectories depending on the initial viral load. Low-level infection was transient, primarily involved macrophages, and induced moderate chemokine release with transient neural hypersensitivity.

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Advances within in vitro biological system complexity have enabled new possibilities for the "Organs-on-a-Chip" field. Microphysiological systems (MPS) as such incorporate sophisticated biological constructs with custom biological sensors. For microelectromechanical systems (MEMS) sensors, the dielectric layer is critical for device performance, where silicon dioxide (SiO) represents an excellent candidate due to its biocompatibility and wide utility in MEMS devices.

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Debilitating chronic pain resulting from genetic predisposition, injury, or acquired neuropathy is becoming increasingly pervasive. Opioid analgesics remain the gold standard for intractable pain, but overprescription of increasingly powerful and addictive opioids has contributed to the current prescription drug abuse epidemic. There is a pressing need to screen experimental compounds more efficiently for analgesic potential that remains unmet by conventional research models.

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Chemotherapy-induced peripheral neuropathy (CIPN) is a well-known, potentially permanent side effect of widely used antineoplastic agents. The mechanisms of neuropathic progression are poorly understood, and the need to test efficacy of novel interventions to treat CIPN continues to grow. Bioengineered microphysiological nerve tissue ("nerve on a chip") has been suggested as an in vitro platform for modeling the structure and physiology of in situ peripheral nerve tissue.

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In this paper, we present a novel strategy for automatic segmentation of biomedical images acquired from bio-engineered nerve tissues exhibiting variable morphological characteristics. Automatic image segmentation is one step towards the end goal of automatic analysis of the impact of various neurotoxic drug treatments on these artificial nerve tissues. We propose a deep learning architecture to perform this task.

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Previous work has demonstrated that estrogen receptors are transcriptionally active in the absence of ovarian estrogens. The current work aims to determine whether brain-derived estrogens influence estrogen receptor-dependent transcription after short- or long-term loss of ovarian function. Experiments were conducted using estrogen response element (ERE)-Luciferase reporter mice, which express the gene for luciferase driven by consensus ERE, allowing for the quantification of ERE-dependent transcription.

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Non-canonical mechanisms of estrogen receptor activation may continue to support women's cognitive health long after cessation of ovarian function. These mechanisms of estrogen receptor activation may include ligand-dependent actions via locally synthesized neuroestrogens and ligand-independent actions via growth factor-dependent activation of intracellular kinase cascades. We tested the hypothesis that ligand-dependent and ligand-independent mechanisms interact to activate nuclear estrogen receptors in the Neuro-2A neuroblastoma cell line in the absence of exogenous estrogens.

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