Respiratory syncytial virus infects peripheral and spinal nerves and induces chemokine-mediated neuropathy.

Respiratory syncytial virus (RSV) primarily infects the respiratory epithelium, but growing evidence suggests it may also be responsible for neurological sequelae. In 3D microphysiological peripheral nerve cultures, RSV infected neurons, macrophages, and dendritic cells along two 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. Infection with higher viral loads was persistent, infected neuronal cells in addition to monocytes, and induced robust chemokine release followed by progressive neurotoxicity. In spinal cord cultures, RSV infected microglia and dendritic cells but not neurons, producing a moderate chemokine expression pattern. The persistence of infection was variable but could be identified in dendritic cells as long as 30 days post-inoculation. This study suggests that RSV can disrupt neuronal function directly through infection of peripheral neurons and indirectly through infection of resident monocytes, and inflammatory chemokines likely mediate both mechanisms.

Fully Integrated 3D Microelectrode Arrays with Polydopamine-Mediated Silicon Dioxide Insulation for Electrophysiological Interrogation of a Novel 3D Human, Neural Microphysiological Construct.

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 (SiO2) represents an excellent candidate due to its biocompatibility and wide utility in MEMS devices. Yet, high temperatures traditionally preclude SiO2 from incorporation in polymer-based BioMEMS. Electron-beam deposition of SiO2 may provide a low-temperature, dielectric serving as a nanoporous MPS growth substrate. Herein, we enable improved adherence of nanoporous SiO2 to polycarbonate (PC) and 316L stainless steel (SS) via polydopamine (PDA)-mediated chemistry. The resulting stability of the combinatorial PDA-SiO2 film was interrogated, along with the nature of the intrafilm interactions. A custom polymer-metal three-dimensional (3D) microelectrode array (3D MEA) is then reported utilizing PDA-SiO2 insulation, for definition of novel dorsal root ganglion (DRG)/nociceptor and dorsal horn (DH) 3D neural constructs in excess of 6 months for the first time. Spontaneous/evoked compound action potentials (CAPs) are successfully reported. Finally, inhibitory drugs treatments showcase pharmacological responsiveness of the reported multipart biological activity. These results represent the initiation of a novel 3D MEA-integrated, 3D neural MPS for the long-term electrophysiological study.

Morphine-sensitive synaptic transmission emerges in embryonic rat microphysiological model of lower afferent nociceptive signaling.

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. The spinal cord dorsal horn is a common target for analgesic intervention, where peripheral nociceptive signals are relayed to the central nervous system through synaptic transmission. Here, we demonstrate that coculturing peripheral and dorsal spinal cord nerve cells in a novel bioengineered microphysiological system facilitates self-directed emergence of native nerve tissue macrostructure and concerted synaptic function. The mechanistically distinct analgesics-morphine, lidocaine, and clonidine-differentially and predictably modulate this microphysiological synaptic transmission. Screening drug candidates for similar microphysiological profiles will efficiently identify therapeutics with analgesic potential.

Comparative Analysis of Chemotherapy-Induced Peripheral Neuropathy in Bioengineered Sensory Nerve Tissue Distinguishes Mechanistic Differences in Early-Stage Vincristine-, Cisplatin-, and Paclitaxel-Induced Nerve Damage.

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. Here, we find that length-dependent nerve conduction and histopathologic changes induced by cisplatin, paclitaxel, or vincristine in rat dorsal root ganglion-derived microphysiological sensory nerve tissue recapitulate published descriptions of clinical electrophysiological changes and neuropathologic biopsy findings in test animals and human patients with CIPN. We additionally confirm the postulated link between vincristine-induced axoplasmic transport failure and functional impairment of nerve conduction, the postulated paclitaxel-induced somal toxicity, and identify a potential central role of gliotoxicity in cisplatin-induced sensory neuropathy. Microphysiological CIPN combines the tight experimental control afforded by in vitro experimentation with clinically relevant functional and structural outputs that conventionally require in vivo models. Microphysiological nerve tissue provides a low-cost, high-throughput alternative to conventional nonclinical models for efficiently and effectively investigating lesions, mechanisms, and treatments of CIPN. Neural microphysiological systems are capable of modeling complex neurological disease at the tissue level offering unique advantages over conventional methodology for both testing and generating hypotheses in neurological disease modeling. Impact Statement Recapitulation of distinct hallmarks of clinical CIPN in microphysiological sensory nerve validates a novel peripheral neurotoxicity model with unique advantages over conventional model systems.

Neuroestrogen-Dependent Transcriptional Activity in the Brains of ERE-Luciferase Reporter Mice following Short- and Long-Term Ovariectomy.

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. Brain regions examined were hippocampus, cortex, and hypothalamus. In Experiment 1, short-term (10 d) ovariectomy had no impact on ERE-dependent transcription across brain regions compared with sham surgery. In Experiment 2, chronic intracerebroventricular administration of the aromatase inhibitor letrozole significantly decreased transcriptional activity in 10-d-old ovariectomized mice across brain regions, indicating that the sustained transcription in short-term ovariectomized mice is mediated at least in part via actions of neuroestrogens. Additionally, intracerebroventricular administration of estrogen receptor antagonist ICI-182,780 blocked transcription in 10-d-old ovariectomized mice across brain regions, providing evidence that sustained transcription in ovariectomized mice is estrogen receptor dependent. In Experiment 3, long-term (70 d) ovariectomy significantly decreased ERE-dependent transcription across brain regions, though some residual activity remained. In Experiment 4, chronic intracerebroventricular letrozole administration had no impact on transcription in 70 d ovariectomized mice across brain regions, indicating that the residual ERE-dependent transcription in long-term ovariectomized mice is not mediated by neuroestrogens. Overall, the results indicate that ERE-dependent transcription in the brain continues after ovariectomy and that the actions of neuroestrogens contribute to the maintenance of ERE-dependent transcription in the brain following short-term, but not long-term, loss of ovarian function.

Nuclear estrogen receptor activation by insulin-like growth factor-1 in Neuro-2A neuroblastoma cells requires endogenous estrogen synthesis and is mediated by mutually repressive MAPK and PI3K cascades.

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. Transcriptional output of estrogen receptors was measured following treatment with insulin-like growth factor-1 (IGF-1) in the presence of specific inhibitors for mitogen-activated protein kinase (MAPK), phosphoinositde-3 kinase (PI3K), and neuroestrogen synthesis. Results indicate that IGF-1-dependent activation of nuclear estrogen receptors is mediated by MAPK, is opposed PI3K, and requires concomitant endogenous neuroestrogen synthesis. We conclude that both cellular signaling context and endogenous ligand availability are important modulators of ligand-independent nuclear estrogen receptor activation.

Semantic Segmentation of Microengineered Neural Tissues.

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. Our proposed architecture can be seen as a variation of U-Net that helps deal with a small manually annotated training data set. We present promising preliminary results and our human expert analysis shows that in some cases the model is even more precise in detecting the relevant morphological characteristics of the tissue compared to the manually annotated data. In the future, our model can be adapted for end-to-end automatic analysis of treated tissues. Moreover, based on a very small set of annotated data, it provides a reasonable segmentation to be used by human annotators. This will reduce the time of manual annotation significantly and streamline the process of generating a larger manually annotated data set for training our final ideal segmentation model.