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Parkinson's disease (PD) patients often experience impairment of autonomic and respiratory functions. These include conditions such as orthostatic hypotension and sleep apnea, which are highly correlated with dysfunctional central chemoreception. Blood flow is a fundamental determinant of tissue CO 2 /H + , yet the extent to which blood flow regulation within chemoreceptor regions contributes to respiratory behavior during neurological disease remains unknown. Here, we tested the hypothesis that 6-hydroxydopamine injection to inducing a known model of PD results in dysfunctional vascular homeostasis, biochemical dysregulation, and glial morphology of the ventral medullary surface (VMS). We show that hypercapnia (FiCO 2 = 10%) induced elevated VMS pial vessel constriction in PD animals through a P2-receptor dependent mechanism. Similarly, we found a greater CO 2 -induced vascular constriction after ARL67156 (an ectonucleotidase inhibitor) in control and PD-induced animals. In addition, we also report that weighted gene correlational network analysis of the proteomic data showed a protein expression module differentially represented between both groups. This module showed that gene ontology enrichment for components of the ATP machinery were reduced in our PD-model compared to control animals. Altogether, our data indicate that dysfunction in purinergic signaling, potentially through altered ATP bioavailability in the VMS region, may compromise the RTN neuroglial vascular unit in a PD animal model., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Evaluation of reactive astrogliosis by neuroanatomical assays represents a common experimental outcome for neuroanatomists. The literature demonstrates several conflicting results as to the accuracy of such measures. We posited that the diverging results within the neuroanatomy literature were due to suboptimal analytical workflows in addition to astrocyte regional heterogeneity. We therefore generated an automated segmentation workflow to extract features of glial fibrillary acidic protein (GFAP) and aldehyde dehydrogenase family 1, member L1 (ALDH1L1) labeled astrocytes with and without neuroinflammation. We achieved this by capturing multiplexed immunofluorescent confocal images of mouse brains treated with either vehicle or lipopolysaccharide (LPS) followed by implementation of our workflows. Using classical image analysis techniques focused on pixel intensity only, we were unable to identify differences between vehicle-treated and LPS-treated animals. However, when utilizing machine learning-based algorithms, we were able to (1) accurately predict which objects were derived from GFAP or ALDH1L1-stained images indicating that GFAP and ALDH1L1 highlight distinct morphological aspects of astrocytes, (2) we could predict which neuroanatomical region the segmented GFAP or ALDH1L1 object had been derived from, indicating that morphological features of astrocytes change as a function of neuroanatomical location. (3) We discovered a statistically significant, albeit not highly accurate, prediction of which objects had come from LPS versus vehicle-treated animals, indicating that although features exist capable of distinguishing LPS-treated versus vehicle-treated GFAP and ALDH1L1-segmented objects, that significant overlap between morphologies exists. We further determined that for most classification scenarios, nonlinear models were required for improved treatment class designations. We propose that unbiased automated image analysis techniques coupled with well-validated machine learning tools represent highly useful models capable of providing insights into neuroanatomical assays., (© 2021 Wiley Periodicals LLC.)

Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been implemented routinely in neurophysiological analyses. The power of these workflows includes the speed at which they can be deployed, their availability of open-source programming languages, and the objectivity permitted in their data analysis. We used classification-based algorithms, including random forest, gradient boosted machines, support vector machines, and neural networks, to test the hypothesis that the animal genotypes could be separated into their genotype based on interpretation of neurophysiological recordings. We then interrogate the models to identify what were the major features utilized by the algorithms to designate genotype classification. By using raw EEG and respiratory plethysmography data, we were able to predict which recordings came from genotype class with accuracies that were significantly improved relative to the no information rate, although EEG analyses showed more overlap between groups than respiratory plethysmography. In comparison, conventional methods where single features between animal classes were analyzed, differences between the genotypes tested using baseline neurophysiology measurements showed no statistical difference. However, ML/AI workflows successfully were capable of providing successful classification, indicating that interactions between features were different in these genotypes. ML/AI workflows provide new methodologies to interrogate neurophysiology data. However, their implementation must be done with care so as to provide high rigor and reproducibility between laboratories. We provide a series of recommendations on how to report the utilization of ML/AI workflows for the neurophysiology community. NEW & NOTEWORTHY ML/AI classification workflows are capable of providing insight into differences between genotypes for neurophysiology research. Analytical techniques utilized in the neurophysiology community can be augmented by implementing ML/AI workflows. Random forest is a robust classification algorithm for respiratory plethysmography data. Utilization of ML/AI workflows in neurophysiology research requires heightened transparency and improved community research standards.

Congenital central hypoventilation syndrome (CCHS) represents a rare genetic disorder usually caused by mutations in the homeodomain transcription factor PHOX2B. Some CCHS patients suffer mainly from deficiencies in CO 2 and/or O 2 respiratory chemoreflex, whereas other patients present with full apnea shortly after birth. Our goal was to identify the neuropathological mechanisms of apneic presentations in CCHS. In the developing murine neuroepithelium, Phox2b is expressed in three discrete progenitor domains across the dorsal-ventral axis, with different domains responsible for producing unique autonomic or visceral motor neurons. Restricting the expression of mutant Phox2b to the ventral visceral motor neuron domain induces marked newborn apnea together with a significant loss of visceral motor neurons, RTN ablation, and preBötzinger complex dysfunction. This finding suggests that the observed apnea develops through non-cell autonomous developmental mechanisms. Mutant Phox2b expression in dorsal rhombencephalic neurons did not generate significant respiratory dysfunction, but did result in subtle metabolic thermoregulatory deficiencies. We confirm the expression of a novel murine Phox2b splice variant which shares exons 1 and 2 with the more widely studied Phox2b splice variant, but which differs in exon 3 where most CCHS mutations occur. We also show that mutant Phox2b expression in the visceral motor neuron progenitor domain increases cell proliferation at the expense of visceral motor neuron development. We propose that visceral motor neurons may function as organizers of brainstem respiratory neuron development, and that disruptions in their development result in secondary/non-cell autonomous maldevelopment of key brainstem respiratory neurons., (© 2020 International Society of Neuropathology.)

Respiratory parameters change during post-natal development, but the nature of their changes have not been well-described. The advent of commercially available plethysmographic instruments provided improved repeatability of measurements and standardization of measured breathing in mice across laboratories. These technologies thus allowed for exploration of more precise respiratory pattern changes during the post-natal developmental epoch. Current methods to analyze respiratory behavior utilize plethysmography to acquire standing values of frequency, volume and flow at specific time points in murine maturation. These metrics have historically been independently analyzed as a function of time with no further analysis examining the interplay these variables have with each other and in the context of postnatal maturation or during blood gas homeostasis. We posit that machine learning workflows can provide deeper physiological understanding into the postnatal development of respiration. In this manuscript, we delineate a machine learning workflow based on the R-statistical programming language to examine how variation and relationships of frequency (f) and tidal volume (TV) change with respect to inspiratory and expiratory parameters. Our analytical workflows could successfully predict age and found that the variation and relationships between respiratory metrics are dynamically shifting with age and during hypercapnic breathing. Thus, our work demonstrates the utility of high dimensional analyses to provide reliable class label predictions using non-invasive respiratory metrics. These approaches may be useful in large-scale phenotyping across development and in disease., (Copyright © 2020. Published by Elsevier B.V.)

Emerging evidence from multiple studies indicates that Parkinson's disease (PD) patients suffer from a spectrum of autonomic and respiratory motor deficiencies in addition to the classical motor symptoms attributed to substantia nigra degeneration of dopaminergic neurons. Animal models of PD show a decrease in the resting respiratory rate as well as a decrease in the number of Phox2b-expressing retrotrapezoid nucleus (RTN) neurons. The aim of this study was to determine the extent to which substantia nigra pars compact (SNc) degeneration induced RTN biomolecular changes and to identify the extent to which RTN pharmacological or optogenetic stimulations rescue respiratory function following PD-induction. SNc degeneration was achieved in adult male Wistar rats by bilateral striatal 6-hydroxydopamine injection. For proteomic analysis, laser capture microdissection and pressure catapulting were used to isolate the RTN for subsequent comparative proteomic analysis and Ingenuity Pathway Analysis (IPA). The respiratory parameters were evaluated by whole-body plethysmography and electromyographic analysis of respiratory muscles. The results confirmed reduction in the number of dopaminergic neurons of SNc and respiratory rate in the PD-animals. Our proteomic data suggested extensive RTN remodeling, and that pharmacological or optogenetic stimulations of the diseased RTN neurons promoted rescued the respiratory deficiency. Our data indicate that despite neuroanatomical and biomolecular RTN pathologies, that RTN-directed interventions can rescue respiratory control dysfunction., (© 2020 International Society of Neuropathology.)

Central chemoreception is the process whereby the brainstem senses blood gas levels and adjusts homeostatic functions such as breathing and cardiovascular tone accordingly. Rodent evidence suggests that the retrotrapezoid nucleus (RTN) is a master regulator of central chemoreception, in particular, through direct sensation of acidosis induced by CO 2 levels. The oscillatory dynamics caused by pH changes as sensed by the RTN surface and its relationship to the fluctuations in cation flux is not clearly understood due to the current limitations of electrophysiology tools and this article presents our investigations to address this need. A cation selective sensor fabricated from polypyrrole doped with dodecyl benzenesulfonate (PPy (DBS)) is placed over RTN in an ex-vivo en bloc brain and changes in cation concentration in the diffusion limited region above the RTN is measured due to changes in externally imposed basal pH. The novelty of this technique lies in its feasibility to detect cation fluxes from the cells in the RTN region without having to access either sides of the cell membrane. Owing to the placement of the sensor in close proximity to the tissue, we refer to this technique as near-field electrophysiology. It is observed that lowering the pH in the physiological range (7.4-7.2) results in a significant increase in cation concentration in the vicinity of RTN with a median value of ~5 μM. The utilization of such quantifiable measurement techniques to detect sub-threshold brain activity may help provide a platform for future neural network architectures. Findings from this paper present a quantifiable, sensitive, and robust electrophysiology technique with minimal damage to the underlying tissue., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Key Points: The embryonic PHOX2B-progenitor domain generates neuronal and glial cells which together are involved in chemosensory control of breathing and sleep homeostasis. Ablating PHOX2B-derived astrocytes significantly contributes to secondary hypoxic respiratory depression as well as abnormalities in sleep homeostasis. PHOX2B-derived astrocyte ablation results in axonal pathologies in the retrotrapezoid nucleus., Abstract: We identify in mice a population of ∼800 retrotrapezoid nucleus (RTN) astrocytes derived from PHOX2B-positive, OLIG3-negative progenitor cells, that interact with PHOX2B-expressing RTN chemosensory neurons. PHOX2B-derived astrocyte ablation during early life results in adult-onset O 2 chemoreflex deficiency. These animals also display changes in sleep homeostasis, including fragmented sleep and disturbances in delta power after sleep deprivation, all without observable changes in anxiety or social behaviours. Ultrastructural evaluation of the RTN demonstrates that PHOX2B-derived astrocyte ablation results in features characteristic of degenerative neuro-axonal dystrophy, including abnormally dilated axon terminals and increased amounts of synapses containing autophagic vacuoles/phagosomes. We conclude that PHOX2B-derived astrocytes are necessary for maintaining a functional O 2 chemosensory reflex in the adult, modulate sleep homeostasis, and are key regulators of synaptic integrity in the RTN region, which is necessary for the chemosensory control of breathing. These data also highlight how defects in embryonic development may manifest as neurodegenerative pathology in an adult., (© 2019 The Authors. The Journal of Physiology © 2019 The Physiological Society.)

Mounting evidence in the literature suggests that RNA-RNA binding protein aggregations can disturb neuronal homeostasis and lead to symptoms associated with normal aging as well as dementia. The specific ablation of cyclin A2 in adult neurons results in neuronal polyribosome aggregations and learning and memory deficits. Detailed histologic and ultrastructural assays of aged mice revealed that post-mitotic hippocampal pyramidal neurons maintain cyclin A2 expression and that proliferative cells in the dentate subgranular zone express cyclin A2. Cyclin A2 loss early during neural development inhibited hippocampal development through canonical/cell-cycle mechanisms, including prolonged cell cycle timing in embryonic hippocampal progenitor cells. However, in mature neurons, cyclin A2 colocalized with dendritic rRNA. Cyclin A2 ablation in adult hippocampus resulted in decreased synaptic density in the hippocampus as well as in accumulation of rRNA granules in dendrite shafts. We conclude that cyclin A2 functions in a noncanonical/non-cell cycle regulatory role to maintain adult pyramidal neuron ribostasis., (Copyright © 2019 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)