Regulation of blood vessels by ATP in the ventral medullary surface in a rat model of Parkinson's disease.

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 CO2/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 (FiCO2 = 10%) induced elevated VMS pial vessel constriction in PD animals through a P2-receptor dependent mechanism. Similarly, we found a greater CO2-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.

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice.

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.

Astrocyte regional heterogeneity revealed through machine learning-based glial neuroanatomical assays.

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.

Neonatal apneic phenotype in a murine congenital central hypoventilation syndrome model is induced through non-cell autonomous developmental mechanisms.

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 CO2 and/or O2 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.

Stimulation of retrotrapezoid nucleus Phox2b-expressing neurons rescues breathing dysfunction in an experimental Parkinson's disease rat model.

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.

The role of PHOX2B-derived astrocytes in chemosensory control of breathing and sleep homeostasis.

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 O2 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 O2 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.

CCNA2 Ablation in Aged Mice Results in Abnormal rRNA Granule Accumulation in Hippocampus.

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.