Key points• The transcription factor Dbx1 gives rise to putatively respiratory rhythm-generating neurons in the pre-Bötzinger complex. Comparative analysis of Dbx1-derived (Dbx1 + ) and non-Dbx1-derived (Dbx1 − ) neurons can help elucidate the cellular bases of respiratory rhythm generation. • In vitro, Dbx1+ neurons activate earlier in the respiratory cycle, discharge larger magnitude inspiratory bursts and exhibit a lower rheobase compared with Dbx1 − neurons.+ neurons tend to express the intrinsic currents I A (transient outward A-current) and I h (hyperpolarization-activated current) in diametric opposition, which may facilitate temporal summation of excitatory synaptic inputs, whereas the Dbx1 − neurons show no significant pattern of expression regarding I A and I h .• The Dbx1 + neurons exhibit smooth, spineless dendrites that project in the transverse plane, whereas the Dbx1 − neurons are confined to the transverse plane to a lesser extent and sometimes exhibit spines.• The properties of Dbx1 + neurons that may contribute to respiratory rhythmogenesis include a high level of excitability linked to ongoing network activity and dendritic properties that may facilitate synaptic integration.Abstract Breathing in mammals depends on an inspiratory-related rhythm that is generated by glutamatergic neurons in the pre-Bötzinger complex (preBötC) of the lower brainstem. A substantial subset of putative rhythm-generating preBötC neurons derive from a single genetic line that expresses the transcription factor Dbx1, but the cellular mechanisms of rhythmogenesis remain incompletely understood. To elucidate these mechanisms, we carried out a comparative analysis of Dbx1-expressing neurons (Dbx1 + ) and non-Dbx1-derived (Dbx1 − ) neurons in the preBötC. Whole-cell recordings in rhythmically active newborn mouse slice preparations showed that Dbx1 + neurons activate earlier in the respiratory cycle and discharge greater magnitude inspiratory bursts compared with Dbx1 − neurons. Furthermore, Dbx1 + neurons required less input current to discharge spikes (rheobase) in the context of network activity. The expression of intrinsic membrane properties indicative of A-current (I A ) and hyperpolarization-activated current (I h ) tended to be mutually exclusive in Dbx1 + neurons. In contrast, there was no such relationship in the expression of currents I A and I h in Dbx1 − neurons. Confocal imaging and digital morphological reconstruction of recorded neurons revealed dendritic spines on Dbx1 in part, to a higher level of intrinsic excitability in the context of network synaptic activity. Furthermore, Dbx1 + neuronal morphology may facilitate temporal summation and integration of local synaptic inputs from other Dbx1 + neurons, taking place largely in the dendrites, which could be important for initiating and maintaining bursts and synchronizing activity during the inspiratory phase.

The relationship between neuron morphology and function is a perennial issue in neuroscience. Information about synaptic integration, network connectivity, and the specific roles of neuronal subpopulations can be obtained through morphological analysis of key neurons within a microcircuit. Here we present morphologies of two classes of brainstem respiratory neurons. First, interneurons derived from Dbx1-expressing precursors (Dbx1 neurons) in the preBötzinger complex (preBötC) of the ventral medulla that generate the rhythm for inspiratory breathing movements. Second, Dbx1 neurons of the intermediate reticular formation that influence the motor pattern of pharyngeal and lingual movements during the inspiratory phase of the breathing cycle. We describe the image acquisition and subsequent digitization of morphologies of respiratory Dbx1 neurons from the preBötC and the intermediate reticular formation that were first recorded in vitro. These data can be analyzed comparatively to examine how morphology influences the roles of Dbx1 preBötC and Dbx1 reticular interneurons in respiration and can also be utilized to create morphologically accurate compartmental models for simulation and modeling of respiratory circuits.

This article moves beyond analysis methods related to a traditional relational database or network analysis and offers a novel graph network technique to yield insights from a hospital’s emergency department work model. The modeled data were saved in a Neo4j graphing database as a time-varying graph (TVG), and related metrics, including degree centrality and shortest paths, were calculated and used to obtain time-related insights from the overall system. This study demonstrated the value of using a TVG method to model patient flows during emergency department stays. It illustrated dynamic relationships among hospital and consulting units that could not be shown with traditional analyses. The TVG approach augments traditional network analysis with temporal-related outcomes including time-related patient flows, temporal congestion points details, and periodic resource constraints. The TVG approach is crucial in health analytics to understand both general factors and unique influences that define relationships between time-influenced events. The resulting insights are useful to administrators for making decisions related to resource allocation and offer promise for understanding impacts of physicians and nurses engaged in specific patient emergency department experiences. We also analyzed customer ratings and reviews to better understand overall patient satisfaction during their journey through the emergency department.