Biology subjects

Hines, M.

Publications and source records attributed to Hines, M..

3 recordsLinked to original sources

bioRxiv2020

Multidimensional Analysis of Bronchoalveolar Lavage Cytokines and Mast Cell Proteases Reveals Interferon-γ as a Key Biomarker in Equine Asthma Syndrome

Naturally-occurring equine asthma is an inflammatory lung disease characterized by chronic, partially reversible airway obstruction, pulmonary remodeling and lower airway inflammation. The cytokine profiles that distinguish asthma groups or subtypes in horses have not been systematically classified, and mast cell phenotypes, which, in human asthma, correlate with asthma type, lung function, and response to therapy, have not been well-described in horses. The purpose of this study was to: (1) compare mast cell protease mRNA expression between healthy and asthmatic horses, (2) analyze the cytokine profile present in BALF of currently defined equine asthma groups, and (3) use these data to evaluate potential biomarkers of defined asthma groups. Mast cell protease gene expression and select cytokine gene expression in cells isolated from BALF, and BALF multiplex cytokine assays were performed. Multidimensional analysis demonstrated that IFN{gamma} differentiates severe from moderate asthma, and that TNF and CXCL8 are key biomarkers of equine asthma subtype. Expression of chymase mRNA, a mast cell-specific protease, was significantly decreased in horses with mastocytic asthma. These results will help further define EAS immunopathology, which could improve understanding and definitions of asthma groups, while also potentially identify novel therapeutic strategies.

immunology↗

bioRxiv2019

Local Glutamate-Mediated Dendritic Plateau Potentials Change the State of the Cortical Pyramidal Neuron

Dendritic spikes in thin dendritic branches (basal and oblique dendrites) of pyramidal neurons are traditionally inferred from spikelets measured in the cell body. Here, we used laser-spot voltage-sensitive dye imaging in cortical pyramidal neurons (rat brain slices) to investigate the voltage waveforms of dendritic potentials occurring in response to spatially-restricted glutamatergic inputs. Local dendritic potentials lasted 200-500 ms and propagated to the cell body where they caused sustained 10-20 mV depolarizations. Plateau potentials propagating from dendrite to soma, and action potentials propagating from soma to dendrite, created complex voltage waveforms in the middle of the thin basal dendrite, comprised of local sodium spikelets, local plateau potentials, and back-propagating action potentials, superimposed on each other. Our model replicated these experimental observations and made predictions, which were tested in experiments. Dendritic plateau potentials occurring in basal and oblique branches put pyramidal neurons into an activated neuronal state ("prepared state"), characterized by depolarized membrane potential and faster membrane responses. The prepared state provides a time window of 200-500 ms during which cortical neurons are particularly excitable and capable of following afferent inputs. At the network level, this predicts that sets of cells with simultaneous plateaus would provide cellular substrate for the formation of functional neuronal ensembles. New & NoteworthyIn cortical pyramidal neurons, we recorded glutamate-mediated dendritic plateau potentials using voltage imaging, and created a computer model that recreated experimental measures from dendrite and cell body. Our model made new predictions, which were then tested in experiments. Plateau potentials profoundly change neuronal state -- a plateau potential triggered in one basal dendrite depolarizes the soma and shortens membrane time constant, making the cell more susceptible to firing triggered by other afferent inputs.

neuroscience↗

bioRxiv2018

NetPyNE: a tool for data-driven multiscale modeling of brain circuits

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, e.g., a connectivity rule, instead of tens of loops to create millions of cell-to-cell connections. Users can then generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing using NeuroML and SONATA standardized formats. NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate different brain regions and phenomena.

neuroscience↗