ABSTRACT
Metabolic flux augmentation via glucose transport activation may be desirable in glucose transporter 1 (Glut1) deficiency syndrome (G1D) and dementia, whereas suppression might prove useful in cancer. Using lung adenocarcinoma cells that predominantly express Glut1 relative to other glucose transporters, we screened 9,646 compounds for effects on the accumulation of an extracellularly applied fluorescent glucose analog. Five drugs currently prescribed for unrelated indications or preclinically characterized robustly enhanced intracellular fluorescence. Additionally identified were 37 novel activating and nine inhibitory compounds lacking previous biologic characterization. Because few glucose-related mechanistic or pharmacological studies were available for these compounds, we developed a method to quantify G1D mouse behavior to infer potential therapeutic value. To this end, we designed a five-track apparatus to record and evaluate spontaneous locomotion videos. We applied this to a G1D mouse model that replicates the ataxia and other manifestations cardinal to the human disorder. Because the first two drugs that we examined in this manner (baclofen and acetazolamide) exerted various impacts on several gait aspects, we used deep learning neural networks to more comprehensively assess drug effects. Using this method, 49 locomotor parameters differentiated G1D from control mice. Thus, we used parameter modifiability to quantify efficacy on gait. We tested this by measuring the effects of saline as control and glucose as G1D therapy. The results indicate that this in vivo approach can estimate preclinical suitability from the perspective of G1D locomotion. This justifies the use of this method to evaluate our drugs or other interventions and sort candidates for further investigation. SIGNIFICANCE STATEMENT: There are few or no activators and few clinical inhibitors of glucose transport. Using Glut1-rich cells exposed to a glucose analog, we identified, in highthroughput fashion, a series of novel modulators. Some were drugs used to modify unrelated processes and some represented large but little studied chemical compound families. To facilitate their preclinical efficacy characterization regardless of potential mechanism of action, we developed a gait testing platform for deep learning neural network analysis of drug impact on Glut1-deficient mouse locomotion.
Subject(s)
Carbohydrate Metabolism, Inborn Errors , Deep Learning , Animals , Humans , Mice , Carbohydrate Metabolism, Inborn Errors/metabolism , Glucose/metabolism , Glucose Transporter Type 1ABSTRACT
Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity. This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.
ABSTRACT
Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV among other regions recorded, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity, and thus decreasing the low:high frequency ratio (LHR). This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.
ABSTRACT
Selective vascular access to the brain is desirable in metabolic tracer, pharmacological and other studies aimed to characterize neural properties in isolation from somatic influences from chest, abdomen or limbs. However, current methods for artificial control of cerebral circulation can abolish pulsatility-dependent vascular signaling or neural network phenomena such as the electrocorticogram even while preserving individual neuronal activity. Thus, we set out to mechanically render cerebral hemodynamics fully regulable to replicate or modify native pig brain perfusion. To this end, blood flow to the head was surgically separated from the systemic circulation and full extracorporeal pulsatile circulatory control (EPCC) was delivered via a modified aorta or brachiocephalic artery. This control relied on a computerized algorithm that maintained, for several hours, blood pressure, flow and pulsatility at near-native values individually measured before EPCC. Continuous electrocorticography and brain depth electrode recordings were used to evaluate brain activity relative to the standard offered by awake human electrocorticography. Under EPCC, this activity remained unaltered or minimally perturbed compared to the native circulation state, as did cerebral oxygenation, pressure, temperature and microscopic structure. Thus, our approach enables the study of neural activity and its circulatory manipulation in independence of most of the rest of the organism.
Subject(s)
Extracorporeal Circulation , Nervous System Physiological Phenomena , Humans , Swine , Animals , Perfusion , Cerebrovascular Circulation , BrainABSTRACT
Gyriform mammals display neurophysiological and neural network activity that other species exhibit only in rudimentary or dissimilar form. However, neural recordings from large mammals such as the pig can be anatomically hindered and pharmacologically suppressed by anesthetics. This curtails comparative inferences. To mitigate these limitations, we set out to modify electrocorticography, intracerebral depth and intracortical recording methods to study the anesthetized pig. In the process, we found that common forms of infused anesthesia such as pentobarbital or midazolam can be neurophysiologic suppressants acting in dose-independent fashion relative to anesthetic dose or brain concentration. Further, we corroborated that standard laboratory conditions may impose electrical interference with specific neural signals. We thus aimed to safeguard neural network integrity and recording fidelity by developing surgical, anesthesia and noise reduction methods and by working inside a newly designed Faraday cage, and evaluated this from the point of view of neurophysiological power spectral density and coherence analyses. We also utilized novel silicon carbide electrodes to minimize mechanical disruption of single-neuron activity. These methods allowed for the preservation of native neurophysiological activity for several hours. Pig electrocorticography recordings were essentially indistinguishable from awake human recordings except for the small segment of electrical activity associated with vision in conscious persons. In addition, single-neuron and paired-pulse stimulation recordings were feasible simultaneously with electrocorticography and depth electrode recordings. The spontaneous and stimulus-elicited neuronal activities thus surveyed can be recorded with a degree of precision similar to that achievable in rodent or any other animal studies and prove as informative as unperturbed human electrocorticography.
Subject(s)
Anesthetics , Wakefulness , Animals , Brain/physiology , Humans , Mammals , Midazolam , Neurons/physiology , Pentobarbital , SwineABSTRACT
Time-to-fall off an accelerating rotating rod (rotarod) is widely utilized to evaluate rodent motor performance. We reasoned that this simple outcome could be refined with additional measures explicit in the task (however inconspicuously) to examine what we call movement sub-structure. Our goal was to characterize normal variation or motor impairment more robustly than by using time-to-fall. We also hypothesized that measures (or features) early in the sub-structure could anticipate the learning expected of a mouse undergoing serial trials. Using normal untreated and baclofen-treated movement-impaired mice, we defined these features and automated their analysis using paw video-tracking in three consecutive trials, including paw location, speed, acceleration, variance and approximate entropy. Spectral arc length yielded speed and acceleration uniformity. We found that, in normal mice, paw movement smoothness inversely correlated with rotarod time-to-fall for the three trials. Greater approximate entropy in vertical movements, and opposite changes in horizontal movements, correlated with greater first-trial time-to-fall. First-trial horizontal approximate entropy in the first few seconds predicted subsequent time-to-fall. This allowed for the separation, after only one rotarod trial, of different-weight, untreated mouse groups, and for the detection of mice otherwise unimpaired after baclofen, which displayed a time-to-fall similar to control. A machine-learning support vector machine classifier corroborated these findings. In conclusion, time-to-fall off a rotarod correlated well with several measures, including some obtained during the first few seconds of a trial, and some responsive to learning over the first two trials, allowing for predictions or preemptive experimental manipulations before learning completion.
Subject(s)
Motor Skills , Animals , Learning , Male , Mice , Movement , Rotarod Performance TestABSTRACT
Enhanced understanding of the molecular features of glioma has led to an expansion of murine glioma models and successful preclinical studies. However, clinical trials continue to have a high cost, extended production time, and low proportion of success. Studies in large-animal models of various cancer types have emerged to bridge the translational gap between in vitro and in vivo animal studies and human clinical trials. The anatomy and physiology of large animals are of more direct relevance to human disease, allowing for more rigorous testing of treatments such as surgical resection and adjuvant therapy in glioma. The recent generation of multiple porcine glioma models supports their use in high-throughput preclinical studies. The demonstration of spontaneous glioblastoma formation in canines further provides a unique avenue for the study of de novo glioma. The aim of this review was to outline the current status of large animal models of glioma and their value as a transitional step between rodent models and human clinical trials.
Subject(s)
Brain Neoplasms , Glioma , Translational Research, Biomedical , Animals , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Brain Neoplasms/genetics , Brain Neoplasms/metabolism , Brain Neoplasms/pathology , Brain Neoplasms/therapy , Disease Models, Animal , Dogs , Glioma/genetics , Glioma/metabolism , Glioma/pathology , Glioma/therapy , Haplorhini , Humans , Mice, Transgenic , Species Specificity , Sus scrofaABSTRACT
The resection of brain tumors located within or near the eloquent tissue has a higher risk of postoperative neurological deficits. The primary concerns include loss of sensory and motor functions in the contralateral face, upper and lower extremities, as well as speech deficits. Intraoperative neurophysiological monitoring (IONM) techniques are performed routinely for the identification and preservation of the functional integrity of the eloquent brain areas during neurosurgical procedures. The IONM modalities involve sensory, motor, and language mapping, which helps in the identification of the boundaries of these areas during surgical resection. Cortical motor Mapping (CmM) technique is considered as a gold-standard technique for mapping of the brain. We present the intraoperative CmM technique, including anesthesia recommendations, types of electrodes, as well as stimulation and recording parameters for successful monitoring.