Multicompartmental Modeling Research Articles

Dendrites contribute to the gradient of intrinsic timescales encompassing cortical and subcortical brain networks.

Cytoarchitectonic studies have uncovered a correlation between higher levels of cortical hierarchy and reduced dendritic size. This hierarchical organization extends to the brain's timescales, revealing longer intrinsic timescales at higher hierarchical levels. However, estimating the contribution of single-neuron dendritic morphology to the hierarchy of timescales, which is typically characterized at a macroscopic level, remains challenging. Here we mapped the intrinsic timescales of six functional networks using functional magnetic resonance imaging (fMRI) data, and characterized the influence of neuronal dendritic size on intrinsic timescales of brain regions, utilizing a multicompartmental neuronal modeling approach based on digitally reconstructed neurons. The fMRI results revealed a hierarchy of intrinsic timescales encompassing both cortical and subcortical brain regions. The neuronal modeling indicated that neurons with larger dendritic structures exhibit shorter intrinsic timescales. Together these findings highlight the contribution of dendrites at the neuronal level to the hierarchy of intrinsic timescales at the whole-brain level. This study sheds light on the intricate relationship between neuronal structure, cytoarchitectonic maps, and the hierarchy of timescales in the brain.

Cholinergic modulation shifts the response of CA1 pyramidal cells to depolarizing ramps via TRPM4 channels with potential implications for place field firing.

A synergistic combination of in vitro electrophysiology and multicompartmental modeling of rat CA1 pyramidal neurons identified TRPM4 channels as major drivers of cholinergic modulation of the firing rate during a triangular current ramp, which emulates the bump in synaptic input received while traversing the place field. In control, fewer spikes at lower frequencies are elicited on the down-ramp compared to the up-ramp due to long-term inactivation of the NaV channel. The cholinergic agonist carbachol (CCh) removes or even reverses this spike rate adaptation, causing more spikes to be elicited on the down-ramp than the up-ramp. CCh application during Schaffer collateral stimulation designed to simulate a ramp produces similar shifts in the center of mass of firing to later in the ramp. The non-specific TRP antagonist flufenamic acid and the TRPM4-specific blockers CBA and 9-phenanthrol, but not the TRPC-specific antagonist SKF96365, reverse the effect of CCh; this implicates the Ca2+-activated nonspecific cation current, ICAN, carried by TRPM4 channels. The cholinergic shift of the center of mass of firing is prevented by strong intracellular Ca2+ buffering but not by antagonists for IP3 and ryanodine receptors, ruling out a role for known mechanisms of release from intracellular Ca2+ stores. Pharmacology combined with modeling suggest that [Ca2+] in a nanodomain near the TRPM4 channel is elevated through an unknown source that requires both muscarinic receptor activation and depolarization-induced Ca2+ influx during the ramp. Activation of the regenerative inward TRPM4 current in the model qualitatively replicates and provides putative underlying mechanisms for the experimental observations.

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI.

We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherical averaging. The use of strong diffusion weightings in magnetic resonance imaging (MRI) allows to approximate the signal in white matter as the sum of the contributions from only axons. At the same time, spherical averaging leads to a major simplification of the modeling by removing the need to explicitly account for the unknown distribution of axonal orientations. However, the spherically averaged signal acquired at strong diffusion weightings is not sensitive to the axial diffusivity, which cannot therefore be estimated although needed for modeling axons - especially in the context of multi-compartmental modeling. We introduce a new general method for the estimation of both the axial and radial axonal diffusivities at strong diffusion weightings based on kernel zonal modeling. The method could lead to estimates that are free from partial volume bias with gray matter or other isotropic compartments. The method is tested on publicly available data from the MGH Adult Diffusion Human Connectome project. We report reference values of axonal diffusivities based on 34 subjects, and derive estimates of axonal radii from only two shells. The estimation problem is also addressed from the angle of the required data preprocessing, the presence of biases related to modeling assumptions, current limitations, and future possibilities.

Towards a mesoscale physical modeling framework for stereotactic-EEG recordings

Objective. Stereotactic-electroencephalography (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMMs). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements. Approach. We provide a framework combining the multi-compartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept. Main results. CSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of NMMs is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer). Significance. Our results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.

Fractional myocardial blood volume by ferumoxytol-enhanced MRI: Estimation of ischemic burden.

To investigate model-fitted fractional myocardial blood volume (fMBV) derived from ferumoxytol-enhanced MRI as a measure of myocardial tissue hypoperfusion at rest. We artificially induced moderate to severe focal coronary stenosis in the left anterior descending artery of 19 swine by percutaneous delivery of a 3D-printed coronary implant. Using the MOLLI pulse sequence, we acquired T1 maps at 3 T after multiple incremental ferumoxytol doses (0.0-4.0mg/kg). We computed pixel-wise fMBV using a multi-compartmental modeling approach in 19 ischemic swine and 4 healthy swine. Ischemic myocardial segments showed a mean MRI-fMBV of 11.72 ± 3.00%, compared with 8.23 ± 2.12% in remote segments and 8.38 ± 2.23% in normal segments. Ischemic segments showed a restricted transvascular water-exchange rate (ki =15.32 ± 8.69 s-1 ) relative to remote segments (ki =17.78 [11.60, 26.36] s-1 ). A mixed-effects model found significant difference in fMBV (p=0.002) and water-exchange rate (p < 0.001) between ischemic and remote myocardial regions after adjusting for biological sex and slice location. Analysis of fMBV as a predictor of impaired myocardial contractility using receiver operating characteristics showed an area under the curve of 0.89 (95% confidence interval [CI] 0.80, 0.95). An MRI-fMBV threshold of 9.60% has a specificity of 90.0% (95% CI 76.3, 97.2) and a sensitivity of 72.5% (95% CI 56.1, 83.4) for prediction of impaired myocardial contractility. Model-fitted fMBV derived from ferumoxytol-enhanced MRI can distinguish regions of ischemia from remote myocardium in a swine model of myocardial hypoperfusion.

ODP011 Single Nuclei RNA-Sequencing of Frozen Human Adipose Tissue and PET/CT Imaging Coupled With Deep-Learning Reveals Single-Cell Landscape and Transcriptional Dynamics Related to Adipocyte Hypertrophy and in Vivo Dysmetabolism

Abstract Background Adipocyte hypertrophy is associated with glucose and lipid dysmetabolism, ectopic fat accumulation, and metabolic complications independently of the level of obesity [1]. In this study, we aimed to explore potential mechanisms driving the obesity-independent, hypertrophy-associated dysmetabolism at a single-cell resolution and to assess the applicability of single nuclei RNA-sequencing of flash-frozen human subcutaneous adipose tissue (AT) to probe for these metabolic differences. Methods In 40 healthy participants, peri-umbilical subcutaneous adipose tissue biopsies were collected by needle aspiration to determine adipocyte size. Tissue uptake of dietary fat was quantified via oral 18-fluoro-thiaheptadecanoic acid administration with positron emission tomography (PET) [2]. Rates of fatty acid oxidation and esterification were measured using intravenous [11C]-palmitate with PET and multi-compartmental modeling. PET/CT segmentation using deep convolutional neural networks was done with DeepImageTranslator [3,4]. Single nuclei RNA-sequencing was performed in two individuals with AT hypertrophy vs. hyperplasia but matched for the same sex, ethnicity, glucose-tolerance status, BMI, total and percent body fat, and waist circumference. Nuclei were extracted from frozen AT and purified by flow cytometry following a protocol that we have developed and validated. Capture of single nuclei and preparation of RNA libraries were done with 10X Genomics technology. Results Unsupervised clustering identified a number of cell-type markers identical to those previously reported in murine epididymal AT and human AT. We found reduced quantities of fibroadipogenic cells per volume of AT with fat cell hypertrophy. Furthermore, the fraction of DPP4+ fibroblasts is increased with AT hypertrophy. Analyses of RNA velocity shows decreased velocity of adipocyte transformation from a transcriptionally active (TADA) phenotype to mature adipocytes in AT hypertrophy. Furthermore, in AT hypertrophy, adipocytes from the early TADA stage are destined to become insulin-resistant adipocytes, whereas those in AT hyperplasia are developing into an insulin-sensitive phenotype. Metabolic imaging results show that hypertrophied subcutaneous AT is associated with lower subcutaneous and higher visceral AT volume and dietary fatty acid storage capacity. Conclusion We have documented, for the first time, the applicability and consistency of single-nuclei RNA-sequencing of frozen human subcutaneous AT. We uncovered changes in cell clusters and subclusters of adipocytes, fibroblasts, pericytes, endothelial and immune cells as well as differences in transcriptional dynamics and developmental trajectory. [1] Ye RZ, et al. Endocrine reviews. 2022 Feb;43(1): 35-60. [2] Montastier É, Ye RZ, et al. American Journal of Physiology-Endocrinology and Metabolism. 2021 Jun 1;320(6): E1093-106. [3] R. Z. Ye, et al., DeepImageTranslator: A free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis, SLAS Technology, https://doi.org/10.1016/j.slast.2021.10. 014, [4] Ye EZ, Ye EH, Ye RZ. DeepImageTranslator V2: analysis of multimodal medical images using semantic segmentation maps generated through deep learning. bioRxiv. 2021 Jan 1. Presentation: No date and time listed

Associations between insulin-like growth factor binding protein-2 and lipoprotein kinetics in men

Low circulating concentrations of insulin-like growth factor binding protein-2 (IGFBP-2) have been associated with dyslipidemia, notably with high triglyceride (TG) levels. However, the determinants by which IGFBP-2 influences lipoprotein metabolism, especially that of TG-rich lipoproteins (TRLs), are poorly understood. Here, we aimed to assess the relationships between IGFBP-2 levels and lipoprotein production and catabolism in human subjects. Fasting IGFBP-2 concentrations were measured in the plasma of 219 men pooled from previous lipoprotein kinetics studies. We analyzed production rate and fractional catabolic rates of TRLapoB-48, and LDL-, IDL-, and VLDLapoB-100 by multicompartmental modeling of l-[5,5,5-D3] leucine enrichment data after a 12 h primed constant infusion in individuals kept in a constant nutritional steady state. Subjects had an average BMI of 30 kg/m2, plasma IGFBP-2 levels of 157 ng/ml, and TG of 2.2 mmol/l. After adjustments for age and BMI, IGFBP-2 levels were negatively associated with plasma TG (r = −0.29; P < 0.0001) and positively associated with HDL-cholesterol (r = 0.26; P < 0.0001). In addition, IGFBP-2 levels were positively associated with the fractional catabolic rate of VLDLapoB-100 (r = 0.20; P < 0.01) and IDLapoB-100 (r = 0.19; P < 0.05) and inversely with the production rate of TRLapoB-48 (r = −0.28; P < 0.001). These correlations remained statistically significant after adjustments for age, BMI, and the amount of fat given during the tracer infusion. These findings show that the association between low plasma IGFBP-2 and high TG concentrations could be due to both an impaired clearance of apoB-100-containing VLDL and IDL particles and an increased production of apoB-48-containing chylomicrons. Additional studies are necessary to investigate whether and how IGFBP-2 directly impacts the kinetics of TRL.

Multi-Compartmental Modeling for Extracellular Stimulation of Neocortex

Aim: To explore the natural origin and changing behavior of neural responses depending on varying conditions, computational modeling of single-neuron or cluster of neurons using multi-compartmental models can provide very consistent predictions integrating with experimental work. Neural electrodes are fundamental therapeutic and diagnostic tools for a large variety of conditions. Understanding, individually or together neuronal responses, is critical for therapeutic and diagnostic techniques while dealing with certain neuropathies like Epilepsy or Parkinson's. The electrodes with different sizes and materials are the only way to interface the nervous system when it is needed to restore sensory or motor functions somehow. Material Method: Multi-compartmental neuron model is prepared by using a neuron with 3D realistic morphology from the neocortex. It is analyzed to see neurons' response to extracellular stimulation using a point source situated in two different locations, one at a time. Ideal conditions are considered for the point source. NEURON v8.0 is used for simulations. The stimulation pulse width, frequency, and amplitude are 1 ms, 20 Hz, and 250 nA respectively. Results: It is seen that the extracellular voltage profile is as expected, then it shifts towards where the stimulation electrode is moved. Closer neural compartments are better targets to generate action potential first. The effect of extracellular stimulation decreases as it moves from the source, but other compartments that are relatively in distance can also generate an action potential in several milliseconds after stimulation onset. Conclusion: Findings confirm multi-compartmental models are well-suited to predict neuronal responses. Different numbers and types of neurons' responses can be examined together with a complex realistic morphology. Parameters related to experimental conditions, like stimulation and recording, can also be analyzed.

Pharmacokinetic and Biochemical Profiling of Sodium Dichloroacetate in Pregnant Ewes and Fetuses.

Sodium dichloroacetate (DCA) is an investigational drug that shows promise in the treatment of acquired and congenital mitochondrial diseases, including myocardial ischemia and failure. DCA increases glucose utilization and decreases lactate production, so it may also have clinical utility in reducing lactic acidosis during labor. In the current study, we tested the ability of DCA to cross the placenta and be measured in fetal blood after intravenous administration to pregnant ewes during late gestation and labor. Sustained administration of DCA to the mother over 72 hours achieved pharmacologically active levels of DCA in the fetus and decreased fetal plasma lactate concentrations. Multicompartmental pharmacokinetics modeling indicated that drug metabolism in the fetal and maternal compartments is best described by the DCA inhibiting lactate production in both compartments, consistent with our finding that the hepatic expression of the DCA-metabolizing enzyme glutathione transferase zeta1 was decreased in the ewes and their fetuses exposed to the drug. We provide the first evidence that DCA can cross the placental compartment to enter the fetal circulation and inhibit its own hepatic metabolism in the fetus, leading to increased DCA concentrations and decreased fetal plasma lactate concentrations during its parenteral administration to the mother. SIGNIFICANCE STATEMENT: This study was the first to administer sodium dichloroacetate (DCA) to pregnant animals (sheep). It showed that DCA administered to the mother can cross the placental barrier and achieve concentrations in fetus sufficient to decrease fetal lactate concentrations. Consistent with findings reported in other species, DCA-mediated inhibition of glutathione transferase zeta1 was also observed in ewes, resulting in reduced metabolism of DCA after prolonged administration.

Improved Characterization of Diffusion in Normal and Cancerous Prostate Tissue Through Optimization of Multicompartmental Signal Models.

Multicompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer. To optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo. Retrospective. Forty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer. 3T multishell diffusion-weighted sequence. Multicompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps. Analysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models. The lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm2 /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P < 0.05). Residuals were lowest in the peripheral zone and highest in tumors. Tumor tissue showed the largest reduction in fitting residual by increasing model order. Tumors had a greater proportion of signal from compartment 1 than normal tissue (P < 0.05). Tumor CNR and SIR were greater on compartment-1 signal maps than conventional DWI (P < 0.05) and increased with model order. The 4-compartment signal model best described diffusion in the prostate. Compartmental signal contributions revealed by this model may improve assessment of prostate cancer. Level of Evidence 3 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:628-639.

Integration of Within-Cell Experimental Data With Multi-Compartmental Modeling Predicts H-Channel Densities and Distributions in Hippocampal OLM Cells.

Determining biophysical details of spatially extended neurons is a challenge that needs to be overcome if we are to understand the dynamics of brain function from cellular perspectives. Moreover, we now know that we should not average across recordings from many cells of a given cell type to obtain quantitative measures such as conductance since measures can vary multiple-fold for a given cell type. In this work we examine whether a tight combination of experimental and computational work can address this challenge. The oriens-lacunosum/moleculare (OLM) interneuron operates as a “gate” that controls incoming sensory and ongoing contextual information in the CA1 of the hippocampus, making it essential to understand how its biophysical properties contribute to memory function. OLM cells fire phase-locked to the prominent hippocampal theta rhythms, and we previously used computational models to show that OLM cells exhibit high or low theta spiking resonance frequencies that depend respectively on whether their dendrites have hyperpolarization-activated cation channels (h-channels) or not. However, whether OLM cells actually possess dendritic h-channels is unknown at present. We performed a set of whole-cell recordings of OLM cells from mouse hippocampus and constructed three multi-compartment models using morphological and electrophysiological parameters extracted from the same OLM cell, including per-cell pharmacologically isolated h-channel currents. We found that the models best matched experiments when h-channels were present in the dendrites of each of the three model cells created. This strongly suggests that h-channels must be present in OLM cell dendrites and are not localized to their somata. Importantly, this work shows that a tight integration of model and experiment can help tackle the challenge of characterizing biophysical details and distributions in spatially extended neurons. Full spiking models were built for two of the OLM cells, matching their current clamp cell-specific electrophysiological recordings. Overall, our work presents a technical advancement in modeling OLM cells. Our models are available to the community to use to gain insight into cellular dynamics underlying hippocampal function.

Model-Based Deep Learning for Reconstruction of Joint k-q Under-sampled High Resolution Diffusion MRI.

We propose a model-based deep learning architecture for the reconstruction of highly accelerated diffusion magnetic resonance imaging (MRI) that enables high resolution imaging. The proposed reconstruction jointly recovers all the diffusion weighted images in a single step from a joint k-q under-sampled acquisition in a parallel MRI setting. We propose the novel use of a pre-trained denoiser as a regularizer in a model-based reconstruction for the recovery of highly under-sampled data. Specifically, we designed the denoiser based on a general diffusion MRI tissue microstructure model for multi-compartmental modeling. By using a wide range of biologically plausible parameter values for the multi-compartmental microstructure model, we simulated diffusion signal that spans the entire microstructure parameter space. A neural network was trained in an unsupervised manner using an autoencoder to learn the diffusion MRI signal subspace. We employed the autoencoder in a model-based reconstruction and show that the autoencoder provides a strong denoising prior to recover the q-space signal. We show reconstruction results on a simulated brain dataset that shows high acceleration capabilities of the proposed method.

Multicompartmental Toxicokinetic Modeling of Discrete Dietary and Continuous Waterborne Uptake of Two Polycyclic Aromatic Hydrocarbons by Zebrafish Danio rerio.

In the present study, we developed a multicompartmental toxicokinetic model for two polycyclic aromatic hydrocarbons (phenanthrene and anthracene) in their deuterated form (PAHs-d10) in zebrafish considering continuous waterborne uptake and discrete dietary uptake. We quantified the bioconcentration, bioaccumulation, and depuration of these two PAHs-d10 in zebrafish, and then estimated the kinetic parameters by fitting the model into the experimental data. The experimental and fitting results both showed that there was a peak concentration in each compartment of zebrafish after every dietary uptake, while the peak value depended on the ingestion amount of the PAH-d10 and varied among different compartments. The PAH-d10 amount in the blood reached 20-27% of the total amount bioaccumulated in zebrafish at steady-state, followed by skin (20-26%), and fillet (16-22%). The rank of PAH-d10 steady-state concentrations in each compartment showed inconsistency with its lipid contents, indicating that the distribution of the PAHs-d10 in zebrafish was not merely affected by the lipid content in each compartment, but also affected by their kinetics and biotransformation. This study suggests that discrete dietary uptake caused by intermittent food ingestion significantly affects the bioaccumulation of PAHs in fish. Further studies are needed to investigate such effect on other toxicants that are more resistant to biotransformation than PAHs in fish.

Incorporating non-linear alignment and multi-compartmental modeling for improved human optic nerve diffusion imaging

In vivo human optic nerve diffusion magnetic resonance imaging (dMRI) is technically challenging with two outstanding issues not yet well addressed: (i) non-linear optic nerve movement, independent of head motion, and (ii) effect from partial-volumed cerebrospinal fluid or interstitial fluid such as in edema. In this work, we developed a non-linear optic nerve registration algorithm for improved volume alignment in axial high resolution optic nerve dMRI. During eyes-closed dMRI data acquisition, optic nerve dMRI measurements by diffusion tensor imaging (DTI) with and without free water elimination (FWE), and by diffusion basis spectrum imaging (DBSI), as well as optic nerve motion, were characterized in healthy adults at various locations along the posterior-to-anterior dimension. Optic nerve DTI results showed consistent trends in microstructural parametric measurements along the posterior-to-anterior direction of the entire intraorbital optic nerve, while the anterior portion of the intraorbital optic nerve exhibited the largest spatial displacement. Multi-compartmental dMRI modeling, such as DTI with FWE or DBSI, was less subject to spatially dependent biases in diffusivity and anisotropy measurements in the optic nerve which corresponded to similar spatial distributions of the estimated fraction of isotropic diffusion components. DBSI results derived from our clinically feasible (∼10 min) optic nerve dMRI protocol in this study are consistent with those from small animal studies, which provides the basis for evaluating the utility of multi-compartmental dMRI modeling in characterizing coexisting pathophysiology in human optic neuropathies.

Myocardial oxygen balance during acute normovolemic hemodilution: A novel compartmental modeling approach

BackgroundHemodilution was introduced initially as a blood conservation technique to reduce allogeneic blood transfusion in patients undergoing surgical procedures. Although the technique has been approved by the National Institute of Health consensus panel, limits of hemodilution under anesthetic conditions have not been established as they have in animal models. MethodsA novel multi-compartmental modeling approach has been proposed that includes the effect of anesthesia to quantify the effect of hemodilution on myocardial oxygen balance during myocardial ischemia. ResultsThe results showed that isovolemic hemodilution would cause detrimental effects around a hematocrit of 15%. Even though the fall in oxygen content caused by the decrease in hemoglobin concentration was compensated by an increase in coronary blood flow induced by hypoxic vasodilation and decreased viscosity, the endocardial tissue received less oxygen compared to the epicardial regions, and this sub-endocardial ischemia eventually led to cardiac failure. Statistical analysis also showed that the type of acellular replacement fluid failed to affect the heart rate, the stroke index or the cardiac index during hemodilution, and supplemental oxygen improved the endocardial oxygen supply. ConclusionThe model validates the clinical conclusions that sub-endocardial ischemia causes cardiac failure under extreme hemodilution conditions and the model can also be easily integrated into other human simulators.

Modeling Neural Adaptation in Auditory Cortex

Neural responses recorded from auditory cortex exhibit adaptation, a stimulus-specific decrease that occurs when the same sound is presented repeatedly. Stimulus-specific adaptation is thought to facilitate perception in noisy environments. Although adaptation is assumed to arise independently from cortex, this has been difficult to validate directly in vivo. In this study, we used a neural network model of auditory cortex with multicompartmental cell modeling to investigate cortical adaptation. We found that repetitive, non-adapted inputs to layer IV neurons in the model elicited frequency-specific decreases in simulated single neuron, population-level and local field potential (LFP) activity, consistent with stimulus-specific cortical adaptation. Simulated recordings of LFPs, generated solely by excitatory post-synaptic inputs and recorded from layers II/III in the model, showed similar waveform morphologies and stimulus probability effects as auditory evoked responses recorded from human cortex. We tested two proposed mechanisms of cortical adaptation, neural fatigue and neural sharpening, by varying the strength and type of inter- and intra-layer synaptic connections (excitatory, inhibitory). Model simulations showed that synaptic depression modeled in excitatory (AMPA) synapses was sufficient to elicit a reduction in neural firing rate, consistent with neural fatigue. However, introduction of lateral inhibition from local layer II/III interneurons resulted in a reduction in the number of responding neurons, but not their firing rates, consistent with neural sharpening. These modeling results demonstrate that adaptation can arise from multiple neural mechanisms in auditory cortex.

Multi-compartmental toxicokinetic modeling of fipronil in tilapia: Accumulation, biotransformation and elimination.

Bioaccumulation and biotransformation are critical processes modifying toxicity of easily metabolizable chemicals to aquatic organisms. In this study, tissue-specific accumulation, biotransformation and elimination of a current-use pesticide fipronil in tilapia (Oreochromis niloticus) were quantified by combining in vivo measurements and a newly developed multi-compartmental toxicokinetic model. Waterborne fipronil was taken up via gills and metabolized rapidly and solely to fipronil sulfone. Significant decrease of fipronil residues in liver and intestine during exposure period strongly suggested the induction of metabolism in these two organs. Significant transport of fipronil and fipronil sulfone in the liver-bile-intestine system implied that hepatobiliary excretion and enterohepatic re-absorption played important roles in fipronil metabolism and system circulation of the parent compound and the metabolite. The multi-compartmental model quantitatively described the highly dynamic inter-compartmental transport and rapid branchial clearance of fipronil in fish. Modeling results also suggested that uptake and biotransformation were the stronger driving forces for the inter-compartmental transport of fipronil in fish than the inherent partitioning capacity. Overall, our findings highlight the importance of biotransformation on internal disposition of fipronil in fish, which helps to improve aquatic toxicity assessment of this pesticide.

Effects of Intranasal Insulin on Triglyceride-Rich Lipoprotein Particle Production in Healthy Men.

Insulin administered directly into the brain acutely suppresses hepatic glucose production and triglyceride-rich lipoprotein (TRL) secretion in rodents. In addition, intranasally administered insulin, which selectively raises cerebrospinal fluid insulin concentration, suppresses hepatic glucose production in humans; however, its effect on TRL secretion in humans has not previously been examined. In this study, we examined whether intranasal insulin, administered at a dose that has previously been shown to suppress hepatic glucose production, modulates TRL particle secretion by the liver and intestine in humans. Nine healthy, normolipidemic, and normoglycemic men participated in a study consisting of 2 randomized study arms. Subjects received intranasal lispro insulin (40 IU) or placebo. Because intranasal insulin results in a rapid and transient increase in systemic insulin concentration after administration, we matched systemic insulin concentrations in the 2 study arms by infusing lispro insulin intravenously for 30 minutes together with intranasal placebo administration. Apo (apolipoprotein) B100-containing (hepatically derived) and apoB48-containing (intestinally derived) TRL lipoprotein particle turnover were measured for the ensuing 10 hours under pancreatic clamp conditions and constant fed state, using stable isotope enrichment techniques and multicompartmental modeling. Under these experimental conditions, no significant effects of intranasal insulin versus placebo on TRL apoB100 or B48 concentrations, fractional catabolic rates, or production rates were observed. Insulin delivered intranasally at a dose that has been shown to raise cerebrospinal fluid insulin concentration and suppress hepatic glucose production does not affect TRL particle production by the liver and intestine in healthy men. URL: http://www.clinicaltrials.gov. Unique identifier: NCT03141827.

Abstract 394: Ldl-cholesterol, ApoB100 Kinetics and Atherosclerosis in Ldlr-deficient Yucatan Minipigs: A New Model for Familial Hypercholesterolemia

Lack of animal models with human-like lipoprotein metabolism and pathology has hampered translational research in atherosclerosis. Recently, a model of familial hypercholesterolemia was developed in Yucatan miniature pigs, in which the LDL receptor (LDLR) was deleted through gene targeting of exon 4. The objective of the present study was to determine the plasma lipoprotein response to a high fat diet and the kinetics of apolipoprotein (apo) B metabolism in LDLR-deficient miniature pigs. LDLR+/+ (n=5), LDLR+/- pigs (n=6) and LDLR-/- pigs (n=5) were fed a diet containing 34% kcal from fat and 0.2% cholesterol (C). At 6 weeks, the kinetics of plasma apoB100 (fasting) were measured using stable isotopic techniques and multi-compartmental modeling. In chow-fed pigs, LDL-C was 0.8mM, 1.3mM and 14mM in LDLR+/+, LDLR+/- and LDLR-/- pigs, respectively. On diet for 6 weeks, LDL-C increased 1.3-fold (to 1.09mM), 1.7-fold (to 2.3mM) and 1.2-fold (to 15.8mM) in LDLR+/+, LDLR+/- and LDLR-/- pigs, respectively. The effect of genotype or diet on plasma TG and HDL-C was modest. Compared to LDLR+/+ pigs, VLDL apoB100 pool sizes increased 1.4-fold in LDLR+/- and 1.7-fold in LDLR-/- pigs, due primarily to a decrease in fractional catabolic rates (FCR) of 18% and 63%, respectively. Compared to LDL+/+ pigs, LDL apoB100 pool sizes increased 2.2-fold and 14-fold in LDLR+/- and LDLR-/-, respectively, which was due to both 1.5-fold and 2-fold increases in production rates and 24% and 85% decreases in FCR, respectively. At 23 weeks, raised lesion area in the abdominal aorta was 3.3% in LDLR+/- pigs and 48.5% in LDLR-/- pigs. In the left anterior descending coronary artery, lesion area was 14.7x10 3 μm 2 in LDLR+/- pigs and 656x10 3 μm 2 in LDLR-/- pigs. This model should prove useful for translational research in lipoprotein metabolism and atherosclerosis.

A novel approach to measuring macrophage-specific reverse cholesterol transport in vivo in humans

Reverse cholesterol transport (RCT) is thought to be an atheroprotective function of HDL, and macrophage-specific RCT in mice is inversely associated with atherosclerosis. We developed a novel method using 3H-cholesterol nanoparticles to selectively trace macrophage-specific RCT in vivo in humans. Use of 3H-cholesterol nanoparticles was initially tested in mice to assess the distribution of tracer and response to interventions known to increase RCT. Thirty healthy subjects received 3H-cholesterol nanoparticles intravenously, followed by blood and stool sample collection. Tracer counts were assessed in plasma, nonHDL, HDL, and fecal fractions. Data were analyzed by using multicompartmental modeling. Administration of 3H-cholesterol nanoparticles preferentially labeled macrophages of the reticuloendothelial system in mice, and counts were increased in mice treated with a liver X receptor agonist or reconstituted HDL, as compared with controls. In humans, tracer disappeared from plasma rapidly after injection of nanoparticles, followed by reappearance in HDL and nonHDL fractions. Counts present as free cholesterol increased rapidly and linearly in the first 240 min after nadir; counts in cholesteryl ester increased steadily over time. Estimates of fractional transfer rates of key RCT steps were obtained. These results support the use of 3H-cholesterol nanoparticles as a feasible approach for the measurement of macrophage RCT in vivo in humans.