spatial-temporal-analysis-of-fieldwise-flow-in-microvasculature

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, ...

Indiana University

Pulmonary neuroepithelial bodies (NEBs) are presumed airway chemoreceptors that express the putative O(2) sensor protein NADPH oxidase and O(2)-sensitive K(+) channels K(+)(O(2)). Although there is a consensus that redox modulation of K(+)(O(2)) may be a common O(2)-sensing mechanism, the identity of the O(2) sensor and related coupling pathways are still controversial. To test whether NADPH oxidase is the O(2) sensor in NEB cells, we performed patch-clamp experiments on intact NEBs identified by neutral red staining in fresh lung slices from wild-type (WT) and oxidase-deficient (OD) mice. In OD mice, cytochrome b(558) and oxidase function was disrupted in the gp91(phox) subunit coding region by insertion of a neomycin phosphotransferase (neo) gene. Expression in NEB cells of neo mRNA, a marker for nonfunctional gp91(phox), was confirmed by nonisotopic in situ hybridization. In WT cells, hypoxia (pO(2) = 15-20 mmHg; 1 mmHg = 133 Pa) caused a reversible inhibition ( approximately 46%) of both Ca(2+)-independent and Ca(2+)-dependent K(+) currents. In contrast, hypoxia had no effect on K(+) current in OD cells, even though both K(+) current components were expressed. Diphenylene iodonium (1 microM), an inhibitor of the oxidase, reduced K(+) current by approximately 30% in WT cells but had no effect in OD cells. Hydrogen peroxide (H(2)O(2); 0.25 mM), a reactive oxygen species generated by functional NADPH oxidase, augmented K(+) current by >30% in both WT and OD cells; further, in WT cells, H(2)O(2) restored K(+) current amplitude in the presence of diphenylene iodonium. We conclude that NADPH oxidase acts as the O(2) sensor in pulmonary airway chemoreceptors.

NADPH oxidase is an O2 sensor in airway chemoreceptors: evidence from K+ current modulation in wild-type and oxidase-deficient mice.

An explanatory computational model is developed of the contiguous areas of retinal capillary loss which play a large role in diabetic maculapathy and diabetic retinal neovascularization. Strictly random leukocyte mediated capillary occlusion cannot explain the occurrence of large contiguous areas of retinal ischemia. Therefore occlusion of an individual capillary must increase the probability of occlusion of surrounding capillaries. A retinal perifoveal vascular sector as well as a peripheral retinal capillary network and a deleted hexagonal capillary network are modelled using Compucell3D. The perifoveal modelling produces a pattern of spreading capillary loss with associated macular edema. In the peripheral network, spreading ischemia results from the progressive loss of the ladder capillaries which connect peripheral arterioles and venules. System blood flow was elevated in the macular model before a later reduction in flow in cases with progression of capillary occlusions. Simulations differing only in initial vascular network structures but with identical dynamics for oxygen, growth factors and vascular occlusions, replicate key clinical observations of ischemia and macular edema in the posterior pole and ischemia in the retinal periphery. The simulation results also seem consistent with quantitative data on macular blood flow and qualitative data on venous oxygenation. One computational model applied to distinct capillary networks in different retinal regions yielded results comparable to clinical observations in those regions.

Progression of Diabetic Capillary Occlusion: A Model.

We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK) modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML) to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics. 

A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

We developed a computational model of the propagation of retinal ischemia in diabetic retinopathy and analyzed the consequences of various patterns and sizes of burns in peripheral retinal photocoagulation. The model addresses retinal ischemia as a phenomenon of adverse local feedback in which once a capillary is occluded there is an elevated probability of occlusion of adjacent capillaries resulting in enlarging areas of retinal ischemia as is commonly seen clinically. Retinal burns of different sizes and patterns, treated as local oxygen sources, are predicted to have different effects on the propagation of retinal ischemia. The patterns of retinal burns are optimized with regard to minimization of the sum of the photocoagulated retina and computer predicted ischemic retina. Our simulations show that certain patterns of retinal burns are effective at preventing the spatial spread of ischemia by creating oxygenated boundaries across which the ischemia does not propagate. This model makes no statement about current PRP treatment of avascular peripheral retina and notes that the usual spot sizes used in PRP will not prevent ischemic propagation in still vascularized retinal areas. The model seems to show that a properly patterned laser treatment of still vascularized peripheral retina may be able to prevent or at least constrain the propagation of diabetic retinal ischemia in those retinal areas with intact capillaries.

A Computational Model of Peripheral Photocoagulation for the Prevention of Progressive Diabetic Capillary Occlusion.

The pervasive role of microRNAs (miRNAs) in cancer pathobiology drives the introduction of new drug development approaches such as miRNA inhibition. In order to advance miRNA-therapeutics, meticulous screening strategies addressing specific tumor targets are needed. Small molecule inhibitors represent an attractive goal for these strategies. In this study, we devised a strategy to screen for small molecule inhibitors that specifically inhibit, directly or indirectly, miR-10b (SMIRs) which is overexpressed in metastatic tumors. We found that the multi-tyrosine kinase inhibitor linifanib could significantly inhibit miR-10b and reverse its oncogenic function in breast cancer and liver cancer both in vitro and in vivo. In addition, we showed that the efficacy of linifanib to inhibit tyrosine kinases was reduced by high miR-10b levels. When the level of miR-10b is high, it can "hijack" the linifanib and reduce its kinase inhibitory effects in cancer resulting in reduced anti-tumor efficacy. In conclusion, our study describes an effective strategy to screen for small molecule inhibitors of miRNAs. We further propose that miR-10b expression levels, due to the newly described "hijacking" effect, may be used as a biomarker to select patients for linifanib treatment.

OncomiR-10b hijacks the small molecule inhibitor linifanib in human cancers.

Computational models of normal liver function and xenobiotic induced liver damage are increasingly being used to interpret in vitro and in vivo data and as an approach to the de novo prediction of the liver's response to xenobiotics. The microdosimetry (dose at the level of individual cells) of xenobiotics vary spatially within the liver because of both compound-independent and compound-dependent factors. In this paper, we build model liver lobules to investigate the interplay between vascular structure, blood flow and cellular transport that lead to regional variations in microdosimetry. We then compared simulation results obtained using this complex spatial model with a simpler linear pipe model of a sinusoid and a very simple single box model. We found that variations in diffusive transport, transporter-mediated transport and metabolism, coupled with complex liver sinusoid architecture and blood flow distribution, led to three essential patterns of xenobiotic exposure within the virtual liver lobule: (1) lobular-wise uniform, (2) radially varying and (3) both radially and azimuthally varying. We propose to use these essential patterns of exposure as a reference for selection of model representations when a computational study involves modeling detailed hepatic responses to xenobiotics.

Modeling of xenobiotic transport and metabolism in virtual hepatic lobule models.

Microvascular perfusion dynamics are vital to physiological function and are frequently dysregulated in injury and disease. Typically studies measure microvascular flow in a few selected vascular segments over limited time, failing to capture spatial and temporal variability. To quantify microvascular flow in a more complete and unbiased way we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow), a macro for FIJI open-source image analysis software. Using high-speed microvascular flow movies, STAFF generates kymographs for every time interval for every vascular segment, calculates flow velocities from red blood cell shadow angles, and outputs the data as color-coded velocity map movies and spreadsheets. In untreated mice, analyses demonstrated profound variation even between adjacent sinusoids over seconds. In acetaminophen-treated mice we detected flow reduction localized to pericentral regions. STAFF is a powerful new tool capable of providing novel insights by enabling measurement of the complex spatiotemporal dynamics of microvascular flow.

Xiao Fu

Biocomplexity Institute,
Department of Physics

Indiana University

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Xiao Fu

Biocomplexity Institute,Department of Physics

Indiana University

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Biocomplexity Institute,
Department of Physics