Ex-vivo Data Research Articles

Ultrasound assessment of pulmonary edema using multiple scattering

Ultrasound imaging in the lungs is challenging because of air-filled alveoli which induce multiple scattering. Pulmonary edema is characterized by increased extravascular lung water, which causes acute dyspnea. There is an urgent need from pulmonologists to non-invasively quantify pulmonary edema, in order to monitor response to treatment. The present methodology takes advantage of multiple scattering and calculates the scattering mean free path (L*) for the quantitative assessment of pulmonary edema. L* is a semi-local property, which could be correlated to the amount of fluid buildup in the lung. Pulmonary edema was induced in 4 Sprague-Dawley rats using ischemia reperfusion injury. Following a sternotomy, L* was calculated from the time evolution of the backscattered incoherent intensity using an L11-4v linear array connected to a Verasonics scanner. Ex-vivo data were also acquired for 2 edematous pig lungs. For measurements, the left lung was edematous whereas the right lung was treated as control. Significant differences (p<0.001) were found between control (L* = 330±89μm) and edema (L* = 876±179 μm) for in-vivo rats. For ex-vivo pig lungs, L* was found to be 190±84 μm for control and 1074±361 μm for edema. This suggests the potential of L* for the assessment of pulmonary edema.

Automatically Determining the Confocal Parameters From OCT B-Scans for Quantification of the Attenuation Coefficients.

The attenuation coefficient is a relevant biomarker for many diagnostic medical applications. Recently, the Depth-Resolved Confocal (DRC) technique was developed to automatically estimate the attenuation coefficients from Optical Coherence Tomography (OCT) data with pixel-level resolution. However, DRC requires that the confocal function parameters (i.e., focal plane location and apparent Rayleigh range) be known a priori. In this paper, we present the autoConfocal algorithm: a simple, automatic method for estimating those parameters directly from OCT imagery when the focal plane is within the sample. We present autoConfocal+DRC results on phantom data, ex-vivo biological tissue data, and in-vivo clinical data.

MRI Based Brain-Specific 3D-Printed Model Aligned to Stereotactic Space for Registering Histology to MRI.

Studies that seek to predict the brain microstructure based on MRI require precise alignment of processed brain histology slices to the corresponding 3D MRI data. However, achieving such alignment is a challenging problem, due to tissue distortions and the different contrasts seen in MRI and the processed tissue. Here we present a pipeline for aligning a histology volume to the MRI data of the tissue and to a stereotaxic brain atlas. To this end, we segment the volume of the brain from ex-vivo MRI data, align the MRI data obtained in the native space to an MRI stereotaxic template and create a 3D printed model (a mold or cradle) that precisely fits the brain. The pipeline then makes it possible to create grooves in the 3D model, for guiding blades for cutting slabs of tissue. Placing the brain in the brain-specific 3D printed model aligns the tissue to the MRI data by default. Aligning the MRI data to an MRI stereotaxic template makes it possible to section histology slices parallel to the standard stereotaxic axes of the atlas. This facilitates comparisons to other MRI contrasts and to images of processed tissue aligned to the standard space, while maintaining the high-resolution of the tissue images along the standard stereotaxic plane. Guiding the positioning of the grooves according to species-specific anatomical information from the co-registered atlas facilitates region-specific histology. The pipeline we introduce can be used to create brain-specific sectioning models for a variety of species, including humans, primates, and rodents. To demonstrate the generalizability of the pipeline across species, we show models generated for macaques and rats.

Highly trabeculated structure of the human endocardium underlies asymmetrical response to low-energy monophasic shocks.

Novel low-energy defibrillation therapies are thought to be driven by virtual-electrodes (VEs), due to the interaction of applied monophasic electric shocks with fine-scale anatomical structures within the heart. Significant inter-species differences in the cardiac (micro)-anatomy exist, however, particularly with respect to the degree of endocardial trabeculations, which may underlie important differences in response to low-energy defibrillation protocols. Understanding the interaction of monophasic electric fields with the specific human micro-anatomy is therefore imperative in facilitating the translation and optimisation of these promising experimental therapies to the clinic. In this study, we sought to investigate how electric fields from implanted devices interact with the highly trabeculated human endocardial surface to better understand shock success in order to help optimise future clinical protocols. A bi-ventricular human computational model was constructed from high resolution (350 μm) ex-vivo MR data, including anatomically accurate endocardial structures. Monophasic shocks were applied between a basal right ventricular catheter and an exterior ground. Shocks of varying strengths were applied with both anodal [positive right ventricle (RV) electrode] and cathodal (negative RV electrode) polarities at different states of tissue refractoriness and during induced arrhythmias. Anodal shocks induced isolated positive VEs at the distal side of “detached” trabeculations, which rapidly spread into hyperpolarised tissue on the surrounding endocardial surfaces following the shock. Anodal shocks thus depolarised more tissue 10 ms after the shock than cathodal shocks where the propagation of activation from VEs induced on the proximal side of “detached” trabeculations was prevented due to refractory endocardium. Anodal shocks increased arrhythmia complexity more than cathodal shocks during failed anti-arrhythmia shocks. In conclusion, multiple detached trabeculations in the human ventricle interact with anodal stimuli to induce multiple secondary sources from VEs, facilitating more rapid shock-induced ventricular excitation compared to cathodal shocks. Such a mechanism may help explain inter-species differences in response to shocks and help to develop novel defibrillation strategies.

Computing dispersion curves of elastic/viscoelastic transversely-isotropic bone plates coupled with soft tissue and marrow using semi-analytical finite element (SAFE) method

We present a semi-analytical finite element (SAFE) scheme for accurately computing the velocity dispersion and attenuation in a trilayered system consisting of a transversely-isotropic (TI) cortical bone plate sandwiched between the soft tissue and marrow layers. The soft tissue and marrow are mimicked by two fluid layers of finite thickness. A Kelvin-Voigt model accounts for the absorption of all three biological domains. The simulated dispersion curves are validated by the results from the commercial software DISPERSE and published literature. Finally, the algorithm is applied to a viscoelastic trilayered TI bone model to interpret the guided modes of an ex-vivo experimental data set from a bone phantom.

DNA methylation variations are required for epithelial-to-mesenchymal transition induced by cancer-associated fibroblasts in prostate cancer cells

Widespread genome hypo-methylation and promoter hyper-methylation of epithelium-specific genes are hallmarks of stable epithelial-to-mesenchymal transition (EMT), which in prostate cancer (PCa) correlates with castration resistance, cancer stem cells generation, chemoresistance and worst prognosis. Exploiting our consolidated 'ex-vivo' system, we show that cancer-associated fibroblasts (CAFs) released factors have pivotal roles in inducing genome methylation changes required for EMT and stemness in EMT-prone PCa cells. By global DNA methylation analysis and RNA-Seq, we provide compelling evidence that conditioned media from CAFs explanted from two unrelated patients with advanced PCa, stimulates concurrent DNA hypo- and hyper-methylation required for EMT and stemness in PC3 and DU145, but not in LN-CaP and its derivative C4-2B, PCa cells. CpG island (CGI) hyper-methylation associates with repression of genes required for epithelial maintenance and invasion antagonism, whereas activation of EMT markers and stemness genes correlate with CGI hypo-methylation. Remarkably, methylation variations and EMT-regulated transcripts almost completely reverse qualitatively and quantitatively during MET. Unsupervised clustering analysis of the PRAD TCGA data set with the differentially expressed (DE) and methylated EMT signature, identified a gene cluster of DE genes defined by a CAF+ and AR- phenotype and worst diagnosis. This gene cluster includes the relevant factors for EMT and stemness, which display DNA methylation variations in regulatory regions inversely correlated to their expression changes, thus strongly sustaining the ex-vivo data. DNMT3A-dependent methylation is essential for silencing epithelial maintenance and EMT counteracting genes, such as CDH1 and GRHL2, that is, the direct repressor of ZEB1, the key transcriptional factor for EMT and stemness. Accordingly, DNMT3A knock-down prevents EMT entry. These results shed light on the mechanisms of establishment and maintenance of coexisting DNA hypo- and hyper-methylation patterns during cancer progression, the generation of EMT and cell stemness in advanced PCa, and may pave the way to new therapeutic implications.

In Vitro Co-Culture of CLL-B Cells Reveals Long-Term Survival, Proliferation, and Maintenance of Telomere Length

Telomere length is a prognostic factor in Chronic Lymphocytic Leukemia (CLL) with short telomere length a powerful predictor of early time to first treatment and reduced overall survival. However, little is known about telomere dynamics through the course of an individual patient's disease. Our recent longitudinal analysis of CLL B-cell telomere length revealed very little dynamic change within individual patients with a mean erosion rate of -52bp/year (p=0.05). In marked contrast, T-cells derived from the same patients showed a significantly higher mean erosion rate of -119bp/year (p=0.02) with a median follow up time of 69 months. Here we present data derived from long-term in-vitro co-culture of peripheral blood from CLL patients coupled with temporal analysis of their telomere length dynamics.We utilized a multi-cellular co-culture system, comprised of autologous T-cells and CD40L-expressing mouse fibroblasts, to maintain CLL cells in long-term culture. Patient-derived peripheral blood mononuclear cells (n=16) were maintained for a median of 70 days (range 54-154); samples were analyzed every two weeks for tumor cell telomere length and evidence of proliferation. We used fluorescence-activated cell sorting (FACS) to sort populations of CD19+CD5+ CLL B-cells and CD3+ T-cells from each of the cultures. We then performed high-resolution single telomere length analysis (STELA) on these sorted subsets of cells and analyzed their telomere dynamics over this extended time course. Analysis of CLL B-cells from these cultures revealed significantly increased Ki-67+ at day 14 when compared to day 0 (p<0.001) and this was evident for the duration of the cultures. Despite sustained tumor cell proliferation, we observed no significant difference in the CLL B-cell telomere length with a mean TL at the start of 4.5kb vs 4.3kb at the end (p=0.14).The presence of T-cells was shown to be critical for the maintenance of the long-term cultures in two ways. Firstly, cultures that were treated with 4μM fludarabine showed a catastrophic reduction in T-cells (p=0.01), which was associated with a significantly shorter duration of survival of CLL B-cells when compared to untreated controls (median 17.5 days (range 7-70); p<0.001). Secondly, it proved impossible to maintain T-cell depleted, purified CLL B-cells, in long-term culture. T-cells isolated from the long-term cultures showed evidence of proliferation with Ki-67+ again being increased at day 14 in comparison to baseline (p=0.003). Furthermore, T-cells derived from these cultures showed a significant alteration in subset composition over time with a decrease in the numbers of naive CD4+ (p=0.05) and CD8+ (p=0.02) T-cells and a corresponding increase in effector memory (p=0.2) and terminally differentiated effector memory (EMRA) subsets (p=0.07).In conclusion, this study demonstrates that we have developed a robust, long-term culture method for the maintenance of CLL cells. Despite evidence of sustained CLL proliferation, CLL B-cells showed little telomere length erosion during long-term co-culture and this is compatible with our recent ex-vivo analysis, which showed that the telomere length of CLL B-cells are remarkably stable with a mean erosion rate of only -52bp/year. In both ex-vivo and in-vitro analysis, telomere erosion correlated with starting telomere length (r2=0.14, p=0.04 and r2=0.3 p=0.03 respectively). Taken together, our in-vitro and ex-vivo data imply that the radically short telomeres observed in some CLL patients are not the result of increased proliferation of the malignant B-cell, but rather the mutagenic event occurs in a B-cell which already has short telomeres. Furthermore, our novel long-term culture model has reinforced the vital role of T-cells in sustaining CLL B-cells viability and proliferation in-vitro. Given the consistent skewing of the T-cell pool towards a memory phenotype it seems unlikely that this is driven in-vitro by cognate TCR antigen recognition but rather a cytokine-mediated response. DisclosuresFegan:Gilead Sciences: Honoraria; Roche: Honoraria; AbbVie: Honoraria.

Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI.

Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e.g. crossings) has proved challenging. Besides optimized data acquisition and advanced biophysical models, computational procedures to fit such models to the data are critical. However, these procedures have been largely overlooked by the dMRI microstructure community and new, more versatile, approaches are needed to solve complex biophysical model fitting problems. Existing methods are limited to models assuming single fiber orientation, relevant to limited brain areas like the corpus callosum, or multiple orientations but without the ability to extract detailed microstructural features. Here, we introduce a new and versatile optimization technique (MIX), which enables microstructure imaging of crossing white matter fibers. We provide a MATLAB implementation of MIX, and demonstrate its applicability to general microstructure models in fiber crossings using synthetic as well as ex-vivo and in-vivo brain data.

Evaluation and comparison of current biopsy needle localization and tracking methods using 3D ultrasound

This article compares four different biopsy needle localization algorithms in both 3D and 4D situations to evaluate their accuracy and execution time. The localization algorithms were: Principle component analysis (PCA), random Hough transform (RHT), parallel integral projection (PIP) and ROI-RK (ROI based RANSAC and Kalman filter). To enhance the contrast of the biopsy needle and background tissue, a line filtering pre-processing step was implemented. To make the PCA, RHT and PIP algorithms comparable with the ROI-RK method, a region of interest (ROI) strategy was added. Simulated and ex-vivo data were used to evaluate the performance of the different biopsy needle localization algorithms. The resolutions of the sectorial and cylindrical volumes were 0.3mm×0.4mm×0.6mmand0.1mm×0.1mm×0.2mm (axial×lateral×azimuthal) respectively. In so far as the simulation and experimental results show, the ROI-RK method successfully located and tracked the biopsy needle in both 3D and 4D situations. The tip localization error was within 1.5mm and the axis accuracy was within 1.6mm. To the best of our knowledge, considering both localization accuracy and execution time, the ROI-RK was the most stable and time-saving method. Normally, accuracy comes at the expense of time. However, the ROI-RK method was able to locate the biopsy needle with high accuracy in real time, which makes it a promising method for clinical applications.

Multi-Layer Mechanical Model of Glagov Remodeling in Coronary Arteries: Differences between In-Vivo and Ex-Vivo Measurements.

When blood vessels undergo remodeling because of the buildup of atherosclerotic plaque, it is thought that they first undergo compensatory or outward remodeling, followed by inward remodeling: the lumen area stays roughly constant or increases slightly and then decreases rapidly. The second phase of remodeling is supposed to start after the plaque burden exceeds about 40%. These changes in the vessel were first observed by S. Glagov who examined cross-sections of coronary arteries at different stages of the disease. In this paper, we use a mathematical model based on growth and elasticity theory to verify the main aspects of Glagov’s result. However, both our model and curve-fitting to the data suggest that the critical stenosis is around 20% rather than 40%. Our model and data from the PROSPECT trial also show that Glagov remodeling is qualitatively different depending on whether measurements are taken ex-vivo or in-vivo. Our results suggest that the first outward phase of “Glagov remodeling” is largely absent for in-vivo measurements: that is, the lumen area always decreases as plaque builds up. We advocate that care must be taken when infering how in-vivo vessels remodel from ex-vivo data.

Estimation of Bounded and Unbounded Trajectories in Diffusion MRI

Disentangling the tissue microstructural information from the diffusion magnetic resonance imaging (dMRI) measurements is quite important for extracting brain tissue specific measures. The autocorrelation function of diffusing spins is key for understanding the relation between dMRI signals and the acquisition gradient sequences. In this paper, we demonstrate that the autocorrelation of diffusion in restricted or bounded spaces can be well approximated by exponential functions. To this end, we propose to use the multivariate Ornstein-Uhlenbeck (OU) process to model the matrix-valued exponential autocorrelation function of three-dimensional diffusion processes with bounded trajectories. We present detailed analysis on the relation between the model parameters and the time-dependent apparent axon radius and provide a general model for dMRI signals from the frequency domain perspective. For our experimental setup, we model the diffusion signal as a mixture of two compartments that correspond to diffusing spins with bounded and unbounded trajectories, and analyze the corpus-callosum in an ex-vivo data set of a monkey brain.

Classification of calcium in intravascular OCT images for the purpose of intervention planning.

The presence of extensive calcification is a primary concern when planning and implementing a vascular percutaneous intervention such as stenting. If the balloon does not expand, the interventionalist must blindly apply high balloon pressure, use an atherectomy device, or abort the procedure. As part of a project to determine the ability of Intravascular Optical Coherence Tomography (IVOCT) to aid intervention planning, we developed a method for automatic classification of calcium in coronary IVOCT images. We developed an approach where plaque texture is modeled by the joint probability distribution of a bank of filter responses where the filter bank was chosen to reflect the qualitative characteristics of the calcium. This distribution is represented by the frequency histogram of filter response cluster centers. The trained algorithm was evaluated on independent ex-vivo image data accurately labeled using registered 3D microscopic cryo-image data which was used as ground truth. In this study, regions for extraction of sub-images (SI's) were selected by experts to include calcium, fibrous, or lipid tissues. We manually optimized algorithm parameters such as choice of filter bank, size of the dictionary, etc. Splitting samples into training and testing data, we achieved 5-fold cross validation calcium classification with F1 score of 93.7±2.7% with recall of ≥89% and a precision of ≥97% in this scenario with admittedly selective data. The automated algorithm performed in close-to-real-time (2.6 seconds per frame) suggesting possible on-line use. This promising preliminary study indicates that computational IVOCT might automatically identify calcium in IVOCT coronary artery images.

Factors that influence muscle shear modulus during passive stretch

Although elastography has been increasingly used for evaluating muscle shear modulus associated with age, sex, musculoskeletal, and neurological conditions, its physiological meaning is largely unknown. This knowledge gap may hinder data interpretation, limiting the potential of using elastography to gain insights into muscle biomechanics in health and disease. We derived a mathematical model from a widely-accepted Hill-type passive force–length relationship to gain insight about the physiological meaning of resting shear modulus of skeletal muscles under passive stretching, and validated the model by comparing against the ex-vivo animal data reported in our recent work (Koo et al. 2013). The model suggested that resting shear modulus of a slack muscle is a function of specific tension and parameters that govern the normalized passive muscle force–length relationship as well as the degree of muscle anisotropy. The model also suggested that although the slope of the linear shear modulus–passive force relationship is primarily related to muscle anatomical cross-sectional area (i.e. the smaller the muscle cross-sectional area, the more the increase in shear modulus to result in the same passive muscle force), it is also governed by the normalized passive muscle force–length relationship and the degree of muscle anisotropy. Taken together, although muscle shear modulus under passive stretching has a strong linear relationship with passive muscle force, its actual value appears to be affected by muscle’s mechanical, material, and architectural properties. This should be taken into consideration when interpreting the muscle shear modulus values.

Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

In vivo 3 T and ex vivo 7 T diffusion tensor imaging of prostate cancer: Correlation with histology

The purpose of this work was to test whether fractional anisotropy (FA) can contribute to the diagnosis and grading of prostate cancer.Turbo spin echo T2-weighted (T2W) and single shot echo planar imaging diffusion tensor imaging (EPI DTI) data were collected from 13 subjects with biopsy proven prostate cancer prior to surgical removal of the gland. Rapid acquisition with relaxation enhancement (RARE) T2W and spin-echo DTI data were acquired ex-vivo from the fixed prostatectomy specimens. Digitized whole mount histology sections, examined and annotated by a pathologist, were registered to the in-vivo and ex-vivo DTI data, and the average values of apparent diffusion coefficient (ADC) and FA were calculated from ROIs encompassing normal and cancerous peripheral zone (PZ). In addition, Monte Carlo simulations were carried out to assess the dependence of the apparent FA on the ADC values for different signal to noise ratios (SNRs).ADC values were significantly lower in tumors than in normal PZ both in-vivo and ex-vivo, while the difference in FA values between tumors and normal PZ was significant only in-vivo. Paired t-test showed significant difference between in-vivo and ex-vivo FA values in tumors, but not in the normal PZ. The simulations showed that lower SNR results in an increasing overestimation of the FA values with decreasing ADC. These results suggest that the in-vivo increase in FA values in tumors is due to low SNR, rather than the presence of cancer.The results of this study suggest that FA does not contribute significantly to the diagnostic capabilities of DTI in prostate cancer.

COMPARATIVE ANALYSIS OF PIB IN VIVO WITH 6-CN-PIB AND Aβ-IMMUNOHISTOCHEMISTRY POSTMORTEM IN FAMILIAL ALZHEIMER DISEASE ASSOCIATED WITH THE PSEN1 I229F MUTATION

low numbers of participants, relatively long intervals between imaging and death, and low level of detail in terms of the spatial patterns of brain atrophy. The purpose of this investigation was to assess the neuropathologic correlates of regional brainvolumes by combining ex-vivoMRvolumetry and pathology on a large community cohort of older persons. Methods: Cerebral hemispheres were obtained from 166 deceased participants of two longitudinal, epidemiologic clinical-pathologic cohort studies of aging. All hemispheres were imaged ex-vivo, while immersed in 4% formaldehyde solution, on a 3T MRI scanner. A multi-atlas approach was used to segment ex-vivo MRI data intowhite and gray matter, and graymatter into 34 cortical and 8 subcortical regions. The volumes of all regions were normalized by the height of the participants. Following imaging, hemispheres underwent neuropathologic examination. The pathologies that were considered in analyses were: Alzheimer’s disease (AD) pathology, Lewy bodies, hippocampal sclerosis, gross and microscopic chronic infarcts, and cerebral amyloid angiopathy. Multiple linear regression was used to investigate the link between regional volumes and neuropathologies, controlling for age at death, sex, education, postmortem interval to fixation and to imaging. False Discovery Rate (FDR) was used to correct for multiple comparisons.Results: Figure 1 shows brain regions with significant negative correlation (p<0.05, FDR-corrected) between their volume and AD pathology (Fig.1A), and hippocampal sclerosis (Fig.1B). No other pathologies showed significant correlations with the volume of the segmented regions. Conclusions: The present study provides information on the neuropathologic correlates of regional brain volumes in a community cohort of older adults, and may help in the development of imaging biomarkers of AD pathology and hippocampal sclerosis. To our knowledge, this is the largest MR volumetry pathology investigation to date, and the only assessing a high number of brain regions.

Signal decomposition for X-ray dark-field imaging.

Grating-based X-ray dark-field imaging is a new imaging modality. It allows the visualization of structures at micrometer scale due to small-angle scattering of the X-ray beam. However, reading darkfield images is challenging as absorption and edge-diffraction effects also contribute to the dark-field signal, without adding diagnostic value. In this paper, we present a novel--and to our knowledge the first--algorithm for isolating small-angle scattering in dark-field images, which greatly improves their interpretability. To this end, our algorithm utilizes the information available from the absorption and differential phase images to identify clinically irrelevant contributions to the dark-field image. Experimental results on phantom and ex-vivo breast data promise a greatly enhanced diagnostic value of dark-field images.

A bioimage informatics based reconstruction of breast tumor microvasculature with computational blood flow predictions

Induction of tumor angiogenesis is among the hallmarks of cancer and a driver of metastatic cascade initiation. Recent advances in high-resolution imaging enable highly detailed three-dimensional geometrical representation of the whole-tumor microvascular architecture. This enormous increase in complexity of image-based data necessitates the application of informatics methods for the analysis, mining and reconstruction of these spatial graph data structures. We present a novel methodology that combines ex-vivo high-resolution micro-computed tomography imaging data with a bioimage informatics algorithm to track and reconstruct the whole-tumor vasculature of a human breast cancer model. The reconstructed tumor vascular network is used as an input of a computational model that estimates blood flow in each segment of the tumor microvascular network. This formulation involves a well-established biophysical model and an optimization algorithm that ensures mass balance and detailed monitoring of all the vessels that feed and drain blood from the tumor microvascular network. Perfusion maps for the whole-tumor microvascular network are computed. Morphological and hemodynamic indices from different regions are compared to infer their role in overall tumor perfusion.

Fetal hemoglobin in preeclampsia

Preeclampsia, one of the leading causes of pregnancy complications, affects 3-7% of pregnant women. This review summarizes the present knowledge of a new potential cause of the disease and suggests a method for its prediction/diagnosis and a possible treatment, both based on the recent findings on the involvement of fetal hemoglobin (HbF) and the heme and radical scavenging protein A1M (alpha-1-microglobulin). Gene and protein profiling studies have independently shown that increased amount of free HbF is accumulated in the preeclampsia placenta. As a result of a predominantly oxidative damage to the blood-placenta barrier, HbF leaks over to the maternal blood circulation. Elevated levels can be measured already in the first trimester, and later in pregnancy, the levels correlate with the blood pressure in women with preeclampsia. Ex-vivo data show that the human protein A1M, an endogeneous antioxidation protection protein, can prevent Hb-induced damage to the placenta, restore the blood-placental barrier and prevent maternal tissue damage. Free HbF may provide both a predictive and a diagnostic clinical biomarker from the first trimester. A1M has the potential as a future pharmacological treatment for preeclampsia.

Mutant prevention concentration and PK–PD relationships of enrofloxacin for Pasteurella multocida in buffalo calves

This study validated the use of mutant prevention concentration (MPC) and pharmacokinetic and pharmacodynamic (PK–PD) modeling approach for optimization of dose regimen of enrofloxacin to contain the emergence of Pasteurella multocida resistance. The PK and PD characteristics of enrofloxacin were investigated in buffalo calves after intramuscular administration at a dose rate of 12mg/kg. The concentration of enrofloxacin and ciprofloxacin in serum were determined by high-performance liquid chromatography. The serum peak concentration (Cmax), terminal half-life (t1/2K10), volume of distribution (Vd(area)/F) and mean residence time (MRT) of enrofloxacin were 1.89±0.35μg/ml, 5.14±0.66h, 5.59±0.99l/kg/h and 8.52±1.29h, respectively. The percent metabolite conversion ratio of ciprofloxacin to enrofloxacin was 79. The binding of enrofloxacin to plasma proteins was 11%. The MIC, MBC and MPC for enrofloxacin against P. multocida were 0.05, 0.06μg/ml and 1.50μg/ml.In vitro and ex-vivo bactericidal activity of enrofloxacin was concentration dependent. Modeling of ex-vivo growth inhibition data to the sigmoid Emax equation provided AUC24h/MIC values to produce bacteriostatic (19h), bactericidal (43h) and bacterial eradication (64h). PK–PD data in conjunction with MPC and MIC90 data predicted dosage schedules for enrofloxacin that may achieve optimum efficacy in respect of bacteriological and clinical cure and minimize the risk of emergence of resistance.