Effects of P4 Antagonist RU486 on VEGF and Its Receptors’ Signaling during the In Vivo Transition from the Preovulatory to Periovulatory Phase of Ovarian Follicles

The development of an adequate blood vessel network is crucial for the accomplishment of ovarian follicle growth and ovulation, which is necessary to support the proliferative and endocrine functions of the follicular cells. Although the Vascular Endothelial Growth Factor (VEGF) through gonadotropins guides ovarian angiogenesis, the role exerted by the switch on of Progesterone (P4) during the periovulatory phase remains to be clarified. The present research aimed to investigate in vivo VEGF-mediated mechanisms by inducing the development of periovulatory follicles using a pharmacologically validated synchronization treatment carried out in presence or absence of P4 receptor antagonist RU486. Spatio-temporal expression profiles of VEGF, FLT1, and FLK1 receptors and the two major MAPK/ERKs and PI3K/AKT downstream pathways were analyzed on granulosa and on theca compartment. For the first time, the results demonstrated that in vivo administration of P4 antagonist RU486 inhibits follicular VEGF receptors’ signaling mainly acting on the theca layer by downregulating the activation of ERKs and AKTs. Under the effect of RU486, periovulatory follicles’ microarchitecture did not move towards the periovulatory stage. The present evidence provides new insights on P4 in vivo biological effects in driving vascular and tissue remodeling during the periovulatory phase.

Evaluation of blood vessel network formation and visual field defect in optic disc melanocytoma

AimTo investigate the association between visual field defects and blood vessel network (BVN) formation in optic disc melanocytomas (ODMs) using optical coherence tomography angiography (OCTA).MethodsSingle-centre, retrospective case series of 32 eyes of 32 patients with ODM, in which eyes were divided into two groups based on complete and incomplete BVN formations.ResultsOCTA revealed incomplete BVN formation in 16 of 32 ODMs. The location of BVN absence corresponded to the location of hypofluorescence from fluorescein angiography (FA) in 12 (75%) and to the location of visual field defect in 13 (81%) ODMs in the incomplete BVN group. Perimetric indices were significantly worse in the incomplete BVN group than in the complete BVN group. Linear regression of mean deviation (MD) and Visual Field Index (VFI) on the area of BVN absence were statistically significant (p=0.01 and p=0.003, respectively), whereas linear regressions of MD and VFI on the tumour area were not statistically significant (both p=0.09) in the incomplete BVN group.ConclusionThe location of BVN absence within ODMs corresponded to the location of visual field defect and the location of FA hypofluorescence. Visual field defect was more severe in the incomplete BVN group than in the complete BVN group. Visual field defect was more significantly associated with the area of BVN absence than the tumour area.

Blood Clotting Decreases Pulmonary Circulation during the Coronavirus Disease

Spontaneous blood clotting in pulmonary circulation caused by thrombo-inflammation is one of the main mortality causes during the COVID-19 disease. Blood clotting leads to reduced pulmonary circulation and blood oxygenation. Lung inflammation can be evaluated with noninvasive diagnostic techniques. However, the correlation of the severity of the inflammation with the pulmonary blood flow has not been established. To address this question, in this work, we develop a multiscale model taking into account the interaction of a local model of thrombus growth with 1D hemodynamics in a vessel network. Flux reduction depending on the level of lung obstruction is evaluated. In particular, the model obtains that an obstruction level of 5% leads to a 12% reduction of blood flux. The suggested approach can be used to investigate the interaction of blood clotting and flow not only in the pulmonary network but also in other complex vessel networks.

Cross-Modality Imaging of Murine Tumor Vasculature—a Feasibility Study

Tumor vasculature and angiogenesis play a crucial role in tumor progression. Their visualization is therefore of utmost importance to the community. In this proof-of-principle study, we have established a novel cross-modality imaging (CMI) pipeline to characterize exactly the same murine tumors across scales and penetration depths, using orthotopic models of melanoma cancer. This allowed the acquisition of a comprehensive set of vascular parameters for a single tumor. The workflow visualizes capillaries at different length scales, puts them into the context of the overall tumor vessel network and allows quantification and comparison of vessel densities and morphologies by different modalities. The workflow adds information about hypoxia and blood flow rates. The CMI approach includes well-established technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), and ultrasound (US), and modalities that are recent entrants into preclinical discovery such as optical coherence tomography (OCT) and high-resolution episcopic microscopy (HREM). This novel CMI platform establishes the feasibility of combining these technologies using an extensive image processing pipeline. Despite the challenges pertaining to the integration of microscopic and macroscopic data across spatial resolutions, we also established an open-source pipeline for the semi-automated co-registration of the diverse multiscale datasets, which enables truly correlative vascular imaging. Although focused on tumor vasculature, our CMI platform can be used to tackle a multitude of research questions in cancer biology.

Vessel network extraction and analysis of mouse pulmonary vasculature via X-ray micro-computed tomographic imaging

In this work, non-invasive high-spatial resolution three-dimensional (3D) X-ray micro-computed tomography (μCT) of healthy mouse lung vasculature is performed. Methodologies are presented for filtering, segmenting, and skeletonizing the collected 3D images. Novel methods for the removal of spurious branch artefacts from the skeletonized 3D image are introduced, and these novel methods involve a combination of distance transform gradients, diameter-length ratios, and the fast marching method (FMM). These new techniques of spurious branch removal result in the consistent removal of spurious branches without compromising the connectivity of the pulmonary circuit. Analysis of the filtered, skeletonized, and segmented 3D images is performed using a newly developed Vessel Network Extraction algorithm to fully characterize the morphology of the mouse pulmonary circuit. The removal of spurious branches from the skeletonized image results in an accurate representation of the pulmonary circuit with significantly less variability in vessel diameter and vessel length in each generation. The branching morphology of a full pulmonary circuit is characterized by the mean diameter per generation and number of vessels per generation. The methods presented in this paper lead to a significant improvement in the characterization of 3D vasculature imaging, allow for automatic separation of arteries and veins, and for the characterization of generations containing capillaries and intrapulmonary arteriovenous anastomoses (IPAVA).

Automated Detection and Tortuosity Characterization of Retinal Vascular Networks

Automated retinal vascular network detection and analysis using digital retinal images continue to play a major role in the field of biomedicine for the diagnosis and management of various forms of human ailments like hypertension, diabetic retinopathy, retinopathy of prematurity, glaucoma and cardiovascular diseases. Although several literature have implemented different automatic approaches of detecting blood vessels in the retinal and also determining their tortuous states, the results obtained show that there are needs for further investigation on more efficient ways to detect and characterize the blood vessel network tortuosity states. This paper implements the use of an adaptive thresholding method based on local spatial relational variance (LSRV) for the detection of the retinal vascular networks. The suitability of a multi-layer perceptron artificial neural network (MLP-ANN) technique for the tortuosity characterization of retinal blood vascular networks is also presented in this paper. Some vessel geometric features of detected vessels are fed into ANN classifier for the automatic classification of the retinal vascular networks as being tortuous vessels or normal vessels. Experimental studies conducted on DRIVE and STARE databases show that the vascular network detection results obtained from the method implemented in this paper detects large and thin vascular networks in the retina. In comparison to preious methods in the literature, the proposed method for vascular network segmentation achieved better performance than several methods in the literature with a mean accuracy value of 95.04% and mean sensitivity value of 75.16% on DRIVE and mean accuracy value of 94.02% and average sensitivity value of 76.55% on STARE with computational processing time of 4.5 seconds and 9.4 seconds on DRIVE and STARE respectively. The MLP-ANN method proposed for the vascular network tortuosity characterization achieves promising accuracy rates of 77.5%, 80%, 83.33%, 85%, 86.67% and 100% for varying training sample sizes.

SMAD6 transduces endothelial cell flow responses required for blood vessel homeostasis

Fluid shear stress provided by blood flow instigates a transition from active blood vessel network expansion during development, to vascular homeostasis and quiescence that is important for mature blood vessel function. Here we show that SMAD6 is required for endothelial cell flow-mediated responses leading to maintenance of vascular homeostasis. Concomitant manipulation of the mechanosensor Notch1 pathway and SMAD6 expression levels revealed that SMAD6 functions downstream of ligand-induced Notch signaling and transcription regulation. Mechanistically, full-length SMAD6 protein was needed to rescue Notch loss-induced flow misalignment. Endothelial cells depleted for SMAD6 had defective barrier function accompanied by upregulation of proliferation-associated genes and down regulation of junction-associated genes. The vascular protocadherin PCDH12 was upregulated by SMAD6 and required for proper flow-mediated endothelial cell alignment, placing it downstream of SMAD6. Thus, SMAD6 is a required transducer of flow-mediated signaling inputs downstream of Notch1 and upstream of PCDH12, as vessels transition from an angiogenic phenotype to maintenance of a homeostatic phenotype.

A fast numerical method for oxygen supply in tissue with complex blood vessel network

Angiogenesis plays an essential role in many pathological processes such as tumor growth, wound healing, and keloid development. Low oxygen level is the main driving stimulus for angiogenesis. In an animal tissue, the oxygen level is mainly determined by three effects—the oxygen delivery through blood flow in a refined vessel network, the oxygen diffusion from blood to tissue, and the oxygen consumption in cells. Evaluation of the oxygen field is usually the bottleneck in large scale modeling and simulation of angiogenesis and related physiological processes. In this work, a fast numerical method is developed for the simulation of oxygen supply in tissue with a large-scale complex vessel network. This method employs an implicit finite-difference scheme to compute the oxygen field. By virtue of an oxygen source distribution technique from vessel center lines to mesh points and a corresponding post-processing technique that eliminate the local numerical error induced by source distribution, square mesh with relatively large mesh sizes can be applied while sufficient numerical accuracy is maintained. The new method has computational complexity which is slightly higher than linear with respect to the number of mesh points and has a convergence order which is slightly lower than second order with respect to the mesh size. With this new method, accurate evaluation of the oxygen field in a fully vascularized tissue on the scale of centimeter becomes possible.

Nanodrug Delivery Systems Modulate Tumor Vessels to Increase the Enhanced Permeability and Retention Effect

The use of nanomedicine for antitumor therapy has been extensively investigated for a long time. Enhanced permeability and retention (EPR) effect-mediated drug delivery is currently regarded as an effective way to bring drugs to tumors, especially macromolecular drugs and drug-loaded pharmaceutical nanocarriers. However, a disordered vessel network, and occluded or embolized tumor blood vessels seriously limit the EPR effect. To augment the EPR effect and improve curative effects, in this review, we focused on the perspective of tumor blood vessels, and analyzed the relationship among abnormal angiogenesis, abnormal vascular structure, irregular blood flow, extensive permeability of tumor vessels, and the EPR effect. In this commentary, nanoparticles including liposomes, micelles, and polymers extravasate through the tumor vasculature, which are based on modulating tumor vessels, to increase the EPR effect, thereby increasing their therapeutic effect.