Vascular Patterning as Integrative Readout of Complex Molecular and Physiological Signaling by VESsel GENeration Analysis.

The molecular signaling cascades that regulate angiogenesis and microvascular remodeling are fundamental to normal development, healthy physiology, and pathologies such as inflammation and cancer. Yet quantifying such complex, fractally branching vascular patterns remains difficult. We review application of NASA's globally available, freely downloadable VESsel GENeration (VESGEN) Analysis software to numerous examples of 2D vascular trees, networks, and tree-network composites. Upon input of a binary vascular image, automated output includes informative vascular maps and quantification of parameters such as tortuosity, fractal dimension, vessel diameter, area, length, number, and branch point. Previous research has demonstrated that cytokines and therapeutics such as vascular endothelial growth factor, basic fibroblast growth factor (fibroblast growth factor-2), transforming growth factor-beta-1, and steroid triamcinolone acetonide specify unique "fingerprint" or "biomarker" vascular patterns that integrate dominant signaling with physiological response. In vivo experimental examples described here include vascular response to keratinocyte growth factor, a novel vessel tortuosity factor; angiogenic inhibition in humanized tumor xenografts by the anti-angiogenesis drug leronlimab; intestinal vascular inflammation with probiotic protection by Saccharomyces boulardii, and a workflow programming of vascular architecture for 3D bioprinting of regenerative tissues from 2D images. Microvascular remodeling in the human retina is described for astronaut risks in microgravity, vessel tortuosity in diabetic retinopathy, and venous occlusive disease.

A novel platform for distributed and remote real-time monitoring of animal model behavior in a bioterium.

Animal models are an important resource in life sciences research; however, many of the procedures involving vivo models are complex and time consuming. A common problem while conducting experiments is observing the behavior of the models throughout their stay in the bioterium. Ideally, behavioral assessment should be frequent and rigorous, as a way of more accurately characterizing the animal model. However, to date, few suitable automated solutions can be found within the state-of-the-art. In this paper, we propose an autonomous platform for distributed behavioral data acquisition from individual animal habitats in bioteriums, with remote and online access to the data. This approach allows real-time observation of the status of the habitats, and retrieval of the logged data for post-processing. The work focuses on the use case of motion, temperature and water intake monitoring in small rodents, although the platform was designed to be general-purpose and extensible to other types of habitats and sensing configurations.

Evaluation of the electric field in the brain during transcranial direct current stimulation: A sensitivity analysis.

The use of computational modeling studies accounts currently for the best approach to predict the electric field (E-field) distribution in transcranial direct current stimulation. As with any model, the values attributed to the physical properties, namely the electrical conductivity of the tissues, affect the predicted E-field distribution. A wide range of values for the conductivity of most tissues is reported in the literature. In this work, we used the finite element method to compute the E-field induced in a realistic human head model for two electrode montages targeting the left dorso-lateral prefrontal cortex (DLPFC). A systematic analysis of the effect of different isotropic conductivity profiles on the E-field distribution was performed for the standard bipolar 7×5 cm2 electrodes configuration and also for an optimized multielectrode montage. Average values of the E-field's magnitude, normal and tangential components were calculated in the target region in the left DLPFC. Results show that the field decreases with increasing scalp, cerebrospinal fluid (CSF) and grey matter (GM) conductivities, while the opposite is observed for the skull and white matter conductivities. The tissues whose conductivity most affects the E-field in the cortex are the scalp and the CSF, followed by the GM and the skull. Uncertainties in the conductivity of individual tissues may affect electric field values by up to about 80%.