Lab-on-a-Chip Platforms as Tools for Drug Screening in Neuropathologies Associated with Blood-Brain Barrier Alterations.

Lab-on-a-chip (LOC) and organ-on-a-chip (OOC) devices are highly versatile platforms that enable miniaturization and advanced controlled laboratory functions (i.e., microfluidics, advanced optical or electrical recordings, high-throughput screening). The manufacturing advancements of LOCs/OOCs for biomedical applications and their current limitations are briefly discussed. Multiple studies have exploited the advantages of mimicking organs or tissues on a chip. Among these, we focused our attention on the brain-on-a-chip, blood-brain barrier (BBB)-on-a-chip, and neurovascular unit (NVU)-on-a-chip applications. Mainly, we review the latest developments of brain-on-a-chip, BBB-on-a-chip, and NVU-on-a-chip devices and their use as testing platforms for high-throughput pharmacological screening. In particular, we analyze the most important contributions of these studies in the field of neurodegenerative diseases and their relevance in translational personalized medicine.

Ca2+ homeostasis in brain microvascular endothelial cells.

Blood brain barrier (BBB) is formed by the brain microvascular endothelial cells (BMVECs) lining the wall of brain capillaries. Its integrity is regulated by multiple mechanisms, including up/downregulation of tight junction proteins or adhesion molecules, altered Ca2+ homeostasis, remodeling of cytoskeleton, that are confined at the level of BMVECs. Beside the contribution of BMVECs to BBB permeability changes, other cells, such as pericytes, astrocytes, microglia, leukocytes or neurons, etc. are also exerting direct or indirect modulatory effects on BBB. Alterations in BBB integrity play a key role in multiple brain pathologies, including neurological (e.g. epilepsy) and neurodegenerative disorders (e.g. Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis etc.). In this review, the principal Ca2+ signaling pathways in brain microvascular endothelial cells are discussed and their contribution to BBB integrity is emphasized. Improving the knowledge of Ca2+ homeostasis alterations in BMVECa is fundamental to identify new possible drug targets that diminish/prevent BBB permeabilization in neurological and neurodegenerative disorders.

Altered Organelle Calcium Transport in Ovarian Physiology and Cancer.

Calcium levels have a huge impact on the physiology of the female reproductive system, in particular, of the ovaries. Cytosolic calcium levels are influenced by regulatory proteins (i.e., ion channels and pumps) localized in the plasmalemma and/or in the endomembranes of membrane-bound organelles. Imbalances between plasma membrane and organelle-based mechanisms for calcium regulation in different ovarian cell subtypes are contributing to ovarian pathologies, including ovarian cancer. In this review, we focused our attention on altered calcium transport and its role as a contributor to tumor progression in ovarian cancer. The most important proteins described as contributing to ovarian cancer progression are inositol trisphosphate receptors, ryanodine receptors, transient receptor potential channels, calcium ATPases, hormone receptors, G-protein-coupled receptors, and/or mitochondrial calcium uniporters. The involvement of mitochondrial and/or endoplasmic reticulum calcium imbalance in the development of resistance to chemotherapeutic drugs in ovarian cancer is also discussed, since Ca2+ channels and/or pumps are nowadays regarded as potential therapeutic targets and are even correlated with prognosis.

Role of microRNAs as Clinical Cancer Biomarkers for Ovarian Cancer: A Short Overview.

Ovarian cancer has the highest mortality rate among gynecological cancers. Early clinical signs are missing and there is an urgent need to establish early diagnosis biomarkers. MicroRNAs are promising biomarkers in this respect. In this paper, we review the most recent advances regarding the alterations of microRNAs in ovarian cancer. We have briefly described the contribution of miRNAs in the mechanisms of ovarian cancer invasion, metastasis, and chemotherapy sensitivity. We have also summarized the alterations underwent by microRNAs in solid ovarian tumors, in animal models for ovarian cancer, and in various ovarian cancer cell lines as compared to previous reviews that were only focused the circulating microRNAs as biomarkers. In this context, we consider that the biomarker screening should not be limited to circulating microRNAs per se, but rather to the simultaneous detection of the same microRNA alteration in solid tumors, in order to understand the differences between the detection of nucleic acids in early vs. late stages of cancer. Moreover, in vitro and in vivo models should also validate these microRNAs, which could be very helpful as preclinical testing platforms for pharmacological and/or molecular genetic approaches targeting microRNAs. The enormous quantity of data produced by preclinical and clinical studies regarding the role of microRNAs that act synergistically in tumorigenesis mechanisms that are associated with ovarian cancer subtypes, should be gathered, integrated, and compared by adequate methods, including molecular clustering. In this respect, molecular clustering analysis should contribute to the discovery of best biomarkers-based microRNAs assays that will enable rapid, efficient, and cost-effective detection of ovarian cancer in early stages. In conclusion, identifying the appropriate microRNAs as clinical biomarkers in ovarian cancer might improve the life quality of patients.

Accuracy vs. computational time: translating aortic simulations to the clinic.

State of the art simulations of aortic haemodynamics feature full fluid-structure interaction (FSI) and coupled 0D boundary conditions. Such analyses require not only significant computational resource but also weeks to months of run time, which compromises the effectiveness of their translation to a clinical workflow. This article employs three computational fluid methodologies, of varying levels of complexity with coupled 0D boundary conditions, to simulate the haemodynamics within a patient-specific aorta. The most comprehensive model is a full FSI simulation. The simplest is a rigid walled incompressible fluid simulation while an alternative middle-ground approach employs a compressible fluid, tuned to elicit a response analogous to the compliance of the aortic wall. The results demonstrate that, in the context of certain clinical questions, the simpler analysis methods may capture the important characteristics of the flow field.

euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling.

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

The effects of aortic coarctation on cerebral hemodynamics and its importance in the etiopathogenesis of intracranial aneurysms.

OBJECTIVES: Hemodynamic changes in the cerebral circulation in presence of coarctation of aorta (CoA) and their significance in the increased intracranial aneurysms (IAs) formation in these patients remain unclear. In the present study, we measured the flow-rate waveforms in the cerebral arteries of a patient with CoA, followed by an analysis of different hemodynamic indices in a coexisting IA. MATERIALS AND METHODS: Phase-contrast Magnetic Resonance (pc-MR) volumetric flow-rate (VFR) measurements were performed in cerebral arteries of a 51 years old woman with coexisting CoA, and five healthy volunteers. Numerical predictions of a number of relevant hemodynamic indices were performed in an IA located in sub-clinoid part of left internal carotid artery (ICA) of the patient. Computations were performed using Ansys(®)-CFX(™) solver using the VFR values measured in the patient as boundary conditions (BCs). A second analysis was performed using the average VFR values measured in healthy volunteers. The VFR waveforms measured in the patient and healthy volunteers were compared followed by a comparison of the hemodynamic indices obtained using both approaches. The results are discussed in the background of relevant literature. RESULTS: Mean flow-rates were increased by 27.1% to 54.9% (2.66-5.44 ml/sec) in the cerebral circulation of patients with CoA as compared to healthy volunteers (1.2-3.95 ml/sec). Velocities were increased inside the IA by 35-45%. An exponential rise of 650% was observed in the area affected by high wall shear stress (WSS>15Pa) when flow-rates specific to CoA were used as compared to population average flow-rates. Absolute values of space and time averaged WSS were increased by 65%. Whereas values of maximum pressure on the IA wall were increased by 15% the area of elevated pressure was actually decreased by 50%, reflecting a more focalized jet impingement within the IA of the CoA patient. CONCLUSIONS: IAs can develop in patients with CoA several years after the surgical repair. Cerebral flow-rates in CoA patients are significantly higher as compared to average flow-rates in healthy population. The increased supra-physiological WSS (>15Pa), OSI (>0.2) and focalized pressure may play an important role in the etiopathogenesis of IAs in patients with CoA.