Compromised Blood-Brain Barrier Junctions Enhance Melanoma Cell Intercalation and Extravasation

Melanoma frequently metastasises to the brain, and a detailed understanding of the molecular and cellular mechanisms underlying melanoma cell extravasation across the blood-brain barrier (BBB) is important for preventing brain metastasis formation. Making use of primary mouse brain microvascular endothelial cells (pMBMECs) as an in vitro BBB model, we imaged the interaction of melanoma cells into pMBMEC monolayers. We observed exclusive junctional intercalation of melanoma cells and confirmed that melanoma-induced pMBMEC barrier disruption can be rescued by protease inhibition. Interleukin (IL)-1β stimulated pMBMECs or PECAM-1-knockout (-ko) pMBMECs were employed to model compromised BBB barrier properties in vitro and to determine increased melanoma cell intercalation compared to pMBMECs with intact junctions. The newly generated brain-homing melanoma cell line YUMM1.1-BrM4 was used to reveal increased in vivo extravasation of melanoma cells across the BBB of barrier-compromised PECAM-1-deficient mice compared to controls. Taken together, our data indicate that preserving BBB integrity is an important measure to limit the formation of melanoma-brain metastasis

Graphical Approach to Model Reduction for Nonlinear Biochemical Networks

Model reduction is a central challenge to the development and analysis of multiscale physiology models. Advances in model reduction are needed not only for computational feasibility but also for obtaining conceptual insights from complex systems. Here, we introduce an intuitive graphical approach to model reduction based on phase plane analysis. Timescale separation is identified by the degree of hysteresis observed in phase-loops, which guides a “concentration-clamp” procedure for estimating explicit algebraic relationships between species equilibrating on fast timescales. The primary advantages of this approach over Jacobian-based timescale decomposition are that: 1) it incorporates nonlinear system dynamics, and 2) it can be easily visualized, even directly from experimental data. We tested this graphical model reduction approach using a 25-variable model of cardiac β1-adrenergic signaling, obtaining 6- and 4-variable reduced models that retain good predictive capabilities even in response to new perturbations. These 6 signaling species appear to be optimal “kinetic biomarkers” of the overall β1-adrenergic pathway. The 6-variable reduced model is well suited for integration into multiscale models of heart function, and more generally, this graphical model reduction approach is readily applicable to a variety of other complex biological systems

From Moscow with love

One of the less researched aspects of postcolonial India’s “progressive” culture is its Soviet connection. Starting in the 1950s and consolidating in the 1960s, the Union of Soviet Socialist Republics invested in building up “committed” networks amongst writers, directors, actors, and other theater- and film-practitioners across India. Thus, an entire generation of cultural professionals was initiated into the anticolonial solidarity of emerging Afro-Asian nations that were seen, and portrayed, by the Soviets as being victims of “Western” imperialism. The aspirational figure of the New Soviet Man was celebrated through the rise of a new form of “transactional sociality” (Westlund 2003). This paper looks at selected cases of cultural diplomacy—through the lens of cultural history—between the USSR and India for two decades after India’s Independence, exploring the possibility of theorizing it from the perspective of an anticolonial cultural solidarity that allowed agency to Indian interlocutors

Introducing evolutionary biologists to the analysis of big data: guidelines to organize extended bioinformatics training courses

Research in evolutionary biology has been progressively influenced by big data such as massive genome and transcriptome sequencing data, scalar measurements of several phenotypes on tens to thousands of individuals, as well as from collecting worldwide environmental data at an increasingly detailed scale. The handling and analysis of such data require computational skills that usually exceed the abilities of most traditionally trained evolutionary biologists. Here we discuss the advantages, challenges and considerations for organizing and running bioinformatics training courses of 2–3 weeks in length to introduce evolutionary biologists to the computational analysis of big data. Extended courses have the advantage of offering trainees the opportunity to learn a more comprehensive set of complementary topics and skills and allowing for more time to practice newly acquired competences. Many organizational aspects are common to any course, as the need to define precise learning objectives and the selection of appropriate and highly motivated instructors and trainees, among others. However, other features assume particular importance in extended bioinformatics training courses. To successfully implement a learning-by-doing philosophy, sufficient and enthusiastic teaching assistants (TAs) are necessary to offer prompt help to trainees. Further, a good balance between theoretical background and practice time needs to be provided and assured that the schedule includes enough flexibility for extra review sessions or further discussions if desired. A final project enables trainees to apply their newly learned skills to real data or case studies of their interest. To promote a friendly atmosphere throughout the course and to build a close-knit community after the course, allow time for some scientific discussions and social activities. In addition, to not exhaust trainees and TAs, some leisure time needs to be organized. Finally, all organization should be done while keeping the budget within fair limits. In order to create a sustainable course that constantly improves and adapts to the trainees’ needs, gathering short- and long-term feedback after the end of the course is important. Based on our experience we have collected a set of recommendations to effectively organize and run extended bioinformatics training courses for evolutionary biologists, which we here want to share with the community. They offer a complementary way for the practical teaching of modern evolutionary biology and reaching out to the biological community.Peer reviewe

Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers

https://deepblue.lib.umich.edu/bitstream/2027.42/138963/1/12987_2017_Article_71.pd

Domain wall network as QCD vacuum and the chromomagnetic trap formation under extreme conditions

The ensemble of Euclidean gluon field configurations represented by the domain wall network is considered. A single domain wall is given by the sine-Gordon kink for the angle between chromomagnetic and chromoelectric components of the gauge field. The domain wall separates the regions with self-dual and anti-self-dual fields. The network of the domain wall defects is introduced as a combination of multiplicative and additive superpositions of kinks. The character of the spectrum and eigenmodes of color-charged fluctuations in the presence of the domain wall network is discussed. The concept of the confinement-deconfinement transition in terms of the ensemble of domain wall networks is outlined. Conditions for the formation of thick domain wall junction during heavy ion collisions are discussed, and the spectrum of color charged quasiparticles inside the trap is evaluated. An important observation is the existence of the critical size $L_c$ of the trap stable against gluon tachyonic modes, which means that deconfinement can occur only in a finite region of space-time in principle. The size $L_c$ is related to the value of gluon condensate $\langle g^2F^2\rangle$.Comment: 20 pages, 10 figure