Rule-based spatial modeling molecules teaching

Computing chemical droplet neurons learning? In this paper, we present general methods that can be used to explore the information processing potential of a medium composed of oscillating (self-exciting) droplets. Networks of Belousov–Zhabotinsky (BZ) droplets seem especially interesting as chemical reaction-diffusion computers because their time evolution is qualitatively similar to neural network activity. Moreover, such networks can be self-generated in microfluidic reactors. However, it is hard to track and to understand the function performed by a medium composed of droplets due to its complex dynamics. Corresponding to recurrent neural networks, the flow of excitations in a network of droplets is not limited to a single direction and spreads throughout the whole medium. In this work, we analyze the operation performed by droplet systems by monitoring the information flow.

Diabetes is a major and growing public health challenge which threatens to overwhelm medical services in the future. Type 2 diabetes confers significant morbidity and mortality, most notably with target organ damage to the eyes, kidneys, nerves and heart. The magnitude of cardiovascular risk associated with diabetes is best illustrated by its position as a coronary heart disease risk equivalent. Complications related to neuropathy are also vast, often working in concert with vascular abnormalities and resulting in serious clinical consequences such as foot ulceration. Increased understanding of the natural history of this disorder has generated the potential to intervene and halt pathological progression before overt disease ensues, after which point management becomes increasingly challenging. The concept of prediabetes as a formal diagnosis has begun to be translated from the research setting to clinical practice.

Budding yeast asymmetric cell division relies upon the precise coordination of spindle orientation and cell cycle progression. The spindle position checkpoint (SPOC) is a surveillance mechanism that prevents cells with misoriented spindles from exiting mitosis. The cortical kinase Kin4 acts near the top of this network. How Kin4 kinase activity is regulated and maintained in respect to spindle positional cues remains to be established. Here, we show that the bud neck–associated kinase Elm1 participates in Kin4 activation and SPOC signaling by phosphorylating a conserved residue within the activation loop of Kin4. Blocking Elm1 function abolishes Kin4 kinase activity in vivo and eliminates the SPOC response to spindle misalignment. These findings establish a novel function for Elm1 in the coordination of spindle positioning with cell cycle progression via its control of Kin4. See more details at Global optimization techniques by Bashar Ibrahim.

The orientation of the mitotic spindle with respect to the polarity axis is crucial for the accuracy of asymmetric cell division. In budding yeast, a surveillance mechanism called the spindle position checkpoint (SPOC) prevents exit from mitosis when the mitotic spindle fails to align along the mother-to-daughter polarity axis. SPOC arrest relies upon inhibition of the GTPase Tem1 by the GTPase-activating protein (GAP) complex Bfa1–Bub2. Importantly, reactions signaling mitotic exit take place at yeast centrosomes (named spindle pole bodies, SPBs) and the GAP complex also promotes SPB localization of Tem1. Yet, whether the regulation of Tem1 by Bfa1–Bub2 takes place only at the SPBs remains elusive. Here, we present a quantitative analysis of Bfa1–Bub2 and Tem1 localization at the SPBs.