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Corrective lower limb osteotomies are innovative and efficient therapeutic procedures for restoring axial alignment and managing unicompartmental knee osteoarthritis. This review presents critical insights into the up-dated clinical knowledge on osteotomies for complex posttraumatic or congenital lower limb deformities with a focus on high tibial osteotomies, including a comprehensive overview of basic principles of osteotomy planning, biomechanical considerations of different implants for osteotomies and insights in specific bone deformity correction techniques. Emphasis is placed on complex cases of lower limb osteotomies associated with ligament and multiaxial instability including pediatric cases, computer-assisted navigation, external fixation for long bone deformity correction and return to sport after such osteotomies. Altogether, these advances in the experimental and clinical knowledge of complex lower limb osteotomies allow generating improved, adapted therapeutic regimens to treat congenital and acquired lower limb deformities.

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Genetically encoded calcium indicators (GECIs) are mainly represented by two- or one-fluorophore-based sensors. One type of two-fluorophore-based sensor, carrying Opsanus troponin C (TnC) as the Ca2+-binding moiety, has two binding sites for calcium ions, providing a linear response to calcium ions. One-fluorophore-based sensors have four Ca2+-binding sites but are better suited for in vivo experiments. Herein, we describe a novel design for a one-fluorophore-based GECI with two Ca2+-binding sites. The engineered sensor, called NTnC, uses TnC as the Ca2+-binding moiety, inserted in the mNeonGreen fluorescent protein. Monomeric NTnC has higher brightness and pH-stability in vitro compared with the standard GECI GCaMP6s. In addition, NTnC shows an inverted fluorescence response to Ca2+. Using NTnC, we have visualized Ca2+ dynamics during spontaneous activity of neuronal cultures as confirmed by control NTnC and its mutant, in which the affinity to Ca2+ is eliminated. Using whole-cell patch clamp, we have demonstrated that NTnC dynamics in neurons are similar to those of GCaMP6s and allow robust detection of single action potentials. Finally, we have used NTnC to visualize Ca2+ neuronal activity in vivo in the V1 cortical area in awake and freely moving mice using two-photon microscopy or an nVista miniaturized microscope.

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One of the greatest challenges in the modern biological and social sciences is to understand the evolution of cooperative behaviour. General outlines of the answer to this puzzle are currently emerging as a result of developments in the theories of kin selection, reciprocity, multilevel selection and cultural group selection. The main conceptual tool used in probing the logical coherence of proposed explanations has been game theory, including both analytical models and agent-based simulations. The game-theoretic approach yields clear-cut results but assumes, as a rule, a simple structure of payoffs and a small set of possible strategies. Here we propose a more stringent test of the theory by developing a computer model with a considerably extended spectrum of possible strategies. In our model, agents are endowed with a limited set of receptors, a set of elementary actions and a neural net in between. Behavioural strategies are not predetermined; instead, the process of evolution constructs and reconstructs them from elementary actions. Two new strategies of cooperative attack and defence emerge in simulations, as well as the well-known dove, hawk and bourgeois strategies. Our results indicate that cooperative strategies can evolve even under such minimalist assumptions, provided that agents are capable of perceiving heritable external markers of other agents.

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This article proposes a method of visualizing and measuring evolution in artificial life simulations. The evolving population of agents is treated as a dynamical system. The proposed method is inspired by the notion of trajectory. The article provides examples of tracking of trajectories of evolutionary systems in the spaces of genotypes, strategies, and some global characteristics. Visualization similar to a bifurcation diagram is used to represent results of a series of simulations.

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