Demyelination in multiple sclerosis (MS) cells is the site of several energy metabolic abnormalities driven by dysregulation between the opposed interplay of peroxisome proliferator-activated receptor γ (PPARγ) and WNT/β-catenin pathways. We focus our review on the opposing interactions observed in demyelinating processes in MS between the canonical WNT/β-catenin pathway and PPARγ and their reprogramming energy metabolism implications. Demyelination in MS is associated with chronic inflammation, which is itself associated with the release of cytokines by CD4⁺ Th17 cells, and downregulation of PPARγ expression leading to the upregulation of the WNT/β-catenin pathway. Upregulation of WNT/β-catenin signaling induces activation of glycolytic enzymes that modify their energy metabolic behavior. Then, in MS cells, a large portion of cytosolic pyruvate is converted into lactate. This phenomenon is called the Warburg effect, despite the availability of oxygen. The Warburg effect is the shift of an energy transfer production from mitochondrial oxidative phosphorylation to aerobic glycolysis. Lactate production is correlated with increased WNT/β-catenin signaling and demyelinating processes by inducing dysfunction of CD4⁺ T cells leading to axonal and neuronal damage. In MS, downregulation of PPARγ decreases insulin sensitivity and increases neuroinflammation. PPARγ agonists inhibit Th17 differentiation in CD4⁺ T cells and then diminish release of cytokines. In MS, abnormalities in the regulation of circadian rhythms stimulate the WNT pathway to initiate the demyelination process. Moreover, PPARγ contributes to the regulation of some key circadian genes. Thus, PPARγ agonists interfere with reprogramming energy metabolism by directly inhibiting the WNT/β-catenin pathway and circadian rhythms and could appear as promising treatments in MS due to these interactions.

Parkinson’s disease (PD) is one of the main neurodegenerative disease characterized by a progressive degeneration of neurons constituted by dopamine in the substantia nigra pars compacta. The etiologies of PD remain unclear. Aging is the main risk factor for PD. Aging could dysregulate molecular pathways controlling cell homeostatic mechanisms. PD cells are the sites of several metabolic abnormalities including neuroinflammation and oxidative stress. Metabolic structures are driven by circadian rhythms. Biologic rhythms are complex systems interacting with the environment and controlling several physiological pathways. Recent findings have shown that the dysregulation of the circadian rhythms is correlated with PD and its metabolic dysregulations. This review is focused on the key role of circadian rhythms and their impact on neuroinflammation and oxidative stress in Parkinson’s disease.

Age-related macular degeneration (AMD) is considered as the main worldwide cause of blindness in elderly adults. Exudative AMD type represents 10 to 15% of macular degeneration cases, but is the main cause of vision loss and blindness. Circadian rhythm changes are associated with aging and could further accelerate it. However, the link between circadian rhythms and exudative AMD is not fully understood. Some evidence suggests that dysregulation of circadian functions could be manifestations of diseases or could be risk factors for the development of disease in elderly adults. Biological rhythms are complex systems interacting with the environment and control several physiological pathways. Recent findings have shown that the dysregulation of circadian rhythms is correlated with exudative AMD. One of the main pathways involved in exudative AMD is the canonical WNT/β-catenin pathway. Circadian clocks have a main role in some tissues by driving the circadian expression of genes involved in physiological and metabolic functions. In exudative AMD, the increase of the canonical WNT/β-catenin pathway is enhanced by the dysregulation of circadian rhythms. Exudative AMD progression is associated with major metabolic reprogramming, initiated by aberrant WNT/β-catenin pathway, of aerobic glycolysis. This review focuses on the interest of circadian rhythm dysregulation in exudative AMD through the aberrant upregulation of the canonical WNT/β-catenin pathway.

The aim of this article is to study the well-posedness and properties of a fast-slow system which is related with brain lactate kinetics. In particular, we prove the existence and uniqueness of nonnegative solutions and obtain linear stability results. We also give numerical simulations with different values of the small parameter $\varepsilon$ and compare them with experimental data.

<!-- *** Custom HTML *** --> Purpose: The automatic segmentation of multiple sclerosis lesions in magnetic resonance imaging has the potential to reduce radiologists’ efforts on a daily time-consuming task and to bring more reproducibility. Almost all new segmentation techniques make use of convolutional neural networks with their own different architecture. Architectural choices are rarely explained. We aimed at presenting the relevance of a U-net-like architecture for our specific task and at building an efficient and simple model. Approach: An experimental study was performed by observing the impact of applying different mutations and deletions to a simple U-net-like architecture. Results: The power of the U-net architecture is explained by the joint benefits of using an encoder–decoder architecture and by linking them with long skip connections. Augmenting the number of convolutional layers and decreasing the number of feature maps allowed us to build an exceptionally light and competitive architecture, the minimally parameterized U-net (MPU-net), with only ∼30,000 parameters. Conclusion: The empirical study of the U-net has led to a better understanding of its architecture. It has guided the building of the MPU-net, a model far less parameterized than others (at least by a factor of seven). This neural network achieves a human-level segmentation of multiple sclerosis lesions on fluid-attenuated inversion recovery images only. It shows that this segmentation task does not necessitate overly complicated models to be achieved. This gives the opportunity to build more explainable models that can help such methods to be adopted in a clinical environment.