Brain phagocytosis and neuroinflammation.

Phagocytes in the central nervous system (CNS), including astrocytes, microglia, and macrophages, shape development and homeostasis by pruning synapses and removing apoptotic debris.

Phagocytosis is mediated by various ligand–receptor dyads and signaling pathways, enabling CNS phagocytes to respond to neuroimmune shifts across the lifespan and during pathology.

Phagocytosis pathways regulate recovery in various models of CNS pathology, including multiple sclerosis, CNS injury, ischemic stroke, and age-associated neurodegeneration.

Phagocytosis pathways are intimately integrated with the inflammatory cell state and remove viable cells in pathology-adjacent tissue, highlighting the complexity of targeting these systems.

To maximize benefit and minimize off target damage, new phagocytic-based approaches should optimize drug delivery timing and location, tailored to each CNS pathology. sciencenewshighlights ScienceMission https://sciencemission.com/resolution-of-inflammation

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New in eNeuro from Boebinger et al: Compared to young adults, older people with and without Parkinson’s disease have larger brain responses and muscle signals that hinder their balance recovery ability.

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We lack a mechanistic understanding of how cortical contributions to balance control change in aging and Parkinson’s disease (PD). Balance is governed by brainstem circuits, with higher-order centers like the cortex or basal ganglia becoming engaged as challenge increases or balance health declines. We previously showed that parallel sensorimotor feedback loops engaging brainstem and cortical circuitry contribute to muscle activity for balance control in young adults (YAs). Here, we analyze data from male and female older adults (OAs) with and without PD, decomposing perturbation-evoked tibialis anterior and medial gastrocnemius muscle activity into hierarchical components based on latencies of feedback control loops. We found that balance-correcting muscle activity followed a stereotypical waveform of long-latency responses (LLRs): LLR1 began ∼120ms and LLR2 occurred ∼210ms, respectively, consistent with subcortical and cortical feedback latencies. Both LLRs increased with balance challenge and could be explained by center of mass kinematics. Perturbation-evoked antagonist muscle activity consisted of destabilizing and stabilizing components categorized based on whether they resist the kinematic errors that drive their activation. The destabilizing component occurred at ∼180ms and was negatively correlated with clinical measures of balance ability in the OA but not PD group. Exploratory comparisons showed OA and PD groups had larger LLR2s at lower challenge levels than YAs, consistent with greater cortical engagement during balance with aging. These findings demonstrate that a neuromechanical model can decompose perturbation-evoked muscle activity into hierarchical components related to clinical balance ability and identify mechanistic changes in the neural control of balance without direct brain measurements.

Significance Statement We show that reactive balance recovery in older adults with and without Parkinson’s disease can be decomposed into distinct components that reflect hierarchical brainstem, cortical, and basal ganglia feedback loops. Using a neuromechanical model of delayed task-level feedback control, we link these components to perturbation difficulty and clinical balance ability in older adults. This framework connects specific features of agonist and antagonist muscle activity to underlying neural control processes without requiring direct brain recordings. Our findings provide a mechanistic basis for age-and disease-related changes in balance control that can inform individualized assessment and future rehabilitation strategies.