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Myelination is an important process in the central nervous system (CNS). Oligodendrocytes (OLs) extend multiple layers to densely sheath on axons, composing the myelin to achieve efficient electrical signal conduction. The myelination during developmental stage maintains a balanced state. However, numerous CNS diseases including neurodegenerative and cerebrovascular diseases cause demyelination and disrupt the homeostasis, resulting in inflammation and white matter deficits. Effective clearance of myelin debris is needed in the region of demyelination, which is a key step for remyelination and tissue regeneration. Microglia and astrocytes are the major resident phagocytic cells in the brain, which may play different or collaborative roles in myelination. Microglia and astrocytes participate in developmental myelination through engulfing excessive unneeded myelin. They are also involved in the clearance of degenerated myelin debris for accelerating remyelination, or engulfing healthy myelin sheath for inhibiting remyelination. This review focuses on the roles of microglia and astrocytes in phagocytosing myelin in the developmental brain and diseased brain. In addition, the interaction between microglia and astrocytes to mediate myelin engulfment is also summarized.

Eye metrics are effective indicators of focused visual attention and perceived workload that have been used to differentiate surgical expertise and task difficulties. However, the change in eye metrics throughout surgical training in a cohort of trainees is under-investigated. This study collected eye-tracking data from 13 medical students practicing the peg transfer task until reaching the passing criteria of the Fundamentals of Laparoscopic Surgery. Six eye metrics measuring focused visual attention and workload were computed and then used in multiple linear regression analysis to predict trial completion time. All predictors were significant in the regression model, collectively explaining 61.7% of the variance in log-transformed completion time. Fixation rates and gaze entropy were the most important metrics at revealing skill acquisition as medical students self-train on the peg-transfer task. The results on these eye metrics demonstrate potential in assessing surgeons-in-training and providing feedback to ensure surgical competency.

Fighters have increasingly demanding performance on both aerodynamic and stealth. To adapt the design requirement of various irregular-shaped supersonic inlets integrated with flat fuselages, a design method for non-axisymmetric generalized internal conical (NAGIC) flowfield is discussed and then developed. By osculating axisymmetric flow concept and method of characteristics, the developed supersonic NAGIC flowfield can be inversely designed with arbitrary capture curves, controllable incident/terminal shock wave geometries, and post terminal shock wave pressure. Employing the streamline tracing technique, a set of external-compression inward-turning inlets with triangle-like flat capture shapes for supersonic stealth fighters are obtained to verify the design method. The study find that the internal contraction ratio and flow distortion of the inlet are reduced significantly by replacing the weak reflected shock wave in the original hypersonic NAGIC flowfield with a strong one. Thus, the compatibility between inlet and engine is improved in a relatively wide range. In addition, the irregular-shaped curved-compression inlet has high mass ratio and total pressure recovery ratio with negligible cross flow and uniform flow at throat. The performance of inlets with complex configurations can be further improved by matching the entrance geometries of basic flowfields and inlets.

Context dependent gaze metrics, derived from eye movements explicitly associated with how a task is being performed, are particularly useful for formative assessment that includes feedback on specific behavioral adjustments for skill acquisitions. In laparoscopic surgery, context dependent gaze metrics are under investigated and commonly derived by either qualitatively inspecting the videos frame by frame or mapping the fixations onto a static surgical task field. This study collected eye-tracking and video data from 13 trainees practicing the peg transfer task. Machine learning algorithms in computer vision were employed to derive metrics of tool speed, fixation rate on (moving or stationary) target objects, and fixation rate on tool-object combination. Preliminary results from a clustering analysis on the measurements from 499 practice trials indicated that the metrics were able to differentiate three skill levels amongst the trainees, suggesting high sensitivity and potential of context dependent gaze metrics for surgical assessment.