Long-term microglial phase-specific dynamics during single vessel occlusion and recanalization

Vascular occlusion leading to brain dysfunctions is usually considered evoking microglia-induced inflammation response. However, it remains unclear how microglia interact with blood vessels in the development of vascular occlusion-related brain disorders. Here, we illuminate long-term spatiotemporal dynamics of microglia during single vessel occlusion and recanalization. Microglia display remarkable response characteristics in different phases, including acute reaction, rapid diffusion, transition and chronic effect. Fibrinogen-induced microglial cluster promotes major histocompatibility complex II (MHCII) expression. Microglial soma represents a unique filament-shape migration and has slower motility compared to the immediate reaction of processes to occlusion. We capture proliferative microglia redistribute territory. Microglial cluster resolves gradually and microglia recover to resting state both in the morphology and function in the chronic effect phase. Therefore, our study offers a comprehensive analysis of spatiotemporal dynamics of microglia and potential mechanisms to both vessel occlusion and recanalization. Microglial phase-specific response suggests the morphological feature-oriented phased intervention would be an attractive option for vascular occlusion-related diseases treatments.

Microglia processes extend toward the excitotoxicity neuron after cerebral ischemia to decrease excitotoxic injury in a P2Y12 receptor-dependent manner through altered somatic junctions (Cserep et al., 2020;Szalay et al., 2016). In addition to microglia-neuron interaction (Cangalaya, Stoyanov, Fischer, & Dityatev, 2020;Lim & Ruthazer, 2021;, the correlation between microglia and blood vessels has drawn increasing attention in the pathological progression of occluded vascular dysfunctions (Dudvarski Stankovic, Teodorczyk, Ploen, Zipp, & Schmidt, 2016;Jolivel et al., 2015;Neumann et al., 2015;Qiu et al., 2021). Blood vessels bring adequate oxygen and glucose delivery, which are required for microglia function and viability. Using the photothrombotic approach, researchers found that the activity of microglia is affected by the blood ow near its cell body, rather than the microenvironment around distal microglial processes (Masuda, Croom, Hida, & Kirov, 2011). Microglia perform phagocytosis leading to vascular disintegration in the middle cerebral artery occlusion (MCAO) treated mouse (Fu, Shen, Xu, Luo, & Tang, 2014;Jolivel et al., 2015). However, the traditional vessel occlusion operations, such as photothrombotic and MCAO model, are limited by the dysfunction resulting from multiple vascular occlusion and inherently activated microglia (induced by in vitro slicing procedure). These factors would intervene the morphological analysis of microglia. The functional performance of microglia is closely associated with changes in its morphology and motility, thus the speci c morphological structure or displacement could indicate microglial functional activities. The function of microglia in extending processes is impaired with P2RY12 receptors inhibition (Mastorakos et al., 2021). Microglia migrate to the contralateral hemisphere through the corpus callosum after cortical microinfarcts in a CX3CR1-dependent manner to affect remote brain regions reorganization (Lubart et al., 2021). Moreover, microglia form clusters following genetic ablation to achieve repopulation (Bruttger et al., 2015). To explore the function of microglia in neurological diseases, it is necessary to investigate the temporally precise microglia morphological dynamics in diverse blood vessels microenvironment in vivo.
Currently, most study of microglia dynamics properties and transformation mechanisms focus on a certain morphological change of microglia during the acute reaction phase. Microglial rapid chemotactic response is regulated by extracellular adenosine triphosphate (ATP) released from damaged tissue and nearby astrocytes after the laser microlesion in the brain parenchyma (Davalos et al., 2005;Mastorakos et al., 2021). Microglia converge on the laser microlesion site, forming a rounded protective barrier to prevent brain damage from further spreading (Hines, Hines, Mulligan, & Macvicar, 2009). However, the microglial complicated spatiotemporal morphological transformation characteristics are not well investigated in the long-term scale. Here, we applied laser ablation technique (Nishimura et al., 2006) to occlude single vessels and performed long-term in vivo imaging with two-photon laser scanning microscope (TPLSM) to investigate the response of microglia during both vessel occlusion and recanalization phase. We describe the microglia dynamics with four different phases: acute reaction, rapid diffusion, transition and chronic effect during the long-term imaging process. These ndings give insights into the spatiotemporal dynamics of microglia during vessel occlusion and recanalization, which might lay the foundation on modulating microglial activities for vascular occlusion-related diseases treatments.

Establishment of single vessel occlusion in CX3CR1-GFP mouse
We applied laser ablation technique to occlude the single vessel to performed long-term in vivo imaging of microglia response. Before making single vessel occlusion model, we did cranial window implantation above the mouse cortex (Fig. 1A). As the primary immune effector cells in the brain, microglia are activated and their morphology changes with functional transformations in response to any kind of brain damage or injury. To eliminate surgery-induced effects on the morphology of microglia, we performed long-term imaging after cranial window implantation to record microglia and blood ow state in uenced by the surgery. After the surgery, we imaged the morphology of microglia on the same FOV for up to a month continuously ( Supplementary Fig. 1A). According to the process tree area and the blood ow velocity results ( Supplementary Fig. 1B, C), about 4-weeks recovery before the single vessel occlusion is necessary for ruling out the in uence factor brought by cranial window implantation. Additionally, increases in imaging quality over time can be observed on the same FOV at day 25, and the morphology of microglia had the appearance of rami ed processes ( Supplementary Fig. 1A).
Subsequently, we made the model of single vessel occlusion. The targeted vessel was imaged with in vivo two-photon microscope (Fig. 1B), which relied on contrast generated by labeling the blood plasma with Texas Red. The vessels diameters varied from 5 μm to 100 μm. We chose the vessel with diameter of ~20 μm and depth of ~80 μm from the pia as the targeted vessel. Insult to the targeted vessel was generated by irradiation of the lumen of the vessel with a laser at the wavelength of 1070 nm (Fig. 1B). This process provided real-time feedback on the progress of vessel diameter and blood ow velocity changing ( Supplementary Fig. 2). When a single vessel is occluded, the clotted site was full of accumulated non uorescent RBCs, which was visualized as a dark lump within the vessel (Supplementary Fig. 2A). It is worth noting that the appropriate laser power should be set to avoid hemorrhage by vessel rupture (Supplementary Fig. 3).

Long-term in vivo imaging of microglia and blood vessel after vessel occlusion
We imaged the dynamics of microglia caused by laser-induced vascular occlusion for more than 70 days.
In this process, microglia experienced morphological transformation from aggregation mass to diffusion individual. According to the dynamic characteristics, we divided the whole pathological process into four phases: acute reaction phase (0-24 h), rapid diffusion phase (day 1-day 5), transition phase (day 5-day 31) and chronic effect phase (>=day 32) ( Fig. 2A).
We employed relative uorescence intensity of occlusion core-centered different areas (X, Y, Z) to quantify microglia response to vessel occlusion from the inner area to the outer area (Fig. 2B). Results demonstrate that the closer to the occlusion core, the higher the uorescence intensity of the microglia (Fig. 2C). Beginning with a general polynomial curve tting of uorescence intensity changes over time, we found uorescence intensity changes can be roughly divided into increasing and decreasing periods. To investigate theoretically possible mechanism of microglial phase-speci c dynamics, we used Scurve (Peleg & Corradini, 2011;P. Xu, 2020) and diffusion-consumption equation (Marinov & Santamaria, 2014;Oyler-Yaniv et al., 2017) to t our data. In the acute reaction phase, uorescence intensity shows an S-curve-like increasing tendency. Subsequently, the diffusion-consumption equation was used to t uorescence intensity data accompanied by recanalization. According to the tting curve, results show that uorescence intensity of area X increased dramatically in the acute reaction phase with the average change rate of uorescence intensity is 634.18 (ΔF/F)/day (Fig. 2D). Previous study demonstrates that the release of nucleotides is one of the important reasons for the aggregation of microglia (Haynes et al., 2006). We speculate that occlusion leads to the release of related cytokines, and these cytokines make microglia quickly gather towards the occlusion core. After the surrounding microglial sensors are occupied, the release of more cytokines cannot increase microglial chemotaxis and the uorescence intensity reaches the maximum at this time. In the rapid diffusion phase, uorescence intensity of occlusion core decreased (Fig. 2D). The average change rate of uorescence intensity of area X, area Y and area Z is 119.45, 34.16 and 2.11 (ΔF/F)/day, respectively. This suggests that microglial diffusion rate is much slower compared with its rapid aggregation. In the transition phase, the average change rate of uorescence intensity of area X, area Y and area Z is 5.24, 1.69 and 0.41 (ΔF/F)/day, respectively. In the chronic effect phase, the average change rate of uorescence intensity of area X, area Y and area Z is 0.41, 0.17 and 0.08 (ΔF/F)/day, respectively. These results indicate that as time increases, the decrease rate of uorescence intensity slows down, that is, the microglial density decreases until it stabilizes.
Considering the diffusion-consumption mechanism (Oyler-Yaniv et al., 2017), we speculate that when microglial uorescence intensity is at a high level and in a rapid decline stage, the spatial spread size of diffusion-effect cytokines is small. On the contrary, diffusion-effect cytokines display a big spatial spread. At the same time, we observed that the blood ow began to recover spontaneously about 1.5 days after occlusion. Unexpectedly, blood ow velocity has been in a uctuating state in the following days, accompanied by vascular malformation ( Supplementary Fig. 4).

Microglia dynamics in the acute reaction phase
Microglia outgrew processes immediately after vessel occlusion, which became obvious 20 minutes later ( Supplementary Fig. 5A). A hollow spherical containment, which was reported as a protective barrier preventing damage from spreading around (Hines et al., 2009), had been formed around the occlusion site 60 minutes after occlusion. This hollow appearance was also consistent with what was shown in the MCAO model, since few microglia present inside the ischemic core (Gelosa et al., 2014). The processes of the nearby microglia reached the clotted site, forming a solid spherical containment within 250 minutes ( Supplementary Fig. 5A). During this phase, we found microglia activation based on the distance to the clotted site, from near to far, which took place sequentially. The ve microglia showed in Figure 3A are named as microglia 1, 2, 3, 4, 5, respectively. Their location was as shown in Supplementary Figure 5A. Microglia 1 was the nearest to the occlusion site, microglia 5 the farthest. We employed T-index to quantitatively analyze the degree of microglia activation (Fig. 3B). Before the occlusion, all the ve microglia had the appearance of normal morphology with rami ed processes. When the blood vessel was blocked, the nearest microglia 1 elongated its occlusion facing process and its non-occlusion facing process retracted at the same time. But the other four microglia retained their rami ed processes. In the next few hours, microglia 2 gone through this transition 100 min post occlusion, 130 min for microglia 3, 250 min for microglia 4, 350 min for microglia 5, respectively (Fig. 3A). T-index signi cantly correlated with time after occlusion ( Supplementary Fig. 5B), which demonstrates the activation degree of microglia increasing over time.
Compared with T-index at 720-780 min, T-index at 24 h increased signi cantly (Fig. 3C, P < 0.0001), which suggests that the process elongation state has ended 24 h after occlusion. At the same time, the core of solid spherical containment got the most microglia aggregation, while the microglia aggregation in the area far away from the core is greatly reduced ( Supplementary Fig. 5C, relative intensity: X = 415.89 ± 68.70, Y = 132.04 ± 21.93, Z = 25.95 ± 2.90).
Although microglial processes responded very quickly, microglial cell bodies motility response was much slower. We found cell bodies migration was performed in two distinct ways ( Fig. 4A-C), including the cell bodies deformation migration and cell bodies non-deformation migration. Cell bodies deformation migration was named lamentous-like movement (Fig. 4A). In this way, the cell body was stretched into laments and then migrated into the occlusion core. Cell bodies non-deformation migration were divided into two categories. The rst category underwent obvious displacement (Fig. 4B), and cell body in another category vanished while adjacent cell bodies kept stationary (Fig. 4C). The cumulative motility was only 2.52% ± 1.51 at 100-120 min after occlusion (Fig. 4D), which suggests the majority of cell bodies keep stationary during this phase. However, the cumulative motility rate increased rapidly reaching 76.71% ± 3.89% at 720-780 min. Cumulative motility rate was 86.87% ± 3.89% at 24 h and suggests that almost all microglia have been translocated. In previous reports, few studies have mentioned the movement of the microglia cell body. Here, our results provide an accurate and concise clari cation about it.

Microglia dynamics in the rapid diffusion phase
After having known the characteristics of the acute response of microglia to vessel occlusion, we repeatedly imaged to investigate what happens to the microglia after cluster formation. At this phase, we can see massed outlines of microglial cell bodies with few short processes around the occlusion core at day 1 (Fig. 5A). Then these cell bodies continued to move out of the core, and the process began to be abundant until the majority of them nally became the ones with normal symmetrical process at day 5.
Due to the removal of the cell bodies from the core, the relative uorescence intensity of the occlusion core decreased from 608.23 ± 220.98 at day 1.5 to 150.42 ± 62.00 at day 5 (Fig. 5B). Unexpectedly, no obvious uctuation was observed in the intensity of the outer area from the occlusion core, which means that the emerged microglia migrated continuously to the remote area to maintain a balance of spatial distribution. The total number of microglia in the FOV also gradually increased, from 34.67 ± 1.86 at day 1 to 55.67 ± 2.73 at day 5 (Fig. 5C). In terms of morphology, we found that the microglia were still activated at day1 (Fig. 5D) with T-index 0.79 ± 0.05, followed by a signi cant increase in the T-index at day 1.1 (Fig. 5E, 0.96 ± 0.05, P < 0.01). No signi cant difference in T-index was observed from day 1.1 to day 5, which indicates the morphology of microglia has been stable.
In addition to cell bodies moving out from the occlusion core, we found that the proliferation of microglia also contributed to the increased microglial number. Our imaging described in detail microglial proliferation procedure (Fig. 5F, top). At the same time, microglia disappeared in their original position and also appeared in the original blank position (Fig. 5F, middle and bottom). Through these various morphological changes discussed above, the microenvironment within the FOV was renewed.
Microglia dynamics in the transition phase and chronic effect phase Next, we continued to study the microglia dynamics in the later phases of vascular occlusion. During the transition phase, although accumulation of perivascular microglia decreased (Fig. 6A), microglia density was still slightly higher in proximity to occlusion core. Therefore, the relative uorescence intensity of occlusion core was signi cantly higher than that of the outer area (Fig. 6B). In terms of microglia number, it decreased signi cantly at day 28-31 (46.00 ± 3.00) compared with that at day 5-6 (53.43 ± 1.93) (Fig.  6C). There was no difference in the morphology of microglia (Fig. 6D). These results show that the pathological effects caused by vascular occlusion still exist in the transition phase.
In the chronic phase, microglial cluster resolved (Fig. 6E). There was no signi cant difference of relative uorescence intensity between inner area and outer area (Fig. 6F). Microglial cell number and morphology T-index within the FOV also showed no obvious uctuations (Fig. 6G, H). Therefore, perivascular microenvironment presented stability in the chronic phase to a certain extent.

Discussion
In this paper, we explore the in vivo spatiotemporal dynamics of microglia during single vessel occlusion and recanalization up to 73 days. We nd that there are four phases of distinct microglia dynamics characteristics, including acute reaction, rapid diffusion, transition and chronic effect. In the acute reaction phase (0-24 h), microglia are rapidly activated manifested by processes elongation towards occluded sites as expected. Furthermore, we identi ed the morphological changes and diverse displacement of cell bodies that occur much later compared to that of processes. In the rapid diffusion phase (day 1-day 5), single microglia move out of the cluster, which leads to decreasing in uorescence intensity of occlusion core and increasing in microglial number. In the transition phase (day 5-day 31), microglia cluster still exist, since uorescence intensity of occlusion core is signi cantly higher than that of distant area. Finally, relative uorescence intensity, cell number and cell morphology of microglia no longer exhibit signi cant uctuations in the chronic phase (>=day 32). Compared with previous research focused on the acute reaction phase, our study well investigated the microglial complicated morphological transformation characteristics in the long-term scale.
It is worth noting that microglia processes are the main participants moving toward to injury site in the acute reaction phase. By tracking the same microglia, we demonstrate that the motility of microglial cell bodies did not start to increase positively until 120 min after the occlusion. Since imaging sessions also has a certain time interval, we found that a small part of the cell bodies, either close to the occlusion core or becoming lamentous ones, could migrate into the occlusion core. Rapid increasing in cumulative mobility is primary contributed by the disappearance of the cell body, so it is ambiguous that whether the cell bodies have migrated to the occlusion core. Strikingly, in the rapid diffusion phase, we found plenty of microglia with clear round shape cell body move out from the cluster. We speculate that microglial proliferation occurs during the phase of interaction between microglia cluster and occluded vessel. In a previous genetic cell ablation study, many microglial micro-clusters are found at around day 7, and mostly resolve by day 14 (Bruttger et al., 2015). These formed clusters prove to be highly proliferative, and single cells migrate away from the cluster once steady state is achieved. IL-1R on microglia participates in this cluster-style proliferation process. This research strongly supports our speculation. Besides, consistent with the previous observation, the cluster resolved to redistribute single microglia territory to regulate brain parenchyma microenvironment. Furthermore, combining pharmacologically manipulating these redistributed proliferation cells, such as cell depletion, with more advanced optical methods (Fan et al., 2020), it is expected to illuminate their role in the subsequent long-term pathological development.
It has been reported in acute experimental research that ATP mediates a rapid microglial chemotaxis requires P2Y receptor through either its associated potassium channels activation or extracellular nucleotides (Haynes et al., 2006;Wu, Vadakkan, & Zhuo, 2007). However, the chemotaxis mechanism of microglia is not the same in different models of neurological diseases, and the detrimental or protective role of microglia remains highly controversial in neurological diseases (Cherry, Olschowka, & O'Banion, 2014;Fu et al., 2014;Gelosa et al., 2014;Prinz & Priller, 2014). In autoimmune encephalomyelitis mice, it is blood protein brinogen that induces rapid microglial responses toward the vasculature leading to axonal damage (Davalos et al., 2012;Merlini et al., 2019). Whereas, under the pathological blood brain barrier (BBB) breakdown condition, perivascular microglial processes play a protective role in the maintenance of BBB integrity following cerebrovascular damage (Lou et al., 2016). Additionally, it is particularly important that microglia respond to ischemic injury dynamically. The microglia experience an early neuroprotective M2 phenotype, followed by a transition to a proin ammatory M1 phenotype (Hu et al., 2015;Hu et al., 2012), which suggests corresponding treatments for different pathological phases should be considered. In particular, the changes in microglial morphology are closely related to microglial functional transformations (Fumagalli, Ortolano, & De Simoni, 2014). Therefore, our nding of speci c morphological dynamics involved in different phases, suggests using different methods (including pharmaceutical and optogenetics) to modulate microglial activities at different pathological phases will strongly support us to further research on functions and mechanisms mediated by microglial morphology.

Transgenic mice
Heterozygous CX3CR1 GFP/+ mice were used for all experiments. In these mice, microglia are labeled with an enhanced green uorescent protein (EGFP), which provides high contrast in microglia soma and processes imaging. The animals were housed in a temperature-controlled and humidity-controlled room with a 12h/12h light/dark cycle. Mice were allowed free access to puri ed water. The appropriate guidelines for the care and use of laboratory animals were approved by the Committee for Animal Experiments of Zhejiang University. Implantation of chronic cranial window Transgenic CX3CR1 GFP/+ mice (8 to 10 weeks old) were anesthetized with iso urane (1.5%-2.5%) and placed in a stereotactic frame with a heating pad (36-37.5 ℃). Depth of anesthesia was assessed by monitoring pinch withdrawal and respiration rate. Eyes were protected with ointment.
The scalp was incised with scissors. Lidocaine (2%) was administrated locally. Then we carefully removed the muscle and connective tissue above skull with a disposable blade or needle. A small craniotomy (approximately 3 mm × 3 mm) was performed using a high-speed drill with a small-tip steel burr (0.5 mm in diameter), centered at 1.7 mm lateral to the midline and 2 mm posterior to bregma. A double-layered coverslip consisted of a small coverslip (3 mm in diameter) attached to a large one (6 mm in diameter), which was embedded and sealed with dental cement. The small layer tted snugly into the craniotomy, and the large one was attached to the polished skull.
The last step used dental cement to x the head plate on the skull. The mice were placed on a heating pad until they were fully awake. Antibiotics injections were administered after surgery for at least one week. Mice were housed for about 4-weeks recovery from the surgery.
In vivo long-term imaging with a two-photon microscope EGFP-labeled microglia were imaged by a two-photon microscope through a small craniotomy as described above. By raster scanning a femtosecond-pulsed laser beam (Chameleon Ultra II, Coherent) via standard galvanometer raster scanning with a moving in vivo microscope (Bruker Corporation), twophoton imaging was performed. A 16×/0.8-NA water-immersion objective (Nikon) was used in all the experiments. The Ti-sapphire laser was set at the excitation wavelength of 920 nm for both EGFPexpressing microglia and Texas red-labeling blood vessels imaging. A stack of image planes (1064 × 1064 pixels) with a step size of 2 μm was acquired using the water-immersion objective at a zoom of 2.0.
The maximum imaging depth was ~350 μm from the pial surface. Images were acquired with low laser power (< 50 mW at the sample).
To visualize the vasculature and the motion of red blood cells (RBCs) with TPLSM, we injected 7 mg/kg Texas Red dextran (70000 MW, neutral; Thermo) in 0.9% NaCl intravenously. Line scans were used along single vessels with a maximum scan rate of 5 kHz to quantify RBCs velocity. RBCs movement resulted in dark diagonal streaks in the image with a slope that was inversely proportional to the RBCs velocity.

Vascular occlusion with two-photon laser
The excitation source for the photostimulation path was a femtosecond-pulsed laser xed at 1070 nm (total output, 2 watts; pulse width, 55 fs; Coherent). We focused a two-photon laser beam (~15 μm in diameter) on the vessel through the cranial window to create a highly localized injury, and the laser power was set at 80-200 mW. The photostimulation beam was paused at the anticipated position of the vessel for approximately 1-30 s to create a small injury site, which was indicated by a bright uorescent circle around the focal point of the beam. We assessed blood ow and vascular appearance from the real-time TPLSM images to adjust the laser power, and pulse duration until the nal establishment of vascular occlusion.

Data analysis
Images were processed by ImageJ software. All z-stacks of images were projected along the z-axis to produce two-dimensional maximum intensity projection images within the imaged volumes. Function as a morphological parameter, the microglial territory areas were quanti ed by circumscribing the outline of the ends of microglia processes with a smooth polygon tool in ImageJ.
To account for signal intensity differences that arose from different long-term imaging experiments, microglia uorescence image was separated from the two-channel images and then signal intensity measurements were conducted. We measured microglia uorescence intensity changes through four concentric circles from the inner area to the outer area (X, Y, Z), and the fourth outermost circle was regarded as baseline uorescence value F 0 . We measured the mean gray value in each circle as F(t). The relative uorescence intensity of all the circular area was therefore given by ΔF/F = (F(t) -F 0 (t))/ F 0 (t) × 100.
The blood vessels were loaded with uorescent dyes that imaging the outline of perfused vessels. RBCs were displayed as dark particles in the bright background. RBCs velocity were measured with MATLAB 2016a (MathWorks, USA). Vessel diameter and morphology analysis were measured manually with ImageJ.
To evaluate the changes in microglia morphology, we quantitatively analyzed the transitional stage morphology index (T-index) (Eles et al., 2017). The T-index was calculated based on the length of the longest microglia process facing the injury blood vessel (n) and the length of the longest microglia process facing away from the injured blood vessel (f). The morphology index was therefore given by Tindex = (f -n)/(f + n) + 1. Lastly, Imaris software was applied to assess microglia morphology threedimensional reconstruction.
For cell bodies cumulative motility analysis, we analyzed microglia in the eld of view (FOV) within a volume of 410.55 μm × 410.55 μm × 20 μm. Individual microglia was identi ed and marked with numbers before vessel occlusion. If the cell bodies maintain their position by comparing the surrounding landmark objects (such as blood vessels), they are considered to be static, or if they are not present or exist in a position greater than 10 μm based on the previous image, they are considered to be migrating. Cumulative motility was determined as the number of migratory cells divided by the total number of cells before occlusion × 100%.
The S-curve equation is: where F 1 (t) ( uorescence intensity) is the dependent variable for the S-curve, t is the time, B and γ are model parameters, while A is the carrying density of microglia in this study.
Immune response-induced cytokine diffusion and consumption is governed by a diffusion-consumption mechanism (Oyler-Yaniv et al., 2017). Fluorescence intensity has a power function relationship with time. We thus modi ed the equation as follows: where F 2 (t) ( uorescence intensity) is the dependent variable, t is the time, K, Δt and C are model parameters.
The parameter values of the two equations of X, Y, Z (from the inner area to the outer area based on occlusion core) are shown in Table 1. The tting curves were smoothly using algorithm processing. The data in this paper is presented as mean ± SEM. We used Prism (GraphPad) and Excel (Microsoft) to perform statistical analysis. Statistical signi cance was calculated using one-way analysis of variance (ANOVA) followed by Tukey's multi-group comparisons or Fisher's LSD multiple comparisons. Groups were identi ed statistically different at P < 0.05. When the P-value was greater than 0.05, it is considered as non-signi cant (ns).

Figure 4
Microglial cumulative motility in the acute reaction phase (A) Microglial cell body changes from round shape to lamentous-like shape and follows the lamentary path to get into occlusion core. Yellow  Microglia dynamics in the rapid diffusion phase (A) Repetitive in vivo imaging in the same FOV after occlusion shows a resolving microglia cluster over time. White arrows indicate microglia of round shape with few processes. Yellow arrows indicate microglia with asymmetric processes. Purple arrows indicate microglia with well-proportioned rami ed process. Scale bar, 40 μm. (B) Persistent relative intensity variance at different time points from the inner to the outer area as shown in Figure 2B (n = 3 mice). Data are plotted as mean ± SEM. (C) The number variance of microglia from day 1 to day 5 after occlusion (n = 3 mice). Data are plotted as mean ± SEM. (D) Images showing difference in the number and morphology of microglia at day 1 and day 5 after occlusion. Compared with that at day 1 (yellow arrows), the symmetry of microglia process is signi cantly improved at day 5 (purple arrows). Scale bar, 20 μm. (E) Quanti cation of T-index at different time points (n = 3 mice, ** P < 0.01, ****P < 0.0001 versus T-index on day 1, one-way ANOVA followed by Tukey's multiple comparison). Error bars, mean and SEM. (F) Images showing proliferative microglia, disappeared microglia and appearance microglia during repeated imaging. Scale bar, 20 μm.