Abstract
Purpose
Neutrophils contribute to thrombosis. However, there is limited information on the temporal course of neutrophil recruitment in thrombosis, the contribution of neutrophils to thrombus growth, and the characteristics of stroke patients with neutrophil-rich thrombi.
Materials and Methods
After inducing carotid artery thrombosis in Institute of Cancer Research mice using ferric chloride, aged thrombi were produced by ligating the distal portion of the carotid artery in mice for 0.5, 1, 2, 3, 6, or 24 h. For thrombus analysis in stroke patients, we used registry data and thrombi that were obtained during intra-arterial thrombectomy. Immunohistochemistry was performed to determine thrombus composition.
Results
In the thrombi of 70 mice, Ly6G positive cell counts (neutrophils) and histone H3-positive cell counts increased in a time-dependent manner (both p<0.001). Ly6G-positive cell count was strongly correlated with histone H3-positive cell counts (r=0.910, p<0.001), but not with thrombus size (p=0.320). In 75 stroke patients, atrial fibrillation and cardioembolism were more frequent in the higher neutrophil group (32/37, 86.5%) than in the lower neutrophil group (19/38, 50%) (p=0.002). The median erythrocyte fraction was higher [52.0 (interquartile range 39.9–57.8)] in the higher neutrophil group than in the lower neutrophil group [40.3 (interquartile range 23.5–53.2)]. The fraction of neutrophils was positively correlated with that of erythrocytes (R=0.35, p=0.002).
Conclusion
Neutrophils were recruited and increased in arterial thrombosis in a time-dependent manner; however, they were not associated with the growth of formed thrombi. Neutrophil fractions in the thrombi of stroke patients appeared to be associated with atrial fibrillation and erythrocyte fraction.
Keywords: Neutrophil, thrombosis, stroke, neutrophil extracellular traps, intra-arterial thrombectomy
INTRODUCTION
Thrombosis is a complex and dynamic process. A thrombus is composed of blood cells and plasma components, such as platelets, erythrocytes, leukocytes, and fibrin. Leukocytes are often considered bystanders or trapped components during thrombosis. However, recent studies suggest that leukocytes and inflammation contribute to thrombosis.1,2 The formation of intravascular thrombi plays a protective role against bacterial infection by immobilizing bacteria and, thus, restricting their invasion of the tissue.3 Therefore, thrombosis and inflammation are mutually reinforcing processes.4
Neutrophils are the first and most abundant leukocytes recruited to inflammation or injury sites.5 Neutrophils also play a role in ischemic injuries and contribute to venous and arterial thrombosis.6,7 Neutrophil depletion has been shown to lead to reduced thrombus size in deep vein thrombosis of mice.8 Neutrophils promote thrombosis by releasing neutrophil extracellular traps (NETs), cathelicidin, and alpha defensin from their granules.4,9,10 NETs are well-known to play a role in promoting thrombosis by providing a scaffold for thrombi and inducing platelet aggregation, thrombin activation, and fibrin clot formation.10,11,12 Furthermore, neutrophils express tissue factor, which is a key coagulation factor in thrombosis initiation.13 Neutrophil elastase (NE) promotes coagulation via fibrin formation and thrombus growth.14 Previous studies suggest that neutrophils are recruited into a thrombus to contribute to its organization. However, the time course of neutrophil recruitment to the thrombus during the early phase of arterial thrombosis remains unknown. In addition, it is unknown whether infiltrated neutrophils contribute to thrombus growth. Thrombi that are retrieved during intra-arterial mechanical thrombectomy in patients with acute stroke show heterogeneous composition.15 Thrombus composition may somehow demonstrate the mechanism of thrombosis and the characteristics of patients with stroke.16 In addition, the efficacy of thrombectomy and clinical outcomes may differ according to thrombus composition.15,17 Both neutrophils and NETs are frequently and abundantly found in venous, coronary, and cerebral thrombi.18,19,20 Nevertheless, previous studies have mainly focused on the role of NETs in thrombosis.19,21 Although neutrophils are a major source of NETs and predominant leukocytes in thrombi, limited information is available on the characteristics of stroke patients with neutrophil-rich thrombi.21
In this study, we investigated the time course of neutrophil recruitment and infiltration in the early stages of arterial thrombosis using an FeCl3-induced carotid thrombosis model in mice, as well as the relationship between neutrophil count and thrombus size. In addition, we investigated the clinical characteristics of stroke patients with high neutrophil fractions in thrombi.
MATERIALS AND METHODS
Preparation of experimental animals
We used 7 to 8-week-old Institute of Cancer Research mice (male and female) weighing 32–34 g. The mice were kept in a cage with soft bedding and allowed free access to food and water in a temperature-controlled animal facility under a standard 12-hour light and 12-hour dark cycle. All animal procedures were approved by the Institutional Animal Care and Use Committee of Yonsei University College of Medicine (Approval No. 2019-0023) and performed in accordance with the Association for Assessment and Accreditation of Laboratory Animal Care guidelines.
FeCl3-induced common carotid artery thrombosis
Arterial thrombosis was induced in the common carotid artery (CCA) using FeCl3.22,23 Briefly, anesthesia was induced with 5% isoflurane in a mixture of 70% N2O and 30% O2 and maintained with 2% isoflurane. Body temperature was continuously monitored and maintained at 37.0±0.5℃ using a homeothermic blanket control unit and heating pad with a rectal probe (Harvard Apparatus, Holliston, MA, USA) during the operative procedures. Under a surgical microscope, a midline incision was made at the cervical area in the supine position, and the left CCA was exposed and isolated. Blood flow was measured in the midportion of the CCA using an ultrasonic Doppler flow probe (MA0.7PSB; Transonic Instruments, Ithaca, NY, USA) and an iWorx IX-304T data acquisition system (iWorx Systems, Inc., Dover, NH, USA). After measurement of baseline blood flow for 5 min, arterial thrombosis was induced using FeCl3 (F2877; Sigma-Aldrich Inc., St. Louis, MO, USA). A piece of filter paper (F2877; Sigma-Aldrich, 0.5×0.7 mm) was soaked in 2 µL of 50% FeCl3 and placed on the midportion of the CCA for 5 min. The filter paper was then removed, the CCA was washed with normal saline, and blood flow was checked again. Subsequently, the probe was carefully positioned in the upper intact CCA, and blood flow was monitored for 10 min. The success of arterial occlusion with thrombus formation was defined as a decrease in blood flow to zero. The blood flow data were analyzed using iWorx LabScribe software (version 4.01).23 After blood flow recording for 10 min, the CCA was washed and excised.
Production of aged thrombi in mouse
After successful thrombotic occlusion (cessation of blood flow for 10 min) by FeCl3, an aged thrombus was produced by tight ligation of the distal end of the CCA for 0.5, 1, 2, 3, 6, and 24 h. After a predefined period of thrombus maturation, blood flow was recorded for 10 min to check whether the cessation of blood flow was maintained. The CCA was, thereafter, washed and excised.
Measurement of thrombus size in mouse
The excised CCA was fixed in 4% paraformaldehyde and embedded in paraffin. The CCA paraffin-embedded block was sectioned longitudinally into 4-µm slices and stained with hematoxylin and eosin. The thrombus area was measured in the slice representing the largest part of the thrombus under a light microscope (Axio Imager.D2; Zeiss, Oberkochen, Germany) and AxioVision software (AxioVs40 V 4.8.1.0; Zeiss) using Image J software.
Immunohistochemistry of mouse thrombus
The paraffinized block was sectioned into 3-µm slices. Thereafter, the sectioned slices were deparaffinized with xylene, passed through graded ethanol for rehydration, and subjected to heat-induced epitope retrieval using the IHC-Tek epitope retrieval solution and steamer (IHC World, Inc., Woodstock, MD, USA), except for TER-119. After cooling and washing with phosphate-buffered saline (PBS), the sections were immersed in 10 mM glycine in PBS for 10 min at room temperature. The sections were blocked with 1% horse serum and 5% nonfat milk in Tris-buffered saline for 20 min at room temperature and reacted with the primary antibody. The primary antibodies for mouse thrombus were anti-TER119 (BL116202; 1:1600, BioLegend, San Diego, CA, USA) for erythrocytes; CD41 (ab63983; 1:800, Abcam, Cambridge, UK) for platelets; anti-fibrinogen (ab34269; 1:1600; Abcam) for fibrin/fibrinogen and Ly6G (BL127601; 1:400, BioLegend) for neutrophils, and citrullinated histone H3 (ab5103, 1:800; Abcam) for NETs. Primary antibodies were incubated for 2 h at 37℃ (anti-TER119) or overnight at 4℃ (anti-CD41, fibrinogen, Ly6G, and histone H3). The sections were incubated for 30 min at 37℃ with 1:200-diluted biotin-conjugated secondary antibodies (goat anti-rabbit IgG, BA-1000, or goat anti-rat IgG, BA-9401; Vector Laboratories, Burlingame, CA, USA). Endogenous peroxidase activity was blocked using 0.3% hydrogen peroxide. After reaction with horseradish peroxidase-conjugated streptavidin-biotin complex (ABC Elite Kit; Vector Laboratories), the peroxidase signal was developed using NovaRed (NovaRed Kit; Vector Laboratories). The sections were counterstained with hematoxylin, dehydrated, and mounted using Permount mounting solution medium (Fisher Scientific, Fair Lawn, NJ, USA).
Immunofluorescence staining of mouse thrombi
For immunofluorescence staining, sectioned slices were deparaffinized, rehydrated, and subjected to antigen retrieval as described above for immunohistochemistry. Thereafter, the slices were blocked with Blotto and incubated overnight at 4℃ with primary antibodies against Ly6G (BL127601; 1:400; BioLegend) and citrullinated histone H3 (NB100-57135; 1:50, Novus Biologicals, CO, USA). All slices were incubated for 1 h at room temperature with Alexa Fluor 488-labeled goat anti-rat IgG (ab150157;1:200, Abcam) and Alexa Fluor 647-labeled donkey anti-rabbit IgG (ab150075; 1:200, Abcam) and mounted with Vectashield H-100 mounting medium (Vector Laboratories) containing DAPI. Images were acquired using an LSM700 laser scanning confocal microscope (Axio Imager.D2; Zeiss).
Analysis of thrombus composition in mice
Images of stained thrombi were obtained using the Stereo Investigator imaging system (MBF Bioscience, Williston, VT, USA) equipped with a light microscope (Axio Imager.D2; Zeiss). After encircling the contour of the entire thrombus manually at low magnification (50×), the image was captured at a high magnification (400×) using the Virtual Slice module.16 Analysis of the images was performed semi-automatically using the color deconvolution program in Image J (NIH, Bethesda, MD, USA).24 Auto threshold of pixel density was used. The fraction (%) of each component (platelets, erythrocytes, and fibrin) was calculated as the percentage of pixel density for the full thrombus area. Ly6G -positive cells and histone H3-positive cells were manually counted using a light microscope equipped with a motorized stage (MAC 6000 System, MBF Bioscience). All measurements were performed in a blinded manner.
Thrombus analysis in patients with stroke
To determine the characteristics of stroke patients with neutrophil-rich thrombi, we used registry data and thrombi that were obtained during intra-arterial mechanical thrombectomy in patients with large intracerebral artery occlusion at Severance Hospital in Korea. This study was approved by the Institutional Review Board of Yonsei University College of Medicine (approval number:4-2017-0426). Written informed consent was obtained from patients or their next of kin for the use of the thrombus for research. For this study, thrombi from 75 consecutive patients whose thrombi were obtained and analyzed between December 2017 and May 2020 were used. The thrombi were immediately fixed in 4% paraformaldehyde, embedded in paraffin blocks, and stored until use. Immunohistochemistry was performed as described for mouse thrombi. The primary antibodies used for human thrombi were anti-glycophorin A (ab129024, 1:400; Abcam) for erythrocytes; anti-CD42b (ab 134087, 1:100; Abcam) for platelets; anti-fibrinogen (ab34269, 1:200; Abcam) for fibrin/fibrinogen, and NE (ab68672, 1:200; Abcam) for neutrophils. Heat-induced epitope retrieval was performed for glycophorin A. The primary antibodies were incubated overnight at 4℃, and goat anti-rabbit IgG antibody (BA-1000, Vector Laboratories) was used as a secondary antibody for all primary antibodies. Peroxidase signal was developed using a 3,3′-diaminobenzidine solution (D5637; Sigma-Aldrich). After staining, the paraffin-embedded sections were scanned using a digital scanner (Aperio AT2; Leica Biosystems, Wetzlar, Germany).
The images were analyzed using Automated Region-of-interest based Image Analysis for automated composition analysis.25 Auto threshold of pixel density was used. The fractions of NE, glycophorin A, CD42b, and fibrin-positive areas were calculated as the percentage pixel density of the total thrombus area.
Demographic data, medical history, laboratory data, and onset-to-recanalization time were collected. Onset time was defined as the last known normal time. Initial stroke severity was assessed using the National Institutes of Health Stroke Scale. Furthermore, the etiology of stroke was determined using the Trial of ORG 10172 in Acute Stroke Treatment classification.26 Recanalization was assessed using the modified thrombolysis in cerebral infarction (TICI) score on conventional angiography immediately after thrombectomy.27 Functional outcomes were determined at 3 months using the modified Rankin scale (mRS). Favorable outcomes were defined as an mRS score <3.
Statistical analysis
To determine the temporal changes of neutrophil recruitment and NETs formation in arterial thrombi in mice, the Jonckheere-Terpstra test was performed. In post-hoc analysis, Ly6G-positive cell count and histone H3-positive cell count at baseline (10 min after thrombotic occlusion) were compared with their counts at different time points using the Mann–Whitney U test. Pearson’s correlation test was performed to calculate the correlation between the number of Ly6G-positive cells and the fractions of erythrocytes, platelets, fibrin, and histone H3-positive cells in mouse thrombi.
To analyze the clinical characteristics of patients with neutrophil-rich thrombi, patients were categorized into higher neutrophil and lower neutrophil groups based on the median value of the neutrophil fraction. The t-test or Mann–Whitney U test was used for continuous variables, and the chi-square test or Fischer’s exact test was used for categorical variables, as appropriate. The Shapiro–Wilk test was used to assess the normality of the continuous variables. Continuous variables are presented as a mean±standard deviation or median [interquartile range (IQR)], and categorical variables are presented as numbers (percentages). Pearson’s correlation test was performed to calculate the correlation between the fraction of neutrophils and the fractions of erythrocytes, platelets, and fibrin in thrombi. Multivariable logistic regression analysis was performed to determine the factors associated with favorable outcomes at 3 months (mRS<3). Age, sex, and other variables (p<0.05) were included in the multivariate analysis. Statistical analyses were performed using R version 4.0.5 (http://www.R-project.org; R Core Team, Vienna, Austria). Statistical significance was set at p<0.05.
RESULTS
Animals and aged thrombus
Seventy mice (35 male and 35 female) were used for the production and analysis of aged thrombi. Ten mice (5 male and 5 female), at each time point, were used to obtain thrombi at baseline (10 min after thrombotic occlusion), 0.5, 1, 2, 3, 6, and 24 h.
Temporal changes in neutrophil infiltration and NET formation in mouse thrombi
Ly6G-positive cell (neutrophil) count was significantly increased starting from 1 h after thrombus formation in a time-dependent manner to 24 h (p<0.001) (Fig. 1A and 2A). In addition, Histone H3-positive cell (NETs) count increased starting from 0.5 h after thrombus formation in a time-dependent manner (p<0.001) (Fig. 1B and 2B). Ly6G-positive cells and histone H3-positive cells increased markedly 3 h after thrombus formation (Fig. 1A and B).
Fig. 1. Temporal course of Ly6G-positive cells (A), histone H3-positive cells (B), and thrombus size (C) after inducing thrombosis in mice using FeCl3. Numbers of Ly6G-positive cells and histone H3-positive cells increase in a time-dependent manner (both p<0.01) (Jonckheere-Terpstra test). The thrombus size was not increased with thrombus age (p=0.683). *p<0.05 in comparison with 0 h by Mann–Whitney U test.
Fig. 2. Representative immunohistochemistry of Ly6G-postive cells (A) and histone H3-positive cells (B) in arterial thrombi of mice.
Association of neutrophils with NETs, thrombus composition, and thrombus size
Ly6G-positive cell count was strongly correlated with the number of histone H3-positive cells (r=0.910, p<0.001) (Fig. 3A). Furthermore, confocal immunofluorescence images showed that Ly6G-positive cells colocalized with histone H3-positive cells (Fig. 3B). However, no significant correlation was observed between the number of Ly6G-positive cells and the fraction of platelets, fibrin, or erythrocytes (Supplementary Fig. 1, only online). We also determined the association between the number of Ly6G-positive cells and thrombus size. There was no significant time-dependent change in thrombus size (p=0.683) (Fig. 1C). Additionally, no significant correlation was observed between Ly6G-positive cell count and thrombus size (p=0.320).
Fig. 3. Correlation between counts of Ly6G-positive cells and those of histone H3-positive cells in arterial thrombi of mice. There was a strong correlation between counts of neutrophils and those of histone H3-positive cells (Pearson’s correlation test) (A). Representative confocal immunofluorescence images of Ly6G-postive cells and histone H3-postive cells. Ly6G-postive cells and histone H3-postive cells are colocalized (B).
Characteristics of stroke patients with higher neutrophil fraction in thrombi
A total of 75 patients were included in the analysis. The median fraction of neutrophils in thrombi was 28.5% (IQR 14.2–32.2). In comparison of baseline characteristics, atrial fibrillation was more frequent in the higher neutrophil group (32/37, 86.5%) than in the lower neutrophil group (19/38, 50%) (p=0.002) (Table 1). Stroke etiology was also different between the groups because cardioembolism was more frequent in the higher neutrophil group, while large artery atherosclerosis was more frequent in the lower neutrophil group (Table 1).
Table 1. Comparison of Baseline Characteristics according to Neutrophil Composition in Thrombi.
| Lower neutrophil group (n=38) | Higher neutrophil group (n=37) | p value | ||
|---|---|---|---|---|
| Demographic | ||||
| Age, yr | 76.5 [61.0–84.0] | 78.0 [71.0–85.0] | 0.256 | |
| Sex, male | 15 (39.5) | 14 (37.8) | >0.999 | |
| Comorbidities | ||||
| Hypertension | 25 (65.8) | 26 (70.3) | 0.866 | |
| Diabetes mellitus | 9 (23.7) | 11 (29.7) | 0.741 | |
| Dyslipidemia | 13 (34.2) | 9 (24.3) | 0.492 | |
| Coronary artery disease | 6 (15.8) | 7 (18.9) | 0.958 | |
| Atrial fibrillation | 19 (50.0) | 32 (86.5) | 0.002 | |
| Peripheral artery disease | 1 (2.6) | 1 (2.7) | >0.999 | |
| Previous stroke | 6 (15.8) | 9 (24.3) | 0.525 | |
| Active cancer | 6 (15.8) | 1 (2.7) | 0.121 | |
| Current smoker | 5 (13.2) | 2 (5.4) | 0.449 | |
| Laboratory findings | ||||
| Hemoglobin, g/dL | 13.4 [11.8–14.4] | 13.4 [12.2–14.5] | 0.521 | |
| Hematocrit, % | 39.0 [35.0–42.3] | 39.1 [36.4–43.3] | 0.289 | |
| White blood cell, 103/μL | 8.6 [7.0–10.2] | 7.8 [6.6–9.2] | 0.144 | |
| Platelet, 109/L | 200.0 [157.0–249.0] | 199.0 [168.0–243.0] | 0.945 | |
| ESR, mm/h | 17.0 [7.0–36.0] | 15.0 [7.0–36.0] | 0.899 | |
| C-reactive protein, mg/L | 7.8 [2.3–24.4] | 7.5 [3.7–15.7] | 0.763 | |
| Total cholesterol, mg/dL | 145.3±33.5 | 155.2±34.9 | 0.218 | |
| HDL-cholesterol, mg/dL | 41.5 [31.0–52.0] | 46.0 [38.0–53.0] | 0.337 | |
| LDL-cholesterol, mg/dL | 83.7±33.0 | 91.4±27.9 | 0.280 | |
| Triglyceride, mg/dL | 101.5 [75.0–146.0] | 98.0 [57.0–121.0] | 0.439 | |
| D-dimer, ng/mL | 766.0 [361.0–1769.0] | 758.0 [341.0–1973.0] | 0.552 | |
| Fibrinogen, mg/dL | 279.0 [211.0–324.0] | 300.0 [168.0–335.0] | 0.787 | |
| BUN, mg/dL | 17.2 [12.8–21.5] | 19.9 [15.8–23.2] | 0.159 | |
| Creatinine, mg/dL | 0.8 [0.7– 1.1] | 0.8 [0.7–1.0] | 0.763 | |
| Albumin, mg/dL | 4.0 [3.7– 4.3] | 3.9 [3.7–4.1] | 0.489 | |
| Glucose, mg/dL | 128.5 [110.0–167.0] | 136.0 [121.0–150.0] | 0.600 | |
| Stroke classification | 0.035 | |||
| Cardioembolism | 23 (60.5) | 32 (86.5) | ||
| Large artery atherosclerosis | 5 (13.2) | 1 (2.7) | ||
| Undetermined | 10 (26.3) | 4 (10.8) | ||
| Intravenous tPA | 13 (34.2) | 10 (27.0) | 0.672 | |
| Initial NIHSS | 13.0 [10.0–18.0] | 15.0 [10.0–20.0] | 0.115 | |
ESR, erythrocyte sedimentation rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; BUN, blood urea nitrogen; tPA, tissue plasminogen activator; NIHSS, National Institute of Health Stroke Scale.
Data are presented as a mean±standard deviation, median [IQR], or number (%).
In terms of thrombus composition, the fraction of platelets was significantly lower and the fraction of erythrocytes was higher in the higher neutrophil group than the lower neutrophil group (Table 2, Fig. 4). The neutrophil fraction was positively correlated with that of erythrocytes (R=0.350, p=0.002) (Fig. 5).
Table 2. Comparison of Endovascular Thrombectomy Outcomes and Thrombus Composition.
| Lower neutrophil group (n=38) | Higher neutrophil group (n=37) | p value | ||
|---|---|---|---|---|
| Occlusion site | 0.132 | |||
| Basilar | 4 (10.5) | 1 ( 2.7) | ||
| Distal ICA | 4 (10.5) | 8 (21.6) | ||
| Proximal ICA | 9 (23.7) | 14 (37.8) | ||
| MCA | 21 (55.3) | 14 (37.0) | ||
| Successful recanalization | 36 (94.7) | 33 (89.2) | 0.646 | |
| Thrombus composition, % | ||||
| Platelet | 21.6 [11.9–34.0] | 14.6 [ 9.6–21.1] | 0.032 | |
| Fibrinogen | 41.1±10.3 | 42.2±10.1 | 0.632 | |
| Erythrocyte | 40.3 [23.5–53.2] | 52.0 [39.9–57.8] | 0.001 | |
| Onset-to-recanalization time, min | 305.5 [185.0–446.0] | 383.0 [195.0–553.0] | 0.491 | |
ICA, internal carotid artery; MCA, middle cerebral artery.
Data are presented as a mean±standard deviation, median [IQR], or number (%).
Fig. 4. Representative immunohistochemistry of thrombi with lower neutrophils (A) and higher neutrophils (B) that were obtained during intra-arterial thrombectomy in patients with stroke. A portion of a neutrophil-rich area is magnified (box in B). The primary antibodies for immunohistochemistry were anti-neutrophil elastase Ab for neutrophils, anti-glycophorin A Ab for erythrocyte, anti-CD42b Ab for platelet, and anti-fibrinogen/fibrin for fibrin.
Fig. 5. Correlation of the fraction of neutrophils and that of platelets (A), erythrocytes (B), and fibrin (C) in thrombi obtained from patients with stroke. The fraction of neutrophils was positively correlated with that of erythrocytes (B) (Pearson’s correlation test).
Occlusion site, rate of successful recanalization (TICI 2b or 3), and onset-to-recanalization time did not differ between the groups (Table 2). mRS score at 3 months was available for 72 of the 75 patients (96%) enrolled in the study. The median neutrophil fraction was higher in patients with poor outcomes [30.0 (IQR 20.9–33.3)] than in patients with good outcomes [23.6 (IQR 10.9–30.1)] (p=0.023) (Supplementary Table 1, only online). However, this difference was not significant in multivariable logistic regression analysis after adjusting for confounders (Table 3).
Table 3. Univariable and Multivariable Logistic Analysis for Factors Associated with Poor Functional Outcomes at 3 Months after Stroke.
| Univariable | Multivariable | ||||
|---|---|---|---|---|---|
| Odds ratio (95% CI) | p value | Odds ratio (95% CI) | p value | ||
| Demographic | |||||
| Age, yr | 1.07 (1.03–1.12) | 0.002 | 1.06 (1.00–1.12) | 0.038 | |
| Sex, male | 0.65 (0.25–1.70) | 0.383 | 0.59 (1.07–2.07) | 0.410 | |
| Comorbidities | |||||
| Hypertension | 2.54 (0.92–6.99) | 0.072 | |||
| Diabetes mellitus | 3.02 (0.95–9.54) | 0.061 | |||
| Dyslipidemia | 0.67 (0.24–1.84) | 0.435 | |||
| Coronary artery disease | 0.45 (0.13–1.53) | 0.199 | |||
| Atrial fibrillation | 2.87 (1.05–7.88) | 0.041 | 1.50 (0.37–6.04) | 0.569 | |
| Peripheral artery disease | 0.82 (0.05–13.64) | 0.890 | |||
| Previous stroke | 1.87 (0.57–6.14) | 0.304 | |||
| Active cancer | 5.65 (0.64–49.49) | 0.118 | |||
| Current smoker | 0.59 (0.12–2.84) | 0.508 | |||
| Laboratory findings | |||||
| Hemoglobin, g/dL | 0.84 (0.56–1.06) | 0.146 | |||
| Hematocrit, % | 1.00 (0.92–1.07) | 0.904 | |||
| WBC, 103/μL | 1.01 (0.86–1.20) | 0.868 | |||
| Platelet, 109/L | 1.00 (0.99–1.01) | 0.847 | |||
| ESR, mm/h | 1.01 (0.99–1.04) | 0.223 | |||
| CRP, mg/L | 0.99 (0.98–1.01) | 0.338 | |||
| Total cholesterol, mg/dL | 1.01 (0.99–1.02) | 0.358 | |||
| HDL-cholesterol, mg/dL | 1.00 (0.97–1.02) | 0.907 | |||
| LDL-cholesterol, mg/dL | 1.01 (0.99–1.02) | 0.295 | |||
| Triglyceride, mg/dL | 1.00 (1.00–1.00) | 0.701 | |||
| D-dimer, ng/mL | 1.00 (1.00–1.00) | 0.059 | |||
| Fibrinogen, mg/dL | 1.00 (0.99–1.06) | 0.211 | |||
| BUN, mg/dL | 1.07 (1.00–1.14) | 0.063 | |||
| Creatinine, mg/dL | 1.45 (0.32–6.63) | 0.630 | |||
| Albumin, mg/dL | 0.50 (0.15–1.67) | 0.260 | |||
| Glucose, mg/dL | 1.01 (1.00–1.03) | 0.045 | 1.02 (1.00–1.04) | 0.048 | |
| Stroke classification | |||||
| Cardioembolism | 1.52 (0.28–8.28) | 0.626 | |||
| Large artery atherosclerosis | Reference | Reference | |||
| Undetermined | 0.56 (0.08–3.86) | 0.552 | |||
| Intravenous tPA | 0.51 (0.18–1.42) | 0.196 | |||
| Initial NIHSS | 1.15 (1.06–1.26) | 0.001 | 1.12 (1.01–1.24) | 0.025 | |
| Recanalization outcome | |||||
| TICI 2b or 3 | 0.22 (0.02–1.97) | 0.176 | |||
| TICI 3 | 0.25 (0.00–0.72) | 0.011 | 0.20 (0.05–0.79) | 0.021 | |
| Onset-to recanalization time, min | 1.00 (1.00–1.00) | 0.752 | |||
| Thrombus composition, % | |||||
| Platelet | 1.01 (0.97–1.04) | 0.797 | |||
| Fibrinogen | 1.00 (0.95–1.04) | 0.917 | |||
| Erythrocyte | 1.00 (0.97–1.03) | 0.146 | |||
| Neutrophil | 1.05 (1.00–1.09) | 0.032 | 1.03 (0.97–1.10) | 0.267 | |
CI, confidence interval; WBC, white blood cell; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; HDL, high-density lipoprotein; LDL, low-density lipoprotein; BUN, blood urea nitrogen; tPA, tissue plasminogen activator; NIHSS, National Institute of Health Stroke Scale; TICI, thrombolysis in cerebral infarction.
DISCUSSION
Our study showed that neutrophils are recruited to arterial thrombi in a time-dependent manner for 24 h in mice. The number of recruited neutrophils was correlated with the formation of NETs. However, thrombus size was not associated with the number of neutrophils present in the thrombus. In patients with stroke, the fraction of neutrophils in thrombi was higher in patients with atrial fibrillation or cardioembolism and positively correlated with the fraction of erythrocytes.
In this study, the number of neutrophils and histone H3-positive cells in thrombi significantly increased in a time-dependent manner after the induction of arterial thrombosis. Our findings suggest that there may be an increase in the number of neutrophils and NETs during the early stages of arterial thrombosis and play a role in the thrombotic process. We also found that the number of neutrophils was significantly correlated with that of NETs, and neutrophils and NETs were colocalized, which confirms the relationship between neutrophils and NET formation.28 However, thrombus size did not increase over time and was not correlated with the number of neutrophils. Thrombosis is a dynamic process. Upon the initiation of the thrombotic process in pathological conditions, the thrombus grows and matures. In venous thrombosis, neutrophils play a role in the propagation of a thrombus through the release of NETs.8 Furthermore, NETs are predominantly found in organized thrombi in patients with venous thromboembolism.11 However, in arterial thrombosis, NETs are detected in the early stages of coronary thrombosis, but not in an organized thrombus.29 NETs in thrombi are degraded by polarized macrophages.30 The number of neutrophils was highest at day 1 and decreased after the induction of venous thrombosis in mice.31 In a previous study, cyclophosphamide-induced leukopenia attenuated thrombosis in a carotid artery thrombosis model in mice, but not decreased thrombus size.32 These findings suggest that neutrophils play a role in the early stages of arterial thrombosis; however, they appear to have a limited role in the growth of an already formed arterial thrombus.
The observed time-dependent increase in neutrophils in this study suggests that the number of neutrophils in a thrombus may be a marker of an aged thrombus. However, in the thrombi of stroke patients in this study, there was no difference in the time from onset to recanalization in the higher and lower neutrophil groups. The time from onset to thrombus formation may partly represent thrombus age. However, this information does not provide accurate timing of initial thrombus formation because stroke might develop by the embolization of a pre-existing, maturated thrombi in the heart. Besides, symptom onset time noted by the patients or their family may often be inaccurate and unknown, particularly symptoms that develop on awakening from sleep. Our findings, therefore, suggest that neutrophil count may not be an accurate indicator of thrombus age. In this study, neutrophil fraction was correlated with erythrocyte fraction in thrombi from stroke patients. In a deep venous thrombosis mouse model, neutrophils were found in erythrocyte-rich and platelet-rich areas.33 In addition, in coronary thrombi, the number of myeloperoxidase-positive cells (mainly neutrophils) was high in the erythrocyte-rich group.34 Activated neutrophils induce hyperaggregability of erythrocytes by secreting proteolytic enzymes and generating oxygen-free radicals.35 These findings suggest that neutrophils may contribute to the aggregation of erythrocytes during thrombosis.
In this study, there were more patients with atrial fibrillation or cardioembolism in the higher neutrophil group. Considering that atrial fibrillation is the most common cause of cardioembolism, neutrophil dominance in the thrombus of cardioembolic stroke may be ascribed to atrial fibrillation. Inflammation contributes to thrombosis in atrial fibrillation.36 Previous studies have failed to prove the traditional idea that atherothrombotic thrombi are platelet-rich and that cardiac thrombi are erythrocyte-rich on analyses of thrombus histology.15 However, some studies based on chemical staining have shown leukocyte dominancy in cardioembolism.37,38 The findings of our study, which is based on immunohistochemistry, showed neutrophil dominancy in atrial fibrillation and cardioembolism. Almost all subsets of leukocytes, including neutrophils, monocytes, T-lymphocytes, and eosinophils, are detected in thrombi retrieved from stroke patients with cerebral artery occlusion.21 The number of T-cells was significantly higher in thrombi from patients with atherothrombosis.39 Assessment of different subsets of leukocytes in thrombi may provide some hints for determining the etiology of stroke.
Few studies have shown an association of neutrophil-rich thrombi with endovascular and clinical outcomes. In previous studies, an abundance of neutrophils in the thrombus was associated with poor endovascular outcomes, including lower recanalization rate, recanalization time, and a number of mechanical maneuvers needed for recanalization.21,40 However, in this study, there was no difference in endovascular outcomes between the higher and lower neutrophil groups. Neutrophil fractions were greater in patients with poor functional outcomes at 3 months; however, they were not significant in multivariable analysis after adjusting for confounders in this study. In a recent study, although an abundance of leukocytes and NETs in thrombi was associated with poor clinical outcomes in stroke patients, they were insignificant after adjusting for possible confounders.21 While neutrophils may be associated with thrombus stability by releasing NETs and promoting aggregation of erythrocytes, their significance on endovascular and clinical outcomes requires further study with a larger cohort and consideration of possible confounders.
This study has some limitations. We aimed to determine the temporal course of neutrophil recruitment in a thrombus during the early stage of thrombosis. As a result, the temporal course after 24 h is unknown. The sample size of stroke patients might not be large enough to determine the association between neutrophil counts in thrombi and clinical outcomes. While stroke occurs from various etiologies, including cardiac diseases and atherosclerosis, the FeCl3-induced thrombosis model used in this study does not reflect the diversity of thrombosis mechanisms in stroke patients it merely represents thrombosis induced by vascular injury. This may partly be responsible for the discrepancy of some findings between stroke patients and mice in this study. In this regard, the arterial thrombosis model in this experiment may be insufficient to fully translate the findings in stroke patients.
In conclusion, this study showed that neutrophils are recruited and increased in arterial thrombus in a time-dependent manner; however, they are not associated with the growth of formed thrombi. Neutrophils in stroke patients are associated with the etiology of atrial fibrillation and cardioembolism. The association between neutrophil fraction and erythrocyte fraction in thrombi of stroke patients suggests a possible pathophysiological relationship during thrombosis.
ACKNOWLEDGEMENTS
This study was supported by the Basic Science Research Program of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Education (NRF-2021R1A2C2003658 and NRF-2020R1I1A1A01061166).
Footnotes
The authors have no potential conflicts of interest to disclose.
- Conceptualization: Myoung-Jin Cha, Il Kwon, and Ji Hoe Heo.
- Data curation: Myoung-Jin Cha, Jimin Ha, Sungeun Kim, Il Kwon, Young Dae Kim, Hyo Suk Nam, and Ji Hoe Heo.
- Formal analysis: Myoung-Jin Cha, Jimin Ha, Hyungwoo Lee, Hye Sun Lee, Il Kwon, and Ji Hoe Heo.
- Funding acquisition: Ji Hoe Heo and Il Kwon.
- Investigation: Myoung-Jin Cha, Jimin Ha, and Sungeun Kim.
- Methodology: Myoung-Jin Cha, Jimin Ha, Hyungwoo Lee, Sungeun Kim, Il Kwon, and Ji Hoe Heo.
- Project administration: Ji Hoe Heo.
- Resources: all authors.
- Software: all authors.
- Supervision: Ji Hoe Heo.
- Validation: Hye Sun Lee, Il Kwon, and Ji Hoe Heo.
- Visualization: Myoung-Jin Cha, Jimin Ha, Hyungwoo Lee, and Il Kwon.
- Writing—original draft: Myoung-Jin Cha, Jimin Ha.
- Writing—review & editing: Il Kwon, Tae-Jin Song, Hyun-Jung Choi, Hyo Suk Nam, and Ji Hoe Heo.
- Approval of final manuscript: all authors.
SUPPLEMENTARY MATERIALS
Factors Associated with Functional Outcome at 3 Months after Stroke
Correlation of counts of Ly6G-positive cells (neutrophils) and the fractions of platelets (A), erythrocytes (B), and fibrin (C) in arterial thrombi in mice. No significant correlations were observed between Ly6G-positive cell counts and the fractions of platelets, erythrocytes, or fibrin (Pearson correlation test). The primary antibodies for immunohistochemistry were anti-Ly6G Ab for neutrophil, anti-TER119 Ab for erythrocyte, anti-CD41 Ab for platelet, and anti-fibrinogen/fibrin for fibrin.
References
- 1.Thålin C, Hisada Y, Lundström S, Mackman N, Wallén H. Neutrophil extracellular traps: villains and targets in arterial, venous, and cancer-associated thrombosis. Arterioscler Thromb Vasc Biol. 2019;39:1724–1738. doi: 10.1161/ATVBAHA.119.312463. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Park Y, Shim Y, Kwon I, Lee HW, Nam HS, Choi HJ, et al. Effects of interleukin-17A on the early stages of arterial thrombosis in mice. Yonsei Med J. 2022;63:632–639. doi: 10.3349/ymj.2022.63.7.632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Martinod K. Resolving thrombosis: resting and polarized macrophages differentially degrade neutrophil extracellular traps. Arterioscler Thromb Vasc Biol. 2020;40:1961–1963. doi: 10.1161/ATVBAHA.120.315013. [DOI] [PubMed] [Google Scholar]
- 4.Abu-Fanne R, Stepanova V, Litvinov RI, Abdeen S, Bdeir K, Higazi M, et al. Neutrophil α-defensins promote thrombosis in vivo by altering fibrin formation, structure, and stability. Blood. 2019;133:481–493. doi: 10.1182/blood-2018-07-861237. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ghasemzadeh M, Hosseini E. Platelet-leukocyte crosstalk: linking proinflammatory responses to procoagulant state. Thromb Res. 2013;131:191–197. doi: 10.1016/j.thromres.2012.11.028. [DOI] [PubMed] [Google Scholar]
- 6.Maida CD, Norrito RL, Daidone M, Tuttolomondo A, Pinto A. Neuroinflammatory mechanisms in ischemic stroke: focus on cardioembolic stroke, background, and therapeutic approaches. Int J Mol Sci. 2020;21:6454. doi: 10.3390/ijms21186454. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kapoor S, Opneja A, Nayak L. The role of neutrophils in thrombosis. Thromb Res. 2018;170:87–96. doi: 10.1016/j.thromres.2018.08.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.von Brühl ML, Stark K, Steinhart A, Chandraratne S, Konrad I, Lorenz M, et al. Monocytes, neutrophils, and platelets cooperate to initiate and propagate venous thrombosis in mice in vivo. J Exp Med. 2012;209:819–835. doi: 10.1084/jem.20112322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Pircher J, Czermak T, Ehrlich A, Eberle C, Gaitzsch E, Margraf A, et al. Cathelicidins prime platelets to mediate arterial thrombosis and tissue inflammation. Nat Commun. 2018;9:1523. doi: 10.1038/s41467-018-03925-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Fuchs TA, Brill A, Duerschmied D, Schatzberg D, Monestier M, Myers DD, Jr, et al. Extracellular DNA traps promote thrombosis. Proc Natl Acad Sci U S A. 2010;107:15880–15885. doi: 10.1073/pnas.1005743107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Savchenko AS, Martinod K, Seidman MA, Wong SL, Borissoff JI, Piazza G, et al. Neutrophil extracellular traps form predominantly during the organizing stage of human venous thromboembolism development. J Thromb Haemost. 2014;12:860–870. doi: 10.1111/jth.12571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Elaskalani O, Abdol Razak NB, Metharom P. Neutrophil extracellular traps induce aggregation of washed human platelets independently of extracellular DNA and histones. Cell Commun Signal. 2018;16:24. doi: 10.1186/s12964-018-0235-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Darbousset R, Thomas GM, Mezouar S, Frère C, Bonier R, Mackman N, et al. Tissue factor-positive neutrophils bind to injured endothelial wall and initiate thrombus formation. Blood. 2012;120:2133–2143. doi: 10.1182/blood-2012-06-437772. [DOI] [PubMed] [Google Scholar]
- 14.Massberg S, Grahl L, von Bruehl ML, Manukyan D, Pfeiler S, Goosmann C, et al. Reciprocal coupling of coagulation and innate immunity via neutrophil serine proteases. Nat Med. 2010;16:887–896. doi: 10.1038/nm.2184. [DOI] [PubMed] [Google Scholar]
- 15.Heo JH, Nam HS, Kim YD, Choi JK, Kim BM, Kim DJ, et al. Pathophysiologic and therapeutic perspectives based on thrombus histology in stroke. J Stroke. 2020;22:64–75. doi: 10.5853/jos.2019.03440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Park H, Kim J, Ha J, Hwang IG, Song TJ, Yoo J, et al. Histological features of intracranial thrombi in stroke patients with cancer. Ann Neurol. 2019;86:143–149. doi: 10.1002/ana.25495. [DOI] [PubMed] [Google Scholar]
- 17.Jolugbo P, Ariëns RAS. Thrombus composition and efficacy of thrombolysis and thrombectomy in acute ischemic stroke. Stroke. 2021;52:1131–1142. doi: 10.1161/STROKEAHA.120.032810. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Riegger J, Byrne RA, Joner M, Chandraratne S, Gershlick AH, Ten Berg JM, et al. Histopathological evaluation of thrombus in patients presenting with stent thrombosis. A multicenter European study: a report of the prevention of late stent thrombosis by an interdisciplinary global European effort consortium. Eur Heart J. 2016;37:1538–1549. doi: 10.1093/eurheartj/ehv419. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ducroux C, Di Meglio L, Loyau S, Delbosc S, Boisseau W, Deschildre C, et al. Thrombus neutrophil extracellular traps content impair tPA-induced thrombolysis in acute ischemic stroke. Stroke. 2018;49:754–757. doi: 10.1161/STROKEAHA.117.019896. [DOI] [PubMed] [Google Scholar]
- 20.Laridan E, Denorme F, Desender L, François O, Andersson T, Deckmyn H, et al. Neutrophil extracellular traps in ischemic stroke thrombi. Ann Neurol. 2017;82:223–232. doi: 10.1002/ana.24993. [DOI] [PubMed] [Google Scholar]
- 21.Novotny J, Oberdieck P, Titova A, Pelisek J, Chandraratne S, Nicol P, et al. Thrombus NET content is associated with clinical outcome in stroke and myocardial infarction. Neurology. 2020;94:e2346–e2360. doi: 10.1212/WNL.0000000000009532. [DOI] [PubMed] [Google Scholar]
- 22.Kwon I, Hong SY, Kim YD, Nam HS, Kang S, Yang SH, et al. Thrombolytic effects of the snake venom disintegrin saxatilin determined by novel assessment methods: a FeCl3-induced thrombosis model in mice. PLoS One. 2013;8:e81165. doi: 10.1371/journal.pone.0081165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Shim Y, Kwon I, Park Y, Lee HW, Kim J, Kim YD, et al. Characterization of ferric chloride-induced arterial thrombosis model of mice and the role of red blood cells in thrombosis acceleration. Yonsei Med J. 2021;62:1032–1041. doi: 10.3349/ymj.2021.62.11.1032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ruifrok AC, Johnston DA. Quantification of histochemical staining by color deconvolution. Anal Quant Cytol Histol. 2001;23:291–299. [PubMed] [Google Scholar]
- 25.Heo J, Seog Y, Lee H, Lee IH, Kim S, Baek JH, et al. Automated composition analysis of thrombus from endovascular treatment in acute ischemic stroke using computer vision. J Stroke. 2022;24:433–435. doi: 10.5853/jos.2022.02054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Adams HP, Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993;24:35–41. doi: 10.1161/01.str.24.1.35. [DOI] [PubMed] [Google Scholar]
- 27.Higashida RT, Furlan AJ, Roberts H, Tomsick T, Connors B, Barr J, et al. Trial design and reporting standards for intra-arterial cerebral thrombolysis for acute ischemic stroke. Stroke. 2003;34:e109–e137. doi: 10.1161/01.STR.0000082721.62796.09. [DOI] [PubMed] [Google Scholar]
- 28.Döring Y, Libby P, Soehnlein O. Neutrophil extracellular traps participate in cardiovascular diseases: recent experimental and clinical insights. Circ Res. 2020;126:1228–1241. doi: 10.1161/CIRCRESAHA.120.315931. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Pfeiler S, Stark K, Massberg S, Engelmann B. Propagation of thrombosis by neutrophils and extracellular nucleosome networks. Haematologica. 2017;102:206–213. doi: 10.3324/haematol.2016.142471. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Haider P, Kral-Pointner JB, Mayer J, Richter M, Kaun C, Brostjan C, et al. Neutrophil extracellular trap degradation by differently polarized macrophage subsets. Arterioscler Thromb Vasc Biol. 2020;40:2265–2278. doi: 10.1161/ATVBAHA.120.314883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Nosaka M, Ishida Y, Kimura A, Kondo T. Time-dependent appearance of intrathrombus neutrophils and macrophages in a stasis-induced deep vein thrombosis model and its application to thrombus age determination. Int J Legal Med. 2009;123:235–240. doi: 10.1007/s00414-009-0324-0. [DOI] [PubMed] [Google Scholar]
- 32.Lee KO, Kwon I, Nam HS, Park Y, Kim J, Shim Y, et al. Effect of leukopenia induced by cyclophosphamide on the initial stage of arterial thrombosis in mice. Thromb Res. 2021;206:111–119. doi: 10.1016/j.thromres.2021.08.017. [DOI] [PubMed] [Google Scholar]
- 33.Brill A, Fuchs TA, Savchenko AS, Thomas GM, Martinod K, De Meyer SF, et al. Neutrophil extracellular traps promote deep vein thrombosis in mice. J Thromb Haemost. 2012;10:136–144. doi: 10.1111/j.1538-7836.2011.04544.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Yunoki K, Naruko T, Sugioka K, Inaba M, Iwasa Y, Komatsu R, et al. Erythrocyte-rich thrombus aspirated from patients with ST-elevation myocardial infarction: association with oxidative stress and its impact on myocardial reperfusion. Eur Heart J. 2012;33:1480–1490. doi: 10.1093/eurheartj/ehr486. [DOI] [PubMed] [Google Scholar]
- 35.Baskurt OK, Meiselman HJ. Activated polymorphonuclear leukocytes affect red blood cell aggregability. J Leukoc Biol. 1998;63:89–93. doi: 10.1002/jlb.63.1.89. [DOI] [PubMed] [Google Scholar]
- 36.Watson T, Shantsila E, Lip GY. Mechanisms of thrombogenesis in atrial fibrillation: Virchow’s triad revisited. Lancet. 2009;373:155–166. doi: 10.1016/S0140-6736(09)60040-4. [DOI] [PubMed] [Google Scholar]
- 37.Ahn SH, Hong R, Choo IS, Heo JH, Nam HS, Kang HG, et al. Histologic features of acute thrombi retrieved from stroke patients during mechanical reperfusion therapy. Int J Stroke. 2016;11:1036–1044. doi: 10.1177/1747493016641965. [DOI] [PubMed] [Google Scholar]
- 38.Boeckh-Behrens T, Schubert M, Förschler A, Prothmann S, Kreiser K, Zimmer C, et al. The impact of histological clot composition in embolic stroke. Clin Neuroradiol. 2016;26:189–197. doi: 10.1007/s00062-014-0347-x. [DOI] [PubMed] [Google Scholar]
- 39.Dargazanli C, Rigau V, Eker O, Riquelme Bareiro C, Machi P, Gascou G, et al. High CD3+ cells in intracranial thrombi represent a biomarker of atherothrombotic stroke. PLoS One. 2016;11:e0154945. doi: 10.1371/journal.pone.0154945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kaesmacher J, Boeckh-Behrens T, Simon S, Maegerlein C, Kleine JF, Zimmer C, et al. Risk of thrombus fragmentation during endovascular stroke treatment. AJNR Am J Neuroradiol. 2017;38:991–998. doi: 10.3174/ajnr.A5105. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
Factors Associated with Functional Outcome at 3 Months after Stroke
Correlation of counts of Ly6G-positive cells (neutrophils) and the fractions of platelets (A), erythrocytes (B), and fibrin (C) in arterial thrombi in mice. No significant correlations were observed between Ly6G-positive cell counts and the fractions of platelets, erythrocytes, or fibrin (Pearson correlation test). The primary antibodies for immunohistochemistry were anti-Ly6G Ab for neutrophil, anti-TER119 Ab for erythrocyte, anti-CD41 Ab for platelet, and anti-fibrinogen/fibrin for fibrin.