Arterial Stiffness Is Associated with White Matter Disruption and Cognitive Impairment: A Community-Based Cohort Study

Abstract

Background:

Mechanisms through which arterial stiffness impacts cognitive function are crucial for devising better strategies to prevent cognitive decline.

Objective:

To examine the associations of arterial stiffness with white matter integrity and cognition in community dwellings, and to investigate whether white matter injury was the intermediate of the associations between arterial stiffness and cognition.

Methods:

This study was a cross-sectional analysis on 952 subjects (aged 55.5±9.1 years) who underwent diffusion tensor imaging and measurement of brachial-ankle pulse wave velocity (baPWV). Both linear regression and tract-based spatial statistics were used to investigate the association between baPWV and white matter integrity. The association between baPWV and global cognitive function, measured as the mini-mental state examination (MMSE) was evaluated. Mediation analysis was performed to assess the influence of white matter integrity on the association of baPWV with MMSE.

Results:

Increased baPWV was significantly associated with lower mean global fractional anisotropy (β= –0.118, p < 0.001), higher mean diffusivity (β= 0.161, p < 0.001), axial diffusivity (β= 0.160, p < 0.001), and radial diffusivity (β= 0.147, p < 0.001) after adjustment of age, sex, and hypertension, which were measures having a direct effect on arterial stiffness and white matter integrity. After adjustment of age, sex, education, apolipoprotein E ɛ4, cardiovascular risk factors, and brain atrophy, we found an association of increased baPWV with worse performance on MMSE (β= –0.093, p = 0.011). White matter disruption partially mediated the effect of baPWV on MMSE.

Conclusion:

Arterial stiffness is associated with white matter disruption and cognitive decline. Reduced white matter integrity partially explained the effect of arterial stiffness on cognition.

Keywords

Arterial stiffness brachial-ankle pulse wave velocity cognitive function diffusion tensor imaging white matter

INTRODUCTION

Central arterial stiffening occurs with aging and results in increased pulsatile stress forward into the cerebrovascular microcirculation which may eventually damage small vessels [1, 2]. Arterial stiffness is an emerging risk factor for the development of str-uctural brain injury, such as white matter hyperintens-ities (WMH), which has been shown to be associated with cognitive decline [3 –5]. Diffusion tensor imaging (DTI) is particularly useful for the investigation of microstructural changes in white neuronal fiber tracts [6]. Several brain regions, including the corpus callosum, the internal capsule, the corona radiata, and the superior longitudinal fasciculus, have been highlighted to be vulnerable to hemodynamic changes and to precede the development of WMHs [7 –11]. Furthermore, increased arterial stiffness has been identified to relate to memory loss, poorer processing speeds, and declines in executive function [12 –17]. Physiological mechanisms through which arterial stiffness impacts cognitive function are crucial for devising better strategies to prevent cognitive decline, but still poorly understood.

To date, carotid-femoral pulse wave velocity (cfPWV) is the most validated technique in the landmark studies of arterial stiffness, such as the Framingham Heart Study [10], the Atherosclerosis Risk in Communities Study [17], and the Rotterdam Study [16]. However, cfPWV has not yet been implemen-ted in routine clinical settings. This methodology is hindered by the technical precision required for carotid pulse acquisition and the intimate nature of femoral pulse acquisition in spite of its accuracy and reproducibility. Branchial-ankle pulse wave velocity (baPWV) has a procedural advantage of being very simple to use, only requiring the wrapping of blood pressure cuffs on four extremities [18]. Previous studies have suggested that baPWV and cfPWV are indices of arterial stiffness that exhibit similar extent of associations with cardiovascular risk factors and clinical events [19]. Although widely incorporated in clinical practice, few population-based studies have employed baPWV to assess arterial stiffness in relation to microstructural changes in white matter (WM) fibers tracts and cognitive function.

The aim of this study was to better understand the impact of arterial stiffness on WM microstructure and cognition in a large community-based sample. We tested the following two hypotheses: 1) higher arterial stiffness, as measured by baPWV, is associated with WM neuronal fiber injury, and 2) lower global cognitive function, as measured by the Mini-Mental State Examination (MMSE), is associated with baPWV, and reduced WM integrity may be a plausible intermediate of the associations between arterial stiffness and cognitive function.

METHODS

Population

The present study was a cross-sectional analysis of the ongoing population-based Shunyi cohort study in China, designed to investigate the risk factors and consequences of cardiovascular and age-related diseases. All inhabitants aged 35 years and older, living in 5 villages of Shunyi, a suburb district of Beijing, China, were invited. From June 2013 to April 2016, 1,586 individuals participated and standard baseline assessments were undertaken. All participants were invited for brain magnetic resonance imaging (MRI) examination and measurement of baPWV. Among those, 329 participates refused or had contraindications of MRI, leaving 1,257 participants with brain MRI scans. Of 1,257 participants who had brain MRI, 1,131 also accomplished baPWV measurement. Par-ticipants with poor structural MRI quality (n = 31) and inadequate DTI scans (n = 98) were excluded. We further excluded individuals with history of stroke and other neurologic disorders that might con-found the assessment of brain volumes, major psy-chiatric disorders, and current or a history of major cardiovascular disease (myocardial infarction and heart failure). For the analyses of associations bet-ween baPWV and DTI metrics, our analytic sample was 952 (Fig. 1). When evaluating the association between baPWV and cognitive function, 19 subjects with unavailable MMSE results were further ex-cluded.

Fig. 1

A flow chart of participants inclusion and exclusion in the study. MRI, magnetic resonance imaging; DTI, diffusion tensor imaging; baPWV, brachial-ankle pulse wave velocity; MMSE, Mini-Mental State Examination.

The study was approved by the Ethical Committee at Peking Union Medical College Hospital. Written informed consent was obtained from all participants.

Measurement of baPWV

baPWV was measured with patients in the supine position using an automated device (VP-1000, Colin, Komaki, Japan). This device simultaneously measures bilateral pulse waves from the brachial and pos-terior tibial arteries and arterial blood pressure by the oscillometric method [18]. baPWV was calculated by dividing arterial transmission distance by the transmission time and expressed in meters per second. The transmission distance between each sampling point and the heart was estimated automatically according to the subject’s height. The transmission time between the brachium and ankle was defined as the time difference between the pressure waveform of brachium and that of ankle. The baPWV obtained bilaterally was averaged for further analysis.

Magnetic resonance imaging and diffusion tensor imaging processing

MRI acquisition was performed using a 3-T Sie-mens Skyra scanner (Siemens, Erlangen, Germany). All participants used the same MRI scanner. Three-dimensional T1-weighted images were acquired using a magnetization-prepared rapid gradient-echo (MPRAGE) sequence with the following parameters: 144 sagittal slices, voxel size = 1×1×1.3 mm³, rep-etition time (TR) = 2,530 ms, echo time (TE) = 3.43 ms, inversion time = 1,100 ms, field of view (FOV) = 256×256 mm², flip angle = 8°. Diffusion weighted images were acquired using a single-shot spin echo-planar imaging sequence covering the whole brain with the following parameters: 62 axial slices, slice thickness = 2.2 mm without gap; TR = 8000 ms, TE = 89 ms, flip angle = 90°, 30 diffusion directions with b = 1000 s/mm² and an additional image without diffusion weighting (i.e., b = 0 s/mm²), acq-uisition matrix = 128×128, FOV = 280×280 mm², average = 2.

The gray matter (GM), WM, and cerebrospinal fluid (CSF) were automatically segmented on 3D T1-weighted images using SPM12 (http://www.fil.ion.ucl.ac.uk/spm/) and CAT12 toolbox (http://www.neuro.uni-jena.de/vbm/). Total intracranial volume (TIV) was computed as the sum of volume of GM, WM, and CSF. Brain parenchymal fraction (BPF), as a surrogate index of brain atrophy, was the ratio of brain tissue volume (GM+WM) to TIV.

DTI data preprocessing were performed using PANDA, which is a pipeline toolbox for diffusion MRI analysis [20]. Briefly, the preprocessing procedure included skull-stripping, eddy-current and head-motion correction. Then, voxel-wise fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated by fitting a diffusion tensor model. Each participant’s global DTI parameters were extracted from the WM tissue mask. To minimize partial volume effects from GM and CSF, we set a threshold for voxels with FA value greater than 0.2. The region of interest (ROI) analysis was performed using the deep WM atlas (ICBM-DTI-81 white matter atlas) developed by the Johns Hopkins University [21]. Based on the four regions indicated as vulnerable to increased arterial stiffness in the literature (i.e., the corpus callosum, the internal capsule, the corona radiata, and the superior longitudinal fasciculus), mean values of a diffusion metric for selected ROI segmentations were extracted from each participant. In tract-based spatial statistics analysis, a mean FA skeleton was created and each participant’s highest FA value near the skeleton was projected onto the mean skeleton. Voxel-wise statistical analysis on the skeleton were performed.

Neurocognitive and cardiovascular measurements

The global cognitive assessment was based on the Chinese version of MMSE [22], which was performed by the trained physicians using standard criteria. The cognitive status was determined by a review panel consisting two neurologists specialized in cognitive disorders. The diagnosis of dementia needs to satisfy the DSM-IV criteria for dementia [23] or 2011 NIA-AA Criteria for all-cause dementia [24]. Hypertension was defined as self-reported hypertension, or blood pressure ≥140/90 mmHg, or use of anti-hypertensive medication. Self-reported hypertension was considered present if an affirmative answer was given to the question: “Have you ever been told by a doctor or other health profe-ssional that you have high blood pressure, also called hypertension?”. Diabetes mellitus was defined as use of oral antidiabetic drugs or insulin, fasting serum glucose ≥7.0 mmol/L, or hemoglobin A1c (HbA1c) ≥6.5%. Hyperlipidemia was defined as fasting serum total cholesterol >5.2 mmol/L, low density lipoprotein cholesterol (LDL-C) >3.62 mmol/L, or use of lipid-lowering drugs. Smoking status was classified as current smoker (at least within the prior month) or non-current smoker. Genotyping for apolipoprotein E (APOE) was performed on coded DNA specimens. Persons were categorized on the basis of presence or absence of an APOE ɛ4 allele.

Statistical analysis

First, we investigated the association between baPWV and brain WM integrity as indicated by FA, MD, AD, and RD. Multiple linear regression models were defined separately for each WM metric as dependent variable and baPWV as independent var-iable. The correlation between baPWV and each WM metric was computed for the mean of the global WM. Three models were employed to evaluate the associations between baPWV and DTI metrics. First, we performed the univariate analysis (model 1). Further adjustment was made for age, sex, and hyp-ertension (model 2) as these measures were significantly correlated with baPWV and WM integrity based on univariate analysis. Then, to examine whet-her associations were independent of other vascular factors, we additionally adjusted for diabetes mellitus, hyperlipidemia, and smoking (model 3). These risk factors have been less consistently linked to WM disruption compared to hypertension. In addition, correlation between baPWV and each WM metric (FA, MD, AD, and RD) was computed for each re-gion of interest: the genu, body and splenium of the corpus callosum, the anterior limb, posterior limb and retrolenticular part of internal capsule, the anterior, superior and posterior corona radiata, and the superior longitudinal fasciculus. Bonferroni method was applied to correct for multiple comparisons. Then, the FSL randomise function was used to per-form permutation-based nonparametric inference using a generalized linear model to investigate the associations between DTI parameters and baPWV (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Randomise). Age, sex, and hypertension were included in the models as covariates. The number of permutation-based correction was set at 5000. Significant thres-hold were determined using a threshold-free cluster enhancement with a p-value <0.05.

Next, we evaluated the associations between arterial stiffness and cognitive function, measured as MMSE. Multiple linear regression models were used to achieve this goal. Estimates of β values and standard error (SE) for MMSE score by per standard deviation (SD) increase of baPWV were calculated. The analysis was adjusted for age, sex, years of education, APOE 4 status, smoking, hypertension, diabetes mellitus, hyperlipidemia, and BPF.

Finally, we conducted a mediation analysis to quantify the mediating effect of WM integrity disruption on the association between baPWV and cognitive function. Each model firstly included age, sex, and hypertension as covariates, and then additionally adj-usted for diabetes mellitus, hyperlipidemia, and smo-king. Indirect effects were examined using a 95% bootstrapped bias-corrected confidence interval est-ablished via bootstrapping with 5000 bootstrap samples. Bootstrap approach has been indicated to be more powerful than traditional methods (e.g., Sobel test) and has been widely used in mediation analysis in recent years [25, 26].

Statistical analyses were performed using SPSS version 24.0 (IBM Co., Armonk, NY, USA). The mediation analysis was performed using the Process macro in SPSS version 24.0 (Hayes, 2013). Two-tailed p values of <0.05 were considered as statistically significant.

RESULTS

Sample characteristics

Demographic, clinical, and neuroimaging characteristics of the study population are provided in Table 1. A total of 952 participants were included in the present analysis. The mean age was 55.5 years (SD, 9.1), and 346 (36.3%) participants were male.

Table 1

Characteristics of the study population (n = 952)

Characteristic
Demographics
Age, mean (SD), y	55.5 (9.1)
35–39	24 (2.5)
40–49	247 (25.9)
50–59	368 (38.7)
60–69	234 (24.6)
70–79	76 (8.0)
80–89	3 (0.3)
Male sex, n (%)	346 (36.3)
Education, mean (SD), y	6.5 (3.4)
Current smoker, n (%)	208 (21.8)
Hypertension, n (%)	474 (49.8)
Diabetes mellitus, n (%)	149 (15.7)
Hyperlipidemia, n (%)	461 (48.4)
baPWV, mean (SD), m/s	15.7 (3.2)
Apolipoprotein E 4 allele	140 (16)
present, n (%)
Mini-Mental State Examination	26.4 (3.9)
score, mean (SD)
Dementia, n (%)	26 (2.7)
Neuroimaging Characteristics
Brain parenchymal fraction,	76.44 (3.12)
mean (SD), %
DTI parameters
Mean global fractional	0.37 (0.02)
anisotropy, mean (SD)
Mean global mean diffusivity,	0.84 (0.05)
mean (SD),×10^-3 mm²/s
Mean global axial diffusivity,	1.17 (0.05)
mean (SD),×10^-3 mm²/s
Mean global radial diffusivity,	0.68 (0.06)
mean (SD),×10^-3 mm²/s

SD, standard deviation; baPWV, brachial-ankle pulse wave velocity; DTI, diffusion tensor imaging.

Compared with participants who were excluded from the present analysis due to inadequate data, participants included were younger (55.5 versus 58.6 years), less likely to be male (36.3% versus 46%), and had better cognition status (mean MMSE score 26.4 versus 24.7).

Arterial stiffness and white matter integrity

Table 2 shows the associations between baPWV and WM integrity using whole-brain DTI metrics. Higher baPWV was a significant predictor of lower mean global FA, higher mean global MD, higher mean global AD, and higher mean global RD after adjustment of age, sex, and hypertension (model 2). Associations attenuated when further adjusted for diabetes, hyperlipidemia, and smoking (model 3), but still significant. We then compared baPWV with DTI metrics in different WM regions which have been reported vulnerable to increased arterial stiffness. Significant correlations of baPWV with the DTI metrics in regions of corpus callosum, internal capsule, corona radiata, and superior longitudinal fasciculus were observed (Supplementary Tables 1–4).

Table 2

Association between microstructural tissue integrity of global white matter fiber tracts and arterial stiffness, as measured by baPWV

	Model 1^a		Model 2^b		Model 3^c
	β	p	β	p	B	p
Mean global FA	–0.374	<0.001	–0.118	<0.001	–0.104	0.002
Mean global MD	0.444	<0.001	0.161	<0.001	0.154	<0.001
Mean global AD	0.430	<0.001	0.160	<0.001	0.157	<0.001
Mean global RD	0.429	<0.001	0.147	<0.001	0.137	<0.001

^aModel 1: unadjusted. ^bModel 2: adjusted for age, sex and hypertension. ^cModel 3: adjusted as in model 2 + smoking, diabetes mellitus and hyperlipidemia. baPWV, brachial-ankle pulse wave velocity; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity.

We subsequently investigated the association of baPWV with each DTI metric on WM skeleton in the whole brain. As shown in Fig. 2, increased baPWV was associated with widespread reduced FA and increased MD, AD and RD, suggesting disruption of WM microstructure.

Fig. 2

Tract-based spatial statistic maps exhibit white matter fiber tracts with fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) that associated with brachial-ankle pulse wave velocity. All analyses were adjusted for age, sex and hypertension. Color scale indicates the p value. Blue color map indicates a negative relationship and red colormap indicates a positive relationship.

Arterial stiffness and cognitive function

After adjustment for age, sex, years of education, APOE ɛ4, smoking, hypertension, diabetes mellitus, hyperlipidemia, and BPF, statistically significant association was found for per SD increased baPWV and worse performance on the MMSE (β= –0.093, SE = 0.124, p = 0.011). When excluded participants with dementia (n = 26) at baseline, the association between baPWV and MMSE remained (β= –0.100, SE = 0.115, p = 0.007).

Then we tested if WM integrity, measured as mean global FA, MD, AD, or RD, mediated the effect of baPWV on MMSE. Detailed statistics of the mediation analyses are shown in Fig. 3. Total effect I consists of direct (c’) and indirect effects. When including age, sex, hypertension, diabetes mellitus, hyperlipidemia, and smoking as covariates, there was a significant indirect effect of baPWV on MMSE through the mean global FA (c’ = –0.131, indirect effect = –0.0207 [95% CI, –0.0653 to –0.0016]), MD (c’ = –0.129, indirect effect = –0.0316 [95% CI, –0.0859 to –0.0015]), and RD (c’ = –0.127, indirect effect = –0.0350 [95% CI, –0.0912 to –0.0044]). These results suggest that arterial stiffness is negatively related to global cognitive function in part through the disruption of WM integrity.

Fig. 3

The mediation analysis by DTI metrics of the association between baPWV and MMSE. a is regression coefficient of the association between baPWV and FA (A), MD (B), AD (C), or RD (D); b is regression coefficient of the association between FA (A), MD (B), AD (C), or RD (D) and MMSE; c is regression coefficient of the association between baPWV and MMSE; c’ is regression coefficient of the association between baPWV and MMSE, using FA (A), MD (B), AD (C), or RD (D) and baPWV as independent variables. Each model included age, sex, and hypertension as covariates. All values represent standardized betas. ^*p < 0.05; ^**p < 0.001. DTI, diffusion tensor imaging; baPWV, brachial-ankle pulse wave velocity; MMSE, Mini-Mental State Examination; FA, fractional anisotropy; MD, mean diffusivity; AD, axial diffusivity; RD, radial diffusivity.

DISCUSSION

Results from the present study indicated that, among a community-based sample, baPWV, the non-invasive measure of systemic arterial stiffness, was independently associated with the deterioration of WM neuron fiber integrity, as reflected by the dec-reases in FA, increases in MD, AD, and RD. In addition, we demonstrated that general cognitive function performance worsened with increasing baPWV. The reduction of WM integrity mediated the link between baPWV and MMSE, suggesting its critical role in the anatomical basis through which systemic arterial stiffness is related to lower cognitive performance.

Impact of arterial stiffness on white matter integrity

Elevation in central arterial stiffness promotes the microvascular damage of the brain. In particular, the association between artery stiffness and WMH burden has been reported consistently [27 –29]. DTI studies suggested that microstructural WM changes precede the development of WMHs visible in FLAIR imaging [30], indicating that WMH may only represent the extreme foci of a more widespread, continuous WM injury process that progresses insidiously during aging. A previous study enrolling 54 cognitively normal or mild-cognitively impaired adults (65±6 years) reported an association between higher cfPWV with lower FA in the regions as vulnerable to increased aortic stiffness, such as corpus callosum, internal capsule, corna radiata, and superior longitudinal fasciculus [11]. These associations were confirmed in 1,903 participants from the Framingham Heart Study Third Generation, which was the first to evaluate the relationships between cfPWV and DTI metrics in population-based sample [10]. Our results were in line with previous reports.

The role of artery stiffness in modifying WM integrity involves multifactorial biological process. As an organ with low-impedance and high flow, brain is more vulnerable to central hemodynamic alt-erations. Arterial stiffness may contribute to micr-ovascular brain injury by exposing the small vessels of the cerebral vasculature to high pressure fluctuations and flow pulsatility [31 –35]. Artery stiffness may also increase short term variability in blood pressure, which may impact supply of oxygen to the brain [33]. This may be critical in brain regions more susceptible to hypoperfusion such as the WM. Moreover, human cerebrovascular defense strategy does not allocate protective measures against circulatory threats uniformly for all regions, leaving certain areas vulnerable to receive more damage. These regions include WM tracts irrigated by arterioles arising from the anterior and middle cerebral arteries, such as the corpus callosum, the internal capsule and the corona radiata [34].

Impact of arterial stiffness on cognitive function

Our results indicated that higher baPWV is independently associated with poorer global cognitive function detected by MMSE. Although there is a good agreement in the literature showing that PWV is associated with alterations in cognitive performance [5], studies that examined the relationship between arterial stiffness and global cognitive function as measured via MMSE reported conflicting results [5 , 13–17]. Several community-based cohort studies, e.g., the Rotterdam Study, did not report an association between arterial stiffness and MMSE score, but did find an association between arterial stiffness and more specific cognitive domains. This could be due to that MMSE, as a screening tool, may not be sensitive enough to measure subtle cognitive changes in healthy populations.

The pathophysiological mechanisms through wh-ich arterial stiffness impact the cognitive function are complicated and poorly understood. The brain WM, which accounts for up to 50% of the paren-chyma, connects distributed network of neurons, and facilitates complex cognitive task via structural and functional integrations. WM integrity of the regions known to be vulnerable to the effects of arterial stif-fness (e.g., corpus callosum, corona radiata) have been shown to correlate with processing speed and executive function [36, 37]. Previous findings have demonstrated that an increase in RD and MD, as well as a decrease in FA was more related to demyelination in the WM [38, 39]. Our findings in the mediation analyses suggest that the mechanisms linking cognitive impairment and arterial stiffness may be related to breakdown of myelin. However, it should be noted that interpretation of variation in specific diffusivity measures is still under debate. On the other hand, arterial stiffness has also been shown to impact gray matter structure as well as cerebral perfusion, which in turn can impact cognitive function. As such, measuring and reducing arterial stiffness may offer a chance to identify early changes of cognitive function and to implement interventions that can delay abnormal brain function before irreversible structural damage occurs.

Strengths and limitations

The strengths of this study include the large sample size, population-based design, and utilization of quantitative DTI metrics that are sensitive to WM microstructure damage. Some limitations also need to be considered. First, the cross-sectional design of the study limits our ability to conclude that arterial stiffness has an impact on WM integrity and cognitive function. Follow-up and longitudinal studies are needed to further confirm whether arterial stiffness has a causal effect on cognitive decline and through what mechanisms. Second, participants with complete DTI data and assessment of cognitive performance were generally younger and had better cognition, which might have caused some selection bias. Third, although previous studies have revealed the validity of baPWV as an index of aortic stiffness, direct assessment using cfPWV, a gold standard for aortic stiffness assessment, on certain size of the patient sample will be a good comparison with the current study. Fourth, the MMSE, a screening test for dementia is not sensitive to early cognitive deficits. Data from multiple cognitive tests to provide more robust measures of domain-specific function should be considered in future analysis. Fifth, the presence of hypertension was self-reported and not based on the actual diagnosis, which may be a source of bias.

Conclusion

In conclusion, this community-based study dem-onstrated the impact of arterial stiffness on WM fiber integrity, as assessed by DTI metrics. Furthermore, systemic arterial stiffening is a plausible independent contributor to cognitive decline. Our study highlights the mediation role of WM integrity disruption in the relationship between arterial stiffness and cognitive function and provides information on a potentially modifiable pathway for improving cognitive outcomes among older adults before irreversible structural brain damage occurs.

Footnotes

ACKNOWLEDGMENTS

This study was supported by National Key Res-earch and Development Program of China (2016YFC0901004), National Natural Science Foundation of China (81971138), the Strategic Priority Research Program “Biological basis of aging and therapeutic strategies” of the Chinese Academy of Sciences (XDB39040300), the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS # 2016-I2M-1-004), the Fundamental Research Funds for the Central Universities (3332020006) and Research Foundation for Young Scholars of Peking Union Medical College Hospital (PUMCH201911275).

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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