Mapping the Changes of Glutamate Using Glutamate Chemical

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Mapping the changes of glutamate using GluCEST technique in a traumatic brain injury model: a longitudinal pilot study Zerui Zhuang, Zhiwei Shen, Yanzi Chen, Zhuozhi Dai, Xiaolei Zhang, Yifei Mao, Bingna Zhang, Haiyan Zeng, Peidong Chen, and Renhua Wu ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00482 • Publication Date (Web): 15 Oct 2018 Downloaded from http://pubs.acs.org on October 24, 2018

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ACS Chemical Neuroscience

Title page (i) Full title of the paper: Mapping the changes of glutamate using GluCEST technique in a traumatic brain injury model: a longitudinal pilot study (ii) Author names and affiliations: Zerui Zhuang1, Zhiwei Shen2, Yanzi Chen2, Zhuozhi Dai2, Xiaolei Zhang2, Yifei Mao2, Bingna Zhang3, Haiyan Zeng4, Peidong Chen2 and Renhua Wu2 1Department

of Neurosurgery, The Second Affiliated Hospital, Medical College of Shantou University,

Shantou, 515041, China 2Department

of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou,

515041, China 3Translational

Medicine, The Second Affiliated Hospital, Medical College of Shantou University, Shantou,

515041, China 4

Medical College of Shantou University, Shantou, 515041, China

(iii) Full postal and email address of the corresponding author: Professor Renhua Wu Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, 69 North Dongxia Road, Shantou, 515041, China. Telephone number: (86) 0754-88915674 Fax number: +86-0754-88346543 E-mail address: [email protected] (iv) Running title: GluCEST MRI in traumatic brain injury

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Abstract Glutamate excitoxicity plays a crucial role in the pathophysiology of traumatic brain injury (TBI) through the initiation of secondary injuries. Glutamate chemical exchange saturation transfer (GluCEST) MRI is a newly developed technique to non-invasively image glutamate in vivo with high sensitivity and spatial resolution. The aim of the present study was to use a rat model of TBI to map changes in brain glutamate distribution, and explore the capability of GluCEST imaging for detecting secondary injuries. Sequential GluCEST imaging scans were performed in adult male Sprague-Dawley rats before TBI, and at 1, 3, 7 and 14 days after TBI. GluCEST% increased and peaked on Day 1 after TBI in the core lesion of injured cortex, and in the ipsilateral hippocampus peaked on Day 3, as compared to baseline and controls. GluCEST% gradually declined to baseline by Day 14 after TBI. A negative correlation between the GluCEST% of the ipsilateral hippocampus on Day 3 and the time in the correct quadrant was observed in injured rats. Immunolabeling for glial fibrillary acidic protein showed significant astrocyte activation in the ipsilateral hippocampus of TBI rats. IL-6 and TNF-α in the core lesion peaked on Day 1 post-injury, while those in the ipsilateral hippocampus peaked on Day 3. These subsequently gradually declined to sham levels by Day 14. It was concluded that GluCEST imaging has potential to be a novel neuroimaging approach for predicting cognitive outcome, and to better understand neuroinflammation following TBI. Keywords: Chemical exchange saturation transfer, MRI, glutamate, neuroinflammation, traumatic brain injury


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Introduction Traumatic brain injury (TBI) mortality, morbidity and disability rates in both developed and developing countries remained high.1, 2 TBI survivors commonly suffer from substantial and lifelong cognitive, physical and behavioral impairments.3 Brain damage consists of an initial primary injury and secondary injury. Primary injury refers to the mechanical disruption of brain tissue leading to immediate cell death,4, 5 whereas secondary injury is a cascade of metabolic, cellular and molecular events resulting to biochemical derangements, such as glutamate excitoxicity, increase free radicals levels, neuroinflammation and apoptosis.6, 7 In particular, glutamate excitoxicity plays a crucial role in the pathophysiology of TBI through the initiation of secondary injuries.8, 9 Detection of these secondary events remains a major goal and an area of ongoing research in neuro-monitoring. Microdialysis is the gold standard for measuring levels of neurotransmitters in the central nervous system in vivo. However, microdialysis has limited applications due to its poor temporal and spatial resolution,10 as well as invasive brain procedures.11 Proton magnetic resonance spectroscopy (1H-MRS) has been widely used to monitor glutamate alterations in animal experiments.12-14 Yet, bottleneck showed poor spatial resolution and long acquisition time.15,

16

Therefore, attaining the ability to accurately and non-

invasively measure changes in glutamate following TBI remains a primary goal for clinical medicine. Glutamate chemical exchange saturation transfer (GluCEST) imaging has been recently developed to measure parenchymal glutamate levels accurately in vivo.15, 17 GluCEST MRI enables indirect measurement of glutamate in vivo by probing the proton exchange of glutamate amine with bulk water, thereby providing higher sensitivity and spatial resolution, when compared to conventional 1H-MRS.15 As previously shown in practice, GluCEST has up to two orders of magnitude higher in sensitivity over 1H-MRS.15 Furthermore, GluCEST is non-invasive with higher spatial resolution, and can simultaneously measure glutamate in various brain regions. GluCEST imaging has shown great success in animal models16, 18-22 and human patients studies.23, 24 In the present study, a longitudinal imaging study was performed using GluCEST imaging to map changes in glutamate distribution of the brain in a cortical impact model of TBI, and explore the capability



of GluCEST imaging for detecting secondary injuries.

Results GluCEST of Glutamate Phantom Figure 1A and 1B presents that the Z-spectra and GluCEST asymmetry curves of Glutamate (Glu) phantoms at different Glu concentrations. The non-symmetry of the Z-spectra and GluCEST asymmetry curves increased with Glu concentration at around 3.0 ppm, which were consistent with a previous study.15 GluCEST value (GluCEST%) was linearly proportional to Glu concentration in the physiological range at pH = 7 (R2=0.9793, Figure 1C). Furthermore, the effect of GluCEST increased by approximately 0.3% for every 1 mM of increase in Glu concentration. Figure 1D presents the GluCEST map of Glu phantoms at different Glu concentrations. The GluCEST value of major neurometabolites, including N-acetylaspartic acid (NAA, 10 mM), creatine (Cr, 6 mM), glutamine (Gln, 2 mM), asparaginic acid (Asp, 2 mM), γ-aminobutyric acid (GABA, 2 mM) and Glu (10 mM), at their physiological concentration was 0.32%, 0.55%, 0.63%, 0.82%, 0.85% and 3.33%, respectively. It was found that these metabolites contributed negligible CEST effects to GluCEST (Figure 1E). Neurological scores of TBI Figure 2 shows the median modified neurological severity score (mNSS) at various time points after TBI. The mNSS of TBI rats and sham rats increased to 9.23 and 7.20, respectively, at the first hour after injury. As time progressed, the mNSS of injured rats decreased gradually and reached a median score of 3.50 at 7 days after TBI, while the mNSS of sham rats returned to baseline within 3 days. Overall, the mNSS of injured rats was significantly higher than that of sham-operated rats at 24 hours, 3 days, and 7 days after TBI (p < 0.05). No significant difference in mNSS was observed between these two groups before injury and at Day 14 after injury (p > 0.05). MRI features of TBI The injured cortex and ipsilateral hippocampus were manually defined as regions of interest (ROIs) on T2weighted (T2w) images, which was used as a reference (Figure 3). Figure 4A shows that the lesions were heterogeneous and hpyerintense on T2w image, indicating the presence of both edematous tissue and


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contusion. Such cerebral edema receded and injured cortex thinned out gradually. Figure 4B presents the representative GluCEST maps in rat brain throughout the experimental period. The GluCEST effect of the injured cortex and ipsilateral hippocampus was high at Day 1 and Day 3 post-injury. The characterization of changes in GluCEST effect at the different times after TBI revealed an increase in GluCEST% in the injured cortex at Day 1 (15.24 ± 0.30%) after injury, when compared to baseline (12.2 ± 0.38%, p < 0.001) and contralateral cortex (13.48 ± 0.34%, p < 0.01), and then decreased gradually to baseline level by 14 days (11.67 ± 0.46%) (Figure 4C). In addition, GluCEST% in the injured cortex was lower than that in the contralateral cortex on Day 14. Figure 4D shows that the GluCEST% of the ipsilateral hippocampus increased gradually and peaked on Day 3 (14.96 ± 0.35%) after injury, and decreased gradually to baseline level by 14 days (12.83 ± 0.31%). Furthermore, GluCEST% in the ipsilateral hippocampus was significant higher than that in the contralateral hippocampus on Day 1 and 3 after injury. In the sham-injured group, no significant difference in GluCEST% was observed at different time points (p > 0.05). Spatial learning and memory outcome Hippocampal-dependent spatial learning and memory were tested at 14 days post-injury in the morris water maze (MWM) test, which was conducted over a 5-day period, followed by a probe trial on Day 6. No significant difference in swimming speed was found between the TBI and sham groups (24.2 ± 0.78 m/s and 26.3 ± 1.31 m/s, respectively, p > 0.05, Figure 5A), indicating that there was no systemic limitations on differences in latency. The latency of each group gradually decreased with training days. However, the latency in the TBI group was higher than that in the sham group (Figure 5B). Furthermore, there was a significant difference in latency to the platform on Day 5 between the TBI (27.20 ± 2.44 sec) and sham (14.93 ± 2.33 sec; p < 0.01) groups, suggesting that TBI group had worse spatial memory than sham group. Overall, TBI rats spent significantly less time in the correct quadrant (19.30 ± 1.52%) during the probe trial, when compared to the sham group (33.15 ± 3.29%, p < 0.001, Figure 5C). The GluCEST% of the ipsilateral hippocampus peaked on Day 3 after injury. Thus, this was selected for evaluating the correlation to hippocampal-dependent memory. A negative correlation between the GluCEST% and the time in the correct quadrant was observed in injured rats using Pearson correlation analysis (R=0.69, p < 0.01, Figure 5D). Immunohistochemistry



The representative images of immunohistochemical staining for the ipsilateral hippocampus with haemotoxylin and eosin (H&E), Nissl, Fluoro-Jade B (FJB), and glial fibrillary acidic protein (GFAP) are presented in Figure 6-7. The hippocampus was selected due to the fact that spatial learning and memory deficits were hippocampus-specific. H&E staining revealed massive neuron loss and abnormal neuron in the CA1 subfield of the ipsilateral hippocampus in TBI rats (Figure 6A). Nissl staining showed that injured neuron bodies shrunken with vacuoles, and nuclei stained darker in the CA1 subfield of the ipsilateral hippocampus in TBI rats (Figure 6B). No degenerating neurons were detected in the ipsilateral hippocampus of sham rats. Furthermore, FJB positivity was found in the DG and hilus of the ipsilateral hippocampus of TBI rats (Figure 6C). Immunolabeling for GFAP showed significant astrocyte activation in the ipsilateral hippocampus of TBI rats, as compared to contralateral hippocampus and sham-injured rats (Figure 7). Cytokine expression A high concentration of IL-6 was found in the core lesion of injured cortex at Day 1 after injury (280.44 ± 57.75 pg/mg protein, p < 0.05), while IL-6 concentration peaked in the ipsilateral hippocampus on Day 3 (323.99 ± 51.99 pg/mg protein, p < 0.05). IL-6 concentration progressively decreased and reached baseline at Day 14 after injury (Figure 8A). Similar to IL-6, TNF-α concentration in the core lesion significantly increased at Day 1 relative to baseline (70.04 ± 18.65 pg/mg protein vs. 43.50 ± 12.93 pg/mg protein; p < 0.05). Furthermore, TNF-α levels peaked in the ipsilateral hippocampus on Day 3 (75.97 ± 18.47 pg/mg protein), and then gradually decreased to baseline at Day 14 after injury (Figure 8B).

Discussion Current study applied GluCEST imaging to map changes in glutamate distribution in the brain in a wellcharacterized and controlled cortical impact model of TBI. Initially, an in vitro experiment was performed to determine the correlation between glutamate concentration and the GluCEST effect. It was found that GluCEST effect increased with the glutamate concentration in an excellent linear relationship at pH7. And it was also revealed that other brain metabolites, including NAA, Cr, Gln, Asp and GABA, contribute negligible CEST effects to GluCEST, which were in line with a previous study.15 Consistent with previous studies,25-28 current study indicated that GluCEST%, which could be correlated to glutamate concentration, significantly increased shortly after TBI and decreased gradually over time.


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GluCEST can monitor regional changes in glutamate concentration at high resolution during the disease course.18 The present study demonstrated the variation in GluCEST% in different parts of the brain. GluCEST% increased and peaked on Day 1 after injury in the core lesion of injured cortex, while GluCEST% in the ipsilateral hippocampus peaked on Day 3. The cell membranes were compromised upon initial damage at the primary injury site, which resulted in the release of glutamate into the extracellular space.29 Thereafter, excito-neurotoxicity resulted from the excessive glutamate release with subsequent excessive influx of Na+ and Ca2+. Such excessive influx could lead to mitochondrial dysfunction and dendritic morphological changes. Eventually, apoptosis and neurodegeneration in other brain areas located away from the primary insult, such as the ipsilateral hippocampus, would occur.30, 31 This could attribute to the delay glutamate elevation in the hippocampus, when compared to glutamate elevation at the primary site. The progression of pathology involving lots of neuron apoptosis at the brain contusion site, and the generation and activation of glia, could lead to the decreased release of glutamate and increased uptake of glutamate.26, 32 This might correspond to the gradual decline in GluCEST effect over time. It was interestingly found that the GluCEST% in the injured cortex was lower than that in the contralateral cortex on Day 14. Crescenzi et al. confirmed that glutamate loss is associated with synapse loss in a mouse model of tauopathy using GluCEST technique.19 Therefore, we speculate that this could be related to the apoptosis and loss of a large number of neurons or synapses at the injured cortex. A MWM experiment was conducted at Day 14 after TBI for the assessment of hippocampal-dependent spatial learning and memory. The learning and memory of injured rats was significantly worse than sham rats, suggesting that hippocampal function was damaged. A negative correlation between the GluCEST% in the ipsilateral hippocampus on Day 3 after TBI and the time in the correct quadrant was found. This suggested that high glutamate concentration in the ipsilateral hippocampus could worsen the performance in the MWM test. Neuronal apoptosis and neurodegeneration in the hippocampus has been reported in TBI due to glutamate excitotoxicity.33 As hippocampus mediates passive and active spatial learning and memory,34 current findings together with the GluCEST MRI data indicate that GluCEST imaging could be used to predict cognitive outcome following TBI. Apart from GluCEST, amide proton transfer-weighted (APTw) imaging, which is another type of CEST



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MRI, has been suggested as a potential and novel molecular neuroimaging tool for the simultaneous detection of neuroinflammation in TBI in vivo.35, 36 However, the APTw is at 3.5 ppm and has a lower exchange rate, so the saturation power is usually much lower (~1.3 µT) and the signal intensity is more susceptible to contamination of nuclear overhauser effect. Compared to APTw, in which the signal intensity is contributed by a wide range of endogenous mobile proteins and peptides,37 GluCEST is more specific to the change of glutamate. TBI can induce measurable metabolic abnormalities, including a sustained depression in cerebral glucose uptake.14, 38 Glucose CEST (GlucoCEST) imaging could be used to study this pathological changes since it has great advantages in detecting cerebral metabolic abnormalities in vivo.39, 40 Recently, Tu et al. showed that endogenous glucoCEST contrast was decreased following TBI, indicated a glucose metabolism abnormality in TBI.40 This abnormality affects the uptake of glutamate, and further aggravates glutamate excitotoxicity.32 Therefore, the combination of multiple CEST images will help to better undertstand the

secondary injuries following TBI. Both humans and animal models studies have extensively investigated neuroinflammation in TBI.41 In particular, an elevation of inflammatory cytokines after TBI has been reported.42-44

Neuroinflammation is

another important mechanism of secondary injury that contributes to the progressive neurodegeneration and neurological impairment following TBI.45-47 IL-6 and TNF-α were found to peak in the injury site at 1 day after injury, and these gradually declined back to baseline, which was consistent with the previous studies.48, 49

More importantly, the alteration of IL-6 and TNF-α in the injury site and ipsilateral hippocampus were

associated with the GluCEST imaging. Studies have shown that glutamate was extensively involved in the regulation of neuroinflammation after TBI.32, 42, 50 Dai et al. revealed that high glutamate concentrations after TBI determined the mode of inflammation, from adenosine–adenosineA2A receptor activation-mediated anti-inflammatory and neuroprotective effect to a proinflammatory and cytotoxic role in vivo and in vitro.25 The over-stimulation of glutamate receptors, particularly mGluR5, which is widely distributed on microglia, was found at increased the levels of extracellular glutamate following TBI.32, 50 Activated microglia were able to secrete a large number of inflammatory cytokines that are toxic to neurons.51 Wang et al. found that pomalidomide could ameliorate glutamate-mediated cytotoxic effects on cell viability, while the reduction of microglial cell activation could significantly attenuate the induction of TNF-α.52 Therefore, GluCEST MRI


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would likely reflect the alteration in neuroinflammation, in which glutamate could be an imaging biomarker to monitor neuroinflammation in the brain following TBI.

Conclusions Current study successfully applied GluCEST imaging to map changes in glutamate distribution in the brain in a controlled cortical impact model of TBI. GluCEST in the ipsilateral hippocampus was found to correlate negatively with hippocampal-dependent memory, suggesting the effect of glutamate elevation on cerebral memory control. GluCEST imaging, as a novel molecular neuroimaging approach, can provide a high sensitivity and spatial resolution assessment for predicting cognitive outcome and better understanding neuroinflammation in TBI.

Methods and materials Phantom Preparation Tissue-like CEST phantoms were prepared based on previous studies to optimize CEST MRI.53, 54 In brief, 1% agarose was added into a phosphate-buffered saline (PBS) solution and heated by microwave. The mixture was then immersed in a water bath at 45°C. Glutamate (Sigma Aldrich, St Louis, MO, USA) was added to attain concentrations of 0, 3, 6, 9, 12 and 15 mmol/L (mM), and the pH was titrated to 7. Tubes were inserted into a phantom holder filled with 1% agarose gel to minimize susceptibility inhomogeneity. Additionally, another phantom that consisted of tubes with solutions of different metabolites at their physiological concentrations (Glu [10 mM], GABA [2 mM], Gln [2 mM], NAA [10 mM], Asp [2 mM] and Cr [6 mM]; Sigma Aldrich, St Louis, MO, USA) in a 1% agarose gel were prepared, and the pH was also titrated to 7. Animal Preparation and Experimental Design All animal experiments were approved by the Ethics Committee of Shantou University Medical College, and carried out in accordance with the guidelines of the Chinese Animal Welfare Agency. Adult male SpragueDawley rats (weighing 250-300 g) were housed under a 12-hour light-dark cycle with free access to standard rat chow and water. TBI or sham surgery was performed on each rat. Experiment 1: The change of glutamate was dynamically monitored in TBI rats (n= 15) and sham rats (n=10). Experiment 2: The change in cytokines levels was analyzed at different time points after injury (n = 5, each group). Serial MR imaging was acquired before TBI to establish baseline levels. Merely rats that completed all imaging time points up to 14 days were



included for the imaging data analysis. Cortical impact model of TBI A weight-drop hitting device (ZH-ZYQ, Electronic Technology Development Co., Anhui, China) was used to produce a moderate cortical impact, as previously described.55 Efforts were made to minimize the number of animals used, and ensure minimal suffering. Briefly, rats were intubated and mechanically ventilated with a mixture of 5% isoflurane for anesthesia induction and 2-3% isoflurane for maintenance, and fixed in a stereotactic frame. The skull was exposed through a midline longitudinal incision. A 5-mm hole was drilled into the right parietal bone, without touching the dura mater. Focal injury to the right hemisphere was induced by dropping a 40-g steel rod with a flat end (4 mm in diameter) from 20 cm above onto a piston resting on the dura with a controlled depth of 1.5 mm. After TBI, the bone flap was repositioned with bone wax, and the scalp incision was sutured. Sham rats underwent identical surgeries without cortical impact by the steel rod. After surgery, isoflurane was discontinued, and rats were placed on a heat pad until fully awake before returning to their cages. MRI data acquisition All phantom and animal experiments were performed using an Agilent 7 T animal MRI scanner (Agilent Technologies, Santa Clara, CA, USA) with a 63-mm internal diameter standard 1H transmission and reception volume coil. MRI was performed under 1–2% isoflurane anesthesia and 1 L/min oxygen administration before TBI, and at 1, 3, 7 and 14 days after TBI. The respiration rate and body temperature of rats were monitored using a MRI compatible monitoring system (Small Animal Instruments, Inc., USA). Rectal temperature was maintained at 37°C using a warm air blown inside the bore of the magnet. T2w imaging was acquired using 2D rapid acquisition with a fast spin echo sequence in the coronal plane. The T2w imaging parameters were as follows: field of view (FOV) = 50 mm × 50 mm (phantom), FOV = 35mm× 35 mm (rat), TR = 3000 ms, TE = 40 ms, slice thickness = 2 mm, imaging matrix = 128 × 128, number of averages = 4. Before CEST acquisition, the B0 field was first corrected by 3D gradient shimming, which adjusted high-order gradient shimming currents according to the derived B0 map. Then, the RF field and center frequency were calibrated in the pre-scan protocol. CEST imaging sequence used a frequency-selective,


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continuous wave (CW) pulse for pre-saturation, and echo planar imaging (EPI) for image acquisition. The CEST imaging and Z-spectra of phantoms were acquired, which ranged from 5 to -5 ppm, with the use of a B1 of 3.6 μT (155 Hz) and a saturation time of 2 seconds. The GluCEST imaging of rats ranged from 5 to 5 ppm with a B1 of 5.9 μT (250 Hz) and a saturation time of 2 seconds. Control images (S0) were obtained at an offset of 300 ppm for normalization, and GluCEST was measured at 3 ppm.18 Other sequence parameters of phantoms and rats were as follows: FOV = 50 mm × 50 mm (phantom), FOV = 35 mm × 35 mm (rat), TR = 4100 ms, TE = 42 ms, slice thickness = 2 mm, imaging matrix = 128×128, number of averages = 2. Static magnetic field (B0) inhomogeneity and radiofrequency field (B1) inhomogeneity were corrected using B0 and B1 maps generated from the same brain slice, as previously described.19 Specifically, the Zspectra was interpolated, and the position of the minimum was determined. After re-aligning the zero frequency with the minimum voxel-by-voxel, the Z-spectra was shifted and corrected accordingly. The CEST data were processed using Matlab 7 software (Mathworks, Natick MA, USA). Z-spectra were calculated from the normalized images for the ROI outlined in each phantom compartment. Acquired images were used to generate a GluCEST contrast map using the following Equation (1): GluCESTasym =

S( ―3ppm) ― S( + 3ppm) S0

(1)

Neurological scores Posttraumatic neurological impairment was assessed using a 10-point modified neurological severity score (mNSS).56 The scoring system included 10 clinical parameters, including motor function, alertness and physiological behavior. One point was given for failing an appointed task, while no point was given for succeeding. A maximum of 10 points, in which all task failed, indicated severe neurological dysfunction. In the present study, the mNSS was assessed before injury, and at 1 hour, 24 hours, 3 days, 7 days and 14 days after injury. Task performance was scored by 2 investigators who were blinded to the animal groups. Cognitive function testing Cognitive function, particularly spatial memory and spatial learning, was assessed using the MWM at 14 days post-injury.57 The MWM system was composed of a black circular pool (150 cm in diameter) of water (temperature at 25 ± 1 °C) divided into four quadrants, and the platform (10 cm×10 cm) was hidden in one these quadrants located 25 cm from the side-wall. Animals were tested using four trials per day, over 5



consecutive days. The starting position was changed after each trial. The animal was gently placed in the tank facing the wall, and allowed to swim for 120 seconds to find the platform. If the animal failed to find the platform, it was placed on the platform and allowed to remain for 10 seconds. To test memory retention, the probe trial, which involved the removal of the platform, was administered 24 hours after the completion of the platform testing. Animal movement was monitored using a video camera, which was connected to a computerized image analysis system (Morris, Mobile Datum Inc., Shanghai, China). Mean swimming speed (cm/s), latency to the platform (maximum of 120 seconds), and time spent in the correct quadrant (%) were recorded. The evaluators were blinded to the animal group. Brain tissue preparation and evaluation Rats from the TBI and sham group were transcardially perfused with saline, followed by 4 % paraformaldehyde. Brains were removed and post-fixed in paraformaldehyde at 4°C for one hour, and processed and embedded in paraffin. Axial tissue sections of 4 μm were mounted on coated slides and dried overnight at 37°C. Standard H&E staining was performed for neuropathological evaluation. Nissl staining was used to evaluate neuronal apoptosis. The sections underwent xylene dewaxing and alcohol gradient rehydration, and stained with Nissl solution (Beyotime Biotech Inc., Shanghai, China). Neuronal degeneration was assessed after TBI using FJB staining.58 Briefly, the sections were rinsed in distilled H2O (dH2O) and incubated at room temperature for 10 minutes in 0.06% potassium permanganate to ensure background suppression. After rinsing in dH2O for 2 minutes, the sections were incubated for 20 minutes in a freshly prepared 0.0004% FJB solution (AG310, FJB; Millipore Corporation, Billerica, USA). Finally, the sections were rinsed for one minute in each of three dH2O washes, air-dried for one hour, immersed in xylene and mounted. Astrocytes and activated glia were identified by GFAP staining, which was carried out as described previously.59 The sections were firstly blocked with 5% goat serum (ZLI-9056; Zhongshan Golden Bridge Biotechnology CO.LTD., Beijing, China) plus 0.2% Triton X-100 (T9284; Sigma Aldrich, St. Louis, MO, USA) Beyotime Biotech Inc., Shanghai, China) for one hour at room temperature. Then subjected to a 20 minute wash in a 1% solution of sodium borohydride and incubated in the primary antibody (anti-GFAP, 1:150K; Dako North America, Inc., Carpenteria, CA) diluted in 0.05 M KPBS + 0.4% Triton X-100 for 48 hours. After several rinses in PBS, the slides were incubated for the secondary antibody (1:600) with


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fluorescent-labeled (Alexa Flour 488; Invitrogen, Molecular Probes, Eugene, OR, USA) for one hour. The sections were cover-slipped with polar mounting medium containing antifade reagent with DAPI (C1006; Beyotime Biotech Inc., Shanghai, China). The sections were then examined using an epifluorescent microscope (Olympus BX-51, Olympus, Tokyo, Japan). Using a × 40 objective, five randomly selected from the hippocampus, nonoverlapping fields with an area of 1350 mm width and 1060 mm height for GFAPpositive reactive astrocytes were examined. Cytokine measurements To quantify the release of cytokines from the brain after TBI, another set of animals (n = 5, each group) were euthanized before injury (baseline), and at 1, 3, 7, and 14 days after TBI. Then, the brains were carefully harvested. The lesion area and ipsilateral hippocampus tissues were isolated, snap-frozen in liquid nitrogen, and stored at -80°C until use. Next, the tissues were homogenized and freeze-thawed for three times in PBS, followed by centrifugation at 14,937 x g at 4˚C for 10 minutes. The supernatant was collected as the protein sample, and the protein concentration was detected using a BCA Protein Quantitative Kit with reference to the protocol of the manufacturer. IL-6 levels were detected using a rat IL-6 ELISA kit (catalogue no. EK0412) and TNF-α levels were detected using a rat TNF-α ELISA kit (catalogue no. EK0526; all Wuhan Boster Biological Technology, Ltd., China), following the manufacturer's protocols. Tissue cytokine concentrations were expressed as picograms of antigen per milligram of protein (pg/mg protein). Statistical analysis Unless specified, all values are presented as mean ± standard error of the mean (SEM). One-way analysis of variance (ANOVA) and Student’s t-test were applied to compare among/between groups. All statistical analyses were performed using the SPSS software (Version 22, Chicago, IL, USA). A p-value < 0.05 was considered statistically significant.

Abbreviations



TBI = Traumatic brain injury; GluCEST = Glutamate chemical exchange saturation transfer; 1H-MRS = Proton magnetic resonance spectroscopy; Glu = Glutamate; NAA = N-acetylaspartic acid; Cr = Creatine; Gln = Glutamine; Asp = Asparaginic acid; GABA = γ-aminobutyric acid; mNSS = Modified neurologicall severity score; ROI = Region of interest; T2w = T2-weighted; MWM = Morris water maze; H&E = Haematoxylin and eosin; FJB = Fluoro-jade B; GFAP = glial fibrillary acidic protein; DG = dentate gyrus; APTw = Amide proton transfer-weighted; PBS

= phosphate-buffered saline; FOV = field of view; dH2O =

distilled H2O; SEM = standard error of the mean; ANOVA = Analysis of variance.

Author Contributions ZZ carried out the TBI surgeries, rat behavior, MRI acquisition and wrote the manuscript. ZZ, YC, ZD, HZ, PC, and ZS supported several experiments and carried out the acquisition and interpretation of the MRI data. BZ undertook the immunohistochemistry analyses. ZZ, ZS, XZ, and YM undertook the MRI data processing and statistical analyses. RW participated in the technical support, obtaining of the funding, conception and design, and revision of the manuscript. All authors read, provided the input into, and approved the final manuscript.

Funding This study was supported in part by grants from the National Natural Science Foundation of China (Grant No. 81471730) from Dr. Renhua Wu and Education Department Foundation of Guangdong Province (Grant No. 2017KQNCX071) from Dr. Zerui Zhuang.

Notes


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The authors declare no competing financial interest.

Acknowledgements Authors would like to express their gratitude to Dr. Stanley Lin for his assistance in the revision of the manuscript.

References 1.

Maas, A. I., Stocchetti, N., and Bullock, R. (2008) Moderate and severe traumatic brain injury in adults.

The Lancet. Neurology. 7, 728-741. 2.

Prins, M. L., and Giza, C. C. (2012) Repeat traumatic brain injury in the developing brain. International

journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience. 30, 185-190. 3.

Brazinova, A., Rehorcikova, V., Taylor, M. S., Buckova, V., Majdan, M., Psota, M., Peeters, W., Feigin,

V., Theadom, A., Holkovic, L., and Synnot, A. (2016) Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review. Journal of neurotrauma. 4.

LaPlaca, M. C., Simon, C. M., Prado, G. R., and Cullen, D. K. (2007) CNS injury biomechanics and

experimental models. Progress in brain research. 161, 13-26. 5.

Greig, N. H., Tweedie, D., Rachmany, L., Li, Y., Rubovitch, V., Schreiber, S., Chiang, Y. H., Hoffer,

B. J., Miller, J., Lahiri, D. K., Sambamurti, K., Becker, R. E., and Pick, C. G. (2014) Incretin mimetics as pharmacologic tools to elucidate and as a new drug strategy to treat traumatic brain injury. Alzheimer's & dementia : the journal of the Alzheimer's Association. 10, S62-75.



6.

Morganti-Kossmann, M. C., Rancan, M., Stahel, P. F., and Kossmann, T. (2002) Inflammatory response

in acute traumatic brain injury: a double-edged sword. Current opinion in critical care. 8, 101-105. 7.

Barkhoudarian, G., Hovda, D. A., and Giza, C. C. (2016) The Molecular Pathophysiology of Concussive

Brain Injury - an Update. Physical medicine and rehabilitation clinics of North America. 27, 373-393. 8.

Bullock, R., Zauner, A., Woodward, J. J., Myseros, J., Choi, S. C., Ward, J. D., Marmarou, A., and

Young, H. F. (1998) Factors affecting excitatory amino acid release following severe human head injury. Journal of neurosurgery. 89, 507-518. 9.

Kumar, A., and Loane, D. J. (2012) Neuroinflammation after traumatic brain injury: opportunities for

therapeutic intervention. Brain, behavior, and immunity. 26, 1191-1201. 10. Nandi, P., and Lunte, S. M. (2009) Recent trends in microdialysis sampling integrated with conventional and microanalytical systems for monitoring biological events: a review. Analytica chimica acta. 651, 1-14. 11. Georgieva, J., Luthman, J., Mohringe, B., and Magnusson, O. (1993) Tissue and microdialysate changes after repeated and permanent probe implantation in the striatum of freely moving rats. Brain research bulletin. 31, 463-470. 12. Marino, S., Ciurleo, R., Bramanti, P., Federico, A., and De Stefano, N. (2011) 1H-MR spectroscopy in traumatic brain injury. Neurocritical care. 14, 127-133. 13. Xu, S., Zhuo, J., Racz, J., Shi, D., Roys, S., Fiskum, G., and Gullapalli, R. (2011) Early microstructural and metabolic changes following controlled cortical impact injury in rat: a magnetic resonance imaging and spectroscopy study. Journal of neurotrauma. 28, 2091-2102. 14. Harris, J. L., Yeh, H. W., Choi, I. Y., Lee, P., Berman, N. E., Swerdlow, R. H., Craciunas, S. C., and Brooks, W. M. (2012) Altered neurochemical profile after traumatic brain injury: (1)H-MRS biomarkers of


Page 16 of 33

Page 17 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


pathological mechanisms. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 32, 2122-2134. 15. Cai, K., Haris, M., Singh, A., Kogan, F., Greenberg, J. H., Hariharan, H., Detre, J. A., and Reddy, R. (2012) Magnetic resonance imaging of glutamate. Nature medicine. 18, 302-306. 16. Bagga, P., Crescenzi, R., Krishnamoorthy, G., Verma, G., Nanga, R. P., Reddy, D., Greenberg, J., Detre, J. A., Hariharan, H., and Reddy, R. (2016) Mapping the alterations in glutamate with GluCEST MRI in a mouse model of dopamine deficiency. Journal of neurochemistry. 139, 432-439. 17. Kogan, F., Hariharan, H., and Reddy, R. (2013) Chemical Exchange Saturation Transfer (CEST) Imaging: Description of Technique and Potential Clinical Applications. Current radiology reports. 1, 102114. 18. Haris, M., Nath, K., Cai, K., Singh, A., Crescenzi, R., Kogan, F., Verma, G., Reddy, S., Hariharan, H., Melhem, E. R., and Reddy, R. (2013) Imaging of glutamate neurotransmitter alterations in Alzheimer's disease. NMR in biomedicine. 26, 386-391. 19. Crescenzi, R., DeBrosse, C., Nanga, R. P., Reddy, S., Haris, M., Hariharan, H., Iba, M., Lee, V. M., Detre, J. A., Borthakur, A., and Reddy, R. (2014) In vivo measurement of glutamate loss is associated with synapse loss in a mouse model of tauopathy. NeuroImage. 101, 185-192. 20. Bagga, P., Pickup, S., Crescenzi, R., Martinez, D., Borthakur, A., D'Aquilla, K., Singh, A., Verma, G., Detre, J. A., Greenberg, J., Hariharan, H., and Reddy, R. (2018) In vivo GluCEST MRI: Reproducibility, background contribution and source of glutamate changes in the MPTP model of Parkinson's disease. Scientific reports. 8, 2883. 21. Crescenzi, R., DeBrosse, C., Nanga, R. P., Byrne, M. D., Krishnamoorthy, G., D'Aquilla, K., Nath, H.,



Morales, K. H., Iba, M., Hariharan, H., Lee, V. M., Detre, J. A., and Reddy, R. (2017) Longitudinal imaging reveals subhippocampal dynamics in glutamate levels associated with histopathologic events in a mouse model of tauopathy and healthy mice. Hippocampus. 27, 285-302. 22. Pepin, J., Francelle, L., Carrillo-de Sauvage, M. A., de Longprez, L., Gipchtein, P., Cambon, K., Valette, J., Brouillet, E., and Flament, J. (2016) In vivo imaging of brain glutamate defects in a knock-in mouse model of Huntington's disease. NeuroImage. 139, 53-64. 23. Davis, K. A., Nanga, R. P., Das, S., Chen, S. H., Hadar, P. N., Pollard, J. R., Lucas, T. H., Shinohara, R. T., Litt, B., Hariharan, H., Elliott, M. A., Detre, J. A., and Reddy, R. (2015) Glutamate imaging (GluCEST) lateralizes epileptic foci in nonlesional temporal lobe epilepsy. Science translational medicine. 7, 309ra161. 24. Roalf, D. R., Nanga, R. P. R., Rupert, P. E., Hariharan, H., Quarmley, M., Calkins, M. E., Dress, E., Prabhakaran, K., Elliott, M. A., Moberg, P. J., Gur, R. C., Gur, R. E., Reddy, R., and Turetsky, B. I. (2017) Glutamate imaging (GluCEST) reveals lower brain GluCEST contrast in patients on the psychosis spectrum. Molecular psychiatry. 22, 1298-1305. 25. Dai, S. S., Zhou, Y. G., Li, W., An, J. H., Li, P., Yang, N., Chen, X. Y., Xiong, R. P., Liu, P., Zhao, Y., Shen, H. Y., Zhu, P. F., and Chen, J. F. (2010) Local glutamate level dictates adenosine A2A receptor regulation of neuroinflammation and traumatic brain injury. The Journal of neuroscience : the official journal of the Society for Neuroscience. 30, 5802-5810. 26. Hinzman, J. M., Thomas, T. C., Quintero, J. E., Gerhardt, G. A., and Lifshitz, J. (2012) Disruptions in the regulation of extracellular glutamate by neurons and glia in the rat striatum two days after diffuse brain injury. Journal of neurotrauma. 29, 1197-1208. 27. Amorini, A. M., Lazzarino, G., Di Pietro, V., Signoretti, S., Lazzarino, G., Belli, A., and Tavazzi, B.


Page 18 of 33

Page 19 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(2017) Severity of experimental traumatic brain injury modulates changes in concentrations of cerebral free amino acids. Journal of cellular and molecular medicine. 21, 530-542. 28. Prins, M., Greco, T., Alexander, D., and Giza, C. C. (2013) The pathophysiology of traumatic brain injury at a glance. Disease models & mechanisms. 6, 1307-1315. 29. Walker, K. R., and Tesco, G. (2013) Molecular mechanisms of cognitive dysfunction following traumatic brain injury. Frontiers in aging neuroscience. 5, 29. 30. Chamoun, R., Suki, D., Gopinath, S. P., Goodman, J. C., and Robertson, C. (2010) Role of extracellular glutamate measured by cerebral microdialysis in severe traumatic brain injury. Journal of neurosurgery. 113, 564-570. 31. Arundine, M., and Tymianski, M. (2004) Molecular mechanisms of glutamate-dependent neurodegeneration in ischemia and traumatic brain injury. Cellular and molecular life sciences : CMLS. 61, 657-668. 32. Yi, J. H., and Hazell, A. S. (2006) Excitotoxic mechanisms and the role of astrocytic glutamate transporters in traumatic brain injury. Neurochemistry international. 48, 394-403. 33. Zhong, C., Zhao, X., Sarva, J., Kozikowski, A., Neale, J. H., and Lyeth, B. G. (2005) NAAG peptidase inhibitor reduces acute neuronal degeneration and astrocyte damage following lateral fluid percussion TBI in rats. Journal of neurotrauma. 22, 266-276. 34. Kosaki, Y., Lin, T. C., Horne, M. R., Pearce, J. M., and Gilroy, K. E. (2014) The role of the hippocampus in passive and active spatial learning. Hippocampus. 24, 1633-1652. 35. Zhang, H., Wang, W., Jiang, S., Zhang, Y., Heo, H. Y., Wang, X., Peng, Y., Wang, J., and Zhou, J. (2017) Amide proton transfer-weighted MRI detection of traumatic brain injury in rats. Journal of cerebral



blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 37, 3422-3432. 36. Wang, W., Zhang, H., Lee, D. H., Yu, J., Cheng, T., Hong, M., Jiang, S., Fan, H., Huang, X., Zhou, J., and Wang, J. (2017) Using functional and molecular MRI techniques to detect neuroinflammation and neuroprotection after traumatic brain injury. Brain, behavior, and immunity. 64, 344-353. 37. Zhou, J., Payen, J. F., Wilson, D. A., Traystman, R. J., and van Zijl, P. C. (2003) Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nature medicine. 9, 1085-1090. 38. Selwyn, R., Hockenbury, N., Jaiswal, S., Mathur, S., Armstrong, R. C., and Byrnes, K. R. (2013) Mild traumatic brain injury results in depressed cerebral glucose uptake: An (18)FDG PET study. Journal of neurotrauma. 30, 1943-1953. 39. Jin, T., Mehrens, H., Wang, P., and Kim, S. G. (2018) Chemical exchange-sensitive spin-lock MRI of glucose analog 3-O-methyl-d-glucose in normal and ischemic brain. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 38, 869880. 40. Tu, T. W., Ibrahim, W. G., Jikaria, N., Munasinghe, J. P., Witko, J. A., Hammoud, D. A., and Frank, J. A. (2018) On the detection of cerebral metabolic depression in experimental traumatic brain injury using Chemical Exchange Saturation Transfer (CEST)-weighted MRI. Scientific reports. 8, 669. 41. Morganti-Kossmann, M. C., Satgunaseelan, L., Bye, N., and Kossmann, T. (2007) Modulation of immune response by head injury. Injury. 38, 1392-1400. 42. Stover, J. F., Schoning, B., Beyer, T. F., Woiciechowsky, C., and Unterberg, A. W. (2000) Temporal profile of cerebrospinal fluid glutamate, interleukin-6, and tumor necrosis factor-alpha in relation to brain


Page 20 of 33

Page 21 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


edema and contusion following controlled cortical impact injury in rats. Neuroscience letters. 288, 25-28. 43. Ziebell, J. M., and Morganti-Kossmann, M. C. (2010) Involvement of pro- and anti-inflammatory cytokines and chemokines in the pathophysiology of traumatic brain injury. Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics. 7, 22-30. 44. Frugier, T., Morganti-Kossmann, M. C., O'Reilly, D., and McLean, C. A. (2010) In situ detection of inflammatory mediators in post mortem human brain tissue after traumatic injury. Journal of neurotrauma. 27, 497-507. 45. Fluiter, K., Opperhuizen, A. L., Morgan, B. P., Baas, F., and Ramaglia, V. (2014) Inhibition of the membrane attack complex of the complement system reduces secondary neuroaxonal loss and promotes neurologic recovery after traumatic brain injury in mice. Journal of immunology. 192, 2339-2348. 46. Alawieh, A., Langley, E. F., Weber, S., Adkins, D., and Tomlinson, S. (2018) Identifying the role of complement in triggering neuroinflammation after traumatic brain injury. The Journal of neuroscience : the official journal of the Society for Neuroscience. 47. Neumann, H., Schweigreiter, R., Yamashita, T., Rosenkranz, K., Wekerle, H., and Barde, Y. A. (2002) Tumor necrosis factor inhibits neurite outgrowth and branching of hippocampal neurons by a rho-dependent mechanism. The Journal of neuroscience : the official journal of the Society for Neuroscience. 22, 854-862. 48. Chen, S. F., Hsu, C. W., Huang, W. H., and Wang, J. Y. (2008) Post-injury baicalein improves histological and functional outcomes and reduces inflammatory cytokines after experimental traumatic brain injury. British journal of pharmacology. 155, 1279-1296. 49. Yan, E. B., Hellewell, S. C., Bellander, B. M., Agyapomaa, D. A., and Morganti-Kossmann, M. C. (2011) Post-traumatic hypoxia exacerbates neurological deficit, neuroinflammation and cerebral metabolism



in rats with diffuse traumatic brain injury. Journal of neuroinflammation. 8, 147. 50. Byrnes, K. R., Loane, D. J., Stoica, B. A., Zhang, J., and Faden, A. I. (2012) Delayed mGluR5 activation limits neuroinflammation and neurodegeneration after traumatic brain injury. Journal of neuroinflammation. 9, 43. 51. Block, M. L., Zecca, L., and Hong, J. S. (2007) Microglia-mediated neurotoxicity: uncovering the molecular mechanisms. Nature reviews. Neuroscience. 8, 57-69. 52. Wang, J. Y., Huang, Y. N., Chiu, C. C., Tweedie, D., Luo, W., Pick, C. G., Chou, S. Y., Luo, Y., Hoffer, B. J., Greig, N. H., and Wang, J. Y. (2016) Pomalidomide mitigates neuronal loss, neuroinflammation, and behavioral impairments induced by traumatic brain injury in rat. Journal of neuroinflammation. 13, 168. 53. Wu, R., Liu, C. M., Liu, P. K., and Sun, P. Z. (2012) Improved measurement of labile proton concentration-weighted chemical exchange rate (k(ws)) with experimental factor-compensated and T(1) normalized quantitative chemical exchange saturation transfer (CEST) MRI. Contrast media & molecular imaging. 7, 384-389. 54. Tang, X., Dai, Z., Xiao, G., Yan, G., Shen, Z., Zhang, T., Zhang, G., Zhuang, Z., Shen, Y., Zhang, Z., Hu, W., and Wu, R. (2017) Nuclear Overhauser Enhancement-Mediated Magnetization Transfer Imaging in Glioma with Different Progression at 7 T. ACS chemical neuroscience. 8, 60-66. 55. Chen, X., Wu, S., Chen, C., Xie, B., Fang, Z., Hu, W., Chen, J., Fu, H., and He, H. (2017) Omega-3 polyunsaturated fatty acid supplementation attenuates microglial-induced inflammation by inhibiting the HMGB1/TLR4/NF-kappaB pathway following experimental traumatic brain injury. Journal of neuroinflammation. 14, 143. 56. Stahel, P. F., Shohami, E., Younis, F. M., Kariya, K., Otto, V. I., Lenzlinger, P. M., Grosjean, M. B.,


Page 22 of 33

Page 23 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Eugster, H. P., Trentz, O., Kossmann, T., and Morganti-Kossmann, M. C. (2000) Experimental closed head injury: analysis of neurological outcome, blood-brain barrier dysfunction, intracranial neutrophil infiltration, and neuronal cell death in mice deficient in genes for pro-inflammatory cytokines. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 20, 369-380. 57. Immonen, R. J., Kharatishvili, I., Grohn, H., Pitkanen, A., and Grohn, O. H. (2009) Quantitative MRI predicts long-term structural and functional outcome after experimental traumatic brain injury. NeuroImage. 45, 1-9. 58. Schmued, L. C., and Hopkins, K. J. (2000) Fluoro-Jade B: a high affinity fluorescent marker for the localization of neuronal degeneration. Brain research. 874, 123-130. 59. Zhuo, J., Xu, S., Proctor, J. L., Mullins, R. J., Simon, J. Z., Fiskum, G., and Gullapalli, R. P. (2012) Diffusion kurtosis as an in vivo imaging marker for reactive astrogliosis in traumatic brain injury. NeuroImage. 59, 467-477.



For Table of Contents Use Only Manuscript title: Mapping the changes of glutamate using GluCEST technique in a traumatic brain injury model: a longitudinal pilot study Authors: Zerui Zhuang, Zhiwei Shen, Yanzi Chen, Zhuozhi Dai, Xiaolei Zhang, Yifei Mao, Bingna Zhang, Haiyan Zeng, Peidong Chen and Renhua Wu Table of Contents Graphic


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Figure 1 GluCEST MRI data of different Glu concentrations and other neurometabolites at physiological concentrations. (A-B) The Z-spectra and GluCEST asymmetry curves for different Glu concentrations are shown. (C) The linear regression analysis revealed an excellent correlation between Glu concentration and the GluCEST effect (R2 = 0.9793). (D) The GluCEST map of pH = 7 Glu phantoms at different Glu concentrations. (E) The GluCEST map of other neurometabolites at their physiological concentrations. It was found that other metabolites contribute negligible CEST effects to GluCEST. Glu = Glutamate.


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Figure 2 The modified neurological severity score (mNSS) of TBI. Data are expressed as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001.



Figure 3 (A) The T2w image revealed the ROIs in the coronal brain slices for the ipsilateral (injured) cortex (Ips_cor), contralateral cortex (Con_cor), ipsilateral hippocampus (Ips_hip) and contralateral hippocampus (Con_hip). Red arrows indicate ROI tissues. (B) ROIs for the GluCEST image were manually drawn on the T2w image. Red arrows indicate ROI tissues.


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Figure 4 (A) The representative T2w images at different time points after TBI. Red arrows indicate injured cortex. (B) The representative GluCEST maps at different time points after TBI. Red arrows indicate injured cortex. (C) Regional GluCEST values at different time points after TBI for the ipsilateral cortex of shaminjured rats (Sham), and for the core lesion of the ipsilateral cortex (Ips_cor) and contralateral cortex (Con_cor) of TBI rats. (D) Regional GluCEST values at different time points after TBI for the ipsilateral hippocampus of sham-injured rats (Sham), and for the ipsilateral hippocampus (Ips_hip) and contralateral hippocampus (Con_hip) of TBI rats. Data are expressed as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001.



Figure 5 Cognitive outcome was assessed using an acquisition paradigm of the MWM test. (A) Swimming speed did not differ between the TBI and sham-injured rats (p > 0.05). (B) The spatial learning and memory test at post-injury days 14-18 revealed that the latency was significantly shortened during the 5 days test in the two groups, but the latency in the TBI group was always greater than that in the sham group on corresponding days after TBI. (C) The memory probe test on post injury Day 19 showed that TBI rats spent less time in the correct quadrant than sham-injured rats. (D) A negative correlation between the GluCEST% of the ipsilateral hippocampus on Day 3 after TBI and the time in the correct quadrant was found in TBI rats. Data are expressed as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001.


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Figure 6 Representative images of the immunohistochemical staining for the ipsilateral hippocampus (Sham and TBI) with H&E, Nissl, and FJB. (A) Representative H&E staining for the ipsilateral hippocampus. White arrows indicate normal neurons; Black arrows indicate the areas of massive neuron loss in the hippocampus. (B) Representative Nissl staining for the ipsilateral hippocampus. White arrows indicate normal neurons; Black arrows indicate apoptotic neurons. (C) Representative FJB staining for the ipsilateral hippocampus. No degenerating neurons were detected in the hippocampus of sham rats. FJB positivity was found in the DG and hilus of the ipsilateral hippocampus of TBI rats. White arrows indicate degenerating neurons. Scale bars = 20 μm. DG = dentate gyrus.



Figure 7 Immunofluorescence labeling of astrocytes (GFAP, green) from the ipsilateral hippocampus of sham-injured rats (Sham, A), and from the contralateral hippocampus (Con_hip, B) and ipsilateral hippocampus (Ips_hip, C) of TBI rats. (D) Bar graphs of mean densities of GFAP-positive reactive astrocytes after TBI (n = 5 per group). The total number of GFAP-positive astrocytes was expressed as the mean number per field of view. A significant increase in the number of GFAP-positive astrocytes was observed in the ipsilateral hippocampus of injured rats, as compared to contralateral hippocampus, and sham-injured rats. Data are expressed as mean ± SEM. *p < 0.05, **p < 0.01, ***p < 0.001. Scale bars = 20 μm.


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Figure 8 Concentration (pg/mg protein) of cytokines IL-6 and TNF-α in the core lesion of the ipsilateral cortex (Ips_cor) and ipsilateral hippocampus (Ips_hip). (A) The concentration of IL-6 peaked on Day 1 after injury in the Ips_cor, and peaked on Day 3 in the Ips_hip. (B) The concentration of TNF-α peaked on Day 1 after injury in the Ips_cor, and peaked on Day 3 in the Ips_hip. Data are expressed as mean ± SEM, n = 5 per group per time point. *p < 0.05.


Mapping the Changes of Glutamate Using Glutamate Chemical

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