Adenosine kinase protects against acetaminophen-induced acute liver injury by activating autophagy in hepatocytes.

Acute liver injury (ALI) is a common life-threatening condition with a high mortality rate due to liver disease-related death. However, current therapeutic interventions for ALI remain ineffective, and the development of effective novel therapies is urgently needed. Liver samples from patients with drug-induced ALI were collected to detect adenosine kinase (ADK) expression. Male C57BL/6 J mice, hepatocyte-specific ADK knockout (ADKHKO) mice, and their controls (ADKf/f) were exposed to acetaminophen (APAP) and other treatments to investigate the mechanisms of APAP-related ALI. ADK expression was significantly decreased in APAP-injured livers. Hepatocyte-specific ADK deficiency exacerbated APAP-induced ALI, while a gain-of-function approach delivering AAV-ADK, markedly alleviated APAP-induced ALI, as indicated by changes in alanine aminotransferases (ALT) levels, aspartate aminotransferase (AST) levels, neutrophil infiltration and hepatocyte death. This study showed that ADK played a critical role in ALI by activating autophagy through two signaling pathways, the adenosine monophosphate-activated protein kinase (AMPK)-mTOR pathway and the adenosine receptor A1 (ADORA1)-Akt-mTOR pathway. Furthermore, we found that metformin upregulated ADK expression in hepatocytes and protected against APAP-induced ALI. These results demonstrate that ADK is critical in protecting against APAP-induced ALI and that developing therapeutics targeting ADK-adenosine-ADORA1 is a new approach for ALI treatment. Metformin is a potential candidate for preventing ALI by upregulating ADK.

Ag/ZnO microcavities with high sensitivity and self-cleaning properties for fast repetitive SERS detection.

A SERS substrate with high sensitivity and reusability was proposed. The chip consists of multiple ZnO microcavities loaded with silver particles. Based on structural characteristics, this coupling between cavity modes and localized surface plasmon modes can highly localize the electric field, where experimental results revealed a detection limit of 10-11 M for R6G. In addition, during carrier control in semiconductors with localized electromagnetic fields, our substrate also exhibits high self-cleaning efficiency and in situ detection stability. Even in a dry environment, it exhibits excellent light-mediated cleaning ability across multiple reuse test cycles. The convenient, rinse-free substrate, with its cost-effective and sustainable features, shows great promise for the study on detection and degradation of active materials.

Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

OBJECTIVE: To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat (AMLwvf) and renal cell carcinoma (RCC). METHODS: This study retrospectively collected 163 patients with pathologically proven small renal mass, including 118 RCC and 45 AMLwvf patients. Target region of interest (ROI) delineation, followed by texture feature extraction, was performed on a representative slice with the largest lesion area on each phase of the four-phase CT images. Fifteen concatenations of the four-phasic features were fed into 224 classification models (built with 8 classifiers and 28 feature selection methods), classification performances of the 3360 resultant discriminative models were compared, and the top-ranked features were analyzed. RESULTS: Image features extracted from the unenhanced phase (UP) CT image demonstrated dominant classification performances over features from other three phases. The two discriminative models "SVM + t_score" and "SVM + relief" achieved the highest classification AUC of 0.90. The 10 top-ranked features from UP included 1 shape feature, 5 first-order statistics features, and 4 texture features, where the shape feature and the first-order statistics features showed superior discriminative capabilities in differentiating RCC vs. AMLwvf through the t-SNE visualization. CONCLUSION: Image features extracted from UP are sufficient to generate accurate differentiation between AMLwvf and RCC using machine learning-based classification model. KEY POINTS: • Radiomics extracted from unenhanced CT are sufficient to accurately differentiate angiomyolipoma without visible fat and renal cell carcinoma using machine learning-based classification model. • The highest discriminative models achieved an AUC of 0.90 and were based on the analysis of unenhanced CT, alone or in association with images obtained at the nephrographic phase. • Features related to shape and to histogram analysis (first-order statistics) showed superior discrimination compared with gray-level distribution of the image (second-order statistics, commonly called texture features).

Clear cell renal cell carcinoma: the value of sex-specific abdominal visceral fat measured on CT for prediction of Fuhrman nuclear grade.

OBJECTIVE: To explore whether sex-specific abdominal visceral fat composition on CT can predict the Fuhrman nuclear grade of clear cell renal cell carcinoma (ccRCC). METHODS: One hundred seventy-one patients (123 males and 48 females) from four hospitals (multicentre group) and 159 patients (109 males and 50 females) from the cancer imaging archive (TCIA-KIRC group) with pathologically proven ccRCC (multicentre: 124 low grade and 47 high grade; TCIA-KIRC: 79 low grade and 80 high grade) were retrospectively included. Abdominal fat was segmented into subcutaneous fat area (SFA) and visceral fat area (VFA) on CT using ImageJ. The total fat area (TFA) and relative VFA (rVFA) were then calculated. Clinical characteristics (age, sex, waist circumference and maximum tumour diameter) were also assessed. Univariate and multivariate logistic regression analyses were performed to identify the association between general or sex-specific visceral fat composition and Fuhrman grade. RESULTS: Females with high-grade ccRCC from the multicentre group had a higher rVFA (42.4 vs 31.3, p = 0.001) than those with low-grade ccRCC after adjusting for age. There was no significant difference in males. The rVFA remained a stable and independent predictor for females high-grade ccRCC in both the univariate (multicentre: OR 1.205, 95% CI 1.074-1.352, p = 0.001; TCIA-KIRC: OR 1.171, 95% CI 1.016-1.349, p = 0.029) and multivariate (multicentre: OR 1.095, 95% CI 1.024-1.170, p = 0.003; TCIA-KIRC: OR 1.103, 95% CI 1.024-1.187, p = 0.010) models. CONCLUSIONS: Sex-specific visceral fat composition has different values for predicting high-grade ccRCC and could be used as an independent predictor for females with high-grade ccRCC. KEY POINTS: • Visceral fat measurement (rVFA) as an independent predictor for high-grade ccRCC had good predictive power in females, but not in males. • Sex-specific visceral fat composition was significantly associated with high-grade ccRCC in females only. • The rVFA could be considered one of the risk factors for high-grade ccRCC for females.

Prefrontal GABA and glutamate levels correlate with impulsivity and cognitive function of prescription opioid addicts: A 1 H-magnetic resonance spectroscopy study.

AIM: Prescription opioids are psychoactive substances that can elicit many neuropsychological effects. There are no studies that directly demonstrate the effects of prescription opioid addiction (POA) on the human brain. This study aimed to quantify γ-aminobutyric acid (GABA) and glutamate (Glu) levels in the prefrontal cortex (PFC) of POA patients using proton magnetic resonance spectroscopy (1 H-MRS), and to explore their association with impulsive behavior and cognitive impairment. METHODS: Thirty-five patients with a definitive clinical diagnosis of codeine-containing cough syrup dependence and 35 matched healthy controls underwent neuropsychological assessments, namely the Barratt Impulsiveness Scale (BIS-11) and the Montreal Cognitive Assessment Scale (MoCA). Point-resolved spectroscopy was performed to detect GABA and glutamate within the medial PFC, and the corresponding levels were estimated using jMRUI and corrected for fraction of cerebrospinal fluid in the 1 H-MRS voxel. The difference in metabolite levels between groups and the correlation between metabolite levels and psychometric scores in patients were analyzed statistically. RESULTS: The peak level predominantly consisting of GABA with a relatively small influence of other chemicals (GABA+) was lower and that of glutamate was higher in the PFC of POA patients than in healthy controls. GABA+ levels correlated negatively with BIS-11 scores but correlated positively with MoCA scores. In contrast, glutamate levels showed a positive correlation with BIS-11 scores but no significant correlation with MoCA scores. CONCLUSION: The quantitative in vivo measurement of GABA and glutamate levels in the PFC by 1 H-MRS could be a reliable way to evaluate impulsivity and cognitive function of POA.

Eye Gaze Based 3D Triangulation for Robotic Bionic Eyes.

Three-dimensional (3D) triangulation based on active binocular vision has increasing amounts of applications in computer vision and robotics. An active binocular vision system with non-fixed cameras needs to calibrate the stereo extrinsic parameters online to perform 3D triangulation. However, the accuracy of stereo extrinsic parameters and disparity have a significant impact on 3D triangulation precision. We propose a novel eye gaze based 3D triangulation method that does not use stereo extrinsic parameters directly in order to reduce the impact. Instead, we drive both cameras to gaze at a 3D spatial point P at the optical center through visual servoing. Subsequently, we can obtain the 3D coordinates of P through the intersection of the two optical axes of both cameras. We have performed experiments to compare with previous disparity based work, named the integrated two-pose calibration (ITPC) method, using our robotic bionic eyes. The experiments show that our method achieves comparable results with ITPC.

Dynamic Rigid Bodies Mining and Motion Estimation Based on Monocular Camera.

Dynamic object perception is an important yet challenging direction in the field of robot navigation. Without any prior knowledge about motion and objects, a novel dynamic rigid bodies mining and motion estimation method based on monocular camera is proposed in this article. Different from the existing works based on sampling that associate feature points to motion hypotheses according to the reprojection errors, our work endeavors to find the intrinsic relevance among motion hypotheses. To represent this relevance, the concept of the probabilistic field on the Lie group Sim(3) manifold is introduced, which is established using random sampling. It provides a computable way for the regions on the manifold where rigid bodies possibly appear. The probability of a motion hypothesis falling on a region is expressed by its confidence. The regions with large confidences in the probabilistic field are selected as potential rigid bodies, whose corresponding feature points are further sampled for pose calculation. As a result, the randomness of sampling is reduced and the inliers for possible rigid bodies are enhanced, which guarantees the accuracy of motion estimation. On this basis, the tracking of rigid bodies is achieved. The proposed method distinguishes the feature points of dynamic objects with 3-D motion from those in the static background, thus enabling simultaneous localization and mapping (SLAM) to be initialized in dynamic environments. The experimental results on the KITTI, Hopkins 155, and MTPV62 datasets demonstrate the effectiveness. Comparison experiments indicate that our method outperforms the other methods in sensitivity of dynamic objects perception.

Polydopamine-assisted tranilast immobilization on a PLA chamber to enhance fat flaps regeneration by reducing tissue fibrosis.

Tissue engineering chambers (TECs) have been shown to be useful in regenerating adipose tissue. However, tissue fibrosis caused by the chambers compromises the final volume of the newly formed adipose tissue. Surface modifications can compensate for the lack of biocompatibility of an implant. Tranilast (Tra) is an antifibrotic drug used to treat fibrotic pathologies, including keloids and scleroderma. In this study, a polydopamine-assisted tranilast coating (pDA + Tra) was prepared on a polylactic acid (PLA) chamber to minimize tissue fibrosis and achieve a large volume of fat flap regeneration. The in vitro results showed that, in contrast to a PLA chamber, roughness increased, and the fibroblast adhesion and smooth muscle antibody-positive immunoreactivity decreased in the PLA + pDA + Tra chamber. In addition, pedicled adipose tissue flaps were separated from the back of the rabbit and inserted into each chamber using the classic TEC procedure. After 16 weeks, the marked attenuation of fibrosis and promotion of fat regeneration was observed in the PLA + pDA + Tra chamber in contrast to the PLA chamber. Moreover, in contrast to the PLA chamber, Q-PCR results showed that fibrotic factor TGF-ß was significantly reduced, associated with a remarkable increase in adipogenic differentiation transcription factors PPAR-γ and C/EBPα in the PLA + pDA + Tra chamber after 16 weeks (p < 0.05). Thus, PLA chambers loaded with pDA + Tra on the surface have good biocompatibility, and chemical anti-fibrosis reagents can synergistically reduce fibrosis formation while excellently promoting adipose tissue regeneration.

Rapid observation of dispersion curves in system-on-chip devices.

We have developed a rapid detection instrument to characterize the behavior of light on the surface of devices during light-matter interactions. The equipment enables the non-destructive and real-time observations of the dispersion curves for microstructures, providing the basis for a large number of new planar photonic chip applications. The method is based on the traditional prismatic reflection and makes full use of the grating dispersion capabilities, enabling simultaneous multi-wavelength and multi-angle reflectance measurements over a wide range. This method is beneficial for designing new microstructure devices and brings convenience to delicate microstructure processing. The instruments do not require any mechanical scanning, allowing for rapid acquisition, and the integrated and reusable optics make them easily miniaturized. Additionally, the functionalized design allows for spectral analysis applications, such as far-field spectral measurements. The instrument can also be easily integrated into established microscopic imaging systems, extending their observational characterization capabilities as well as accomplishing dynamic monitoring in proven system-on-a-chip devices.

Use of intravoxel incoherent motion MRI to assess placental perfusion in normal and Fetal Growth Restricted pregnancies on their third trimester.

INTRODUCTION: Intravoxel Incoherent Motion (IVIM) MRI is a non-invasive, in vivo techniques which can assess placental perfusion quantitatively, and be useful for evaluating placental microcirculation. Our primary aim was to investigate whether fetal growth restriction (FGR) pregnancies have different placental perfusion and diffusion compared with normal pregnancies using IVIM. A secondary aim was to investigate correlations between placental IVIM parameters and gestational age in normal pregnancy. METHODS: This study population included 17 FGR pregnancies and 36 normal pregnancies between 28 + 3 to 38 + 0 weeks. All women underwent a MRI examination including an IVIM sequence with 9 b-values on a 3.0 T MRI system. The standard diffusion coefficeint (D), pseudodiffusion (D*) and perfusion fraction (f) were calculated. RESULTS: Placental f was significantly lower in the FGR group than that in the normal group (33.96 ± 2.62(%) vs 38.48 ± 5.31(%), p = 0.002). Placental D and D* in two groups showed no statistical significance (P > 0.05). Placental f moderately increased with increasing gestational age in normal pregnancies (r = 0.411, p = 0.013), and there existed a negative correlation between D values and gestational age (r = -0.390, p = 0.019). DISCUSSION: The f values are able to distinguish FGR from normal pregnancies. It can be uses as a feasible index to evaluate placenta perfusion. Gestational age-associated changes in placental IVIM parameters likely reveal trajectories of microvascular perfusion fraction and diffusion characteristics in the normal developing placenta.

Application of amide proton transfer imaging for the diagnosis of neonatal hypoxic-ischemic encephalopathy.

Objective: This study aimed to evaluate cerebral amide proton transfer signal intensity (SI) among controls, hypoxic-ischemic encephalopathy (HIE) neonates with normal conventional magnetic resonance imaging (HIE/MRI-) findings, and HIE neonates with abnormal conventional MRI (HIE/MRI+) findings. Methods: Forty neonates diagnosed with neonatal HIE and sixteen normal neonates were evaluated. All neonates underwent conventional MRI scans and APT imaging. Cerebral APT SIs were compared to identify cerebral regions with significant APT changes among sixteen controls, thirteen HIE/MRI- patients, and twenty-seven HIE/MRI+ patients. Results: Significantly increased APT SIs were observed in the HIE/MRI- group compared with controls, in the left insula, right occipital lobe, left cingulate gyrus (posterior part), and corpus callosum. Significantly increased APT SIs were found in the HIE/MRI+ group compared with controls, in the right anterior temporal lobe (medial part), anterior parts of the right parahippocampal and ambient gyri, left superior temporal gyrus (middle part), left insula, left cingulate gyrus (posterior part), and right lentiform nucleus. No significant APT SI differences were observed in the cerebellum and brainstem among the three groups. Conclusion: Amide proton transfer imaging plays an important role in detecting hypoxic-ischemic encephalopathy regardless of conventional MRI findings. Changes in APT signal intensity may provide important insights into the characterization of the cerebral internal environment. This study suggests that APT imaging could be used as a complement to conventional MRI in the detection of hypoxic-ischemic encephalopathy in clinical practice.

Integrated multiomic approach for identification of novel immunotherapeutic targets in AML.

BACKGROUND: Immunotherapy of acute myeloid leukemia has experienced considerable advances, however novel target antigens continue to be sought after. To this end, unbiased approaches for surface protein detection are limited and integration with other data types, such as gene expression and somatic mutational burden, are poorly utilized. The Cell Surface Capture technology provides an unbiased, discovery-driven approach to map the surface proteins on cells of interest. Yet, direct utilization of primary patient samples has been limited by the considerable number of viable cells needed. METHODS: Here, we optimized the Cell Surface Capture protocol to enable direct interrogation of primary patient samples and applied our optimized protocol to a set of samples from patients with acute myeloid leukemia (AML) to generate the AML surfaceome. We then further curated this AML surfaceome to exclude antigens expressed on healthy tissues and integrated mutational burden data from hematologic cancers to further enrich for targets which are likely to be essential to leukemia biology. Finally, we validated our findings in a separate cohort of AML patient samples. RESULTS: Our protocol modifications allowed us to double the yield in identified proteins and increased the specificity from 54 to 80.4% compared to previous approaches. Using primary AML patient samples, we were able to identify a total of 621 surface proteins comprising the AML surfaceome. We integrated this data with gene expression and mutational burden data to curate a set of robust putative target antigens. Seventy-six proteins were selected as potential candidates for further investigation of which we validated the most promising novel candidate markers, and identified CD148, ITGA4 and Integrin beta-7 as promising targets in AML. Integrin beta-7 showed the most promising combination of expression in patient AML samples, and low or absent expression on healthy hematopoietic tissue. CONCLUSION: Taken together, we demonstrate the feasibility of a highly optimized surfaceome detection method to interrogate the entire AML surfaceome directly from primary patient samples and integrate this data with gene expression and mutational burden data to achieve a robust, multiomic target identification platform. This approach has the potential to accelerate the unbiased target identification for immunotherapy of AML.

Activin receptor-like kinase 7 promotes apoptosis of vascular smooth muscle cells via activating Smad2/3 signaling in diabetic atherosclerosis.

Vascular smooth muscle cells (VSMCs) is a vital accelerator in the late phase of diabetic atherosclerosis, but the underlying mechanism remains unclear. The aim of our study was to investigate whether activin receptor-like kinase 7 (ALK7)-Smad2/3 pathway plays an important role in VSMC apoptosis of diabetic atherosclerosis. It was shown that ALK7 expression was obviously elevated in the aorta of ApoE-/- mice with type 2 diabetes mellitus. Inhibition of ALK7 expression significantly improved the stability of atherosclerotic plaques and reduced cell apoptosis. Further experiments showed that ALK7 knockdown stabilized atherosclerotic plaques by reducing VSMC apoptosis via activating Smad2/3. Our study uncovered the important role of ALK7-Smad2/3 signaling in VSMCs apoptosis, which might be a potential therapeutic target in diabetic atherosclerosis.

Microarray-based gene expression profiles of silkworm brains.

BACKGROUND: Molecular genetic studies of Bombyx mori have led to profound advances in our understanding of the regulation of development. Bombyx mori brain, as a main endocrine organ, plays important regulatory roles in various biological processes. Microarray technology will allow the genome-wide analysis of gene expression patterns in silkworm brains. RESULTS: We reported microarray-based gene expression profiles in silkworm brains at four stages including V7, P1, P3 and P5. A total of 4,550 genes were transcribed in at least one selected stage. Of these, clustering algorithms separated the expressed genes into stably expressed genes and variably expressed genes. The results of the gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis of stably expressed genes showed that the ribosomal and oxidative phosphorylation pathways were principal pathways. Secondly, four clusters of genes with significantly different expression patterns were observed in the 1,175 variably expressed genes. Thirdly, thirty-two neuropeptide genes, six neuropeptide-like precursor genes, and 117 cuticular protein genes were expressed in selected developmental stages. CONCLUSION: Major characteristics of the transcriptional profiles in the brains of Bombyx mori at specific development stages were present in this study. Our data provided useful information for future research.

Two amide glycosides from Portulaca oleracea L. and its bioactivities.

Two novel amide glycosides, named oleraciamide E (1) and oleraciamide F (2), were isolated from the Portulaca oleracea L. Their structures were determined by means of 1D and 2D NMR spectroscopic and UHPLC-ESI-TOF-MS methods. Oleraciamide E (1) exhibited anticholinesterase activity with IC50 values of 52.43 ± 0.33 µM, and presented scavenging activity in 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical quenching assay, with the IC50 values of 24.64 ± 0.33 µM.

Multiphase Contrast-Enhanced CT-Based Machine Learning Models to Predict the Fuhrman Nuclear Grade of Clear Cell Renal Cell Carcinoma.

OBJECTIVE: To investigate the predictive performance of different machine learning models for the discrimination of low and high nuclear grade clear cell renal cell carcinoma (ccRCC) by using multiphase computed tomography (CT)-based radiomic features. MATERIALS AND METHODS: A total of 137 consecutive patients with pathologically proven ccRCC (including 96 low-grade [grade 1 or 2] and 41 high-grade [grade 3 or 4] ccRCC) from January 2011 to January 2019 were enrolled in this retrospective study. Target region of interest (ROI) delineation followed by texture extraction was performed on a representative slice with the largest section of the tumor on the four-phase (unenhanced phase [UP], corticomedullary phase [CMP], nephrographic phase [NP] and excretory phase [EP]) CT images. Fifteen concatenations of the four-phase features were fed into 176 classification models (built with 8 classifiers and 22 feature selection methods), the classification performances of the 2640 resultant discriminative models were compared, and the top-ranked features were analyzed. RESULTS: Image features extracted from the unenhanced phase (UP) CT images demonstrated a dominant classification performance over features from the other three phases. The discriminative model "Bagging + CMIM" achieved the highest classification AUC of 0.75. The top-ranked features from the UP included one shape-based feature and five first-order statistical features. CONCLUSION: Image features extracted from the UP are more effective than other CT phases in differentiating low and high nuclear grade ccRCC based on machine learning-based classification modeling.

Preparation of a graphene-phosphorene composite by pressure quenching and its ferromagnetism.

A graphene-phosphorene composite was prepared by quenching the pressure in a LECO high-temperature and high-pressure hydrothermal reaction device. The results suggest that the graphene-phosphorene composite is a layered sandwich structure and shows strong ferromagnetism due to the P-C and P-O-C bonds formed between the graphene and phosphorene.

Feature-Related Searching Control Model for Curve Detection.

In this paper, a novel method is proposed for curve detection in images using a feature-related searching control model. It is composed of three parts: 1) prediction; 2) searching; and 3) updating. First, curve related features are modeled to a three order array. Then, equations of the prediction, searching, and curve parameter updating are deduced. Third, an optimal model for curve parameter estimation during iterations is given. Based on the proposed model, a curve detection algorithm is designed. Experiments on thousands of images demonstrate the effectiveness and advantages of the proposed method. Comparison experiments with state-of-the-art methods show that the proposed method outperforms the existing methods on most indexes. Our method can describe the contents of original images more completely with fewer curves. The contour evaluation framework and the Berkeley segmentation dataset are used to evaluate the performances of different curve detection methods. The proposed method can also detect curves in the order relates to their importance, which has been validated in experiments.

Early identification of neonatal mild hypoxic-ischemic encephalopathy by amide proton transfer magnetic resonance imaging: A pilot study.

PURPOSE: This study aimed to evaluate the amide proton transfer (APT) values in neonates with mild hypoxic-ischemic encephalopathy (HIE) using APT imaging. METHOD: A total of 30 full-term neonates with mild HIE (16 males and 14 females; mean postnatal age 4.2 days, age range 2-7 days) and 12 normal neonates (six males and six females; mean postnatal age 3.3 days, age range 2-5 days) underwent conventional magnetic resonance imaging and APT imaging. APT measurements were performed in multiple regions of interest (ROIs) in the brain. APT values were statistically analyzed to assess for significant differences between the mild HIE and normal neonates in different regions of the brain, and correlation with neonatal gestational age. RESULTS: In 30 neonates with mild HIE, 10% (3/30) of the HIE patients had normal conventional MRI. There were significant differences in APT values of the HIE group in bilateral caudate, bilateral thalamus, bilateral centrum semiovale and left globus pallidus/putamen (p < 0.05), and no statistical difference was observed in right globus pallidus/putamen (p = 0.051) and brainstem (p = 0.073) between the two groups. Furthermore, APT values in bilateral caudate, bilateral globus pallidus/putamen, bilateral thalamus, and brainstem regions (p < 0.05) exhibited positive linear correlations with gestational age in the control group, except for bilateral centrum semiovale (right: Pearson's r = 0.554, p = 0.062; left: Pearson's r = 0.561, p = 0.058). In the mild HIE groups, no significant correlation with gestational age was found in all regions. CONCLUSIONS: APT imaging is a feasible and useful technique with diagnostic capability for neonatal HIE.

Reliability of Glutamate Quantification in Human Nucleus Accumbens Using Proton Magnetic Resonance Spectroscopy at a 70-cm Wide-Bore Clinical 3T MRI System.

The human nucleus accumbens is a challenging region to study using proton magnetic resonance spectroscopy (1H-MRS) on a 70-cm wide-bore clinical 3T MRI system. The aim of this study was to investigate the reliability for quantitative measurement of glutamate concentration in the nucleus accumbens using a 70-cm wide-bore clinical 3T MRI. 1H-MRS of the nucleus accumbens was acquired using the Point-Resolved Spectroscopic Sequence (PRESS) with echo time of 40 ms from 10 healthy volunteers (5 female; age range: 18-30 years) on two separate visits (a baseline, and 1-month time point). The Java-based Magnetic Resonance User Interface (jMRUI) software package was used to quantitatively measure the absolute metabolite concentrations. The test-retest reliability and reproducibility were assessed using intraclass correlations coefficients (ICC), and coefficients of variation (CV). Glutamate concentrations were similar across visits (P = 0.832). Reproducibility measures for all metabolites were good with CV ranging from 7.8 to 14.0%. The ICC values of all metabolites for the intra-class measures were excellent (ICC > 0.8), except that the reliability for Glx (glutamate + glutamine) was good (ICC = 0.768). Pearson correlations for all metabolites were all highly significant (r = 0.636-0.788, P < 0.05). In conclusion, the short-echo-time PRESS can reliably obtain high quality glutamate spectrum from a ~3.4 cm3 voxel of the nucleus accumbens using a 70-cm wide-bore clinical 3T MRI.