Dynamic Simulation of Nitrifying Microbial Communities for Establishing Acidic Partial Nitritation in Suspended Activated Sludge.

Acidic partial nitritation (PN) is a promising technology to achieve low-cost and energy-efficient shortcut nitrogen removal from wastewater. However, a comprehensive understanding of the acidic PN under dynamic changes of pH in a sequencing batch reactor (SBR) is still lacking. In this study, we successfully established acidic PN (NO2- accumulation ratio >80%) under dynamic pH variation from 7.0 to 4.5 in a lab-scale SBR. By accumulating in situ free nitrous acid (FNA) generation based on the dynamic pH change, acidic PN maintained stability even at a low NH4+ concentration of 100 mg N L-1. The microbial community analysis revealed that two ammonium-oxidizing bacteria (AOB) genera, Nitrosospira and Nitrosomonas, successfully coexisted and cooperated during acidic PN. None of the species of nitrite-oxidizing bacteria (NOB) showed adaptation to intermittent inhibition of in situ FNA even under high DO conditions (>4.0 mg O2 L-1). Furthermore, we innovatively incorporated the classic nitrification model with the growth and decay of different nitrifying bacterial species and their inhibition by pH, FNA, and free ammonia (FA) to predict the nitrifying microbial communities shifting for establishing acidic PN. The extended model was calibrated by using short-term batch experiments and was validated by using long-term dynamic data of the nitrifying microbial community during SBR operation. The validated model was further used to identify feasible influent conditions for the SBR PN process, including influent HCO3- concentration, NH4+ concentration and molar ratio (HCO3/NH4+). Outcomes from this study support the optimal design of acidic PN-based short-cut nitrogen removal processes for future application.

Diffusion Tensor Imaging Reveals Altered Topological Efficiency of Structural Networks in Type-2 Diabetes Patients With and Without Mild Cognitive Impairment.

BACKGROUND: Some patients with type 2 diabetes mellitus (T2DM) progress towards mild cognitive impairment (MCI), while some patients can always maintain normal cognitive function. Network topologic alterations at global and nodal levels between T2DM individuals with and without cognitive impairment may underlie the difference. PURPOSE: To investigate the topological alterations of the whole-brain white matter (WM) structural connectome in T2DM patients with and without MCI and characterize its relationship with disease severity. STUDY TYPE: Cross-sectional and prospective study. SUBJECTS: Forty-four (63.6% females) T2DM patients, 22 with mild cognitive impairment (DM-MCI) and 22 with normal cognition (DM-NC), and 34 (58.8% females) healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3 T/diffusion tensor imaging. ASSESSMENT: Graph theoretical analysis was used to investigate the topological organization of the structural networks. The global topological properties and nodal efficiency were investigated and compared. Relationship between network metrics and clinical measurements was characterized. STATISTICAL TESTS: Student's t-test, chi-square test, ANOVA, partial correlation analyses, and multiple comparisons correction. RESULTS: The global topological organization of WM networks was significantly disrupted in T2DM patients with cognitive impairment (reduced global and local efficiency and increased shortest path length) but not in those with normal cognition, compared with controls. The DM-MCI group had significantly decreased network efficiency compared with the DM-NC group. Compared with controls, decreased nodal efficiency was detected in three regions in DM-NC group. More regions with decreased nodal efficiency were found in the DM-MCI group. Altered global network properties and nodal efficiency of some regions were correlated with diabetic duration, HbA1c levels, and cognitive assessment scores. DATA CONCLUSION: The more disrupted WM connections and weaker organized network are found in DM-MCI patients relative to DM-NC patients and controls. Network analyses provide information for the neuropathology of cognitive decline in T2DM patients. Altered nodal efficiency may act as potential markers for early detection of T2DM-related MCI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Characterization and Functional Implications of the Nonexpressor of Pathogenesis-Related Genes 1 (NPR1) in Saccharum.

Sugarcane (Saccharum spp.) is an important sugar and energy crop worldwide. As a core regulator of the salicylic acid (SA) signaling pathway, nonexpressor of pathogenesis-related genes 1 (NPR1) plays a significant role in the response of the plant to biotic and abiotic stresses. However, there is currently no report on the NPR1-like gene family in sugarcane. In this study, a total of 18 NPR1-like genes were identified in Saccharum spontaneum and classified into three clades (clade I, II, and III). The cis-elements predicted in the promotors revealed that the sugarcane NPR1-like genes may be involved in various phytohormones and stress responses. RNA sequencing and quantitative real-time PCR analysis demonstrated that NPR1-like genes were differentially expressed in sugarcane tissues and under Sporisorium scitamineum stress. In addition, a novel ShNPR1 gene from Saccharum spp. hybrid ROC22 was isolated by homologous cloning and validated to be a nuclear-localized clade II member. The ShNPR1 gene was constitutively expressed in all the sugarcane tissues, with the highest expression level in the leaf and the lowest in the bud. The expression level of ShNPR1 was decreased by the plant hormones salicylic acid (SA) and abscisic acid (ABA). Additionally, the transient expression showed that the ShNPR1 gene plays a positive role in Nicotiana benthamiana plants' defense response to Ralstonia solanacearum and Fusarium solani var. coeruleum. This study provided comprehensive information for the NPR1-like family in sugarcane, which should be helpful for functional characterization of sugarcane NPR1-like genes in the future.

WGCNA Identifies a Comprehensive and Dynamic Gene Co-Expression Network That Associates with Smut Resistance in Sugarcane.

Sugarcane smut is a major fungal disease caused by Sporisorium scitamineum, which seriously reduces the yield and quality of sugarcane. In this study, 36 transcriptome data were collected from two sugarcane genotypes, YT93-159 (resistant) and ROC22 (susceptible) upon S. scitamineum infection. Data analysis revealed 20,273 (12,659 up-regulated and 7614 down-regulated) and 11,897 (7806 up-regulated and 4091 down-regulated) differentially expressed genes (DEGs) in YT93-159 and ROC22, respectively. A co-expression network was then constructed by weighted gene co-expression network analysis (WGCNA), which identified 5010 DEGs in 15 co-expressed gene modules. Four of the 15 modules, namely, Skyblue, Salmon, Darkorange, and Grey60, were significantly associated with smut resistance. The GO and KEGG enrichment analyses indicated that the DEGs involving in these four modules could be enriched in stress-related metabolic pathways, such as MAPK and hormone signal transduction, plant-pathogen interaction, amino acid metabolism, glutathione metabolism, and flavonoid, and phenylpropanoid biosynthesis. In total, 38 hub genes, including six from the Skyblue module, four from the Salmon module, 12 from the Darkorange module, and 16 from the Grey60 module, were screened as candidate hub genes by calculating gene connectivity in the corresponding network. Only 30 hub genes were amplifiable with RT-qPCR, of which 27 were up-regulated upon S. scitamineum infection. The results were consistent with the trend of gene expression in RNA-Seq, suggesting their positive roles in smut resistance. Interestingly, the expression levels of AOX, Cyb5, and LAC were higher in ROC22 than in YT93-159, indicating these three genes may act as negative regulators in response to S. scitamineum infection. This study revealed the transcriptome dynamics in sugarcane challenged by S. scitamineum infection and provided gene targets for smut resistance breeding in sugarcane.

Effects of cocaine and HIV on decision-making abilities.

Our study aimed to understand the impact of cocaine dependence on high-risk decision-making abilities in individuals with the human immunodeficiency virus (HIV) and individuals with cocaine dependence. We recruited 99 participants (27 HIV/Cocaine, 20 HIV Only, 26 Cocaine Only, and 26 Healthy Controls). The Iowa Gambling Task (IGT) was applied to assess decision-making abilities. Independent and interactive effects of HIV status and cocaine dependence were examined using 2 × 2 factorial ANCOVA with premorbid IQ (WRAT-4: WR) as the covariate. We found cocaine dependence had a significant adverse effect on overall IGT performance (p = 0.015). We also found individuals who were HIV-positive tended to have less total money at the end of the game than individuals who were HIV-negative (p = 0.032), suggesting individuals living with HIV had less focus on long-term gains and more focus on short-term gains. Our findings highlight the significant impact of cocaine dependence on decision-making abilities and the difficulty individuals with HIV have in adequately weighing the cost and benefits of their decisions and making appropriate changes for the future.

Impaired biophysical integrity of macromolecular protein pools in the uncinate circuit in late-life depression.

Major depressive disorder is a common mood disorder in the elderly. Although the neuroanatomical abnormalities have been identified in patients with late-life depression (LLD), the precise biological basis of LLD remains largely unknown. The purpose of this study was to examine the biophysical integrity of macromolecular protein pools in the nodal regions of the "uncinate circuit," a component of fronto-limbic circuitry that is connected by the uncinate fasciculus and is critical in the regulation of mood and emotions, using novel magnetization transfer (MT) imaging. Twenty-four patients with LLD and 27 non-depressed healthy control subjects (HCs) of comparable age, sex, and race were recruited from the communities of the greater Chicago Area. The nodal regions of the uncinate circuit, i.e., bilateral amygdala, hippocampus, and lateral and medial orbitofrontal cortices (OFCs), were examined. Compared with HCs, patients with LLD had significantly lower magnetization transfer ratio (MTR), a measure of the biophysical integrity of macromolecular protein pools, in bilateral amygdala and hippocampus. The lower MTR was negatively correlated with the depression score. Moreover, the MTR of these regions decreased with age and positively correlated with neuropsychological performance in the LLD group but not in the HC group. These findings suggest that LLD is associated with compromised biophysical integrity of macromolecular protein pools in nodal regions of the uncinate circuit, and that major depression may accentuate age-related attenuation of the biophysical integrity of macromolecular protein pools in this circuit. These findings provide important new insights into the neurobiological mechanisms of the pathophysiology of LLD.

Brain microstructural alterations in type 2 diabetes: diffusion kurtosis imaging provides added value to diffusion tensor imaging.

OBJECTIVES: To investigate brain microstructural changes in white matter and gray matter of type 2 diabetes mellitus (T2DM) patients using diffusion kurtosis imaging. METHODS: Diffusion kurtosis imaging (b values = 0, 1250, and 2500 s/mm2) was performed for 30 T2DM patients and 28 controls. FMRIB Software Library with tract-based spatial statistics was used to analyze intergroup differences in fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), axial kurtosis (K∥), and radial kurtosis (K⊥) of multiple white matter regions. Atlas-based ROI analysis was conducted in gray matter structures and some fiber tracts. Correlations between MK changes and clinical measurements were determined. RESULTS: In whole-brain tract-based spatial statistics analysis, T2DM patients exhibited abnormalities in 29.6%, 30.4%, 35.4%, 10.5%, and 26.0% of white matter regions as measured by FA, MD, MK, K∥, and K⊥, respectively, when compared to the controls. MK reduction was contributed more by the decreased K⊥. In atlas-based analysis, MK detected more ROIs (27/48) with white matter microstructural changes than FA (13/48) and MD (17/48). MK decreased in bilateral thalamus and caudate, while FA showed statistically significant difference only in the left caudate. MK values negatively correlated with disease duration in the genu of corpus callosum and anterior corona radiata (R = -0.512 and -0.459) and positively correlated with neuropsychological scores in the cingulum (hippocampus) (R = 0.466 and 0.440). CONCLUSIONS: Diffusion kurtosis imaging detects more brain regions with white matter and gray matter microstructural alterations of T2DM patients than DTI metrics. It provides valuable information for studying the pathology of diabetic encephalopathy and may lead to better imaging biomarkers for monitoring disease progression. KEY POINTS: • Diffusion kurtosis imaging detects more brain regions with microstructural alterations in white matter and gray matter of T2DM patients than DTI. • Mean kurtosis changes are associated with disease severity and impaired neuropsychological function in T2DM. • Diffusion kurtosis imaging demonstrates potential to assess cognitive impairment in T2DM patients and predict disease progression.

Apparent diffusion coefficients in prostate cancer: correlation with molecular markers Ki-67, HIF-1α and VEGF.

Prostate cancer (PCa) is the second most common cancer in men. The Gleason score (GS) and biomarkers play important roles in the diagnosis and treatment of patients with PCa. The purpose of this study was to investigate the relationship between the apparent diffusion coefficient (ADC) and the molecular markers Ki-67, hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) in PCa. Thirty-nine patients with 39 lesions, who had been diagnosed with PCa, were enrolled in this study. All patients underwent diffusion-weighted magnetic resonance imaging (DW-MRI) (b = 800 s/mm2 ). The expression of Ki-67, HIF-1α and VEGF was assessed by immunohistochemistry. Statistical analysis was applied to analyze the association between ADC and prostate-specific antigen (PSA), GS and the expression of Ki-67, HIF-1α and VEGF. The group differences in ADC among different grades of Ki-67, HIF-1α and VEGF were also analyzed. The mean ± standard deviation of ADC was (0.76 ± 0.27) × 10-3  mm2 /s. ADC correlated negatively with PSA and GS (p < 0.05). The Ki-67 staining index (SI), HIF-1α expression and VEGF expression in PCa were correlated inversely with ADC, controlling for age (r = -0.332, p < 0.05; r = -0.662, p < 0.0005; and r = -0.714, p < 0.0005, respectively). ADC showed a significant difference among different grades of Ki-67 (F = 9.164, p = 0.005), HIF-1α (F = 40.333, p < 0.0005) and VEGF (F = 22.048, p < 0.0005). In conclusion, ADC was correlated with PSA, GS, and Ki-67, HIF-1α and VEGF expression in patients with PCa. ADC may be used to evaluate tumor proliferation, hypoxia and angiogenesis in PCa.

Adaptively Optimized Combination (AOC) of Phased-Array MR Spectroscopy Data in the Presence of Correlated Noise: Compared with Noise-Decorrelated or Whitened Methods.

PURPOSE: A method for adaptively optimized combination (AOC) of MR spectroscopic data from a coil array was recently introduced. The superior performance of the AOC method is evident when compared with the methods that assume uncorrelated noise between coil elements. However, it is unclear whether the AOC method represents the most optimal combination in the presence of correlated noise, when compared with the noise-decorrelated or whitened methods that specifically tackle the correlated noise between coil elements. METHODS: A new, unified theoretical framework was developed to illustrate the relationship between the AOC method and three noise-decorrelated or whitened methods, namely, noise-decorrelated combination (nd-comb), whitened singular value decomposition (WSVD), and improved WSVD (WSVD+Apod). Simulation-based comparisons and in vivo human brain experiments on a 3 Tesla (T) MRI scanner were performed using an 8-channel phased-array head coil. RESULTS: Compared with the noise-decorrelated or whitened methods, the AOC method consistently yielded the best combination in terms of the robustness against noise and maintaining the combined spectrum from distortion, and the superior performance was most evident at a low signal-to-noise ratio (SNR). CONCLUSION: The AOC method represents the theoretical optimal combination in the presence of correlated noise between coil elements, whereas the three noise-decorrelated or whitened methods are asymptotically optimal. Magn Reson Med 78:848-859, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Divergent Influences of Cardiovascular Disease Risk Factor Domains on Cognition and Gray and White Matter Morphology.

OBJECTIVE: Hypertension, diabetes, dyslipidemia, and obesity are associated with preclinical alterations in cognition and brain structure; however, this often comes from studies of comprehensive risk scores or single isolated factors. We examined associations of empirically derived cardiovascular disease risk factor domains with cognition and brain structure. METHODS: A total of 124 adults (age, 59.8 [13.1] years; 41% African American; 50% women) underwent neuropsychological and cardiovascular assessments and structural magnetic resonance imaging. Principal component analysis of nine cardiovascular disease risk factors resulted in a four-component solution representing 1, cholesterol; 2, glucose dysregulation; 3, metabolic dysregulation; and 4, blood pressure. Separate linear regression models for learning, memory, executive functioning, and attention/information processing were performed, with all components entered at once, adjusting for age, sex, and education. MRI analyses included whole-brain cortical thickness and tract-based fractional anisotropy adjusted for age and sex. RESULTS: Higher blood pressure was associated with poorer learning (B = -0.19; p = .019), memory (B = -0.22; p = .005), and executive functioning performance (B = -0.14; p = .031), and lower cortical thickness within the right lateral occipital lobe. Elevated glucose dysregulation was associated with poorer attention/information processing performance (B = -0.21; p = .006) and lower fractional anisotropy in the right inferior and bilateral superior longitudinal fasciculi. Cholesterol was associated with higher cortical thickness within left caudal middle frontal cortex. Metabolic dysfunction was positively associated with right superior parietal lobe, left inferior parietal lobe, and left precuneus cortical thickness. CONCLUSIONS: Cardiovascular domains were associated with distinct cognitive, gray, and white matter alterations and distinct age groups. Future longitudinal studies may assist in identifying vulnerability profiles that may be most important for individuals with multiple cardiovascular disease risk factors.

Investigating the separate and interactive associations of trauma and depression on brain structure: implications for cognition and aging.

OBJECTIVE: Trauma and depression are associated with brain structural alterations; their combined effects on these outcomes are unclear. We previously reported a negative effect of trauma, independent of depression, on verbal learning and memory; less is known about underlying structural associates. We investigated separate and interactive associations of trauma and depression on brain structure. METHODS: Adults aged 30-89 (N = 203) evaluated for depression (D+) and trauma history (T+) using structured clinical interviews were divided into 53 D+T+, 42 D+T-, 50 D-T+, and 58 D-T-. Multivariable linear regressions examined the separate and interactive associations of depression and trauma with prefrontal and temporal lobe cortical thickness composites and hippocampal volumes adjusting for age, sex, predicted verbal IQ, comorbid anxiety, and vascular risk. Significant results informed analyses of tract-based structural connectomic measures of efficiency and centrality. RESULTS: Trauma, independent of depression, was associated with greater left prefrontal cortex (PFC) thickness, in particular the medial orbitofrontal cortex and pars orbitalis. A trauma × depression interaction was observed for the right PFC in age-stratified analyses: Older D + T+ had reduced PFC thickness compared with older D - T+ individuals. Regardless of age, trauma was associated with more left medial orbitofrontal cortex efficiency and less pars orbitalis centrality. In the T+ group, left pars orbitalis cortical thickness and centrality negatively correlated with verbal learning. CONCLUSIONS: Trauma, independent of depression, associated with altered PFC characteristics, morphologically and in terms of structural network communication and influence. Additionally, findings suggest that there may be a combined effect of trauma and depression in older adults. Copyright © 2017 John Wiley & Sons, Ltd.

Development and aging of superficial white matter myelin from young adulthood to old age: Mapping by vertex-based surface statistics (VBSS).

Superficial white matter (SWM) lies immediately beneath cortical gray matter and consists primarily of short association fibers. The characteristics of SWM and its development and aging were seldom examined in the literature and warrant further investigation. Magnetization transfer imaging is sensitive to myelin changes in the white matter. Using an innovative multimodal imaging analysis approach, vertex-based surface statistics (VBSS), the current study vertexwise mapped age-related changes of magnetization transfer ratio (MTR) in SWM from young adulthood to old age (30-85 years, N = 66). Results demonstrated regionally selective and temporally heterochronologic changes of SWM MTR with age, including (1) inverted U-shaped trajectories of SWM MTR in the rostral middle frontal, medial temporal, and temporoparietal regions, suggesting continuing myelination and protracted maturation till age 40-50 years and accelerating demyelination at age 60 and beyond, (2) linear decline of SWM MTR in the middle and superior temporal, and pericalcarine areas, indicating early maturation and less acceleration in age-related degeneration, and (3) no significant changes of SWM MTR in the primary motor, somatosensory and auditory regions, suggesting resistance to age-related deterioration. We did not observe similar patterns of changes in cortical thickness in our sample, suggesting the observed SWM MTR changes are not due to cortical atrophy. Hum Brain Mapp 37:1759-1769, 2016. © 2016 Wiley Periodicals, Inc.

Adaptively optimized combination (AOC) of magnetic resonance spectroscopy data from phased array coils.

PURPOSE: MR spectroscopy (MRS) can benefit from multi-element coil arrays with enhanced signal-to-noise ratio (SNR). However, how to combine the MRS data in an optimized way from a multi-element coil array has been studied much less than MRI. A recently published method and routine combination methods have detrimental effects on SNR. We present herein a new method for optimal combination of multi-coil MRS data. METHODS: Based on an analytical solution for maximizing the SNR of the combined spectrum, a new method called "adaptively optimized combination (AOC)" of MRS data from phased array coils was developed in which the inversion of the full noise correlation matrix was incorporated into the coil weighting coefficients. Simulations were carried out to demonstrate the superior performance of the proposed AOC method in various noise scenarios. Validation experiments on human subjects were performed with different voxel locations and sizes on a 3T MRI scanner using an eight-element phased array head coil. RESULTS: Compared with a recently published method (i.e., weighting with the ratio of signal to the square of noise) and routine methods, our proposed AOC method adaptively and robustly produced significant SNR improvement in the combined spectra. CONCLUSION: The simulation and human experiments demonstrate that the proposed AOC method represents the theoretical optimal combination of MR spectroscopic data from multi-element coil arrays. Magn Reson Med 75:2235-2244, 2016. © 2015 Wiley Periodicals, Inc.

Multisite evaluations of a T2 -relaxation-under-spin-tagging (TRUST) MRI technique to measure brain oxygenation.

PURPOSE: Venous oxygenation (Yv ) is an important index of brain physiology and may be indicative of brain diseases. A T2 -relaxation-under-spin-tagging (TRUST) MRI technique was recently developed to measure Yv . A multisite evaluation of this technique would be an important step toward broader availability and potential clinical utilizations of Yv measures. METHODS: TRUST MRI was performed on a total of 250 healthy subjects, 125 from the developer's site and 25 each from five other sites. All sites were equipped with a 3 Tesla (T) MRI of the same vendor. The estimated Yv and the standard error (SE) of the estimation εYv were compared across sites. RESULTS: The averaged Yv and εYv across six sites were 61.1% ± 1.4% and 1.3% ± 0.2%, respectively. Multivariate regression analysis showed that the estimated Yv was dependent on age (P = 0.009) but not on performance site. In contrast, the SE of the Yv estimation was site-dependent (P = 0.024) but was less than 1.5%. Further analysis revealed that εYv was positively associated with the amount of subject motion (P < 0.001) but negatively associated with blood signal intensity (P < 0.001). CONCLUSION: This work suggests that TRUST MRI can yield equivalent results of Yv estimation across different sites.

Measuring embeddedness: Hierarchical scale-dependent information exchange efficiency of the human brain connectome.

This article presents a novel approach for understanding information exchange efficiency and its decay across hierarchies of modularity, from local to global, of the structural human brain connectome. Magnetic resonance imaging techniques have allowed us to study the human brain connectivity as a graph, which can then be analyzed using a graph-theoretical approach. Collectively termed brain connectomics, these sophisticated mathematical techniques have revealed that the brain connectome, like many networks, is highly modular and brain regions can thus be organized into communities or modules. Here, using tractography-informed structural connectomes from 46 normal healthy human subjects, we constructed the hierarchical modularity of the structural connectome using bifurcating dendrograms. Moving from fine to coarse (i.e., local to global) up the connectome's hierarchy, we computed the rate of decay of a new metric that hierarchically preferentially weighs the information exchange between two nodes in the same module. By computing "embeddedness"-the ratio between nodal efficiency and this decay rate, one could thus probe the relative scale-invariant information exchange efficiency of the human brain. Results suggest that regions that exhibit high embeddedness are those that comprise the limbic system, the default mode network, and the subcortical nuclei. This supports the presence of near-decomposability overall yet relative embeddedness in select areas of the brain. The areas we identified as highly embedded are varied in function but are arguably linked in the evolutionary role they play in memory, emotion and behavior.

CEST signal at 2ppm (CEST@2ppm) from Z-spectral fitting correlates with creatine distribution in brain tumor.

In general, multiple components such as water direct saturation, magnetization transfer (MT), chemical exchange saturation transfer (CEST) and aliphatic nuclear Overhauser effect (NOE) contribute to the Z-spectrum. The conventional CEST quantification method based on asymmetrical analysis may lead to quantification errors due to the semi-solid MT asymmetry and the aliphatic NOE located on a single side of the Z-spectrum. Fitting individual contributors to the Z-spectrum may improve the quantification of each component. In this study, we aim to characterize the multiple exchangeable components from an intracranial tumor model using a simplified Z-spectral fitting method. In this method, the Z-spectrum acquired at low saturation RF amplitude (50 Hz) was modeled as the summation of five Lorentzian functions that correspond to NOE, MT effect, bulk water, amide proton transfer (APT) effect and a CEST peak located at +2 ppm, called CEST@2ppm. With the pixel-wise fitting, the regional variations of these five components in the brain tumor and the normal brain tissue were quantified and summarized. Increased APT effect, decreased NOE and reduced CEST@2ppm were observed in the brain tumor compared with the normal brain tissue. Additionally, CEST@2ppm decreased with tumor progression. CEST@2ppm was found to correlate with the creatine concentration quantified with proton MRS. Based on the correlation curve, the creatine contribution to CEST@2ppm was quantified. The CEST@2ppm signal could be a novel imaging surrogate for in vivo creatine, the important bioenergetics marker. Given its noninvasive nature, this CEST MRI method may have broad applications in cancer bioenergetics.

Brain connectivity in late-life depression and aging revealed by network analysis.

OBJECTIVE: To use novel methods to examine age associations across an integrated brain network in healthy older adults (HOA) and individuals with late-life depression (LLD). Graph theory metrics describe the organizational configuration of both the global network and specified brain regions. METHODS: Cross-sectional data were acquired. Graph theory was used to explore diffusion tensor imaging-derived white matter networks. Forty-eight HOA and 28 adults with LLD were recruited from the community. Global and local metrics in prefrontal, cingulate, and temporal regions were calculated. Group differences and associations with age were explored. RESULTS: Group differences were noted in local metrics of the right prefrontal and temporal regions, but no significant differences were observed on global metrics. Local (not global) metrics were associated with age differently across groups. For HOA, local metrics across all regions correlated with age, whereas in adults with LLD, correlations were only observed within temporal regions. In keeping with hypothesized regions impacted by LLD, stronger hubs in right temporal regions were observed among HOA, whereas LLD individuals were characterized by robust hubs in frontal regions. CONCLUSION: We demonstrate widespread age-related changes in local network properties among HOA with different and more restricted local changes in LLD. Although a preliminary analysis, different patterns of correlations in local networks coupled with equivalent global metrics may reflect altered local structural brain networks in patients with LLD.

Withdrawal from long-term methamphetamine self-administration 'normalizes' neurometabolites in rhesus monkeys: a (1) H MR spectroscopy study.

(1) H magnetic resonance spectroscopy has demonstrated alterations in several neurometabolites in methamphetamine (METH)-dependent individuals in brain regions implicated in addiction. Yet, it is unclear whether these neurochemicals return to homeostatic levels after an individual abstains from drug use, a difficult question to address due to high recidivism and poor study retention in human subjects. We thus utilized a non-human primate model of addiction to explore the effects of long-term drug exposure and withdrawal on brain neurochemistry. Ten rhesus macaque monkeys on an active METH self-administration protocol (average use 4.6 ± 0.8 years, average daily intake between 0.4 and 1.2 mg/kg) and 10 age- and sex-matched drug-naive controls (CONT) served as subjects. Concentrations of several neurochemicals were evaluated at several timepoints following withdrawal from drug availability (10 monkeys at 1 week and 1 and 3 months, and 6 monkeys at 6 and 12 months; CONT examined at one timepoint). At 1 week following METH withdrawal, we found increases in myo-inositol in anterior cingulate cortex in the METH group relative to CONT. These alterations showed a linear pattern of decreased levels ('normalization') by 1 year of abstinence. We also found decreases in glutamine and Glx (composed mainly of glutamate and glutamine) in the caudate-putamen of the same animals at early withdrawal that showed a similar linear pattern of increasing concentration by 1 year. These results demonstrate that despite protracted, long-term use, neurochemical changes seen following long-term drug administration do not persist following prolonged abstinence, suggesting therapeutic effects of long-term withdrawal from drug use.

Development of superficial white matter and its structural interplay with cortical gray matter in children and adolescents.

Healthy human brain undergoes significant changes during development. The developmental trajectory of superficial white matter (SWM) is less understood relative to cortical gray matter (GM) and deep white matter. In this study, a multimodal imaging strategy was applied to vertexwise map SWM microstructure and cortical thickness to characterize their developmental pattern and elucidate SWM-GM associations in children and adolescents. Microscopic changes in SWM were evaluated with water diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in 133 healthy subjects aged 10-18 years. Results demonstrated distinct maturational patterns in SWM and GM. SWM showed increasing FA and decreasing MD and RD underneath bilateral motor sensory cortices and superior temporal auditory cortex, suggesting increasing myelination. A second developmental pattern in SWM was increasing FA and AD in bilateral orbitofrontal regions and insula, suggesting improved axonal coherence. These SWM patterns diverge from the more widespread GM maturation, suggesting that cortical thickness changes in adolescence are not explained by the encroachment of SWM myelin into the GM-WM boundary. Interestingly, age-independent intrinsic association between SWM and cortical GM seems to follow functional organization of polymodal and unimodal brain regions. Unimodal sensory areas showed positive correlation between GM thickness and FA whereas polymodal regions showed negative correlation. Axonal coherence and differences in interstitial neuron composition between unimodal and polymodal regions may account for these SWM-GM association patterns. Intrinsic SWM-GM relationships unveiled by neuroimaging in vivo can be useful for examining psychiatric disorders with known WM/GM disturbances.

Two-dimensional J-resolved LASER and semi-LASER spectroscopy of human brain.

PURPOSE: Two-dimensional J-resolved localized and semi-localized by adiabatic selective refocusing (LASER and semi-LASER) spectroscopy, named "J-resolved LASER" and "J-resolved semi-LASER", were introduced to suppress chemical shift artifacts, additional J-refocused artifactual peaks from spatially dependent J-coupling evolution, and sensitivity to radiofrequency (RF) field inhomogeneity. METHODS: Three pairs of adiabatic pulses were employed for voxel localization in J-resolved LASER and two pairs in J-resolved semi-LASER. The first half of t1 period was inserted between the last pair of adiabatic pulses, which was proposed in this work to obtain two-dimensional adiabatic J-resolved spectra of human brain for the first time. Phantom and human experiments were performed to demonstrate their feasibility and advantages over conventional J-resolved spectroscopy (JPRESS). RESULTS: Compared to JPRESS, J-resolved LASER or J-resolved semi-LASER exhibited significant suppression of chemical shift artifacts and additional J-refocused peaks from spatially dependent J-coupling evolution, and demonstrated insensitivity to the change of RF frequency offset over large bandwidth. CONCLUSION: Experiments on phantoms and human brains verified the feasibility and strengths of two-dimensional adiabatic J-resolved spectroscopy at 3T. This technique is expected to advance the application of in vivo two-dimensional MR spectroscopy at 3T and higher field strengths for more reliable and accurate quantification of metabolites.