scholarly journals 31P Transversal Relaxation Times and Metabolite Concentrations in the Human Brain at 9.4T

2021 ◽  
Author(s):  
Johanna Dorst ◽  
Tamas Borbath ◽  
Loreen Ruhm ◽  
Anke Henning
Keyword(s):  
Human Brain ◽  
Inorganic Phosphate ◽  
Relaxation Times ◽  
Spin Systems ◽  
Basis Sets ◽  
Healthy Human ◽  
Brain Metabolite ◽  
Metabolite Concentrations ◽  
The Brain ◽  
Coupled Spin Systems

A method to estimate phosphorus (31P) transversal relaxation times (T2) of coupled spin systems is demonstrated. Additionally, intracellular and extracellular pH (pHext, pHint) and relaxation corrected metabolite concentrations are reported. Echo time (TE) series of 31P metabolite spectra were acquired using STEAM localization. Spectra were fitted using LCModel with accurately modeled Vespa basis sets accounting for J−evolution of the coupled spin systems. T2s were estimated by fitting a single exponential two−parameter model across the TE series. Fitted inorganic phosphate frequencies were used to calculate pH, and relaxation times were used to determine the brain metabolite concentrations. The method was demonstrated in the healthy human brain at a field strength of 9.4T. T2 relaxation times of ATP and NAD are the shortest between 8 ms and 20 ms, followed by T2s of inorganic phosphate between 25 ms and 50 ms, and PCr with a T2 of 100 ms. Phosphomonoesters and −diesters have the longest T2s of about 130 ms. Measured T2s are comparable to literature values and fit in a decreasing trend with increasing field strengths. Calculated pHs and metabolite concentrations are also comparable to literature values

scholarly journals Is There a Brain Microbiome?

2021 ◽  
Vol 16 ◽  
pp. 263310552110187
Author(s):  
Christopher D Link
Keyword(s):  
Animal Models ◽  
Human Brain ◽  
Neurodegenerative Diseases ◽  
Ground Truth ◽  
Healthy Human ◽  
Strong Motivation ◽  
The Many ◽  
The Brain

Numerous studies have identified microbial sequences or epitopes in pathological and non-pathological human brain samples. It has not been resolved if these observations are artifactual, or truly represent population of the brain by microbes. Given the tempting speculation that resident microbes could play a role in the many neuropsychiatric and neurodegenerative diseases that currently lack clear etiologies, there is a strong motivation to determine the “ground truth” of microbial existence in living brains. Here I argue that the evidence for the presence of microbes in diseased brains is quite strong, but a compelling demonstration of resident microbes in the healthy human brain remains to be done. Dedicated animal models studies may be required to determine if there is indeed a “brain microbiome.”

scholarly journals The Role of the Human Brain Neuron–Glia–Synapse Composition in Forming Resting-State Functional Connectivity Networks

2021 ◽  
Vol 11 (12) ◽  
pp. 1565
Author(s):  
Sayan Kahali ◽  
Marcus E Raichle ◽  
Dmitriy A Yablonskiy
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Functional Networks ◽  
Bold Signal ◽  
Resting State Functional Connectivity ◽  
Healthy Human ◽  
Neuronal Density ◽  
Wide Range ◽  
Functional Units ◽  
The Brain

While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain’s cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood–oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units’ connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.

scholarly journals Rare Copy Number Deletions Predict Individual Variation in Human Brain Metabolite Concentrations in Individuals with Alcohol Use Disorders

2011 ◽  
Vol 70 (6) ◽  
pp. 537-544 ◽  
Author(s):  
Ronald A. Yeo ◽  
Steven W. Gangestad ◽  
Charles Gasparovic ◽  
Jingyu Liu ◽  
Vince D. Calhoun ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Human Brain ◽  
Individual Variation ◽  
Copy Number ◽  
Alcohol Use Disorders ◽  
Brain Metabolite ◽  
Metabolite Concentrations

FRACTAL DIMENSION AND LACUNARITY OF TRACTOGRAPHY IMAGES OF THE HUMAN BRAIN

Fractals ◽  
2009 ◽  
Vol 17 (02) ◽  
pp. 181-189 ◽  
Author(s):  
P. KATSALOULIS ◽  
D. A. VERGANELAKIS ◽  
A. PROVATA
Keyword(s):  
Fractal Dimension ◽  
Human Brain ◽  
Fractal Dimensions ◽  
Resonance Imaging ◽  
Self Similarity ◽  
Healthy Human ◽  
Box Counting ◽  
Self Similar ◽  
Box Method ◽  
The Brain

Tractography images produced by Magnetic Resonance Imaging scans have been used to calculate the topology of the neuron tracts in the human brain. This technique gives neuroanatomical details, limited by the system resolution properties. In the observed scales the images demonstrated the statistical self-similar structure of the neuron axons and its fractal dimensions were estimated using the classic Box Counting technique. To assess the degree of clustering in the neural tracts network, lacunarity was calculated using the Gliding Box method. The two-dimensional tractography images were taken from four subjects using various angles and different parts in the brain. The results demonstrated that the average estimated fractal dimension of tractography images is approximately Df = 1.60 with standard deviation 0.11 for healthy human-brain tissues, and it presents statistical self-similarity features similar to many other biological root-like structures.

scholarly journals The Relationship between Glucose Metabolism, Resting-State fMRI BOLD Signal, and GABAA-Binding Potential: A Preliminary Study in Healthy Subjects and Those with Temporal Lobe Epilepsy

2015 ◽  
Vol 35 (4) ◽  
pp. 583-591 ◽  
Author(s):  
Allison C Nugent ◽  
Ashley Martinez ◽  
Alana D'Alfonso ◽  
Carlos A Zarate ◽  
William H Theodore
Keyword(s):  
Glucose Metabolism ◽  
Temporal Lobe Epilepsy ◽  
Human Brain ◽  
Temporal Lobe ◽  
Resting State ◽  
Healthy Subjects ◽  
Binding Potential ◽  
Bold Signal ◽  
Healthy Human ◽  
The Brain

Glucose metabolism has been associated with magnitude of blood oxygen level-dependent (BOLD) signal and connectivity across subjects within the default mode and dorsal attention networks. Similar correlations within subjects across the entire brain remain unexplored. [18F]-fluorodeoxyglucose positron emission tomography ([18F]-FDG PET), [11C]-flumazenil PET, and resting-state functional magnetic resonance imaging (fMRI) scans were acquired in eight healthy individuals and nine with temporal lobe epilepsy (TLE). Regional metabolic rate of glucose (rMRGlu) was correlated with amplitude of low frequency fluctuations (ALFFs) in the fMRI signal, global fMRI connectivity (GC), regional homogeneity (ReHo), and gamma-aminobutyric acid A—binding potential (GABAA BPND) across the brain. Partial correlations for ALFFs, GC, and ReHo with GABAA BPND were calculated, controlling for rMRGlu. In healthy subjects, significant positive correlations were observed across the brain between rMRGlu and ALFF, ReHo and GABAA BPND, and between ALFFs and GABAA BPND, controlling for rMRGlu. Brain-wide correlations between rMRGlu and ALFFs were significantly lower in TLE patients, and correlations between rMRGlu and GC were significantly greater in TLE than healthy subjects. These results indicate that the glutamatergic and GABAergic systems are coupled across the healthy human brain, and that ALFF is related to glutamate use throughout the healthy human brain. TLE may be a disorder of altered long-range connectivity in association with glutamate function.

scholarly journals Two New Fucose-α (1–2)-Glycans Assigned In The Healthy Human Brain Taking The Number To Seven

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Nathan Tosh ◽  
Scott Quadrelli ◽  
Graham Galloway ◽  
Carolyn Mountford
Keyword(s):  
Human Brain ◽  
Molecular Mechanisms ◽  
Neuronal Development ◽  
Chemical Shifts ◽  
Healthy Human ◽  
Men And Women ◽  
Healthy Men ◽  
Water Resonance ◽  
Neck Coil ◽  
The Brain

AbstractFucosylated glycans are involved in the molecular mechanisms that underpin neuronal development, learning and memory. The capacity to study the fucose-α(1–2)-glycan residues noninvasively in the human brain, is integral to understanding their function and deregulation. Five fucose crosspeaks were assigned to fucosylated glycans using invivo two-dimensional magnetic resonance Correlated SpectroscopY (2D L-COSY) of the brain. Recent improvements encompassed on the 3T Prisma (Siemens, Erlangen) with a 64-channel head and neck coil have allowed two new assignments. These are Fuc VI (F2:4.44, F1:1.37 ppm) and Fuc VII (F2: 4.29, F1:1.36 ppm). The Fuc VI crosspeak, close to the water resonance, is resolved due to decreased T1 noise. Fuc VII crosspeak, located between Fuc I and III, is available for inspection due to increased spectral resolution. Spectra recorded from 33 healthy men and women showed a maximum variation of up to 0.02 ppm in chemical shifts for all crosspeaks.

scholarly journals Comparison of two programs for quantification of 1H MR spectra of rat brain using a vascular dementia model

2015 ◽  
Vol 8 (1) ◽  
pp. 11-16
Author(s):  
Mária Jozefovičová ◽  
Ivica Just ◽  
Tibor Liptaj ◽  
Svatava Kašparová
Keyword(s):  
Magnetic Resonance ◽  
Vascular Dementia ◽  
Pathological Conditions ◽  
Brain Metabolite ◽  
Metabolite Concentrations ◽  
Echo Time ◽  
Short Echo Time ◽  
The Brain

Abstract The quantification of in vivo 1H magnetic resonance (MR) spectra measured from the rat brains provides important information about the brain metabolite concentrations and can help to understand the role of the metabolites under normal and pathological conditions. The purpose of this study was to compare the most frequently used algorithms for quantification of 1H spectra: LCModel (Linear Combination of Model spectra) and QUEST (QUantitation based on QUantum ESTimation) from jMRUI software (Java based Magnetic Resonance User Interface). The comparison was done on a rat model of vascular dementia (VD). The MR spectra were measured on 4.7T spectrometer with ultra-short echo time by sequence SPECIAL. For these types of spectra the contribution from the macromolecules and lipids is large. Our analysis revealed that all values determined by QUEST, except for one value, were lower in comparison to values obtained by LCModel. The minimal differences were found in N-acetylaspartate/(phospho) creatine (−0.3 %) and maximal in inositol in both control and VD rats. This underestimation of a metabolite concentration in QUEST may be caused by an overestimation of baseline. Although our study found the different values of metabolite concentrations by these two methods, the quantified metabolite changes in pathological brain were comparable in both analyses.

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