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Record W1996847672 · doi:10.1002/mrm.21055

<i>T</i><sub>2</sub> measurement and quantification of glutamate in human brain in vivo

2006· article· en· W1996847672 on OpenAlexaff
Changho Choi, Nicholas J. Coupland, Paramjit P. Bhardwaj, Sanjay Kalra, Colin Casault, Kimberly J. Reid, Peter S. Allen

Bibliographic record

VenueMagnetic Resonance in Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNuclear magnetic resonanceChemistryMagnetization transferGlutamate receptorGlutamineAnalytical Chemistry (journal)PhysicsMagnetic resonance imagingReceptorBiochemistryMedicine

Abstract

fetched live from OpenAlex

The proton NMR transverse relaxation time T(2) of glutamate (Glu) in human brain was measured by means of spectrally selective refocusing at 3.0 T in vivo. An 81.4-ms-long dual-band Gaussian 180 degrees RF pulse, designed for refocusing at 2.35 and 3.03 ppm, was employed within point-resolved spectroscopy (PRESS) to generate the Glu C4-proton target multiplet and the total creatine (tCr) singlet. Six optimal echo times (TEs) between 128 and 380 ms were selected from numerical analysis of the filtering performance for effective detection of the Glu signal with minimal contamination from glutamine (Gln), N-acetylaspartate (NAA), and glutathione (GSH). The magnetization of Glu and tCr was extracted from spectral fitting of experimental and calculated spectra. Apparent T(2) values of Glu and tCr were estimated as 201 +/- 18 and 164 +/- 12 ms for the medial prefrontal (PF) cortex, and 198 +/- 22 and 169 +/- 15 ms (mean +/- SD, N = 5) for the left frontal (LF) cortex, respectively. With water segmentation data, the magnetization values of Glu and tCr of the two adjacent voxels, calculated from the T(2) values and spectra following the thermal equilibrium magnetization, were combined to give the Glu and tCr concentrations as 10.37 +/- 1.06 and 8.87 +/- 0.56 mM for gray matter (GM), and 5.06 +/- 0.57 and 5.16 +/- 0.45 mM (mean +/- SD, N = 5) for white matter (WM), respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.299
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations89
Published2006
Admission routes1
Has abstractyes

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