Windows on the working brain: magnetic resonance spectroscopy
Bibliographic record
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is an observational technique based on detection of signals from magnetic atomic nuclei such as 1 H, 31 P, 13 C, 15 N, and 17 O. It is most familiar to physicians and the public as magnetic resonance imaging (MRI), which uses the strong signal from water protons to make the most highly detailed pictures of living tissue available from any non-invasive method. In consequence, MRI, including its special forms magnetic resonance angiography, diffusion-weighted imaging, and magnetization transfer imaging – quickly became a major tool for medical diagnosis and research on living creatures. Its applications to neurological disease are described in several other chapters of this book. Magnetic resonance spectroscopy (MRS) is the designation used in the biomedical world for measurement of NMR signals from non-water protons and other magnetic nuclei. The usage is not accurate, MRI is the MRS of water, but it is convenient. MRS signals detectable in living brain are thousands of times weaker than the water proton signal; hence observing them requires extra time and special procedures. The reward for the effort is an abundance of chemically specific information which can be acquired as often as necessary, since the measurement process is non-invasive. In the living human brain, 1 H signals can be obtained from N -acetyl aspartate, creatine, choline moieties, glutamate, glutamine, lactate, and several other small molecules. Phosphocreatine, adenosine triphosphate, and inorganic phosphate can be measured directly by their 31 P signals, and intracellular pH calculated from its effect on these signals. Information from the 31 P spectrum allows calculation of the rate of the creatine kinase reaction. The spectra of 13 C, 15 N, 17 O, and other magnetic nuclei contain many more small signals from a variety of molecules which will become detectable as technology advances. This unprecedented measurement capability provides an opportunity for characterization of human neurological diseases along several axes of chemical variation throughout their natural histories. The data are obtained without hazard to the patient, are free from artefacts of tissue preparation, and can be compared in as much detail as necessary to identically acquired information from normal subjects. As MRS matures technically over the first decades of the twenty-first century, it can be expected to take a place among the principal technologies contributing to illumination of disease processes and evaluation of new treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.018 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".