Position sensitive measurement of lithium traces in brain tissue with neutrons
Bibliographic record
Abstract
PURPOSE: The application of lithium is well known to have an antimanic-depressive effect, however, the influence it has on the human brain is still insufficiently known. The aim of our work is to develop a method to investigate the lithium concentration in the human brain with a very high sensitivity and a submillimeter resolution. Present methods either do not provide spatial resolution or are not sensitive enough to measure the naturally occurring lithium content in the human brain. Our method provides the opportunity to perform postmortem series measurements and obtain a detailed map of the lithium distribution in the human brain. This way possible correlations of the lithium distribution in the human brain and biological reasons for affective disorder can be clarified. METHODS: To study the lithium distribution in different regions of the human brain the authors developed a method to measure lithium traces postmortem with a submillimeter spatial resolution using the neutron capture reaction (6)Li(n, α)(3)H. The lithium is measured by coincident detection of the alpha particles and tritons, emitted in opposite directions. The general concept, the preparation of the brain samples, the experimental setup at the measurement station of the Forschungs-Neutronenquelle Heinz Maier-Leibnitz, and a first measurement on human brain tissue are presented. RESULTS: A first measurement on a brain tissue sample nicely showed a spatial distribution of lithium down to a few hundreds of pg∕cm(3) with a maximal resolution of about σ(x) = σ(y) ≈ 200 μm. Also a direct correlation of lithium and optical tissue structure is observable. Typical measurement times of a few minutes allow for series measurements of up to 20 × 20 mm(2) large samples with a thickness of w = 10-20 μm in medical studies. CONCLUSIONS: The combination of a very high lithium sensitivity with position resolving measurement makes this method well suited for postmortem studies of the microscopic lithium distribution in the human brain and thus to form a microscopic picture of the impact of lithium in different areas of the human brain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".