Imaging Taurine in the Central Nervous System Using Chemically Specific X-ray Fluorescence Imaging at the Sulfur K-Edge
Bibliographic record
Abstract
A method to image taurine distributions within the central nervous system and other organs has long been sought. Since taurine is small and mobile, it cannot be chemically "tagged" and imaged using conventional immuno-histochemistry methods. Combining numerous indirect measurements, taurine is known to play critical roles in brain function during health and disease and is proposed to act as a neuro-osmolyte, neuro-modulator, and possibly a neuro-transmitter. Elucidation of taurine's neurochemical roles and importance would be substantially enhanced by a direct method to visualize alterations, due to physiological and pathological events in the brain, in the local concentration of taurine at or near cellular spatial resolution in vivo or in situ in tissue sections. We thus have developed chemically specific X-ray fluorescence imaging (XFI) at the sulfur K-edge to image the sulfonate group in taurine in situ in ex vivo tissue sections. To our knowledge, this represents the first undistorted imaging of taurine distribution in brain at 20 μm resolution. We report quantitative technique validation by imaging taurine in the cerebellum and hippocampus regions of the rat brain. Further, we apply the technique to image taurine loss from the vulnerable CA1 (cornus ammonis 1) sector of the rat hippocampus following global brain ischemia. The location-specific loss of taurine from CA1 but not CA3 neurons following ischemia reveals osmotic stress may be a key factor in delayed neurodegeneration after a cerebral ischemic insult and highlights the significant potential of chemically specific XFI to study the role of taurine in brain disease.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".