Synchrotron light source imaging of brain tissue shows changes in iron concentration after chronic implantation of electrodes and electrical stimulation
Bibliographic record
Abstract
PURPOSE Various metallic electrodes are used in research and clinical applications because of their purported biological compatibility. However, little is known about the effects on surrounding tissue following subsequent stimulation. Using X‐ray fluorescence imaging, we examined metal distribution in the brain after stimulation with three types of electrodes. METHODS Bilateral implantation of stainless steel, nickel‐chromium, or platinum‐iridium electrodes into amygdala was used in a rat preparation of epilepsy. Stage 5 seizures were kindled by a once‐daily application of electrical stimulation. Rapid scanning X‐Ray fluorescence and microprobe analysis of brain sections were performed using the imaging beam lines at the Stanford Synchrotron Radiation Lightsource. RESULTS Images showed elevated iron concentrations around the electrode tips in both control and kindled tissue. Concentrations varied according to electrode type and were greater in kindled tissue as compared to yoked controls. CONCLUSIONS Chronic implantation of electrodes in the brain results in an increased concentration of iron around the electrode track, which is further increased by stimulation. These findings raise the issue of possible adverse effects from these metal depositions and suggest the need to evaluate the effects of chronic electrical stimulation in clinical settings. Support: NSERC, CIHR
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 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".