Use of Telemetry Blood Pressure Transmitters to Measure Intracranial Pressure (ICP) in Freely Moving Rats
Bibliographic record
Abstract
Stroke and traumatic brain injuries often lead to cerebral edema and persistent elevations in intracranial pressure (ICP) that can be life threatening. Thus, rodent models would benefit from a simple and reliable method to measure ICP in awake, mobile animals. Up to now most techniques have been limited to anesthetized or immobile animals, which is not practical for following the prolonged elevations in ICP that follow stroke and traumatic brain injury. With an initial set of data, we describe a simple method that uses blood pressure telemetry sensors, which are commercially available (Data Sciences Int.) to measure ICP in freely moving rats for several days following implantation. Basically, an epidural cannula is secured to the skull and connected to the catheter of the telemetry probe, which is then secured inside a protective plastic shield on the skull. We confirm the sensitivity of our measurements by experimentally modifying ICP by either the Valsalva maneuver (abdominal compression) or a large ischemic brain injury. The Valsalva maneuver caused a small brief spike in ICP (lasting about 2-3 sec), whereas a transient middle cerebral artery occlusion substantially increased ICP (up to 50 mmHg) for approximately 3 days post-surgery. In summary, the current method allows for ICP to be continuously monitored in rats for several days, and thus is suitable for studies investigating mechanisms of raised ICP and in testing experimental treatments that mitigate it.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".