The role of a gel filled tip in maintaining the frequency response of telemetry based blood pressure measurements
Bibliographic record
Abstract
In recent years, measurement of blood pressure via telemetry in a variety of laboratory animals has become an indispensable part of cardiovascular physiology, drug development and safety pharmacology. The solution provided by Data Sciences Inc almost 20 years ago is in the form of a catheter attached to a pressure sensor and wireless link to a remote receiver. This design features a catheter made of compliant tubing and filled at the tip with a gel material. This gel was suggested to contribute to the frequency response of blood pressure telemetry system. However, the actual influence of the specialized tip on the dynamic response of the pressure sensor has not been reported. In the present experiment, we investigated the role of the specialized gel‐filled catheter tip in the frequency response of fluid filled catheters. Experiments were carried out using a custom made sinusoidal pressure generator and the data analyzed using Labview software. The experiments reveal that the bandwidth of the DSI system is ultimately limited to less than 100 Hz by the low power transmission system and not the gel tip catheter. When a high bandwidth transmission system is available, −3 dB bandwidths of 400 Hz are attainable for rat sized catheters. The results of the study suggest that the gel tip reduces the frequency response slightly when compared to a tip‐less catheters but not to the extent that the blood pressure measurements are compromised.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".