Comparison of Cooling Systems during Islet Purification
Bibliographic record
Abstract
Islet isolation is a complex procedure that includes digestion and purification of pancreatic tissue. As we move towards clinical regulatory control and standardization, understanding of the detailed stages of the procedure have become increasingly important. Purification on a COBE 2991 density gradient allows human islets to be separated from a large volume of acinar tissue. Cooling the gradient and tissue is thought to be important to reduce metabolic activity but cooling systems for the gradient are expensive, with limited availability. In this study, the efficiency of cooling methods for the COBE 2991 cell separator has been investigated. The two cooling systems were: a) COBE 2991 modified internally to allow coolant (polyethylene glycol) from a chiller to circulate either side of the spindle and around the bowl (original system), and b) an air-cooled system using an air conditioner to blow cold air into the bowl from above (air cooler system). Cooling required 20 min for the original system and temperature was stabilized within 4-7 degrees C. The air system cooled rapidly but was not stable. There was an increase in the temperature of the medium with using both systems during centrifugation because of heat generated by the COBE machine; however, the temperature of the medium after centrifugation with the air system was significantly higher than that with the original system (13.3 +/- 0.2 degrees C vs. 8.7 +/- 0.7 degrees C, p < 0.05). The original cooler system was found to be more efficient at reducing heat generated by the COBE machine than the air system. Further investigation of the importance of the recorded temperatures is required.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".