Isolating Human Islets of Langerhans Causes Loss of Decay Accelerating Factor (CD55) on β-Cells
Bibliographic record
Abstract
It has previously been reported that human decay accelerating factor (DAF; CD55) is not expressed on cells isolated from human islets. We have investigated if this absence is caused by the islet isolation procedure and/or the single cell isolation technique. We focused on loss of DAF expression on beta-cells within the intact islet and on isolated individual beta-cells. We established that DAF was expressed in islets and on beta-cells prior to isolation by in situ analysis in the intact pancreas. In situ immunohistochemistry (IHC) was used to examine DAF expression on human pancreatic islets and isolated islets. A reverse transcriptase-polymerase chain reaction (RT-PCR) specific for human DAF mRNA was developed to measure mRNA levels in situ in islets within the intact pancreas, isolated islets, and purified beta-cells. beta-Cells were purified by fluorescence-activated cell sorting. DAF protein expression on these purified cells was measured using flow cytometry. Expression of DAF protein was present on the islets, including beta-cells within the human pancreas; however, comparative data from IHC and flow cytometry revealed the absence of DAF protein on beta-cells in both isolated islets and single cell preparations. Furthermore, compared to mRNA levels detected by in situ RT-PCR in the intact pancreas and in human HEK 293 cells, isolated islets, and purified human beta-cells showed downregulation of DAF mRNA. mRNA was detectable in both of these preparations by RT-PCR; levels were lower following both the islet isolation process (53%) and single cell preparation (a further 62%) compared to HEK 293 controls. Human islet allotransplantation might be more successful if either de novo transfer of DAF onto the isolated islets or novel techniques for islet isolation preserving DAF could be developed.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".