Defining a standard and weighted mathematical index for maturation of dendritic cells
Bibliographic record
Abstract
The concept of dendritic cell (DC) maturation generally refers to the changes in morphology and function of DCs. Conventionally, DC maturity is based on three criteria: loss of endocytic ability, gain of high-level capacity to present antigens and induce proliferation of T cells, and mobility of DCs toward high concentrations of CCL19. Impairment of DC maturation has been suggested as the main reason for infectivity or chronicity of several infectious agents. In the case of hepatitis C virus, this has been a matter of controversy for the last two decades. However, insufficient attention has been paid to the method of ex vivo maturation as the possible source of such controversies. We previously reported striking differences between DCs matured with different methods, so we propose the use of a standard quantitative index to determine the level of maturity in DCs as an approach to compare results from different studies. We designed and formulated a mathematically calculated index to numerically define the level of maturity based on experimental data from ex vivo assays. This introduces a standard maturation index (SMI) and weighted maturation index (WMI) based on strictly standardized mean differences between different methods of generating mature DCs. By calculating an SMI and a WMI, numerical values were assigned to the level of maturity achieved by DCs matured with different methods. SMI and WMI could be used as a standard tool to compare diversely generated mature DCs and so better interpret outcomes of ex vivo and in vivo studies with mature DCs.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".