Invasive fungal infections are associated with severe depletion of circulating RANTES
Bibliographic record
Abstract
Serum RANTES (regulated on activation, normal T-cell expressed and secreted) concentrations were measured in 14 patients who had haematological malignancies and developed invasive fungal infections (three of them definite, eight probable and three possible). RANTES levels fell substantially from pre-chemotherapy values at the start of and throughout the fungal infection, and recovered in patients who survived the fungal infection. However, in patients who died from the invasive fungal infection, RANTES levels did not recover. For survivors the mean +/- sd levels for RANTES were 7656 +/- 877 pg ml(-1) on the day prior to chemotherapy, 3723 +/- 2443 pg ml(-1) on the first day of fungal infection diagnosis (significantly different from baseline; P = 0.001) and 9078 +/- 2256 pg ml(-1) at recovery from the fungal infection (significantly different from lowest value; P < 0.0001). Platelet counts were closely correlated with the RANTES levels (r = 0.63, P < 0.001). The RANTES concentrations for the three patients who died were similar to those who survived at all equivalent timepoints, but were significantly lower at the time of death (792 +/- 877) compared to the values at recovery for survivors (P = 0.005). The finding that patients who died from an invasive fungal infection had very low platelet counts and RANTES concentrations suggests that these could play a role in host response to such infections.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".