Low expression of dendritic cell-specific intercellular adhesion molecule-grabbing nonintegrin-related protein in non-Hodgkin lymphoma and significant correlations with lactic acid dehydrogenase and β2-microglobulin
Bibliographic record
Abstract
Dendritic cell-specific intercellular adhesion molecule-grabbing nonintegrin-related protein (DC-SIGNR), a type II integral membrane protein and a member of the C-type lectins, has been reported to bind various strains of HIV-1, HIV-2, and simian immunodeficiency virus. Serum DC-SIGNR is not currently available for the detection of non-Hodgkin lymphoma (NHL). Using an enzyme-linked immunosorbent assay (ELISA), we assessed the serum levels of DC-SIGNR in 70 cancer patients and 100 healthy controls. Additionally, using immunohistochemistry, we determined the expression of DC-SIGNR in the lymph nodes. Using the ELISA, low serum levels of DC-SIGNR were detected in the patients (median, 4.513 ng·L(-1); range, 1.066-9.232 ng·L(-1); p = 0.0003). Serum concentrations of DC-SIGNR correlated significantly with age (p = 0.0077) and lactic acid dehydrogenase (p = 0.0046) and β2-microglobulin (p = 0.0491) levels. However, we found no statistically significant correlation between serum DC-SIGNR levels and clinical data such as sex, Ann Arbor stage, B symptoms, and histologic subtypes. Moreover, NHL patients with a lower level of serum DC-SIGNR expression in lymphatic endothelial cells also showed negative immunostaining levels. These results suggest that DC-SIGNR is a biological molecule that may be potentially useful in NHL clinical settings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".