Up-regulation of functional CXCR4 expression on human lymphocytes in sepsis
Bibliographic record
Abstract
OBJECTIVE: Lymphocyte dysfunction has been documented in sepsis, and evidence suggests that lymphocyte infiltration contributes to tissue injury. The purpose of this study was to examine chemokine receptor expression and function in lymphocytes from septic patients and healthy donors. DESIGN: Observational study of septic patients and laboratory investigation of normal controls. SETTING: Tertiary care intensive care unit. PATIENTS AND SUBJECTS: Nine critically ill patients fulfilling criteria for the systemic inflammatory response syndrome and with a Sepsis Score of >/=3 were included in this study. Lymphocytes were also obtained from healthy volunteers. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The total number of circulating leukocytes in septic patients was markedly increased; however, lymphocyte counts were decreased. Chemokine receptor expression on lymphocytes was examined by flow cytometry. CXCR4 expression on lymphocytes from septic patients was increased whereas CCR5 was decreased and CCR7 was unchanged. Lipopolysaccharide stimulation of normal lymphocytes increased CXCR4 expression but decreased CCR5 and did not change CCR7 expression. This lipopolysaccharide-stimulated CXCR4 expression required 20 hrs of stimulation and was accompanied by increased messenger RNA. Lymphocytes from septic patients or after lipopolysaccharide treatment demonstrated enhanced actin polymerization and migration in response to CXCL12. Taken together, sepsis and lipopolysaccharide up-regulated CXCR4 expression and enhanced lymphocyte activation and migration in response to CXCL12. CONCLUSIONS: Blocking CXCR4 and CXCL12 function may provide a novel therapeutic method for controlling systemic inflammation and tissue injury in sepsis.
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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) | 0.002 | 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".