C-C Chemokine Receptor Type 2 Expression on Monocytes Before Sepsis Onset Is Higher Than That of Postsepsis in Septic Burned Patients
Bibliographic record
Abstract
OBJECTIVE: The present study aims to investigate the alterations in monocytes (Mo) and dendritic cells (DCs) in septic burned patients with a special focus on C-C chemokine receptor type 2 (CCR2) expressions on classical Mo. BACKGROUND: The phenotypes of Mo and DCs, particularly CCR2 expression on Mo, are not fully explored in severely burned patients with sepsis. METHODS: The prospective cohort study was conducted in Ross Tilley Burn Centre and Sunnybrook Research Institute (Toronto, Canada). We enrolled 8 healthy patients and 89 burned patients with various burned sizes, of those burned patients, 12 were with sepsis. Blood was collected upon admission to the hospital and throughout their course in hospital. The expression of human leukocyte antigen-DR was determined on all DCs and Mo, along with CCR2 on CD14/CD16 Mo. RESULTS: We found a profound decrease in human leukocyte antigen-DR on Mo and DCs in burned patients with sepsis compared with healthy controls and nonseptic burned patients. In addition, septic burned patients presented an increased CCR2 expression on classical Mo (CD14/CD16), which was paralleled by greater chemokine (C-C motif) ligand 2 concentrations in the plasma when compared with controls and nonseptic burned patients. Furthermore, burned patients with sepsis had a more profound expansion of CD14/CD16 Mo when compared with nonseptic burned patients. CONCLUSION: Our results demonstrate that burned patients with sepsis have more profound impairment of monocytes and dendritic cells than burned patients without sepsis. With CCR2 level on Mo before sepsis onset being higher than postsepsis, CCR2 expression could be a new predictor of sepsis onset in severe burn injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".