Sepsis Increases Perioperative Metastases in a Murine Model
Bibliographic record
Abstract
ABSTRACT Background Cancer surgery can promote tumour metastases and worsen prognosis, but the effects of perioperative complications such as sepsis, blood loss, and hypothermia on subsequent cancer metastases have not been addressed. Objective To evaluate the effect of common perioperative factors on postoperative tumour metastases in murine models of cancer surgery. We hypothesize that perioperative blood loss, hypothermia, and sepsis facilitate tumour metastases in these murine models. Methods Prior to surgery, pulmonary metastases were established by intravenous challenge of CT26LacZ colon cancer cells in Balb/c mice or B16LacZ melanoma cells in C57Bl/6 mice. Surgical stress was generated through partial hepatectomy (PH) or left nephrectomy (LN). Sepsis was induced by puncturing the cecum to express stool into the abdomen. Hemorrhagic shock was induced by removal of 30% of total blood volume via saphenous vein. Hypothermia was induced by removing the heating apparatus during surgery and lowering core body temperatures to 30°C. Lung tumour burden was quantified 3 days following surgery. Results Surgically stressed mice subjected to Stage 3 hemorrhagic shock or hypothermia did not show an additional increase in lung tumour burden. In contrast, surgically stressed mice subjected to intraoperative sepsis demonstrated an additional 2-fold increase in the number of tumour metastases. Furthermore, natural killer (NK) cell function, as assessed by YAC-1 tumour cell lysis, was significantly attenuated in surgically stressed mice subjected to intraoperative sepsis. Both NK cell-mediated cytotoxic function and lung metastases were improved with perioperative administration of polyI:C, which is a ligand for toll-like receptor (TLR)-3 Conclusions Perioperative sepsis, but not hemorrhagic shock or hypothermia, enhances the prometastatic effect of surgery in murine models of cancer. Identification of the mechanisms underlying perioperative immune suppression will be critical in the development of immunomodulation strategies that aim to attenuate perioperative metastatic disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".