Exposure of Prostate to Lipopolysaccharide and Hypoxia Potentiates Neoplastic Behavior and Risk for Prostate Carcinogenesis In Vivo
Bibliographic record
Abstract
A number of studies showed that men from tropical countries have higher burden of prostate cancer similar to data from USA. We developed a translational model to examine whether exposure to microbial inflammation-inducing molecule lipopolysacchride LPS was associated with prostatic cell transformation to more proliferative phenotype as indicated by PSA secretion. Immunocompetent adult mice were divided into two groups; the first group received a local prostate inoculation with E. coli, while the second group received inoculation with sterile solution of saline as vehicle. At the end of 6 days, the PSA values were measured and compared. In the second experiment, two groups of animals were involved. The test group received two drops of the hydrogen peroxide orally for six to seven days to induce hypoxia, while the control group received normal saline. Blood samples were evaluated for serum level of PSA. Result showed a 2-fold increase in level of PSA compared to the control mice in the E. coli inoculated-LPS exposed animals. In addition, exposure of the animals to hypoxic stress resulted in 3.5 fold increase in the serum PSA compared to the control group, which was found to be statistically significant (P < 0.0001). In conclusion, our data shows that chronic prostatic infection and exposure to inflammatory stimulus, especially LPS, may alter the phenotype of prostate epithelial cells for increased PSA secretion, a known cancer-like behavior; this is mediated by compromised redox state and oxidative stress injury. We propose that exposure of the prostate epithelial cells to lipopolysaccharide (LPS) promotes chronic inflammation and risk of neoplastic behavior of the prostate in vivo; this may explain the high rate of prostate cancer in tropics.
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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) | 0.000 | 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 | 0.001 |
| 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".