Role of Vitamin D in Preventing Colorectal Carcinogenesis
Bibliographic record
Abstract
Introduction: Colorectal carcinoma is one of the cancers with a high disease burden globally. Previous observational studies have found a connection between colorectal cancer incidence with sunlight exposure and vitamin D levels. Subsequent studies investigated this relationship further and found various anti-tumoral pathways regulated by vitamin D in colorectal tissue. This paper aims to elucidate the actions of those pathways in preventing the malignant transformation of the colorectal cell by reviewing relevant literature. Methods: A search was conducted on several medical literature electronic databases for original research studying the effects of vitamin D treatment on colorectal adenoma and colorectal cancer and its underlying anti-tumoral mechanism. A total of 122 studies were included for evaluation. Results: Twenty-seven studies passed for analysis. These in vitro and in vivo study reveals that vitamin D treatment can suppress cell proliferation, induce apoptosis, maintain cellular differentiation, reduce the pro-inflammatory response, inhibit angiogenesis, and hinder metastatic progression in colorectal cancer and colorectal adenoma cells by regulating associated gene transcription or directly prevents activation of selected signalling pathways. Five studies have also shown that adding calcium to vitamin D treatment increases the anti-tumoral activity of vitamin D through cross-talk between both of their pathways. Conclusion: Vitamin D could potentially impede colorectal cancer transformation and growth through interaction with various signalling pathways and regulating gene transcription. Further clinical studies are needed to confirm whether vitamin D can be used as the basis of targeted colorectal cancer therapy using its inherent anti-tumoral properties.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".