Establishing a standardized murine orthotopic intra-rectal model for the study of colorectal adenocarcinoma
Bibliographic record
Abstract
Background: Orthotopic models offer a more accurate representation of colorectal cancer (CRC) compared to subcutaneous models. Despite promising results from the reported intra-rectal models, establishing a standardized method for CRC research remains challenging due to model variability, hindering comprehensive studies on CRC pathogenesis and treatment modalities, such as brachytherapy. This study aimed to establish a standardized workflow for an orthotopic intra-rectal animal model to induce the growth of colorectal adenocarcinoma in male and female mice. Methods: HT-29 colorectal adenocarcinoma cells were injected into the rectal mucosa of female (n=21) and male (n=26) non-obese diabetic severe combined immunodeficiency (NOD SCID) gamma (NSG) mice. Mice were placed on a 45° wedge elevating their pelvis for better visualization of the anus. Tumor growth and localization were monitored using a 7-T magnetic resonance imaging (MRI) scanner with rapid acquisition with relaxation echo (RARE) sequence at weeks 1, 2, and 3 post-cell instillation. Once tumors reached 5-8 mm in diameter, the mice were euthanized. Histopathology and immunohistochemical analyses confirmed the tumors' morphology, including necrosis, vascularity (CD-31) and apoptosis (cleaved caspase-3). Results: There was a 92% and 95% tumor growth success rate in male and female mice, respectively. Tumors grew to 5-8 mm in diameter within ~20 days. No significant difference in tumor size was observed between genders. Tumor morphology was consistent across cases. Most tumors exhibited a lack of central blood vessels, accompanied by varying degrees of necrosis and apoptosis, whereas external portions were highly vascularized. Conclusions: An orthotopic intra-rectal model was successfully developed. This model will be used in future studies to evaluate the efficacy of CRC treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".