Advanced searches left 3/3

Colon Cancer - Astrophysics Data System

Summarized by Plex Scholar
Last Updated: 19 August 2022

* If you want to update the article please login/register

Explanation of Machine Learning Models of Colon Cancer Using SHAP Considering Interaction Effects

Shapley's explanation is one of the most common machine learning techniques. Interaction effects occur when the effect of one variable is dependent on the value of another variable. Understanding interactions is vital in understanding machine learning schemes; however, naive SHAP findings are unable to distinguish between the main effect and interaction effects. We use the technique to analyze what combination of risk factors contributes to colon cancer risk.

Source link: https://ui.adsabs.harvard.edu/abs/2022arXiv220803112N/abstract


Computer extracted features of tumor-infiltrating lymphocytes (TILs) architecture are prognostic of progression-free survival in stage III colon cancer

Stage III Colorectal cancer is treated with surgery and chemotherapy. Hence, our research sought to classify stage III CRC patients into distinct risk groups based on TIL characteristics and to determine if this classification could have independent prognostic value. In stage III CRC patients, a survival system was developed to reduce the possibility of recurrence. To find top 5 characteristics and risk scores for each patient, a Cox proportional hazards regression model was used in conjunction with least absolute shrinkage and selection operator. The risk scores for the training dataset were calculated using the chosen features with their respective coefficients. The median PFS for the high-risk group was 15. 1mos in the validation set, while the low-risk group was 27mos.

Source link: https://ui.adsabs.harvard.edu/abs/2022SPIE12039E..0VA/abstract


Nano-scale imaging of dual stable isotope labeled oxaliplatin in human colon cancer cells reveals the nucleolus as a putative node for therapeutic effect

Oxaliplatin has superior clinical activity in colorectal cancer compared to cisplatin, according to Oxaliplatin. In this research, we combined highly sensitive element specific and isotope specific imaging by nanometer-scale secondary ion mass spectrometry with transmission electron microscopy to determine the subcellular accumulation of oxaliplatin in three human colon cancer cell lines. In all of the tested cell lines, oxaliplatin was discovered to have a strong tendency for cytoplasmic aggregation in single membrane bound organelles, possibly related to various stages of the endocytic pathway. In a pair of isogenic malignant cell lines with different levels of drug sensitivity, subcellular drug transport patterns were investigated in order to investigate the consequences of oxaliplatin resistance. The subcellular platinum delivery was found to be similar in both cell lines, with only marginally higher accumulation in the sensitive HCT116 wt cells, which is inconsistent with a resistance factor of more than 20 percent.

Source link: https://ui.adsabs.harvard.edu/abs/2021NanoA...3..249L/abstract

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions