Publications by authors named "R Cavill"
Mathematical modeling plays an important role in our understanding and targeting therapy resistance mechanisms in cancer. The polymorphic Gompertzian model, analyzed theoretically and numerically by Viossat and Noble to demonstrate the benefits of adaptive therapy in metastatic cancer, describes a heterogeneous cancer population consisting of therapy-sensitive and therapy-resistant cells. In this study, we demonstrate that the polymorphic Gompertzian model successfully captures trends in both in vitro and in vivo data on non-small cell lung cancer (NSCLC) dynamics under treatment.
View Article and Find Full Text PDFProstate-specific antigen (PSA) is the most commonly used serum marker for prostate cancer. It plays a role in cancer detection, treatment monitoring, and more recently, in guiding adaptive therapy protocols, where treatment is alternated based on PSA levels. However, the relationship between PSA levels and tumor volume remains poorly understood.
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- Blood-derived DNA methylation shows potential for early detection of dementia risk, linking biological factors with lifestyle and environmental influences.
- A multivariate methylation risk score (MMRS) was developed, predicting mild cognitive impairment independently of age and sex, alongside significant future risk of cognitive decline in Alzheimer’s and Parkinson’s diseases.
- The study highlights the integration of machine learning and omics data to enhance dementia risk prediction at the population level.
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- Some heart disease risk factors can change how a type of blood cell called monocytes reacts to infections.
- Researchers studied these cells from patients with heart disease and found that higher blood pressure makes monocytes less responsive to infection signals.
- A potential new drug, MW-STK33-97, might help improve how these cells react when faced with infections in patients with high blood pressure.
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- Researchers improved a model called Deep Embedded Clustering (DEC) to better handle different types of data, like numbers and categories.
- They created a new version called X-DEC by using a special tool (an X-shaped variational autoencoder) to make it work better.
- After testing both models on patients in intensive care, they found that while both created clear groups, X-DEC gave more consistent results.