Tootfinder

A DNA Methylation Classification Model Predicts Organ and Disease Site
Keng-Jung Lee, Dharanya Sampath, Konstantinos Mavrommatis
https://arxiv.org/abs/2506.00146

A DNA Methylation Classification Model Predicts Organ and Disease Site
Cell-free DNA (cfDNA) analysis is a powerful, minimally invasive tool for monitoring disease progression, treatment response, and early detection. A major challenge, however, is accurately determining the tissue of origin, especially in complex or heterogeneous disease contexts. To address this, we developed a machine learning framework that leverages tissue-specific DNA methylation signatures to classify both tissue and disease origin from cfDNA data. Our model integrates methylation datasets …

On the Potential of Microtubules for Scalable Quantum Computation
Nick E. Mavromatos, Andreas Mershin, Dimitri V. Nanopoulos
https://arxiv.org/abs/2505.20364

On the Potential of Microtubules for Scalable Quantum Computation
We examine the quantum coherence properties of tubulin heterodimers in the Microtubule (MT) lattice. In the cavity-MT model proposed by the authors, according to which the MT interiors are modeled as high-Q quantum-electrodynamics cavities, decoherence-resistant entangled states have been argued to emerge under physiological conditions, with decoherence times of order $\mathcal{O}(10^{-6})$ s. The latter is the result of strong electric-dipole interactions of tubulin dimers with ordered-water d…