Dataset DOI: 10.5061/dryad.3tx95x6xp

The noninvasive data of 70 healthy individuals and 70 patients with distinct cancer types and stages show significant nonlinear differences between healthy individuals and patients with all tested cancers (p < 0.001). 

A systemic nonlinear phase transition was detected with greater nonlinear complexity in patients with cancer, which we termed ‘the nonlinear signature of cancer’.

Hypothesis: A regression towards a Precambrian unicellular state, according to recent phylogenetic evidence, is hypothetically driven by nonlinear disruption. We termed this process "Devolution,"

Description of the data and file structure

1. Final_Results_Anonymous_(2).ods
2. Attractor_Sequence_of_a_Cancer_Patient.mp4
3. Attractor_Sequence_of_a_Control.mp4

Description of the previous data files:

1. Final_Results_Anonymous (2).ods: Contains in anonymised form all results of the trial separately for all healthy participants and cancer patients.
2. Attractor_Sequence_of_a_Cancer_Patient.mp4: Contains, as an example, a sequence of screenshots for all 5000 data points sectors of a total of 50,000 data points of one single capacitography measurement. The corresponding capacitography was performed on a cancer patient and first computed as 10 single attractors. A video of all screenshots was then compiled to form an attractor sequence. The fractal dimension is specified on each single attractor screenshot.
3. Attractor_Sequence_of_a_Control.mp4: Contains, as an example, a sequence of screenshots for all 5000 data points sectors of a total of 50,000 data points of one single capacitography measurement. The corresponding capacitography was performed on a healthy participant (control) and first computed as 10 single attractors. A video of all screenshots was then compiled to form an attractor sequence. The fractal dimension is specified on each single attractor screenshot.

Description of the variables used: Fractal Dimension, KS Entropy, Lyapunov (Wolf), Lyapunov (Rosenstein), Lyapunov (Kantz), Capacitance-Level, and Capacitance-Frequency

Permutation Entropy: Permutation Entropy (PE) is a robust, computationally efficient tool for measuring the complexity of dynamic systems by tracking ordinal patterns in time series data.

Kolmogorov-Sinai (KS) entropy is a mathematical tool used to measure the average rate at which a system creates or loses information.

Fractal dimension is a mathematical index that quantifies a shape's complexity by measuring how densely it fills space as the scale of observation changes.

Lyapunov exponent is a metric that measures how quickly two infinitesimally close states in a dynamical system diverge or converge over time. The algorithms used in the present paper were those of Wolf, Rosenstein, and Kantz.

Capacitance is the physical property of a capacitor to store charge. We evaluated its oscillatory behaviour in human skin, measuring its levels in Nanofarads (nF) and its frequency in oscillations per second.

Units of measurement:

Capacitance-Frequency: Capacitance oscillations per minute.

Capacitance-Level: nF (Nanofarad).

All other parameters have no dimension.

Human subjects data

I herewith confirm that all my data have been de-identified and cannot be used to identify individual participants.