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Daniel R. Amor

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Published work

4 published item(s)

preprint2026arXiv

A hyperbolic cell cycle law for early embryonic developmental timing

Across metazoans, early embryos exhibit a strikingly conserved slowing down of their cell duplication speed, despite widely varying developmental paces and underlying molecular mechanisms. Here we show that this common behavior arises because early development unfolds along a biochemical rather than a chronological timescale, resulting from the coupling of finite maternal resource consumption to the Michaelis-Menten-like kinetics governing the rates of the biochemical reactions involved in cell duplication. This leads to a hyperbolic growth of the Cell Cycle Length (CCL), approaching a mathematical singularity, which would correspond to developmental arrest. Data from a wide range of organisms -- cnidarians, nematodes, arthropods, molluscs, echinoderms, tunicates, amphibians, and fish -- collapse on a single curve, quantitatively capturing not only a universal CCL dynamical behaviour, but also key hallmarks of early metazoan development, including cell-number temporal evolution, the dependency of CCL on cell size, and, remarkably, gastrulation timing at the predicted singularity. Crucially, experimental modulation of resource availability and consumption rates validate the model and further demonstrate that a source of heterochrony in early development is an altered biochemical timescale of resource depletion. Overall, this work reveals resource consumption rates as a fundamental mechanism driving developmental timing in early embryogenesis across species.

preprint2016arXiv

Population dynamics of synthetic Terraformation motifs

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation, and human-driven habitat degradation. Such threats are pushing ecosystems to the brink of collapse. Because of a general presence of multiple stable states, including states involving population extinction, and due to intrinsic nonlinearities associated with feedback loops, collapse can occur in a catastrophic manner. Such catastrophic shifts have been suggested to pervade many of the future transitions affecting ecosystems at many different scales. Many studies have tried to delineate potential warning signals predicting such ongoing shifts but little is known about how such transitions might be effectively prevented. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. Four classes of such ecological engineering designs or {\em Terraformation motifs} have been defined in a qualitative way. Here we develop the simplest mathematical models associated with these motifs, defining the expected stability conditions and domains where the motifs shall properly work.

preprint2014arXiv

Catastrophic shifts and lethal thresholds in a propagating front model of unstable tumour progression

Unstable dynamics characterizes the evolution of most solid tumors. Because of an increased failure of maintaining genome integrity, a cumulative increase in the levels of gene mutation and loss is observed. Previous work suggests that instability thresholds to cancer progression exist, defining phase transition phenomena separating tumor-winning scenarios from tumor extinction or coexistence phases. Here we present an integral equation approach to the quasispecies dynamics of unstable cancer. The model exhibits two main phases, characterized by either the success or failure of cancer tissue. Moreover, the model predicts that tumor failure can be due to either a reduced selective advantage over healthy cells or excessive instability. We also derive an approximate, analytical solution that predicts the front speed of aggressive tumor populations on the instability space.

preprint2014arXiv

On singularities in combination-driven models of technological innovation

It has been suggested that innovations occur mainly by combination: the more inventions accumulate, the higher the probability that new inventions are obtained from previous designs. Additionally, it has been conjectured that the combinatorial nature of innovations naturally leads to a singularity: at some finite time, the number of innovations should diverge. Although these ideas are certainly appealing, no general models have been yet developed to test the conditions under which combinatorial technology should become explosive. Here we present a generalised model of technological evolution that takes into account two major properties: the number of previous technologies needed to create a novel one and how rapidly technology ages. Two different models of combinatorial growth are considered, involving different forms of ageing. When long-range memory is used and thus old inventions are available for novel innovations, singularities can emerge under some conditions with two phases separated by a critical boundary. If the ageing has a characteristic time scale, it is shown that no singularities will be observed. Instead, a "black hole" of old innovations appears and expands in time, making the rate of invention creation slow down into a linear regime.