Optimal generation of entanglement under local control

We study the optimal generation of entanglement between two qubits subject to local unitary control. With the only assumptions of linear control and unitary dynamics, by means of a numerical protocol based on the variational approach (Pontryagin's Minimum Principle), we evaluate the optimal control strategy leading to the maximal achievable entanglement in an arbitrary interaction time, taking into account the energy cost associated to the controls. In our model we can arbitrarily choose the relative weight between a large entanglement and a small energy cost.Comment: 4 page

Computational challenges of tumor spheroid modeling

The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we put forward general considerations that apply to any fine-grained numerical model of tumors. We discuss ways to bypass computational limitations and discuss our incremental approach, where each step is validated by experimental observations on a quantitative basis. We present a few results on the growth of tumor cells in closed and open environments and of tumor spheroids. This study suggests new ways to explore the initial growth phase of solid tumors and to optimize anti-tumor treatments.Comment: 19 pages, 4 figures, 2 tables. Accepted for publication in Journal of Bioinformatics and Computational Biolog

Ab initio phenomenological simulation of the growth of large tumor cell populations

In a previous paper we have introduced a phenomenological model of cell metabolism and of the cell cycle to simulate the behavior of large tumor cell populations (Chignola R and Milotti E, Phys. Biol. 2 (2005) 8-22). Here we describe a refined and extended version of the model that includes some of the complex interactions between cells and their surrounding environment. The present version takes into consideration several additional energy-consuming biochemical pathways such as protein and DNA synthesis, the tuning of extracellular pH and of the cell membrane potential. The control of the cell cycle - that was previously modeled by means of ad hoc thresholds - has been directly addressed here by considering checkpoints from proteins that act as targets for phosphorylation on multiple sites. As simulated cells grow, they can now modify the chemical composition of the surrounding environment which in turn acts as a feedback mechanism to tune cell metabolism and hence cell proliferation: in this way we obtain growth curves that match quite well those observed in vitro with human leukemia cell lines. The model is strongly constrained and returns results that can be directly compared with actual experiments, because it uses parameter values in narrow ranges estimated from experimental data, and in perspective we hope to utilize it to develop in silico studies of the growth of very large tumor cell populations (10^6 cells or more) and to support experimental research. In particular, the program is used here to make predictions on the behaviour of cells grown in a glucose-poor medium: these predictions are confirmed by experimental observation.Comment: 67 pages, pdf only, submitted to Physical Biolog

Thresholds, long delays and stability from generalized allosteric effect in protein networks

Post-transductional modifications tune the functions of proteins and regulate the collective dynamics of biochemical networks that determine how cells respond to environmental signals. For example, protein phosphorylation and nitrosylation are well-known to play a pivotal role in the intracellular transduction of activation and death signals. A protein can have multiple sites where chemical groups can reversibly attach in processes such as phosphorylation or nitrosylation. A microscopic description of these processes must take into account the intrinsic probabilistic nature of the underlying reactions. We apply combinatorial considerations to standard enzyme kinetics and in this way we extend to the dynamic regime a simplified version of the traditional models on the allosteric regulation of protein functions. We link a generic modification chain to a downstream Michaelis-Menten enzymatic reaction and we demonstrate numerically that this accounts both for thresholds and long time delays in the conversion of the substrate by the enzyme. The proposed mechanism is stable and robust and the higher the number of modification sites, the greater the stability. We show that a high number of modification sites converts a fast reaction into a slow process, and the slowing down depends on the number of sites and may span many orders of magnitude; in this way multisite modification of proteins stands out as a general mechanism that allows the transfer of information from the very short time scales of enzyme reactions (milliseconds) to the long time scale of cell response (hours).Comment: 5 figures, submitted to Physica

The 15-Months Clinical Experience of SARS-CoV-2: A Literature Review of Therapies and Adjuvants

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the coronavirus disease of 2019 (COVID-19) that emerged in December 2019 in Wuhan, China, and rapidly spread worldwide, with a daily increase in confirmed cases and infection-related deaths. The World Health Organization declared a pandemic on the 11th of March 2020. COVID-19 presents flu-like symptoms that become severe in high-risk medically compromised subjects. The aim of this study was to perform an updated overview of the treatments and adjuvant protocols for COVID-19. Methods: A systematic literature search of databases was performed (MEDLINE PubMed, Google Scholar, UpToDate, Embase, and Web of Science) using the keywords: “COVID-19”, “2019-nCoV”, “coronavirus” and “SARS-CoV-2” (date range: 1 January 2019 to 31st October 2020), focused on clinical features and treatments. Results: The main treatments retrieved were antivirals, antimalarials, convalescent plasma, immunomodulators, corticosteroids, anticoagulants, and mesenchymal stem cells. Most of the described treatments may provide benefits to COVID-19 subjects, but no one protocol has definitively proven its efficacy. Conclusions: While many efforts are being spent worldwide in research aimed at identifying early diagnostic methods and evidence-based effective treatments, mass vaccination is thought to be the best option against this disease in the near future