Bridging the gap between the micro- and the macro-world of tumors

At present it is still quite difficult to match the vast knowledge on the behavior of individual tumor cells with macroscopic measurements on clinical tumors. On the modeling side, we already know how to deal with many molecular pathways and cellular events, using systems of differential equations and other modeling tools, and ideally, we should be able to extend such a mathematical description up to the level of large tumor masses. An extended model should thus help us forecast the behavior of large tumors from our basic knowledge of microscopic processes. Unfortunately, the complexity of these processes makes it very difficult -- probably impossible -- to develop comprehensive analytical models. We try to bridge the gap with a simulation program which is based on basic biochemical and biophysical processes -- thereby building an effective computational model -- and in this paper we describe its structure, endeavoring to make the description sufficiently detailed and yet understandable.Comment: 24 pages, 10 figures. Accepted for publication in AIP Advances, in the special issue on the physics of cance

Analysis of the fluctuations of the tumour/host interface

In a recent analysis of metabolic scaling in solid tumours we found a scaling law that interpolates between the power laws μ∝V and μ∝V2∕3, where μ is the metabolic rate expressed as the glucose absorption rate and V is the tumour volume. The scaling law fits quite well both in vitro and in vivo data, however we also observed marked fluctuations that are associated with the specific biological properties of individual tumours. Here we analyse these fluctuations, in an attempt to find the population-wide distribution of an important parameter (A) which expresses the total extent of the interface between the solid tumour and the non-cancerous environment. Heuristic considerations suggest that the values of the A parameter follow a lognormal distribution, and, allowing for the large uncertainties of the experimental data, our statistical analysis confirms this

Basalt Intrusions in Palaeokarst Caves in the Central Lessini Mountains (Venetian Prealps, Italy)

The Lessini Mountains carbonate plateau (Venetian Prealps, Italy) is one of the most important karst areas in Italy. Along with alpine-type caves and well-developed karst landscapes, palaeokarst features are also common. In most cases, palaeokarst is represented by caves and fissures filled by limonitic-haematitic palaeosols (ochres) in which fossiliferous arenite layers are sometimes embedded. These features developed and fossilised during a late Eocene-middle Miocene phase of emersion. Between the Palaeocene and the Oligocene, over a time span partially overlapping the development of palaeokarst, basaltic volcanism took place in the Lessini Mountains. Along with ochre fills, cave passages that were intruded by basalt provide further evidence that a well developed karst network existed in the Lessini Mountains area in the middle-late Palaeogene. Moreover, basalt intrusions provide the only available data for the dating of palaeokarst in the central Lessini Mountains, where fossiliferous layers in ochre beds have not been found. We have started a new survey on palaeokarst in the Lessini plateau, with the aim of identifying ancient features on the basis of unusual fills (namely, ochre and basalt) and morphologies. New instances of basalt intrusions in three caves, Spigola di Canova, Covoli di Velo, and Covolo della Croce, have been recognised; evidence of pre-existing karst features filled by basalt in a previously studied cave (Grotta A Veja) has been identified, and an unusual basalt outcrop that might relate to palaeokarst has also been observed. This paper aims to document the new findings and to discuss previous ones. At the same time, we would like to point out some cautionary observations to prevent a “basalt = palaeokarst” misunderstanding.Key words: palaeokarst, basalt intrusion, cave fills, Lessini Mountains

Pulsation-limited oxygen diffusion in the tumour microenvironment

Hypoxia is central to tumour evolution, growth, invasion and metastasis. Mathematical models of hypoxia based on reaction-diffusion equations provide seemingly incomplete descriptions as they fail to predict the measured oxygen concentrations in the tumour microenvironment. In an attempt to explain the discrepancies, we consider both the inhomogeneous distribution of oxygen-consuming cells in solid tumours and the dynamics of blood flow in the tumour microcirculation. We find that the low-frequency oscillations play an important role in the establishment of tumour hypoxia. The oscillations interact with consumption to inhibit oxygen diffusion in the microenvironment. This suggests that alpha-blockers\u2013a class of drugs used to treat hypertension and stress disorders, and known to lower or even abolish low-frequency oscillations of arterial blood flow \u2013may act as adjuvant drugs in the radiotherapy of solid tumours by enhancing the oxygen effect

Optimal entropic properties of SARS-CoV-2 RNA sequences

The reaction of the scientific community against the COVID-19 pandemic has generated a huge (approx. 106 entries) dataset of genome sequences collected worldwide and spanning a relatively short time window. These unprecedented conditions together with the certain identification of the reference viral genome sequence allow for an original statistical study of mutations in the virus genome. In this paper, we compute the Shannon entropy of every sequence in the dataset as well as the relative entropy and the mutual information between the reference sequence and the mutated ones. These functions, originally developed in information theory, measure the information content of a sequence and allows us to study the random character of mutation mechanism in terms of its entropy and information gain or loss. We show that this approach allows us to set in new format known features of the SARS-CoV-2 mutation mechanism like the CT bias, but also to discover new optimal entropic properties of the mutation process in the sense that the virus mutation mechanism track closely theoretically computable lower bounds for the entropy decrease and the information transfer