Metastability of life

The physical idea of the natural origin of diseases and deaths has been presented. The fundamental microscopical reason is the destruction of any metastable state by thermal activation of a nucleus of a nonreversable change. On the basis of this idea the quantitative theory of age dependence of death probability has been constructed. The obtained simple Death Laws are very accurately fulfilled almost for all known diseases.Comment: 3 pages, 4 figure

Effect of expectoration on inflammation in induced sputum in α-1-antitrypsin deficiency

SummaryIt is unclear how chronic expectoration influences airway inflammation in patients with chronic lung disease. The aim of this study was to investigate factors influencing inflammation in induced sputum samples, including, in particular, chronic sputum production. Myeloperoxidase, interleukin-8, leukotriene B4 (LTB4), neutrophil elastase, secretory leukoprotease inhibitor (SLPI) and protein leakage were compared in induced sputum samples from 48 patients (36 with chronic expectoration) with COPD (with and without alpha-1-antitrypsin deficiency; AATD), 9 individuals with AATD but without lung disease and 14 healthy controls. There were no differences in inflammation in induced sputum samples from healthy control subjects and from AATD deficient patients with normal lung function but without chronic expectoration (P>0.05). Inflammation in induced sputum from AATD patients with airflow obstruction and chronic sputum expectoration was significantly greater than for similar patients who did not expectorate: Interleukin-8 (P<0.01), elastase activity (P=0.01), and protein leakage (P<0.01). The presence of spontaneous sputum expectoration in AATD patients with airflow obstruction was associated with increased neutrophilic airway inflammation in induced sputum samples. The presence of chronic expectoration in some patients will clearly complicate interpretation of studies employing sputum induction where this feature has not been identified

Fallback accretion on to a newborn magnetar : long GRBs with giant X-ray flares

Flares in the X-ray afterglow of gamma-ray bursts (GRBs) share more characteristics with the prompt emission than the afterglow, such as pulse profile and contained fluence. As a result, they are believed to originate from late-time activity of the central engine and can be used to constrain the overall energy budget. In this paper, we collect a sample of 19 long GRBs observed by Swift-XRT that contain giant flares in their X-ray afterglows. We fit this sample with a version of the magnetar propeller model, modified to include fallback accretion. This model has already successfully reproduced extended emission in short GRBs. Our best fits provide a reasonable morphological match to the light curves. However, 16 out of 19 of the fits require efficiencies for the propeller mechanism that approach 100%. The high efficiency parameters are a direct result of the high energy contained in the flares and the extreme duration of the dipole component, which forces either slow spin periods or low magnetic fields. We find that even with the inclusion of significant fallback accretion, in all but a few cases it is energetically challenging to produce prompt emission, afterglow and giant flares within the constraints of the rotational energy budget of a magnetar

The Heumann-Hotzel model for aging revisited

Since its proposition in 1995, the Heumann-Hotzel model has remained as an obscure model of biological aging. The main arguments used against it were its apparent inability to describe populations with many age intervals and its failure to prevent a population extinction when only deleterious mutations are present. We find that with a simple and minor change in the model these difficulties can be surmounted. Our numerical simulations show a plethora of interesting features: the catastrophic senescence, the Gompertz law and that postponing the reproduction increases the survival probability, as has already been experimentally confirmed for the Drosophila fly.Comment: 11 pages, 5 figures, to be published in Phys. Rev.

Interplay between distribution of live cells and growth dynamics of solid tumours

Experiments show that simple diffusion of nutrients and waste molecules is not sufficient to explain the typical multilayered structure of solid tumours, where an outer rim of proliferating cells surrounds a layer of quiescent but viable cells and a central necrotic region. These experiments challenge models of tumour growth based exclusively on diffusion. Here we propose a model of tumour growth that incorporates the volume dynamics and the distribution of cells within the viable cell rim. The model is suggested by in silico experiments and is validated using in vitro data. The results correlate with in vivo data as well, and the model can be used to support experimental and clinical oncology

Exact Solution of an Evolutionary Model without Ageing

We introduce an age-structured asexual population model containing all the relevant features of evolutionary ageing theories. Beneficial as well as deleterious mutations, heredity and arbitrary fecundity are present and managed by natural selection. An exact solution without ageing is found. We show that fertility is associated with generalized forms of the Fibonacci sequence, while mutations and natural selection are merged into an integral equation which is solved by Fourier series. Average survival probabilities and Malthusian growth exponents are calculated indicating that the system may exhibit mutational meltdown. The relevance of the model in the context of fissile reproduction groups as many protozoa and coelenterates is discussed.Comment: LaTeX file, 15 pages, 2 ps figures, to appear in Phys. Rev.

AT2023fhn (the Finch): a Luminous Fast Blue Optical Transient at a large offset from its host galaxy

Luminous Fast Blue Optical Transients (LFBOTs) - the prototypical example being AT 2018cow - are a rare class of events whose origins are poorly understood. They are characterised by rapid evolution, featureless blue spectra at early times, and luminous X-ray and radio emission. LFBOTs thus far have been found exclusively at small projected offsets from star-forming host galaxies. We present Hubble Space Telescope, Gemini, Chandra and Very Large Array observations of a new LFBOT, AT2023fhn. The Hubble Space Telescope data reveal a large offset (greater than 3.5 half-light radii) from the two closest galaxies, both at a redshift of 0.24. The isolated environment of AT 2023fhn is in stark contrast with previous events, is challenging to explain with most LFBOT progenitor models, and calls into question the homogeneity of LFBOTs as a class.Comment: Submitted to MNRASL. 7 pages, 4 figures, 2 table

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally