Theoretical Biology Forum最新文献

Atherosclerosis and diabetes are largely recognized as inflammatory disorders underlying cardiovascular disease. C-reactive protein, interleukin-6 and fibrinogen constitute the most established inflammatory biomarkers in clinical practice for the characterization of individuals affected by atherosclerosis, diabetes and heart failure. In addition to their traditional role as inflammatory markers, emerging evidence suggests their role as active mediators in cardiovascular pathogenesis. The interplay between these circulating inflammatory biomarkers and established cardiovascular risk factors, such as dyslipidemia, hyperglycemia, insulin resistance and elevated NTproBNP needs to be investigated. In this review, we aim to determine whether these biomarkers are merely hallmarks of inflammation or active factors in the pathogenesis of cardiovascular diseases by analyzing their links with HDL/LDL, glycemia, insulin resistance and NT-pro-BNP, respectively. C-reactive protein directly promotes atherosclerosis by increasing LDL transcytosis across endothelial cells and enhancing LOX-1 expression. It provides complementary information to NT-pro-BNP for high risk of major adverse cardiac events in post-MI patients and predicts mortality in type 2 diabetic subjects. Interleukin- 6 activates hepatic LDL receptor transcription and correlates with endothelial dysfunction and carotid intima-media thickness. It is related to higher NT-pro-BNP levels and insulin resistance. Fibrinogen is independently associated with a more atherogenic lipoprotein subfraction profile in diabetic patients and insulin resistance. In these patients the fibrinogen glycation level is higher and forms fibrin clots with enhanced resistance to fibrinolysis. Finally, the fibrinogen-to-albumin ratio in heart failure is positively correlated with NT-pro-BNP. In conclusion, C-reactive protein, interleukin-6 and fibrinogen may emerge as active drivers and promising therapeutic targets in cardiovascular diseases.

This article examines the role played by E.-É. Duvillard in the formalization of the idea of mortality in modern mathematical demography. Both his published and unpublished works will be considered with a view to understand his notion of the instantaneous death rate, in terms of notions such as vital force and destructive force.

The sympatric speciation is an important phenomenon in the Evolution where a population able to express two different phenotypes gives rise to a new species without a physical separation from the initial population. Our goal is to show as simple assumptions on the initial population phenotypes and the selection process induced by a fluctuating environment allow to define a simple stochastic model that can explain the sympatric speciation via a stochastic bifurcation mechanism. We analyze the dynamical properties of the model and its possible relevance to describe the evolution of the speciation process as the result of enviromental fluctuations, highlighting the control parameters.

Its fiftieth anniversary seems like a good occasion to compare Richard Dawkins' The Selfish Gene (1976) with other science classics. As is often the case with influential ideas, its core message is deeply rooted in earlier thought. Moreover, because of the specific, sociobiological context in which it emerged, that message was advanced for the wrong reason - as a misguided argument against group selection - for which there are also important precedents. Furthermore, as is often the case when important insights gain traction through a landmark publication, The Selfish Gene provoked controversy, which in this instance was intensified by its sociobiological origins. Yet in one crucial respect, Dawkins' book differs from other classics. Whereas new theories typically evolve beyond their initial breakthrough, Dawkins' original and controversial selfish gene theory has remained remarkably influential. This historical anomaly can be linked to the "messy patchwork of several loosely connected subfields" that make up evolutionary biology. Seen in this broader historical light, The Selfish Gene stands out, not only as a scientific milestone, but also as an atypical millstone for the message it conveyed.

This discussion note contrasts Richard Dawkins' genecentric neo-Darwinian theory of evolution with Alfred North Whitehead's process philosophy to propose a philosophical critique of mechanistic evolutionary models. Dawkins' The Selfish Gene frames evolution as a struggle of selfish genes, with organisms as mere vehicles. Whitehead's process philosophy, however, reimagines evolution as a creative, relational process driven by creativity and subjective aim, where chaos fosters novelty. Drawing on the chaostability hypothesis, which posits that higher chaos enhances system stability, I argue that Whitehead's framework offers a holistic alternative to Dawkins' reductionism, emphasizing evolution as a dance of becoming. This note invites further exploration of evolution's metaphysical dimensions in the philosophy of biology.

In this paper we present a first analysis on the analogies between the theory of evolution and business management. In both cases, the mathematical tool, in this approach, is the game theory. We have preliminarly proposed historiographical considerations in order to frame the topic. Then we have presented an example-model of business management, with reference to a particular Nash equilibrium (NE). Analogy with ESS.

It has long been understood that new genes evolve from duplication events and subsequent divergence. Since 2006, however, many studies have argued that entire protein-coding genes can emerge "from scratch" by recruiting "random", non-coding and functionless sequences, contrary to what was thought possible. The hypothesis of "de novo" origination is used to explain why some genes do not possess homologs and appear to be lineagespecific "orphans". Some have been implicated in important evolutionary adaptations. Unfortunately, the new field is marred by theoretical problems, false positives, misleading claims and a failure to validate. Many de novo genes are likely to be derived from diverged fragments of older genes that have since been lost in most lineages or revived in one alone. Instead of scouring genomes for evidence of de novo gene birth, improvements in detection tools and methodologies are now urgently required.