arXiv subjects

Irun R. Cohen

Publications and source records attributed to Irun R. Cohen.

4 recordsLinked to original sources

arXiv2024

Natural Averaging May Complement Known Biological Constraints in Bi-parental Reproduction's Advantages Over Mono-parental in Conserving Species Quantitative Traits

Commonly recognized evolutionarily relevant effects of sexual reproduction include increased diversity, accelerated adaptation, and constrained accumulation of deleterious mutations, along with a secondary effect of species genotype homogenization. Still, strong published arguments prioritize the contribution of biological mechanisms underlying bi-parental reproduction to maintaining species identity above their contribution to diversity. Here, we contribute to the latter position. In an initial mathematical analysis and simulation, we show that in an environment where copying is prone to error, quantitative polygenic traits that are shared within a parents' generation are transmitted to future generations under bi-parental reproduction with less deviation than under asexual reproduction. Furthermore, we abstract away many biological details, and show that this trait conservation is a general statistical effect, driven by the very nature of mixing of parental traits, separately from DNA repair and from the reproductive failures, barriers and disadvantages induced by biological mechanisms. Since survival of ecosystem interaction networks depends on the ability of individuals to replace the networked function of failing, dying or absent members of the same species, more faithful inheritance of common traits helps sustain species and ecosystems. This sustaining effect may have contributed to the very evolution of sexual reproduction.

q-bio.PE↗

arXiv2023

Evolution is Driven by Natural Autoencoding: Reframing Species, Interaction Codes, Cooperation, and Sexual Reproduction

The continuity of life and its evolution, we proposed, emerge from an interactive group process manifested in networks of interaction. We term this process \textit{survival-of-the-fitted}. Here, we reason that survival of the fitted results from a natural computational process we term \textit{natural autoencoding}. Natural autoencoding works by retaining repeating biological interactions while non-repeatable interactions disappear. (1) We define a species by its \textit{species interaction code}, which consists of a compact description of the repeating interactions of species organisms with their external and internal environments. Species interaction codes are descriptions recorded in the biological infrastructure that enables repeating interactions. Encoding and decoding are interwoven. (2) Evolution proceeds by natural autoencoding of sustained changes in species interaction codes. DNA is only one element in natural autoencoding. (3) Natural autoencoding accounts for the paradox of genome randomization in sexual reproduction -- recombined genomes are analogous to the diversified inputs required for artificial autoencoding. The increase in entropy generated by genome randomization compensates for the decrease in entropy generated by organized life. (4) Natural autoencoding and artificial autoencoding algorithms manifest defined similarities and differences. Recognition of the importance of fittedness could well serve the future of a humanly livable biosphere.

cs.NE↗

arXiv2004

Functional immunomics: Microarray analysis of IgG autoantibody repertoires predicts the future response of NOD mice to an inducer of accelerated diabetes

One's present repertoire of antibodies encodes the history of one's past immunological experience. Can the present autoantibody repertoire be consulted to predict resistance or susceptibility to the future development of an autoimmune disease? Here we developed an antigen microarray chip and used bioinformatic analysis to study a model of type 1 diabetes developing in non-obese diabetic (NOD) male mice in which the disease was accelerated and synchronized by exposing the mice to cyclophosphamide at 4 weeks of age. We obtained sera from 19 individual mice, treated the mice to induce cyclophosphamide-accelerated diabetes (CAD), and found, as expected, that 9 mice became severely diabetic while 10 mice permanently resisted diabetes. We again obtained serum from each mouse afterCAD induction. We then analyzed the patterns of antibodies in the individualmice to 266 different antigens spotted on the antigen chip. We identified a select panel of 27 different antigens (10% of the array) that revealed a pattern of IgG antibody reactivity in the pre-CAD serathat discriminated between the mice resistant or susceptible to CAD with 100% sensitivity and 82% specificity (p=0.017). Surprisingly, the set of IgG antibodies that was informative before CAD induction did not separate the resistant and susceptible groups after the onset of CAD; new antigens became criticalfor post-CAD repertoire discrimination. Thus, at least for a model disease, present antibody repertoires can predict future disease; predictive and diagnostic repertoires can differ; and decisive information about immune system behavior can be mined by bioinformatic technology. Repertoires matter.

q-bio.TO↗

arXiv2000

The Emergence of Spatial Complexity in the immune System

Biological systems, unlike physical or chemical systems, are characterized by the very inhomogeneous distribution of their components. The immune system, in particular, is notable for self-organizing its structure. Classically, the dynamics of natural systems have been described using differential equations. But, differential equation models fail to account for the emergence of large-scale inhomogeneities and for the influence of inhomogeneity on the overall dynamics of biological systems. Here, we show that a microscopic simulation methodology enables us to model the emergence of large-scale objects and to extend the scope of mathematical modeling in biology. We take a simple example from immunology and illustrate that the methods of classical differential equations and microscopic simulation generate contradictory results. Microscopic simulations generate a more faithful approximation of the reality of the immune system.

cond-mat.stat-mech↗