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PubMed1990

Precambrian evolution of the climate system.

Climate is an important environmental parameter of the early Earth, likely to have affected the origin and evolution of life, the composition and mineralogy of sedimentary rocks, and stable isotope ratios in sedimentary minerals. There is little observational evidence constraining Precambrian climates. Most of our knowledge is at present theoretical. Factors that must have affected the climate include reduced solar luminosity, enhanced rotation rate of the Earth, an area of land that probably increased with time, and biological evolution, particularly as it affected the composition of the atmosphere and the greenhouse effect. Cloud cover is a major uncertainty about the early Earth. Carbon dioxide and its greenhouse effect are the factors that have been most extensively studied. This paper presents a new examination of the biogeochemical cycles of carbon as they may have changed between an Archean Earth deficient in land, sedimentary rocks, and biological activity, and a Proterozoic Earth much like the modern Earth, but lacking terrestrial life and carbonate-secreting plankton. Results of a numerical simulation of this transition show how increasing biological activity could have drawn down atmospheric carbon dioxide by extracting sedimentary organic carbon from the system. Increasing area of continents could further have drawn down carbon dioxide by encouraging the accumulation of carbonate sediments. An attempt to develop a numerical simulation of the carbon cycles of the Precambrian raises questions about sources and sinks of marine carbon and alkalinity on a world without continents. More information is needed about sea-floor weathering processes.

Atmosphere↗
PubMed2006

Regional heterogeneity and gene flow maintain variance in a quantitative trait within populations of lodgepole pine.

Genetic variation is of fundamental importance to biological evolution, yet we still know very little about how it is maintained in nature. Because many species inhabit heterogeneous environments and have pronounced local adaptations, gene flow between differently adapted populations may be a persistent source of genetic variation within populations. If this migration-selection balance is biologically important then there should be strong correlations between genetic variance within populations and the amount of heterogeneity in the environment surrounding them. Here, we use data from a long-term study of 142 populations of lodgepole pine (Pinus contorta) to compare levels of genetic variation in growth response with measures of climatic heterogeneity in the surrounding region. We find that regional heterogeneity explains at least 20% of the variation in genetic variance, suggesting that gene flow and heterogeneous selection may play an important role in maintaining the high levels of genetic variation found within natural populations.

Climate↗
PubMed2006

Machine learning in bioinformatics.

This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization. Applications in genomics, proteomics, systems biology, evolution and text mining are also shown.

Artificial Intelligence↗
PubMedDate not supplied

[Expression of epithelial oncoproteins in large intestine neoplasms].

The high incidence of the colorectal cancer in the industrialized countries has drawn the interest of the scientific community to detect and investigate its morphologic precursors. Growth factors and oncoproteins could be useful to investigate the morphologic and biologic evolution of precancerous lesions of the large bowel. Therefore the Authors report the results obtained from 30 selected patients with hyperplastic and adenomatous polyps, and different histotypes of colorectal cancer, investigated using the EGF-r and p62 protein expression. The results show the potential usefulness of such markers to evaluate the biology of intestinal tumors.

ErbB Receptors↗
PubMed2004

Adiposity signaling and biological defense against weight gain: absence of protection or central hormone resistance?

An abundant and compelling literature supports the existence of a homeostatic system that dynamically adjusts energy intake and energy expenditure to promote stability of body fat mass. In the context of this system, the ease with which many individuals gain weight is difficult to explain. Some have argued that energy homeostasis operates primarily to defend against weight loss and that, over the course of evolution, biological defense against weight gain was not selected for. According to this Absence of Protection model, obesity is seen as the natural result of living in an obesigenic environment. An alternative hypothesis, termed the Central Resistance model, proposes that under normal circumstances, the energy homeostasis system provides an effective defense against weight gain as well as weight loss and that common forms of obesity involve genetic or acquired defects (or interactions between them) that impair the function of this system. Here, we discuss these dichotomous possibilities within the context of current literature regarding energy homeostasis and suggest a strategy for distinguishing between them.

Animals↗
PubMed2002

Natural language from artificial life.

This article aims to show that linguistics, in particular the study of the lexico-syntactic aspects of language, provides fertile ground for artificial life modeling. A survey of the models that have been developed over the last decade and a half is presented to demonstrate that ALife techniques have a lot to offer an explanatory theory of language. It is argued that this is because much of the structure of language is determined by the interaction of three complex adaptive systems: learning, culture, and biological evolution. Computational simulation, informed by theoretical linguistics, is an appropriate response to the challenge of explaining real linguistic data in terms of the processes that underpin human language.

Artificial Intelligence↗
PubMed1988

Mixed-lineage leukemias and phenotypic shifts occurring in relapsed cases of acute T lymphoblastic lymphomas.

Specimens from 19 patients with NHL were also phenotyped at the onset of the disease; among them, 9 were studied in the relapse phase. The analysis was carried out with monoclonal antibodies directed against T and myeloid cells; at diagnosis, all cases presented an immature thymic phenotype. When analyzed at relapse, phenotypic changes were observed: intra-lineage dedifferentiations (6 cases); mixed-lineage lymphoid and myeloid (2 cases), and pure myeloid relapses (1 case). The molecular analysis of the TCR-genes configuration showed a germ-line pattern at onset and relapse in Case 9 and a modification of the rearrangement patterns during the evolution of the disease in Case 6. These data point out that the relapse is often accompanied by intra-lineage modifications resembling dedifferentiation and, more rarely by a myeloid switch. The phenotypic follow-up of these patients may be important to the implementation of chemotherapeutic protocols that are more adequate for the biological evolution of the disease.

Antibodies, Monoclonal↗
PubMed1979

Immunoblastic lymphadenopathy: evolution into immunoblastic sarcoma.

A case of immunoblastic lymphadenopathy which underwent transformation into immunoblastic sarcoma is reported. A 64-year-old man presented with a rash, generalised lymphadenopathy, and hepatosplenomegaly. A cervical lymph node removed at biopsy showed the features of immunoblastic lymphadenopathy with the presence of heavy chain classes IgG, IgM, and IgA and both kappa and lambda light chain types in the cytoplasm of the immunoblasts. No such immunoglobulins could be demonstrated in the lymph nodes obtained at necropsy when the patient died of widespread immunoblastic sarcoma. The biological evolution and histogenesis of the disease are discussed and the current literature is reviewed.

Bone Marrow↗
PubMed1997

Origin of biochemical organization.

The problems of the origin of life and biochemical evolution are analyzed in the context of the biochemical organization concept proposed earlier by the authors. The traditional view according to which the evolution of biological systems occurred from lower levels to systems of higher levels is criticized. It is suggested that the formation of the cell and biological systems of lower levels (subcellular structures, supramolecular structures, biomacromolecules) occurred in a coordinated manner. The liposome and inorganic hypotheses of the origin of life are discussed. Regosome model based on ideas of Nussinov and Mekler which combines advantages of the liposome and inorganic hypotheses has been adopted and modernized. It is suggested that the initial metabolism of protocells based itself on C2-C3-compounds. Autodevelopment of catalytic systems of protocells is discussed.

Biochemical Phenomena↗
PubMed2003

Delayed gratification habitable zones: when deep outer solar system regions become balmy during post-main sequence stellar evolution.

Like all low- and moderate-mass stars, the Sun will burn as a red giant during its later evolution, generating of solar luminosities for some tens of millions of years. During this post-main sequence phase, the habitable (i.e., liquid water) thermal zone of our Solar System will lie in the region where Triton, Pluto-Charon, and Kuiper Belt objects orbit. Compared with the 1 AU habitable zone where Earth resides, this "delayed gratification habitable zone" (DGHZ) will enjoy a far less biologically hazardous environment - with lower harmful radiation levels from the Sun, and a far less destructive collisional environment. Objects like Triton, Pluto-Charon, and Kuiper Belt objects, which are known to be rich in both water and organics, will then become possible sites for biochemical and perhaps even biological evolution. The Kuiper Belt, with >10(5) objects > or =50 km in radius and more than three times the combined surface area of the four terrestrial planets, provides numerous sites for possible evolution once the Sun's DGHZ reaches it. The Sun's DGHZ might be thought to only be of academic interest owing to its great separation from us in time. However, approximately 10(9) Milky Way stars burn as luminous red giants today. Thus, if icy-organic objects are common in the 20-50 AU zones of these stars, as they are in our Solar System (and as inferred in numerous main sequence stellar disk systems), then DGHZs may form a niche type of habitable zone that is likely to be numerically common in the Galaxy.

Earth, Planet↗
PubMed2006

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

BACKGROUND: To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. RESULTS: To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. CONCLUSION: By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence information. This method may yield further information about biological evolution, such as the history of horizontal transfer of each gene, by studying the detailed structure of the phylogenetic tree constructed by the kernel-based method.

Archaeal Proteins↗
PubMed2001

Biological effects of space radiation.

To determine the effects of space radiation on human health for long-term stays in space, we performed 21 space experiments on radiation biology. Two main characteristics of space are microgravity and space radiation that consists of low dose, chronic exposure at low dose-rates, and heavy particles. Through space experiments, we demonstrated the formation of DNA strand breaks, induced mutations, abnormal cell differentiation and the inducible gene expression of a tumor suppressor gene product, p53, in various kinds of organisms. In addition, we investigated the influence of microgravity on radiation-induced biological effects in in vitro biochemical reaction systems and in vivo cell culture systems of bacteria and lower eukaryotes. We review here the importance of radiation biology studies on space radiation from the viewpoints of human health and biological evolution, from the beginning of life until today, in the context of environmental genotoxic radiation.

Aerospace Medicine↗
PubMed1977

A model for macromolecular selection in complementary instructing systems.

In this paper we consider a model for the selection and evolution of biological macromolecules when their reproduction is based on complementary instruction. The model is an extension of one of Eigen's models for selection and takes in account explicitly the formation of both single stranded and double stranded molecular complexes. We construct exact solutions to the rate equations for the case of constant rate parameters and error distributions. Criteria for selection are discussed.

Biological Evolution↗
PubMed1999

Cell behaviour as a dynamic attractor in the intracellular signalling system.

We present a model of the cell signalling network based on the generic properties of interactions between protein kinases (PKs) and protein phosphatases (PPs) inside cells. The model is designed to examine the global properties and intrinsic dynamics of the phosphorylation system. A genetic algorithm (GA) is used to evolve populations of "cells". The GA selects cells and ranks them based on an analysis of the dynamics of the proteins within the networks from a series of different random starting conditions. The fittest cells are taken to be those which can generate a variety of different "behaviours" from a series of different initial conditions. During the GA, intracellular protein interactions evolve via mutation and an analogue of domain shuffling between protein types that is thought to occur during biological evolution. The dynamics of the simulated networks are presented and we discuss the hypothesis that changes in the behaviour of a cell may be interpretable as a switch between attractor basins in the intracellular signalling network.

Algorithms↗