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The Neo-Darwinist Modern Synthesis of evolutionary biology mistakenly relied on Crick`s Central Dogma of molecular biology as excluding any control of genome sequences by organisms. The mistake can be unraveled by considering how DNA is replicated. The most important part of that process is open to control by organisms. The reason is that only a small part of the process can be attributed to a mechanism of replication “like a crystal”, as proposed by the Selfish Gene theory. The larger part is attributable to extensive proof-correction by cut and paste enzymes that are coordinated by the living cell. That process reduces the error rate of replication from 1 to 104 nucleotides to 1 in 1010, which is a million-fold increase in accuracy. There is therefore no replicator separate from its vehicle, the living cell. That error rate is under control by organisms. The mechanisms by which Electro-Transcription (ET) coupling is achieved have now been identified. Similar mechanisms must exist for Electro-Gene-engineering (EG) coupling. Such mechanisms change the fundamentals of biology.

Xin Su Ning (XSN), a China patented and certified multi-herbal medicine, has been available in China since 2005 for treating cardiac ventricular arrhythmia including arrhythmia induced by ischemic heart diseases and viral myocarditis, without adverse reactions being reported. It is vitally important to discover pharmacologically how XSN as a multicomponent medicine exerts its clinical efficacy, and whether the therapeutic effect of XSN can be verified by standard clinical trial studies. In this paper we report our discoveries in a cellular electrophysiological study and in a three-armed, randomized, double-blind, placebo-controlled, parallel-group, multicenter trial. Conventional electrophysiological techniques were used to study the cellular antiarrhythmic mechanism of XSN. Data was then modeled with computational simulation of human action potential (AP) of the cardiac ventricular myocytes. The clinical trial was conducted with a total of 861 eligible participants randomly assigned in a ratio of 2:2:1 to receive XSN, mexiletine, or the placebo for 4 weeks. The primary and secondary endpoint was the change of premature ventricular contraction (PVC) counts and PVC-related symptoms, respectively. This trial was registered in the Chinese Clinical Trial Register Center (ChiCTR-TRC-14004180). We found that XSN prolonged AP duration of the ventricular myocytes in a dose-dependent, reversible manner and blocked potassium channels. Patients in XSN group exhibited significant total effective responses in the reduction of PVCs compared to those in the placebo group (65.85% vs. 27.27%, P < 0.0001). No severe adverse effects attributable to XSN were observed. In conclusion, XSN is an effective multicomponent antiarrhythmic medicine to treat PVC without adverse effect in patients, which is convincingly supported by its class I & III pharmacological antiarrhythmic mechanism of blocking hERG potassium channels and hNaV1.5 sodium channel reported in our earlier publication and prolongs AP duration both in ventricular myocytes and with computational simulation of human AP presented in this report.

Since the Principle of Biological Relativity was formulated and developed there have been many implementations in a wide range of biological fields. The purpose of this article is to assess the status of the applications of the principle and to clarify some misunderstandings. The principle requires circular causality between levels of organization. But the forms of causality are also necessarily different. They contribute in asymmetric ways. Upward causation can be represented by the differential or similar equations describing the mechanics of lower level processes. Downward causation is then best represented as determining initial and boundary conditions. The questions tackled in this article are: (1) where and when do these boundaries exist? and (2) how do they convey the influences between levels? We show that not all boundary conditions arise from higher-level organization. It is important to distinguish those that do from those that don’t. Both forms play functional roles in organisms, particularly in their responses to novel challenges. The forms of causation also change according to the levels concerned. These principles are illustrated with specific examples.

Models of cardiac cells are sufficiently well developed to answer questions concerning the actions of drugs on repolarization and the initiation of arrhythmias. These models can be used to characterize drug-receptor action profiles that would be expected to avoid arrhythmia and so help to identify drugs that may be safer. Several examples of such action profiles are presented here, including a recently-developed blocker of persistent sodium current, ranolazine. The models have also been incorporated into tissue and organ models that enable arrhythmia to be modelled also at these levels. Work at these levels can reproduce both re-entrant arrhythmia and fibrillation. Keywords:: cardiac cell model, cardiac organ model, repolarization, early after-depolarization (EAD), delayed after-depolarization (DAD)

The recent growth of the systems approach to biology provides a better conceptual framework within which to interpret holistic approaches to medicine. The reason is that systems biology respects the way in which the whole constrains the parts to behave in ways that are different from what they would do in isolation. Holistic treatments depend on the same insight and can therefore be successful in practice where reductionist approaches would fail.

The question whether evolution is blind is usually presented as a choice between no goals at all (‘the blind watchmaker’) and long-term goals which would be external to the organism, for example in the form of special creation or intelligent design. The arguments either way do not address the question whether there are short-term goals within rather than external to organisms. Organisms and their interacting populations have evolved mechanisms by which they can harness blind stochasticity and so generate rapid functional responses to environmental challenges. They can achieve this by re-organising their genomes and/or their regulatory networks. Epigenetic as well as DNA changes are involved. Evolution may have no foresight, but it is at least partially directed by organisms themselves and by the populations of which they form part. Similar arguments support partial direction in the evolution of behavior.

Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights. [ABSTRACT FROM AUTHOR]

Relating genotypes to phenotypes is problematic not only owing to the extreme complexity of the interactions between genes, proteins and high-level physiological functions but also because the paradigms for genetic causality in biological systems are seriously confused. This paper examines some of the misconceptions, starting with the changing definitions of a gene, from the cause of phenotype characters to the stretches of DNA. I then assess whether the ‘digital’ nature of DNA sequences guarantees primacy in causation compared to non-DNA inheritance, whether it is meaningful or useful to refer to genetic programs, and the role of high-level (downward) causation. The metaphors that served us well during the molecular biological phase of recent decades have limited or even misleading impacts in the multilevel world of systems biology. New paradigms are needed if we are to succeed in unravelling multifactorial genetic causation at higher levels of physiological function and so to explain the phenomena that genetics was originally about. Because it can solve the ‘genetic differential effect problem’, modelling of biological function has an essential role to play in unravelling genetic causation. [ABSTRACT FROM AUTHOR]