Archive | October 2016

Biological Semiconductors: Frontiers

The concept of biological semiconductors has been around for some years (e.g A V Vannikov 1970.

Bioelectrical signals play critical roles in many biological processes such as energy harvesting, rapid communications and inter/intra cellular synchronisation.  Specific examples include photosynthesis, vision, carbohydrate metabolism, neurophysiology, wound healing, tissue regeneration and embryonic development.

Biological semiconductors already identified include melanin and peptides. Charge transport has also been found in a variety of naturally-derived small molecule, semiconducting biological compounds including carotenoids (produced by plants and bacteria), which offer protection against oxidative species, pigmentation, and light harvesting for photosynthesis. M Mukovich 2012.  

The Giese Group, examined electron transfer along a series of polypeptides and demonstrated that the existence of central aromatic acids can serve as stepping stones to support the electron hopping mechanism. W Sun 2016.  It has been noted that ‘assuming an electron or hole in a polypeptide is located on any peptide group, then if the life of this state is comparable with the period of interpeptide vibrations, the distances between all the bonds in the peptide group are changed and stabilised in this state.  Furthermore, in the neighbourhood of this peptide group, the distances between neighbouring peptitdes also becomes different, which changes the probability of transfer from group to group.  It is observed that the proposed mechanism for this is extremely similar to the mechanism of the motion of a polaron in an oxide semiconductor’. L I. Boguslavskii – 2013

Current Research

Biological semiconductors are receiving increasing interest from the research community as “semiconductor and information technologies are facing many challenges as CMOS/Moore’s Law approaches its physical limits, with no obvious replacement technologies in sight. Several recent breakthroughs in synthetic biology have demonstrated the suitability of biomolecules as carriers of stored digital data for memory applications” Mitra Basu 2017.

Quantum Biology and Biological Semiconductors.

There are several evidenced examples in biology of processes which involve ultra-fast electron transfer, singlet and triplet spin mechanisms and quantum coherence (taking place at room temperature).

  1. Evidence of the solid state photo-CIDNP effect, singlet and triplet states, ultra-fast electron transfer, and quantum coherence in photosynthesis.
  2. Evidence of the solid state photo-CIDNP effect, singlet and triplet states and ultra-fast electron transfer in some flavoproteins.  In addition there are widely explored scientific theories of cryptochrome (a flavoprotein) triggering a quantum mechanical effect during ‘magnetoreception’.

Manifestations of quantum coherence in different solid state systems include semiconductor confined systems, magnetic systems, crystals and superconductors.  Ultrafast electron transfer and charge separation is possible in semiconductors A Ayzner 2015, S Gélinas 2014. Read More…

Good Timing: The Synchronisation of Neural Networks in Computing and Implications for Neurology

A symbiotic relationship now exists between the study of neural networking in computing, and neurology.  Artificial neural networks were originally inspired by neuroscience, although major developments have been guided by insights into the mathematics of efficient optimization, rather than neuroscientific findings.  A H Marblestone 2016.  Now neurology is looking towards the development of neural networks to increase our understanding of how the brain works.  There is the possibility that  the two fields will increasingly merge – with particular recognition of the importance of bio-physics in the study of intelligence.

For a long time, the accepted model of memory formation was linear. Short term memories were thought to directly transform into long term memory in a classical, mechanistic fashion. But this model has been challenged.

The new model emerging is complex and non-linear.  The brain is starting to be seen as ‘more than the sum of its parts’ – analogous to a parallel computer (with many interconnected networks), artificial neural networks/deep learning, or a ‘network of networks (such as the Internet), with all the problems (cascading failures) and solutions (built in redundancy) that are associated with such a model.

Modern neuroscience is going through a renaissance of its own – moving away from mechanistic views of the brain, to focus on connectivity.  It recognises some networks may be particularly important for such connectivity e.g the default mode network – which is effected in various neurological conditions such as Alzheimer’s, as well as altered states of consciousness such as meditation and psychedelic drug use.
Read More…

Circadian Rhythms and Ageing

Intraterrestrial life extends down at least 5 km and animals are found even in the deepest oceans. The biosphere is, therefore, dominated by dark, largely “arrhythmic” habitats, and in terms of biomass, most of life on earth resides in places isolated from the direct effects of the sun…studies of species that live away from the sun […]

Is the Coupling of Circadian Rhythms and Metabolism/Redox Regulating Morphogenesis

Self Organisation Far from Equilibrium

New states can arise from far from equilibrium, possessing an extraordinary degree of order, whereby trillions of molecules coordinate their actions in space and time. Under certain circumstances, entropy producing processes are able to organise themselves in the presence of noise, in a way that so called dissipative structures are formed (Prigogine and Lefever 1975, and Nicolis and Prigogine 1977).  Also see J England 2015 on ‘dissipative adaptation in driven self-assembly’.

Dissipative processes are present in biology.  It is asked whether these could be contributing to morphogenesis.

Stochastic reaction-diffusion simulations have been successfully used in a number of biological applications. Formation of skin patterns and the biochemical processes in living cells (like gene regulatory networks), the cell cycle, circadian rhythms, signal transduction in E Coli chemotaxis, MAPK pathway, oscillations of Min proteins in cell division, and intracellular calcium dynamics are examples of processes mathematically modelled by reaction and reaction-diffusion systems. T Vejchodsky 2013, J Eliaš – ‎2014A Zakharov 2014T Hinze 2011. Read More…