Rejecting what is known about viral microRNAs and nutrient-dependent microRNAs

terrarium eco system
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Of Cells and Limits

Leonard Hayflick has been unafraid to speak his mind, whether it is to upend a well-entrenched dogma or to challenge the federal government. At 86, he’s nowhere near retirement.

By Anna Azvolinsky | March 1, 2015


The rejection letter came from Francis Peyton Rous who received the Nobel Prize a few years later for his discovery of chicken tumor viruses.

My comment:

My 2014 invited review of nutritional epigenetics detailed how differences in the microRNA/messenger RNA balance link viral microRNAs from ecological variation to ecological adaptations via the RNA-mediated differentiation of all cell types in all individuals of all species. It was returned without review.

The problem appears to be the clear link from viruses to RNA-mediated cell type differentiation via amino acid substitutions that stabilize DNA in the organized genomes of all species. That clear link led to the invitation to submit the review.

The invitation came after publication of  Nutrient-dependent/pheromone-controlled adaptive evolution: a model and a series of other previously published works that detail the molecular epigenetics of biophysically constrained RNA-mediated protein folding.

Many of my “peers” still seem to think that mutations lead to the evolution of biodiversity. They won’t consider the fact that viral microRNAS cause entropy or that nutrient-dependent microRNAs link entropic elasticity from DNA repair to the physiology of reproduction.

That anti-entropic fact links the metabolism of nutrients to species-specific pheromones that control the physiology of reproduction. The pheromones link RNA-mediated fixation of nutrient-dependent amino acid substitutions from metabolic networks to genetic networks in species from microbes to humans. See for examples in humans: Clinically Actionable Genotypes Among 10,000 Patients With Preemptive Pharmacogenomic Testing.

Examples from more than 14,000 patients now show what serious scientists have learned during the past two decades. What they have learned is exemplified in the honeybee model organism and many other model organisms.

In 2013, I wrote: “The honeybee already serves as a model organism for studying human immunity, disease resistance, allergic reaction, circadian rhythms, antibiotic resistance, the development of the brain and behavior, mental health, longevity, diseases of the X chromosome, learning and memory, as well as conditioned responses to sensory stimuli (Kohl, 2012).”

In his 2003 presentation to the American Philosophical Society, Greg Bear told others about ancient viruses in the human genome that link sexual recombination and pheromonal interaction in multicellular organisms. The organisms communicate with each other, which links what is currently known about physics, chemistry, and molecular epigenetics to species-wide epigenesis and to the obvious anti-entropic examples of epistasis via metabolic and genetic networks.

Unfortunately, more than a decade after Greg Bear presented the facts about biodiversity in two of his science fiction novels, the accuracy of his claims about viruses goes largely unnoticed. Honeybee colony collapse is noticed. But, despite the fact that facts are facts and the fact that facts about viral microRNAs and nutrient-dependent microRNAs have replaced theories, theorists prefer their ridiculous theories.

Perhaps honeybee colony collapse has nothing to do with their nutrient-dependent pheromone-controlled reproduction. Perhaps Greg Bear was wrong when he claimed that “Networks from beehives to brains solve problems through the exchange and the selective cancellation and modification of signals. Species and organisms in ecosystems live and die like signals in a network.”

Perhaps evolutionary theorists like Masatoshi Nei are correct and “…genomic conservation and constraint-breaking mutation is the ultimate source of all biological innovations and the enormous amount of biodiversity in this world.” Mutation-Driven Evolution (p. 199).

Is there a model for that?

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