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The Revivals Of Cryonics Patients, Using Simulations


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#1 jonano

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Posted 27 November 2007 - 09:43 AM


Hi Alcor Members,

I believe that simulation will evoluate, and progress over time, we will simulate, emulate, with a simulator, a powerful and mature one, biology in a more complete manner and with a biggest, complete complexity.

Simulation is cool because you can try many things and watch what happens next in time. You can try several hypothetical solutions and never touch to the real biology in question.

So I believe simulation will become the next big thing in cryonics just after aging will be solved.

1) Aging is cured. OK! What is next?
2) A simulation technology is developed. (which include all the accurate biology + all the nanomachines [in the simulation])
3) The work is being processed on the simulation, then we know what to do perfectly.
4) We just need to develop the real nanomachines and what the simulation revealed. We have already the real biology.

So I see simulation as a correct try & fail technology, as important as biomedical gerontology, nanomachines and the patients.

The best is to know this:

1) The computer cpu power & memory required to realistically simulate all (and how much, how many) atoms, molecules, cells, organs etc.. + nanomachines and then the whole body of the patient.
2) Run the optimal simulation!

Here I created a page on links about the simulation technology:
http://future.wikia....imulation_Links

In Cryonics only 3 technologies will be required:

1) Biomedical Gerontology
2) Nanomedicine
3) Simulation

The revival of cryonics patients will need mathematics.

As a fan of mathematics I am curious to know what kind of mathematics is used to revive the patients.

Mathematics will be needed in those:

1) Nanomedicine
2) Simulation
3) Aging

Several books on different subjects would clearly define the mathematics required in revival.

--Jon

Edited by jonano, 01 December 2007 - 04:55 PM.


#2 jonano

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Posted 29 November 2007 - 04:37 PM

http://news-service....altman-929.html

Researchers establish national center for biological simulations

BY DAWN LEVY

The National Institutes of Health has awarded $19.9 million over five years to Russ Altman, associate professor of genetics, and Scott Delp, associate professor and chair of bioengineering, to establish and lead the National Center for Physics-Based Simulation of Biological Structures (SimBioS). The new center is charged with developing a simulation toolkit to enable scientists worldwide to model biological systems ranging from molecules to whole organisms.

SimBioS is one of four new national centers endeavoring to build the biomedical computing infrastructure urgently needed to speed progress in biomedical research. The centers will create innovative software programs and other tools allowing the biomedical community to integrate, analyze, model, simulate and share data on human health and disease. Establishment of the four centers this month was an important step in the National Institutes of Health Roadmap, a series of far-reaching initiatives designed to transform the nation's medical research capabilities and speed the transfer of research discoveries from the benchtop to the bedside.

"There has been over the last couple of decades a lot of progress in simulating biological structures in order to understand how they work and how they function," said Altman, a practicing physician and bioinformatics expert who holds departmental appointments in Genetics, Medicine and Bioengineering, as well as a courtesy appointment in Computer Science. "We would like to bring this capability to all biologists in a routine way."

The grant, which holds the possibility for renewal for another five years, aims to build an easy-to-use software package allowing high-quality physical modeling. Altman's vision? "A biologist working on a problem at the molecular, cellular or organismal level may have questions about how the physics of their system affects its function. Using our software, they will, without having to establish new collaborations or going back to school, have a well-supported tool to do the initial modeling. We think this is within grasp."

The SimBioS Center will be located in the Clark Center in shared spaces that the biocomputation faculty has allocated for just this sort of collaboration.

"One of the challenging elements of the project is our goal to simulate a range of living systems from individual atoms to entire organisms," said Delp, who is a bioengineer and expert in biomechanical modeling and simulation. "If you look at the physics of many different biological structures, the fundamental equations that describe these systems have a lot in common. We're going to create a package that can simulate everything from proteins folding to human movement."

Mathematical and computational models provide the framework for understanding complexity in life-a requirement for further progress in biology and medicine. "The group at Stanford has a wide range of expertise, but a particular strength in physics-based simulation of biologic structures," Delp said. "Russ brought together the faculty members from Computer Science, Structural Biology, Biochemistry, Genetics, Mechanical Engineering, Bioengineering and many other departments to define a vision for how Stanford could provide the computing infrastructure for the nation, and the world, to manage biological complexity."

Many faculty played leadership roles during the three years of planning that led to the grant proposal. They include computer science core researchers Leo Guibas, Oussama Khatib, Adrian Lew, Ron Fedkiw, Pat Hanrahan and Jean-Claude Latombe and biomedical computation core researchers Michael Levitt, Vijay Pande, Charles Taylor and Sandy Napel.

Those leaders also include faculty working on four "driving biological problems"-physics-based challenges that are archetypes of common problems in a field, cover a range of scales and have a lot of experimental data from the real world to provide the constraints necessary to drive and validate models and simulations. The problems under investigation are all currently existing peer-reviewed projects: RNA folding, which has implications for rheumatological diseases (principal investigator Dan Herschlag); myosin dynamics, which is important for understanding myopathies and generation of motive force throughout organ systems (Jim Spudich); neuromuscular dynamics, which must be understood to better treat movement disorders resulting from cerebral palsy, stroke and Parkinson's disease (Scott Delp); and cardiovascular dynamics, which has important implications for coronary artery and peripheral vascular disease (Chris Zarins).

Addressing these problems "makes sure we make contributions soon to the science," Altman said. "We have scientists in those domains who've signed up to be early users of our software and to give us feedback as to whether it's working or not working and what it needs to do."

The center also will support creation of new courses in the Bioengineering Department and a newsletter about biomedical computation geared for the public. It will provide on-site training to users of the simulation toolkit, as well as streaming online instruction through the Stanford Center for Professional Development.

#3 jonano

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Posted 01 December 2007 - 11:37 AM

http://www.ncbi.nlm....;indexed=google

Modeling the heart--from genes to cells to the whole organ.Noble D.
University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK. denis.noble@physiol.ox.ac.uk

Successful physiological analysis requires an understanding of the functional interactions between the key components of cells, organs, and systems, as well as how these interactions change in disease states. This information resides neither in the genome nor even in the individual proteins that genes code for. It lies at the level of protein interactions within the context of subcellular, cellular, tissue, organ, and system structures. There is therefore no alternative to copying nature and computing these interactions to determine the logic of healthy and diseased states. The rapid growth in biological databases; models of cells, tissues, and organs; and the development of powerful computing hardware and algorithms have made it possible to explore functionality in a quantitative manner all the way from the level of genes to the physiological function of whole organs and regulatory systems. This review illustrates this development in the case of the heart. Systems physiology of the 21st century is set to become highly quantitative and, therefore, one of the most computer-intensive disciplines.

PMID: 11872832 [PubMed - indexed for MEDLINE]

#4 jonano

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Posted 01 December 2007 - 12:27 PM

ScienceDaily (Nov. 1, 2005) — Researchers at Los Alamos National Laboratory have set a new world's record by performing the first million-atom computer simulation in biology. Using the "Q Machine" supercomputer, Los Alamos computer scientists have created a molecular simulation of the cell's protein-making structure, the ribosome. The project, simulating 2.64 million atoms in motion, is more than six times larger than any biological simulations performed to date.

The ribosome is the ancient molecular factory responsible for synthesizing proteins in all organisms. Using the new tool, the Los Alamos team led by Kevin Sanbonmatsu is the first to observe the entire ribosome in motion at atomic detail. This first simulation of the ribosome offers a new method for identifying potential antibiotic targets for such diseases as anthrax. Until now, only static, snapshot structures of the ribosome have been available.

A paper describing the effort will appear in the Proceedings of the National Academy of Sciences, Oct. 24 edition.

Sanbonmatsu posits that this technique offers a powerful new tool for understanding molecular machines and improving the efficacy of antibiotics. Antibiotic drugs are less than one one-thousandth the size of the ribosome and act like a monkey-wrench in the machinery of the cell. Such drugs diffuse into the most critical sites of this molecular machine and grind the inner working of the ribosome to a halt.

"Designing drugs based on only static structures of the ribosome might be akin to intercepting a missile knowing only the launch location and the target location with no radar information. Our simulations enable us to map out the path of the missile's trajectory," Sanbonmatsu said.

"The methods and implications lie at the interface between biochemistry, computer science, molecular biology, physics, structural biology and materials science," said Sanbonmatsu. "I believe the results serve as a proof-of-principle for materials scientists, chemists and physicists performing similar simulations of artificial molecular machines in the emerging field of nano-scale information processing.

Sanbonmatu's study focuses on decoding, the essential phase during protein synthesis within the cell wherein information transfers from RNA to protein, completing the information flow specified by Francis Crick in 1958 and known as the Central Dogma of Molecular Biology. "The ribosome is, in fact, a nano-scale computer and is very much analogous to the 'CPU' of the cell," he said.

The ribosome is so fundamental to life that many portions of this molecular machine are identical in every organism ever genetically sequenced. In developing the project, the team identified a corridor inside the ribosome that the transfer RNA must pass through for the decoding to occur, and it appears to be constructed almost entirely of universal bases, implying that it is evolutionarily ancient.

The corridor represents a new region of the ribosome containing a variety of potential new antibiotic targets. The simulations also reveal that the essential translating molecule, transfer RNA, must be flexible in two places for decoding to occur, furthering the growing belief that transfer RNA is a major player in the machine-like movement of the ribosome. The simulation also sets the stage for future biochemical research into decoding by identifying 20 universally conserved ribosomal bases important for accommodation, as well as a new structural gate, which may act as a control mechanism during transfer RNA selection.

The multi-million-atom simulation was run on 768 of the "Q" machine's 8,192 available processors. Sanbonmatsu worked to develop the simulation with Chang-Shung Tung of Los Alamos, as well as Simpson Joseph of the University of California at San Diego.

Funding for the research was provided by the National Institutes of Health, Los Alamos National Laboratory's research and development fund, and support from the Laboratory's Institutional Computing Project.

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See an image of the Q machine at http://www.lanl.gov/asci/.

Adapted from materials provided by Los Alamos National Laboratory.




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