The race to put a man on the Moon between the United States and the Soviet Union is long over. NASA got there first, national glory was achieved and then NASA and the American public lost interest in the Moon. The Russians’ all out space effort collapsed with the Soviet Union and is slowly rebuilding with intermittently successful commercial rocketry. In the follow-up to the Moon as the Next Big Thing, the International Space Station (ISS) is ‘completed’ and doing far less science, or anything else, than was expected. The NASA shuttle craft that were to establish healthy trade between Earth and the ISS – are finished, history, already on their way to becoming museum pieces. These days, the squabbles over mission priorities and budgets at NASA are tawdry and dispiriting. Budgets for space are riddled with cuts and complex politics in most of the other countries that have a presence in space – except China. China appears to be gung ho about space (if the right expression is gung ho, which in the original Chinese are the two words, ‘work’ and ‘together’); but strangely there’s hardly any reaction to China’s space achievements from governments, the media or otherwise. It appears there will be no space race with China. It’s as if we – the professionals, enthusiasts and the non-space engaged public – have mostly lost interest.

What seems to be missing is motivation, a real and powerful motivation to once again garner the attention and interest of the public in exploring space. With the exception of the Chinese, national pride seems to be out of the picture. Science, for all its true value, has never produced much general passion. There is always economics, but so far the exploration of space is a massive loss operation – as if it had any serious economic intention to begin with. Now that could change, perhaps in a big way.

Enter these gentlemen, multi-multi-millionaires and billionaires all: Larry Page, K. Ram Shiram, and Eric Schmidt (Google), James Cameron (film director), Ross Perot Jr. (Perot Systems), Charles Simonyi, Paul Allen (Microsoft), Peter Diamandis (X-Prize), Burt Rutan (aerospace engineer), Eric Anderson (Space Adventures). They have aligned with a company called Planetary Resources, Inc. that has the express purpose of exploring about 1,500 of the 9,000 or so Near-Earth Asteroids (NEA) with the intention of extracting from them valuable resources such as water and platinum. The company predicts that the value of such extraction will be measured in trillions (dollars, presumably).

Although the company was founded in 2009 by Peter Diamandis (a key figure in the personal space flight industry) and Eric C. Anderson (co-founded Space Adventures with Diamandis), the public launch was a rather eagerly anticipated formal announcement made from the home base in Seattle (Washington, USA) on April 24, 2012. In the years since 2009, the company’s narrative has been developed and more importantly the impressive list of names was added to the support roster. The announcement made a relatively big splash in the news for a company that as yet has far more plans than product. So, what have we here?

First, a disclaimer: Three years ago I wrote a novel precisely about the subject of commercial resource extraction from Near-Earth Asteroids, which means I’ve done some homework and have a bias in the direction of thinking the company’s plans are reasonable and feasible. That said, I’m aware that Planetary Resource’s notion of ‘mining asteroids’ is borderline fodder for late-night comedy. Some say it is crazy; et cetera.

I would say that for most people the idea of mining asteroids is brand new, and I use the word ‘brand’ intentionally. As a rule of thumb, most people know about exploring the Moon; most people are aware of plans to reach Mars – but the asteroids? The notion of reaching asteroids with orbits in the neighborhood of Earth has been a fringe idea. There is an important exception: In 2009, a report by the NASA commissioned blue-ribbon committee, the so-called Augustine Report, examined the future of the American humans in space program and recommended that NASA make reaching an NEA a priority. The recommendation was generally disregarded. The choice of a mission to reach an NEA, compared to return to the Moon or a major deep-space mission to Mars has had little or no constituency. However, some of the people involved with Planetary Resources noticed the Augustine Report recommendation.

To explain all the comparative reasoning behind an NEA versus other missions would require a book; I won’t attempt much here except some key points.

Ease of access: Some of the asteroids that have orbits approaching Earth are at their nearest point relatively as close to Earth as the Moon. Although the navigation is more complicated, reaching these asteroids is not much more difficult or time consuming than reaching the Moon. The major factor is that asteroids have no significant gravity. Unlike the Moon, which has one-sixth the gravity of Earth, there is no gravity well to fight on the way onto or off an asteroid. This is a huge savings in energy and simplifies local maneuvering.

Resources: There are many kinds of asteroids, three are the most common. Some are composed primarily of metals (M-type), mostly nickel-iron, mixed with stone and other metals and minerals. Others are composed mostly of carbon-based materials (C-type) including complex hydrocarbons (e.g. methane, ethane, etc.) and materials containing water. More than 75% of asteroids are C-type. Then there are asteroids composed mainly of stony material, often high in silicon mixed with a wide range of minerals. All types of asteroids contain material of commercial-industrial value, but the two materials that are singled out are water and precious metals. Water is arguably the most important because of its potential as a source of rocket fuel (hydrogen and oxygen), and oh yes, life requires it. Water is unfortunately quite heavy, and lifting it off the Earth’s surface is very expensive. The Moon has some water in deep polar craters, but from what we know; it is not available in industrial quantities and would still have to be lifted out of the Moon’s gravity well.

Precious metals – gold, silver, platinum, palladium, ruthenium, rhodium, osmium, and iridium – are of high commercial value, relatively compact for value, and are present in asteroids in what are believed to be accessible conditions. That is, unlike the Moon, the concentrations are relatively high – possibly high-grade ores – that can be extracted and potentially processed on site. Of course the big draw here is these metals are of extreme value on Earth for cosmetic or industrial uses. A thousand kilos of platinum is worth about $50 million at today’s spot price. Lifting quantities such as that from an asteroid for transportation back to Earth is feasible and potentially profitable.

That’s where Planetary Resources, Inc. comes into the picture.

A single 500-meter platinum-rich asteroid contains the equivalent of all the Platinum Group Metals mined in history. “Many of the scarce metals and minerals on Earth are in near-infinite quantities in space. As access to these materials increases, not only will the cost of everything from microelectronics to energy storage be reduced, but new applications for these abundant elements will result in important and novel applications.”
[Source: Planetary Resources press release]

In short, extracting water especially for rocket fuel and human environment supply and mining of valuable ores is the core of Planetary Resource’s plans. Sounds pretty good, but of course how this is to be done – that’s the thing isn’t it? The good news here, which you would expect from people who are both visionary and carefully rich, is that the company isn’t planning a gold rush. Contrary to some of the gushing media coverage, the program spans many years, perhaps decades, and takes everything step-by-step. The first step is to select, explore and analyze candidate NEAs for their commercial value. This will be done by robotic probes – asteroid prospectors. Planetary Resources is already building the first of these probes called the Arkyd-100 Series, which will orbit Earth and participate in the study of NEA candidates. A follow-up series, Arkyd-300, will journey to the target asteroids to conduct on-site exploration. Launch of the first robotics will be in 2013-2014 aboard various rockets.

Common intuition would caution not to minimize the technical difficulty of what Planetary Resources proposes to do. Launching expensive probes is never a sure thing. Getting them to their targets is not trivial. The technology for gathering the appropriate information, especially material samples, is still largely experimental. Returning samples to the Earth is also difficult. Then there comes the whole business of seriously extracting material from the asteroids – the technology for which exists only in Earth-based experience and the imagination of engineers. Let’s put it another way, the path to profitability is very long and uncertain. Why then are the quite intelligent and successful people who support Planetary Resources willing to put up their name and their cash?

Some of them have spoken about it, but I’ll summarize and extrapolate. In a nutshell: The vision of mining asteroids combines some of the romance of space exploration and development of the human race with the notion of making a great deal of money. It replaces the fading motivations of nationalism, the semi-obscure goals of science, and the abstract ideas about building things for Earth in space with something tangible and lucrative. I suppose one could kvetch about greed and profit motive as a mass motivator for developing our solar system, but few who have thought about it would argue that it would, sooner or later, become the ongoing driver.

Meanwhile, the Planetary Resources program will probably have a couple of important effects: It will provide a continuing story that can be followed by the media and the public. It will also require – and put pressure on – governments and space agencies to collaborate with and support the effort. It’s no secret that Planetary Resources will need to work with the science, technology, expertise and funding of academic and government sources. These folks may be rich, but not that rich. So, the effort to reach the asteroids and develop extraction techniques will be a massive joint effort – or it won’t work at all.

I have no idea whether this will happen. I hope so. In a sense, Planetary Resources, Inc. represents the human race getting off its collective butt and once again trying to do something really ‘out there’ – difficult, challenging, and at least in the long run exciting. There’s no need to romanticize the development of space to make it exciting, making a lot of money will do.

If you’ve had any exposure to how the brain and nervous system works, you probably know about synapses – the juncture where the end of one neuron almost meets the beginning of another neuron. The synapse is two neurons and the gap between them, the point where either chemical neurotransmitters or gap junctions for electrical current carry a nerve signal from one neuron to another. I’m simplifying here in order to get at something that significantly complicates the notion of a synapse. The traditional picture of a synapse tends to obscure the fact that the ‘gap’ (synaptic cleft) between neurons isn’t self contained – it’s part of something outside the neurons. And what is that ‘something’ outside the neurons? Again, traditionally, this has been pictured as the realm of glia, the ‘other’ cells of the brain and nervous system. There are seven kinds of glia and they’ve been considered for a long time to be mainly structural (holding the neurons in place) or supportive (providing nutrients and other housekeeping activity for neurons). In general, the various glia were considered not very interesting compared to the neurons and certainly were not important to the signaling operation of the nervous system. That evaluation is changing and may profoundly affect how we believe the nervous system works.

It’s been known for some time that there are roughly as many glia cells in the brain as there are neurons. Few thought this was significant, although in general, where there is a lot of some material, Nature tends to put it to multiple uses. It was roughly during the 1990’s that researchers began to discover other functions for glia, the most significant was arguably that instead having a passive role in neurotransmission, some forms of glia – astrocytes in particular – have an intimate relationship with neurons in the role of modulating neurotransmission. One of the leaders in these discoveries is Miaken Nedergaard, professor of neurosurgery at the University of Rochester Medical Center (New York, USA). Her pioneering work demonstrated that astrocytes participate in communication with neurons, albeit in a passive role.

The basic idea for astrocytes’ role in the synapse is to regulate the concentration of potassium ions in the synaptic cleft – translated: A signal travelling from one neuron to the other across a synapse may use chemical ions (electrons), including those of potassium and calcium, to transfer the signal. When this happens, astrocytes perform the function of withdrawing ions (potassium) so that the signal will stop, in preparation for the next signal. It was originally assumed that the stopping was controlled by the neurons. The Nedergaard team’s newest research indicates that astrocytes can actively (that is, on their own) stop the signal by withdrawing ions. In a recent paper to be published by Nature Signaling [ April 2012, paywalled, ] the indication is that astrocytes in some way orchestrate the synaptic firing of neurons so that ‘noise’ (random or unwanted neuron activity) is minimized. Neuroscientists call this ‘maintaining synaptic fidelity’ (something like a noise filter on a hi-fi system).

How astrocytes do this ‘orchestration’ and how this all fits together in terms of functioning synapses – to say nothing of how all this fits with general brain and nervous system activity – remains to be seen. As Nedergaard puts it, “Astrocytes are integral to the most sophisticated brain processes.” Indeed, if her team’s findings are corroborated, it implies that the functioning of synapses is more complicated than was already thought. It adds to the notion that there is a ‘third partner’ in the operation of synapses, the astrocytes. What that brings to the party, and why, leaves open questions of potentially high impact. Neuroscientists have already coined a term for this model of neuron activity back around 2006: the tripartite synapse, consisting of the presynapse (axon neuron), postsynapse (dendritic neuron) and glia (astrocytes). Since then, research such as Nedergaard’s continues to show more involvement by astrocytes in modulating how synapses work.

One of the biggest unknowns in neuroscience, especially for the working of the human brain, is how the all-important connections (the synapses) in the neural system (the network of neurons) are organized and cooperate. It appears that the formerly ignored glia may be part of the answer, but the answer, whatever it is, will be yet more complicated. There may be a reason why two of the most complicated intelligences on the planet – humans and elephants – also have the greatest percentage of glia in the brain.

[SciTechStory: Confirmation: Quantum entanglement in photosynthesis]
[SciTechStory: The robin flies with quantum coherence]

From bird navigation to photosynthesis the evidence is mounting that quantum effects, especially quantum coherence, are used in biological processes, and most astonishingly, the effects persist in functioning at biologically sustainable temperatures. While biologists are thrilled by this discovery and for them it opens a new world of research, called quantum biology, for physicists it is also a massive conundrum. How is this persistence of quantum states at high temperatures possible?

There are attempts to answer that question, the newest just hitting the Net at arXiv [29 February 2012, Open Access, Quantum biology on the edge of quantum chaos] by a trio of physicists, Gabor Vattay and Stuart Kauffman and the University of Vermont (USA) and Samuli Niiranen at the Tampere Institute of Technology (Finland). They believe they have found a mechanism that explains how quantum coherence is maintained at biological temperatures.

The heart of their theory is that biological persistence of quantum effects depends on the existence of what is called state transition. The most intuitive of these transition states is where water goes through phases between solid (ice), liquid (water) and gas (water vapor).

The transitions the researchers consider a template are more subtle (atomic rather than physical) – the metal to insulator transition (MIT). There are various materials, especially semiconductors (as the name implies) that with a little nudge (chemical or electrical, for example) can conduct electrons (conductor), or not (insulator). In the technical terms of the paper, the quantum process they are describing is a metal-insulator transition from Anderson localization to extended wave functions. (Where waves of energy remain ordered, coherent, and then transition to disordered wave functions. During this transition a semiconductor changes from an insulator with ordered electro-magnetic wave functions to a metal (conductor) with disordered wave functions.)

Here’s where their story becomes even more difficult to follow. I’ll do my best to keep it simple, but that means losing precision: At an even more subtle level are the quantum effects, especially quantum coherence where particles such as photons, electrons or even molecules are said to be ‘entangled,’ which in quantum-speak is where pairs of particles are, in effect, identical (share the same state). Measure one particle of the pair and you know everything about the other particle (called quantum superposition). The transition in this realm is based on moving to and from quantum coherence to quantum chaos (where the particles are no longer entangled).

In the previous world of quantum mechanics, at least in the research lab, a state of quantum coherence is incredibly fleeting, measured in nano or micro seconds. Quantum coherence ‘normally’ decoheres (breaks down) very rapidly, and at higher temperatures can’t be created (in the lab) at all. Yet nature seems to do it – continually and at high temperatures. Here’s where the new theory steps in and maintains that in photosynthesis, for example, the transition state between quantum coherence and chaos is maintained by the continual addition of new particles – photons of sunlight. In a system they tested, using the light-collecting components of plants called chromophores; they were able to show that loss of quantum coherence is significantly delayed and rebuilt by trapping (harvesting) incoming photons. The researchers call it the “Poised Realm” between the coherent (quantum mechanics) and incoherent (classical mechanics) world.

What is this all about? The key to an answer, at least in the case of photosynthesis, is that the quantum effect involved is part of the ‘harvesting mechanism’ that converts sunlight (photons) into stored energy (as carbohydrate). In short, it is one of the fundaments of life.

What Vattay, Kauffmann and Niiranen have done is work out a model (in mathematics, of course) that they have been able to demonstrate with a biological experiment that explains the quantum mechanism behind this process. They believe that their model can eventually explain many if not all occurrences of quantum biology. The implications are vast, for example, as they put it: “Using this new critical design principle from biology might open the way to build lossless quantum coherent energy and information processing devices operating at room temperature.”

That remains to be seen, of course. Their paper presents a theory and minimum experimental evidence. It will now undergo what all challenging theories experience – critique and attempts to re-create the original experiment along with any number of new experiments to test the theory. In a few years, more will be known about how robust their theory actually is. In the meantime, it at least shows that plausible explanations can be found for something that up to now were considered unexplainable. That’s called progress in science.

The Global Warming controversy is ended. Right.

Take a look at the graph above. It shows the results of global temperature measurements over a span of some 100-200 years as compiled by four groups: NASA Goddard Institute for Space Studies, NOAA (National Oceanic and Atmospheric Administration), United Kingdom Meteorology Office Climatic Research Unit (hadCRU), and the Berkeley Earth Surface Temperature Project. Notice that the graph lines are almost identical and they all show a strong trend in global warming.

This is not exactly news, is it? No, but one line in the graph of particular interest is from a report that is making its way toward official release. It’s important because the data for that line on the graph is from those skeptical of scientific measurement of global warming. The Berkeley Earth Surface Temperature Project was begun by University of California physics professor Richard Muller, a man highly critical of the manner in which climate scientists were gathering and manipulating their data. Initial project funding included sources that generally contribute to climate change denial. Muller’ stated goal was to establish an independent source of climate data that would be thoroughly vetted for bias and error.

The Berkeley team, ten scientists led by Robert Rohde, a specialist in climatology with large data sets, included Saul Perlmutter, this year’s Nobelist in physics. The goal was to assemble a merged set of climate data from surface weather stations, check it for various errors, bias, or other distortions, analyze it with new and existing statistical methods, and provide public access to all the data and results. The result of the multi-year project is a database of 1.6 billion records of climate data, and a report that is now available at the website [Berkeley Earth Surface Temperature], which is heading for peer review and publication. Though not final, this is the official report.

The report is based on data collected from about 40,000 weather stations around the world. It will be difficult to impugn the source, as the Berkeley project explicitly stated that the quality of weather station reporting was sufficiently reliable and more importantly did not reflect the contention that modern ‘urban heat islands’ (the heat generated by cities and roads) affected a significant number of measurements. I would say that this data was also subjected to scrupulous statistical analysis, although that will have to wait for the peer review process to be validated. The essential results, in the words of Dr. Muller:

“Our biggest surprise was that the new results agreed so closely with the warming values published previously by other teams in the US and the UK,” said Professor Muller. “This confirms that these studies were done carefully and that potential biases identified by climate change sceptics did not seriously affect their conclusions.”

[Source: BBC News]

The findings of the Berkeley project agree that the global temperature has increased 1 degree Celsius since 1950 and the trend is up. In short, global warming is real.

So here we are in 2011, more than twenty years after the first warnings about the rise in global temperatures, and most people in the United States still think there is no global warming. The Republican Party has virtually enshrined climate change denial as part of its platform. At the same time, the U.S. military is planning for the effects of global warming on world politics and conflict. The energy industry is preparing a full-scale development of the Arctic petrochemical fields as the ice recedes, and plans are already in motion for shipping routes through the Arctic seas. Many countries, especially island states around the world, are making plans for rising coastal waters. This is what some like to call cognitive dissonance, the discrepancy between what people choose to believe and what is actually happening around them.

Will the addition of one more global warming report, albeit from a group inclined to be skeptics, have an impact? Watch your favorite media outlets. Will the results be highlighted? Will they be mentioned even once? Then judge for yourself.

First a little background: As a simple description, methylation is a switch mechanism for DNA. Chemically, methylation of DNA takes place when a methyl group (a molecule of carbon and hydrogen, CH₃) is added to either cytosine or adenine (two of the bases of DNA). The addition of a methyl group disables (turns off) the corresponding gene, that is, the gene is no longer available to guide the production of protein. Removing the methyl group, demethylation, reverses the process (turns it on). Methylation or demethylation is used within the genome to set up a pattern of active and inactive genes so that, among other things, cells become specialized. For example, a particular methylation pattern directs a cell to become a heart muscle. That pattern in then passed on (inherited) through subsequent cell divisions. The overall process is called epigenetic regulation and is one of if not the principle means of determining cell development, as in a stem cell that becomes a heart cell and stays that way through the life of an organism. It is also used to modify cell functioning in response to environmental conditions. As a rule, changes in epigenetic regulation are not inheritable through the egg or sperm (intergenerational), although the number of known exceptions is growing. The discovery and study of methylation and epigenetics is not much more than thirty years old with the bulk of the research starting in the 1990’s – it is a very young field.

Recent research in methylation continues to expand its reach. Neuroscientists primarily at the Johns Hopkins Brain Science Institute and led by Hongiun Song have been working on the role of methylation in the genome of brain cells (neurons). In previous research they had discovered that the brain cells of mice could be induced to faster growth through electric shock, which was decreasing the amount of DNA methylation. In the recent work, published in Nature Neuroscience [28 August 2011, paywalled, Neuronal activity modifies the DNA methylation landscape in the adult brain] they sequenced the genome of electrically stimulated and non-stimulated mouse brains and compared the results. They found that stimulated brains decreased or increased methylation (cytosine methylation) by 1.4%.

More significantly, they discovered that demethylation was taking place in neurons that were non-dividing on a large scale. This was surprising, as existing scientific consensus held that non-dividing cells were basically passive and the methylation would change very little, if at all. In other words, methylation in brain cells was almost exclusively for directing cell development.

“It was mind-boggling to see that so many methylation sites — thousands of sites — had changed in status as a result of brain activity,” Song says. “We used to think that the brain’s epigenetic DNA methylation landscape was as stable as mountains and more recently realized that maybe it was a bit more subject to change, perhaps like trees occasionally bent in a storm. But now we show it is most of all like a river that reacts to storms of activity by moving and changing fast.”

[Source: Johns Hopkins Medical Center]

Dr. Song’s expression is rather poetic, but the impact of this finding could be far-reaching. It implies that the methylation process in neurons has a function other than cell development (via cell division). What that function is and how exactly it works remains high on the research agenda. Since it is known that in other circumstances methylation is a means of responding to the environment, it is possible that a similar process is at work in the brain. I should mention that other studies have already forwarded the idea that methylation, or some form of epigenetics, may be the basis of memory.

Specifically: Neutrinos produced by the Super Proton Synchrotron at CERN in Geneva Switzerland were directed toward the Gran Sasso facility deep within the mountain of the same name, a distance of some 730km (455 mi). All other nuclear particles won’t go that far, but among the many weird particles in physics, neutrinos take the prize. In this case, the relevant fact is that neutrinos pass through matter – rock, metal, water – like matter doesn’t exist. So, 0.0024 seconds after the neutrinos are produced in Switzerland, they show up passing through bricks of photographic film in Italy. The interesting part, gathered from the OPERA experiment, is that at least some of the neutrinos show up 60 nanoseconds faster than if they were travelling at the speed of light. That’s 0.00000006 of a second faster. The results are published at arXiv [22 September 2011, Measurement of the neutrino velocity with the OPERA detector in the CNGS beam].

If the experimental results are correct, this is…like…awesome. I’m being deliberately obtuse. I know the number is very small; but that is absolutely and relatively not the point. If the speed of light can indeed be broken, a whole lot of physics needs to be re-thought and Einstein probably needs to be reburied. At the moment the implications of the discovery seem to be driving much of the coverage, but it’s way too early for anything other than thought experiments. Real science needs to do its thing. Discoveries of this magnitude must be verified, repeated, challenged and confirmed or not confirmed. The scientists involved are, obviously, no dummies. They are well aware of the burden of proof. They did what they could to check, re-check, examine and criticize their methods and results. Now they have released the information, which they consider preliminary, to the rest of the scientific community. Have at it! Which indeed they will because as Carl Sagan was fond of saying: Extraordinary claims require extraordinary evidence. Besides, nothing gets scientists engaged so much as something that threatens to destroy their work.

If you polled 100 physicists this morning, probably 98 of them would say something like, “What interesting results! No doubt wrong, of course.” The probabilities are that’s correct. Equipment calibration, measurement error, unidentified forces – there are many ways an experiment of such delicacy and precision can go wrong. However, the original scientists did their homework; they established a six-sigma level of confidence in their results. Five sigma would normally suffice to get attention.

However, don’t hold your breath waiting for a resolution. It will take years to play out. New experiments to recreate the measurements will need to be put in place; that alone could take months to years. Undoubtedly there will be some new theoretical modeling. There will be controversy. So be patient; there should be a number of interesting moments yet to come.

Neuroscientists have known for some time that nerve endings near the critical junction points between nerve cells, the synapses, are filled with tiny sacs (like microscopic bubbles) containing chemicals called neurotransmitters. Neurons work by sending a pulse of electro-chemical energy along the length of the cell (through nerve fibers of the axons) until it reaches a synapse – a gap between the end of one neuron and the beginning of another. For the pulse to cross this gap it must trigger the release of neurotransmitters stored in vesicles (those tiny sacs) that cross the gap. Depending on how much and what kinds of neurotransmitters are released, they may fire triggers in the next neuron and so the nerve impulse passes on, from toe to brain in some cases. This is not, as you can tell, the convenient metaphor of an electrical charge travelling down a wire. We are not ‘wired,’ actually; it’s more like tenuously and conditionally connected, something like your computer connected to Wi-Fi.

This is not the most efficient or high speed way of transmitting an electrical signal (parenthetically, some types of neuron actually do act like an efficient ‘wire’); so why are most neurons set up this way? That’s one of the big questions in neuroscience. I mention this because it’s also been clear for some time that the function of the synaptic vesicles and their neurotransmitters is to ‘filter’ or ‘weigh’ the meaning or importance of a pulse coming across the synapse.

An important sub-question for neuroscientists concerns the nature of the vesicles. There are two kinds, identified many years ago because some of them sit around the very end of neuron and release the neurotransmitters when an impulse arrives, and others (the majority) are pooled-up nearby. As far as scientists could tell, the two kinds of vesicles were identical, except that one was in a ‘resting’ pool and the others were in the ‘recycling’ pool. How do these two pools of vesicles interact? What roles are played? The chemistry involved, especially in the composition of the neurotransmitters and their function in transferring electrical information from one neuron to another, is very complicated. It all added up to a lot of unknowns, a mystery, if you like.

A research team at the University of California San Francisco (USA) under Robert Edwards and publishing in the journal Neuron [11 August 2011, paywalled, v-SNARE Composition Distinguishes Synaptic Vesicle Pools] has developed the first evidence that the two vesicles are not the same, that they are defined by having different proteins on their surface.

By using very high powered microscopes and ‘labeling’ specific proteins with glowing markers derived from jellyfish, they were able to determine that the vesicles in the resting pool have a high concentration of the protein VAMP7 on their surface. From this they were able to learn that the particular protein is involved in regulating the release of neurotransmitters, and that there are connections between the behavior of ‘resting’ and ‘recycling’ vesicles.

At this point, it would seem the appropriate reaction might be, “That’s it?” Yes, for the moment. Like a lot of important advances in science, this is one of those seemingly little keystone pieces. It’s a starting point, a piece of knowledge, upon which a much greater edifice will eventually be built. Now that scientists know that the two kinds of vesicles are different in their protein composition and that the protein(s) involved are significant in the release of neurotransmitters, it opens up a vast new area of research. It also points in the direction of that big question in neuroscience, how (and eventually why) do synapses use vesicles to transmit information? It appears that proteins may be at the basis of answering that question. This is consistent with the discoveries across the board in biochemistry that the role of proteins is far more crucial and complex than previously thought. Thus the burgeoning of the new field of proteomics, the study of proteins.

I was debating whether this story has real ‘impact’ or is it just another one of those many steps in the process of scientific discovery. Well, it is that, but I think that in this case science is dealing with one of the most fundamental biological mechanisms, finally dealing with it at the molecular level. In there, we can suspect, might be some answers to how the brain (all the trillions of connections and billions of neurons) turns into ‘mind’ and ‘consciousness.’ This discovery is a long way and maybe decades from that, but just learning that vesicles are different in their use of proteins points neuroscience in a new and potentially important direction.

It would be futile in a blog entry to attempt a satisfying description of supersymmetry and its relationship to the Standard Model of particle physics. Anyway, this piece is about scientists reacting to new information, not about the inner workings of the theory. Still, for convenience: supersymmetry, often shortened to SUSY, is a theory that relates to symmetry between certain elementary particles that are similar to those in the Standard Model but have different characteristics – so called superparticles. Symmetry for these superparticles consists of having for every type of boson a corresponding type of fermion. This relationship forms what are known as superpartners. Superpartners are not considered to belong to the Standard Model of physics.

Supersymmetry was developed in large part to deal with certain problems in the Standard Model. For example, the problem that there is more matter in the universe than we can detect – the problem of so called dark matter. Supersymmetry provides the existence of superparticles to explain dark matter. It also can explain the Higgs boson and some aspects of cosmology. As many a physicist will tell you, SUSY is a lovely theory, earning the high praise of ‘elegant.’ Just one problem, a big one: There is no evidence that superparticles exist.

One of the reasons for building the very expensive high speed colliders, most notably the Large Hadron Collider (LHC) in Switzerland, is to look for superparticles. Up to the point where the LHC came on line, other colliders at lower levels of energy had failed to provide conclusive evidence for the existence of superparticles. It was hoped that the LHC would find them at higher levels. So far, it has not.

That was the message given to physicists at the Lepton-Photon Conference (August, 2011) in Mumbai, India. Most specifically, data from the LHC Beauty experiment, which looked at the frequency of decay for B-meson particles as an indicator of the presence of superparticles (more superparticles, more frequent decay), came up negative. Other LHC experiments also failed to definitively isolate a superparticle at a variety of energy levels.

Generally this might be called bad news. I’m certain many scientists don’t consider it good news. However, as a piece of science, it’s just news – a report on new data. One way to look at it is as a spectrum of data from a variety of experiments. Over the years, colliders in various parts of the world have run experiments attempting to show, directly or indirectly, that superparticles exist. One of the main elements in the experiments was the level of energy at which the ‘collisions’ of particles took place. It was always suspected that superparticles would not appear except at very high energy levels. As expected, at lower energy levels, nothing was detected. Then the Tevatron particle accelerator (Chicago, USA) seemed to show a higher B-meson decay level. The LHC, running at Tevatron and higher energy levels, now has been unable to confirm this.

The data from these tests is enormous in volume and often tricky to analyze; it can take months or years and even then results are almost always ‘tentative.’ Nevertheless, cumulatively and at an ever greater range of energy levels, no convincing evidence for superparticles has been found. Physicists, like every other scientists, have their skeptics and nay-sayers, whose role it is to raise a hand and say – enough. In this kind of science, which is very expensive, the hands go up early (often before experiments are run) and starting waving vigorously when experiments don’t show positive results. Those hands are now joined by quite a few moderate supporters of supersymmetry.

This does not mean that SUSY is dead. Far from it, as bad news typically stimulates the creative juices in a search for other forms of supersymmetry, usually far more complicated forms, to explain the lack of data. Still, data drives the theory in the end. Lack of data suggests the need for a new theory. The news will also spur those physicists who are working on alternative explanations for dark matter and other problems with the Standard Model. Indeed, it will spur a few to increase their questioning of the Standard Model.

This is called scientific ferment. It’s a kind of purgatory for practicing scientists – old theories appear to be dying, new theories are unproven – and a lot of careers are in the balance. It’s hard to be gracious and some individuals fail under pressure. Others rise to the occasion and boost new ideas. To the rest of the world, the uncertainty may seem like chaos. Witness the hash made of conditional scientific consensus in climate science by the deniers of global warming. Supersymmetry, whether it exists or not, doesn’t decide the fate of the universe (or..probably not), but it’s fundamental science so in an intellectual sense, at least, the stakes are high.

The results from the LHC are not totally conclusive, so there will be a call for more experiments and even bigger colliders. Others will say, we’ve run out the string, we can’t afford to go further. The question for everyone in the field of particle physics is: Where do we go from here? Arriving at an answer to that question will be an interesting process, even for non-physicists.

I can see the “?” form over your head. I’ll explain in a bare moment, but first the “Why?” Using the new DNA, biochemists will be able to create proteins that mimic disease conditions, or components of diseases – and turn them on or off as part of experimental testing. Doing this should give scientists much greater insight into the role of proteins in diseases and how to control them. In short, it creates a kind of ‘sandbox’ (controlled) environment to test hypotheses about diseases and how they work. Now, for a bit of explanation…

The place to start is with the concept of phosphorylation. This is what happens to proteins when a phosphate group (PO4) is added, it activates (or deactivates) the protein (often an enzyme) like a chemical on-off switch. Phosphorylation is one of the most fundamental of biochemical processes, used within cells for an untold number of chemical pathways, and the subject of an enormous amount of research. Interestingly, although phosphorylation is crucial to the timing and control of many biological processes, it is not something directly controlled by DNA. It falls into the area known as epigenetics, genetic (reproducible and sometimes inheritable) characteristics that occur largely outside of the usual DNA/RNA mechanics.

What the Yale researchers did is take the phosphorylation capability and code it into the genome, into the DNA of E. coli, a remarkable technical feat. They added the ability to synthesize phosphoserine, a key compound in the phosphorylation of enzymes (among other things), and added it to the natural bag of genetic tricks – using synthetic biology to produce a new form of natural biology (so to speak).

The outcome of adding new DNA to E. coli is that the bacteria can produce ‘natural’ proteins, proteins that scientists choose to create, that have the phosphorylation capability built into them.

“Essentially, we have expanded the genetic code of E. coli, which allows us synthesize special forms of proteins that can mimic natural or disease states,” said Jesse Rinehart co-corresponding author of the research. “What we have done is taken synthetic biology and turned it around to give us real biology that has been synthesized.”

[Source: EurekAlert]

This does sound like a new sandbox to play in, but there are probably rules and limitations built into this sandbox that are yet to be discovered. I’m using the sandbox analogy to emphasize that while the ability to synthesize phosphorylate proteins via DNA is a powerful concept, it may yet prove to have problems in practice. It’s certainly possible that synthesizing disease proteins with phosphorylation built-in is a key to understanding the interaction of living proteins and disease conditions. However, there is more – much more – to the complexity of biological processes that is not well understood, especially in the area of epigenetics. A few years down the road, and the techniques used in this research may be deemed ‘flawed’ or ‘too difficult’ or any number of other conditions that will sideline the technique. Or this could be the beginning of a highly successful approach that opens the research doors to the understanding of many forms of disease. Hopefully so.

The next steps for the Yale team is to actually manufacture proteins for diseases such as cancer(s), type 2 diabetes and hypertension (for example) and put them into experimental environments where they can be observed in vivo or in vitro.

Believe me, if this information is all you’ve heard or remembered (if, of course, you’ve seen anything at all); you’ve just caught sight of the first icy pinnacle of the above water iceberg.

As is typical, what gets the most attention is the thing someone made, in this case the neural core chips. In this case, that misses something far more important – the history and progress of a specific research unit within IBM, the Cognitive Computing group, and its chief scientist, Dharmendra Modha. The neural core chip isn’t some one-off research product; it’s a component that researchers decided was necessary to make progress in a massive research program that began in 2006. Funded to the tune of many tens of millions of dollars [most recently$21 million by the Defense Advanced Research Projects Agency (DARPA) for Phase 2 of the Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project], the Cognitive Computing group encompasses the efforts of IBM’s Almaden Research Center, IBM’s T. J. Watson Research Center and five academic institutions (Columbia University; Stanford University, Cornell University; University of California, Merced; and University of Wisconsin, Madison).

The Cognitive Computing group first made news in 2007 with a mouse-scale brain simulation, followed by a rat-scale brain simulation, then in 2008 a cat-scale brain simulation and finally a simulation of a monkey brain. At each step the simulation required a much bigger supercomputer and it became apparent to the researchers that a traditional computer with enough power to achieve a human-scale simulation would require so much energy, it would probably incinerate itself. Yet the human mind doesn’t (usually) incinerate, in fact, it operates rather nicely at about 10 watts, a rather dim bulb. Modha and his team came to realize that if computers were going to achieve human level mental complexity, they too would have to use less energy. This demanded a different model of computing, hardware and software, than the current mainstream (von Neumann) computers. The new model, as expressed by the tiny, low power building blocks of the neural cores is the cognitive computer.

The Big Picture here is the analogy Modha uses, comparing traditional computers with the left side of the human brain and the cognitive computer (composed of neural cores) with the right side of the brain. In this picture you need both sides to make a complete brain. It’s a useful analogy but as usual beware analogies. The cognitive computer, if and when it gets built, will not be a brain hemisphere. For one thing, as neuroscientists will freely admit, we don’t know how the brain works, much less how thinking works. Yes, there has been great progress in understanding the physical and chemical processes of the brain – enough progress so that the knowledge can inspire ideas like the cognitive computer, but there is no one-to-one correspondence between what we currently know about the brain and the ability to design artificial intelligence.

In an important sense, it doesn’t matter. The inspiration may be enough. For example, in the neural cores IBM has created a silicon chip that weaves the function of memory (RAM) into the function of processing (CPU) so close together (45 nanometers) – like neurons and synapses in the brain – so that an enormous amount of energy is saved at each moment of processing (a thousand times less energy than a transaction in a standard computer). The neural core chips run cool, so to speak, and achieve something already accomplished in the brain without needing to be exact copies of the brain. Indeed, there is nothing biological in the neural core chips.

Another crucial element of the cognitive computer that usually is unmentioned in a discussion about the neural chips is the software. Software in this case isn’t the traditional programming – logic, rules, step-wise sequences – of the von Neumann type computer, instead it is the means of interconnecting the operation of the neural cores so that the system learns. Learning is its programming; something like it is for all animals.

It’s impossible to do justice to this research in something short of a book (an e-book anyway). It’s also possible to overlook the possibility that this approach won’t lead to the results the researchers want. In any case, the cognitive computer, which I repeat doesn’t exist yet, does not get to sentient artificial intelligence. It will, however, be a really big step in that direction. Whether the notion of cognitive computers is ever completely realized, the process of developing the notion will teach us a great deal, for we remain the ultimate in learning machines.