A research team led by Australian engineers has created the first working quantum bit based on a single atom in silicon, opening the way to ultra-powerful quantum computers of the future.
In a landmark paper published today in the journal Nature, the team describes how it was able to both read and write information using the spin, or magnetic orientation, of an electron bound to a single phosphorus atom embedded in a silicon chip.... Read more »
UNSW News, NATURE, Physics4u, Physicsgg, & Γούσια Πολυξένη. (2012) Quantum computers | Κβαντικοί υπολογιστές . Tracing Knowledge. info:/
KIPP’s character report card and Paul Tough’s new book have laudably placed an emphasis on how emotional skills and character traits (e.g. persistence, curiosity, optimism, etc.) influence a child’s academic trajectory. Yet the question remains, will our education system make a real effort to emphasize these new ideas, or will they join things like Carol [...]... Read more »
Ventura, M., Shute, V., & Zhao, W. (2013) The relationship between video game use and a performance-based measure of persistence. Computers and Education. DOI: 10.1016/j.compedu.2012.07.003
Earlier this week an important cheminformatics paper appeared in the Journal of Cheminformatics. It is about the Open Molecule Generator (see below for the paper). This was one important piece of functionality still missing from Open Source cheminformatics. This works uses the Chemistry Development Kit, and was written by Julio Peironcely.
The Analytical Biosciences' group of Prof. Hankemeier (and many others, including also Theo Reijmers) and funded by the Netherlands Metabolomics Centre has been using the CDK for metabolomics for a while now, with Miguel Rojas-Chertó as other principle user (and of course CDK developer!). I congratulate them all with this piece of work, and particularly with their choice of license!
Julio (with the other authors) have picked up a difficult algorithm, based in mathematics, but not the straightforward graph theory either. Others have tried to implement structure generation in the CDK, and I looked into this too, when working in Christoph Steinbeck's group back in Cologne. What the OMG team has achieved is significant.
The paper compares their results with MolGen, resulting in results like those in this table (from the CC-SA-BY paper):
It shows that the results are identical, when you consider the atom types it uses. And the use the CDK atom type framework I initiated, which is way cool! Julio found the tables I constructed from earlier CDK code incomplete (as did others) and extended them, to match their needs.
One "problem" with their current code base is that it is quite slow compared to OMG. This is easily compensated by the added functionality of OMG, such as restricting the structure generation with multiple fragments. Now, the CDK data classes are know to be somewhat sluggish, as compared to competition, but the community is increasingly improving this.
But I also think that the OMG use of Naughty via JNI is not helping performance either, and I hope someone will soon jump in and convert that C code into Java code, which should speed up performance too. Another side to this is that removing the dependency on C code will also make it easier to integrate into other tools, like Bioclipse, Taverna, and KNIME.
Julio E Peironcely, Miguel Rojas-Chertó, Davide Fichera, Theo Reijmers, Leon Coulier, Jean-Loup Faulon, & Thomas Hankemeier (2012). OMG: open molecule generator Journal of Cheminformatics, 4 DOI: 10.1186/1758-2946-4-21... Read more »
We have generally believed that animals are not capable of very complex thought, even though many species use tools and engage in other complex behaviors.
Even a bird brain appears to be capable of understanding things that are not visible may be affecting their environment.
This study looks at whether New Caledonian crows, that were caught just for this experiment, are capable of attributing actions to a hidden cause, when they see that possible cause come and go.... Read more »
Taylor AH, Miller R, Gray RD. (2012) New Caledonian crows reason about hidden causal agents. PNAS. DOI: 10.1073/pnas.1208724109
So you want to build a neuron, but don't have the time to fill and stain it, digitally reconstruct it, or even to knit one. Knitting Neuroscience from Knit a Neuron Well you are in luck because a lot of scientists have collected a lot of data already and some of them are even willing to openly share their work. While it is great that people are willing to share their data, that willingness alone is not enough to actually make the data widely accessible (or searchable for that matter). To bridge the chasm, other scientists have developed databases and repositories. These databases and repositories store large datasets and organize them in a searchable way. The first shortcut to building a neuron I will discuss is the Cell Centered Database (CCDB).Sounds a little like "self-centered" but represents just the opposite: scientists willing to share their data with everyoneIn 2003, Martone and colleagues created the CCDB as a repository for 2D, 3D, and 4D images of cells that could be downloaded and used by researchers around the globe. There is a ton of data here, protein stains, electron microscopy, and fluorescent confocal images just to name a few. While you could do a lot with this kind of information, I am just going to give you one example of how it can be used as a major short cut in the process of building a neuron. So say you want to make a model of a cerebellum purkinje cell, but you don't have the time or lab facilities to fill and stain your own neuron. You could go to CCDB, type in 'purkinje neuron' in the search box and download whichever 3D image stack suits your fancy. example Purkinje neuron that I just got from CCDBWith this data you could go straight to step 2: reconstructing the neuron. But what if you don't have the time to digitally reconstruct the neuron? We have already discussed how much time reconstructing a neuron can take, so it's pretty easy to see why you would want to bypass that step too. And in fact, there is a database for that! Halavi et al (2008) developed Neuromorpho.org as a repository for neural reconstructions. Neuromorpho.org has almost 8,000 downloadable digital reconstructions of neurons, which as they say on the website represents over 200,000 hours of manual reconstruction time. NeuroMorpho.org, for all your neural needs.Similar to CCDB, Neuromorpho offers much more than just a shortcut for lazy computational modelers. It has such detailed information about each neuron that a whole project could be done simply by comparing neural characteristics of different cell classes or different species. But my job here is to tell you how you can use it as a shortcut to building a neuron.Say you want to build a computational model of a CA1 Hippocampal Pyramidal Cell, but you don't want to stain it and you don't want to reconstruct it. Well, just go to Neuromorpho.org and click 'browse by brain region' and then on 'hippocampus'. Then look through the 1,000 hippocampal cells (organized by class) that have already been reconstructed for you...Pyramidal cell in the Hippocampus from Neuromorpho.org ...and pick your favorite. Then you can jump right on through to step 3. (coming soon)Halavi M, Polavaram S, Donohue DE, Hamilton G, Hoyt J, Smith KP, & Ascoli GA (2008). NeuroMorpho.Org implementation of digital neuroscience: dense coverage and integration with the NIF. Neuroinformatics, 6 (3), 241-52 PMID: 18949582Martone ME, Tran J, Wong WW, Sargis J, Fong L, Larson S, Lamont SP, Gupta A, & Ellisman MH (2008). The cell centered database project: an update on building community resources for managing and sharing 3D imaging data. Journal of structural biology, 161 (3), 220-31 PMID: 18054501... Read more »
Halavi M, Polavaram S, Donohue DE, Hamilton G, Hoyt J, Smith KP, & Ascoli GA. (2008) NeuroMorpho.Org implementation of digital neuroscience: dense coverage and integration with the NIF. Neuroinformatics, 6(3), 241-52. PMID: 18949582
Martone ME, Tran J, Wong WW, Sargis J, Fong L, Larson S, Lamont SP, Gupta A, & Ellisman MH. (2008) The cell centered database project: an update on building community resources for managing and sharing 3D imaging data. Journal of structural biology, 161(3), 220-31. PMID: 18054501
Today, the Journal of Neural Engineering published rather an interesting paper. In it, they showed that they had been able to restore (and in some cases, improve) decision-making ability in primates through the use of an implanted prosthetic. Sounds like something out of science fiction, doesn’t it? The region of the brain responsible [...]
[Click on the hyperlinked headline for more of the goodness]... Read more »
Robert E Hampson, Greg A Gerhardt, Vasilis Marmarelis, Dong Song, Ioan Opris, Lucas Santos, Theodore W Berger and Sam A Deadwyler. (2012) Facilitation and restoration of cognitive function in primate prefrontal cortex by a neuroprosthesis that utilizes minicolumn-specific neural firing. Journal of Neural Engineering. DOI: 10.1088/1741-2560/9/5/056012
Why settle for good enough, when there can be improvements? “Conventional hydrogels are very weak and brittle—imagine a spoon breaking through jelly,” says lead author Jeong-Yun Sun, a postdoctoral fellow [...]... Read more »
S. Khetan, C. Chung, & JA. Burdick. (2009) Tuning hydrogel properties for applications in tissue engineering. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2094-6. PMID: 19963530
Most metallic things around us—bridges, microchip wires, buildings—are made of arrays of tiny crystals that owe their strength to an orderly, repeating pattern of grains. However, these mixtures, or alloys, of different metals are unstable; under heat or stress they tend to meld together and become larger and weaker. But the right mix can produce a metal that’s stronger, more heat-resistant and capable of creating structures never thought possible.... Read more »
New user-generated content music genres such as the "Bytebeat", that is a new genre of electronic music where a piece of rhythmic and/or somewhat melodic music is generated in real-time using just a relatively short formula. In this experiment I combine both approaches, generative L-systems and executable formulae.... Read more »
Ville-Matias Heikkilä. (2011) Discovering novel computer music techniques by exploring the space of short computer programs. Corr. arXiv: 1112.1368v1
Cyborgs, or cybernetic organisms, are creatures in which biological tissues and artificial additions are closely intertwined. Well-known recent examples include moths and beetles that can be controlled through the use of electronic steering mechanisms attached to their brains. But, the … Continue reading →... Read more »
Tian, B., Liu, J., Dvir, T., Jin, L., Tsui, J.H., Qing, Q., Suo, Z., Langer, R., Kohane, D.S., & Lieber, C.M. (2012) Macroporous nanowire nanoelectronic scaffolds for synthetic tissues. Nature Materials. DOI: 10.1038/nmat3404
Recently we've discussed the first step in how to build a neuron. Today we will discuss step 2: reconstructing that stained cell.Hippocampus CA1 Pyramidal neuron (from Neuromorpho.org)There are a couple of ways that you turn an image (or image stack) of a neuron into a digital neuron file like the one pictured above. Basically there is an easy way and a hard way. The hard way is to reconstruct the neuron manually, where you literally trace the neuron by hand. The easy way is to auto-trace the neuron.In a recent Frontier's in Neuroinformatics article, Myatt et al. (2012) explain the hard to easy gradient in reconstruction methods."Manual (Camera lucida). Prisms are employed to visually overlay the microscope image onto a piece of paper, and the neuron is then traced by hand. Although primarily used for 2D tracings, 3D reconstructions can be derived from these with time consuming post-processing (Ropireddy et al., 2011).Semi-manual (e.g., Neuron_Morpho, Neurolucida). Digital segments are added by hand through a software interface, typically sequentially, beginning at the soma, and working down the dendritic tree.Semi-automatic [e.g., NeuronJ (Meijering et al., 2004; 2D reconstruction only) and Imaris (3D reconstruction)]. User interaction defines the basic morphology, such as identifying the tree root and terminations, but branch paths are traced by the computerFully automatic (e.g., Imaris, NeuronStudio; Rodriguez et al., 2003, AutoNeuron add-on for Neurolucida). The entire morphology is extracted with minimal user-input. " (Myatt et al., 2012)You may ask: "Why not just do it the easy way?" Good question. It is actually surprisingly difficult to make a versatile program that can accurately reconstruct neurons. So difficult in fact that in 2010 an open challenge was issued with a monetary prize for the best automatic reconstruction algorithm. Five teams competed in this DIADEM challenge and the results and process are explained in detail in a special issue of Neuroinformatics. (And in less detail in this HHMI press release)automatic reconstructions of neurons (source)Advances in automatic reconstruction are being made at an astounding pace, but most neural reconstructions are still being done in a semi-manual or semi-automatic way. If you are interested in reconstructing some neurons, you can download Neuromantic for free or Neurolucida for money. There is other reconstruction software available, summarized nicely in Myatt et al. 2012, but these are the two I am most familiar with. In the next edition of "How to Build a Neuron" I will tell you how you can completely skip step 1 (the staining of the neuron) and step 2 (the reconstruction of the neuron). For ease of access, the whole "How to Build a Neuron" series is archived. © TheCellularScaleMyatt DR, Hadlington T, Ascoli GA, & Nasuto SJ (2012). Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology. Frontiers in neuroinformatics, 6 PMID: 22438842... Read more »
Myatt DR, Hadlington T, Ascoli GA, & Nasuto SJ. (2012) Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology. Frontiers in neuroinformatics, 4. PMID: 22438842
Having grown up with reduce, reuse, recycle campaigns (Tweety’s Global Patrol circa 1990), recycling is part of my daily routine. In fact, I’ve even spent time at a Japanese university lab [...]... Read more »
As we’re starting to test artificially grown organs, scientists are wondering how to make sure that their methods result in viable tissues. One of the first steps was to take organ growth into three dimensions, letting the cells grow on a scaffold and self-organize into the right muscles, valves, and other soft tissue. Usually these scaffolds are derived from existing organs purified of all their old cells and many are designed to break down into [...]... Read more »
Bozhi Tian,, Jia Liu,, Tal Dvir,, Lihua Jin,, Jonathan H. Tsui,, Quan Qing,, Zhigang Suo,, Robert Langer,, Daniel S. Kohane,, & Charles M. Lieber. (2012) Macroporous nanowire nanoelectronic scaffolds for synthetic tissues. Nature Materials. DOI: 10.1038/nmat3404
The field of synthetic biology has been simmering for quite a while. It occasionally takes a big leap, such as when Venter’s team published about their work on M. genitalium, and it took a big leap recently with the paper about modeling a lot of the cellular processes in a simple cell that I talked [...]... Read more »
Wilson ML, Hertzberg R, Adam L, & Peccoud J. (2011) A step-by-step introduction to rule-based design of synthetic genetic constructs using GenoCAD. Methods Enzymol. , 173-188. DOI: 10.1016/B978-0-12-385120-8.00008-5
Cai Y., Wilson M. L., & Peccoud J. (2010) GenoCAD for iGEM: a grammatical approach to the design of standard-compliant constructs. Nucleic Acids Research, 38(8), 2644. DOI: 10.1093/nar/gkq086
Tyson John J., & Novák Béla. (2010) Functional Motifs in Biochemical Reaction Networks. Annual Review of Physical Chemistry, 61(1), 240. DOI: 10.1146/annurev.physchem.012809.103457
A recent study looking at how colonies of ants regulate their foraging behaviour has caused a bit of a buzz online. A …Continue reading »... Read more »
Balaji Prabhakar, Katherine N. Dektar, & Deborah M. Gordon. (2012) The Regulation of Ant Colony Foraging Activity without Spatial Information. PLoS Computational Biology, 8(8). DOI: 10.1371/journal.pcbi.1002670
A team of biomedical engineering researchers from Carnegie Mellon University and the University of Louisville are developing surgical tools that could be used for future expeditionary spaceflights to the moon, an asteroid or Mars.
“In deep space, surgical procedures will be severely complicated by absence of gravity, where it becomes difficult to prevent cabin contamination from blood and body fluids,” said James Antaki, a professor of biomedical engineering at CMU.... Read more »
Carnegie Mellon University. (2012) Press Release: Carnegie Mellon University Biomedical Engineers Lead Collaborative Team Developing New Astro Surgery Tools for NASA Deep Space Missions. Press Release: Carnegie Mellon University. info:/
Over the last few months, I’ve noticed an growing number of reports about declining opportunities and increasing pressure for early stage academic researchers (Ph.D. students, post-docs and junior faculty). For example, the Washington Post published an article in early July about trends in the U.S. scientific job market entitled “U.S. pushes for more scientists, but [...]... Read more »
Kealey T. (2000) More is less. Economists and governments lag decades behind Derek Price's thinking. Nature, 405(6784), 279. PMID: 10830939
Sauermann H, & Roach M. (2012) Science PhD career preferences: levels, changes, and advisor encouragement. PloS one, 7(5). PMID: 22567149
Researchers have created a new type of biosensor that can detect minute concentrations of glucose in saliva, tears and urine and might be manufactured at low cost because it does not require many processing steps to produce.... Read more »
Emil Venere. (2012) Sensor detects glucose in saliva and tears for diabetes testing. Purdue University News. info:/
The other day a tweet came over my “genome” search column that intrigued me: RT @oshaer: Our paper on a tabletop interface for collaborative exploration of genomic data is finally available online: http://t.co/VQMD67wi Tabletop interface? Wha? Ok–I had to check this out. And, in fact, this group has software that will let you explore eukaryotic [...]... Read more »
Shaer O., Strait M., Valdes C., Wang H., Feng T., Lintz M., Ferreirae M., Grote C., Tempel K., & Liu S. (2012) The design, development, and deployment of a tabletop interface for collaborative exploration of genomic data. International Journal of Human-Computer Studies, 70(10), 764. DOI: 10.1016/j.ijhcs.2012.05.003
There are many reasons to try to build a neuron, but fully building a model neuron is an extensive process with many steps. Today we will discuss the very first step in the neuron-building process: determining the activity and shape of the neuron. Biocytin filled cortical neurons (source)To determine the shape of neuron, you have to stain it somehow. There are several ways to do this, but we will focus on the biocytin filling method. To determine the activity of a neuron, you have to use electrophysiology to record its electrical activity. The biocytin filling method makes use of the same patch clamp electrode to record the electrical activity of the neuron and to fill it with the biocytin molecule that can be later dyed. So this method is perfect for building a neuron because with it you can correlate the shape of the neuron directly with its activity patterns. Neural activity correlated with neural morphology (source)A recent Nature Protocols paper by Marx et al. (2012) provides step by step details for how to fill and dye a neuron using the biocytin method. The basic biocytin staining protocol is as follows:1. make brain slices2. fill the neuron with biocytin while recording its electrical activity3. fix the brain slice in paraformaldehyde4. quench the endogenous peroxidase5. connect the biocytin to avidin (using the vectastain ABC kit)6. colorize the avidin (using DAB and nickel)7. mount the slices on gelatin subbed slides8. dehydrate the slices SLOWLY through very small steps of ethanol concentration9. clear with xylene and coverslipMarx et al. provide some excellent specifics in the paper that make the whole process understandable and more importantly, doable. They even have a troubleshooting section which explains what might have gone wrong under several conditions.Marx et al., 2012 Figure 2 One of their best tips in the paper is to dehydrate the slices very slowly. They show that when you dehydrate the tissue quickly, you get a cork-screw artifact (A) that is not physiologically meaningful, but when you dehydrate slowly, you get a more accurate morphology. So there you have it, Step 1 of neuron building. Step 2 will be coming soon. © TheCellularScaleMarx M, Günter RH, Hucko W, Radnikow G, & Feldmeyer D (2012). Improved biocytin labeling and neuronal 3D reconstruction. Nature protocols, 7 (2), 394-407 PMID: 22301777... Read more »
Marx M, Günter RH, Hucko W, Radnikow G, & Feldmeyer D. (2012) Improved biocytin labeling and neuronal 3D reconstruction. Nature protocols, 7(2), 394-407. PMID: 22301777
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