I’ve previously discussed how to sort CTCs, and the standards used to characterize device performance. Today, I’ll explain what some of the most common evaluation metrics are, and place them in context of eventual clinical/industrial application.... Read more »
Marrinucci Dena, Bethel Kelly, Lazar Daniel, Fisher Jennifer, Huynh Edward, Clark Peter, Bruce Richard, Nieva Jorge, & Kuhn Peter. (2010) Cytomorphology of circulating colorectal tumor cells:a small case series. Journal of oncology. PMID: 20111743
Kirby Brian J, Jodari Mona, Loftus Matthew S, Gakhar Gunjan, Pratt Erica D, Chanel-Vos Chantal, Gleghorn Jason P, Santana Steven M, Liu He, & Smith James P. (2012) Functional characterization of circulating tumor cells with a prostate-cancer-specific microfluidic device. PloS one. PMID: 22558290
In my “How to Sort CTCs” series, I covered a variety of sorting methodologies used for patient prognosis. However, before clinical implementation, it is important characterize device performance with a series of standards. This is impossible to do with a patient blood sample, because there is an unknown number of CTCs floating around with other blood cells, which can be effected by the cancer treatment process (e.g. radiation patients often have anemia)1. Furthermore, this is all changing dynamically as a function of both time and treatment.... Read more »
Kirby Brian J, Jodari Mona, Loftus Matthew S, Gakhar Gunjan, Pratt Erica D, Chanel-Vos Chantal, Gleghorn Jason P, Santana Steven M, Liu He, & Smith James P. (2012) Functional characterization of circulating tumor cells with a prostate-cancer-specific microfluidic device. PloS one. PMID: 22558290
Lazar Daniel C, Cho Edward H, Luttgen Madelyn S, Metzner Thomas J, Uson Maria Loressa, Torrey Melissa, Gross Mitchell E, & Kuhn Peter. (2012) Cytometric comparisons between circulating tumor cells from prostate cancer patients and the prostate-tumor-derived LNCaP cell line. Physical biology. PMID: 22306736
Powell Ashley A, Talasaz Amirali H, Zhang Haiyu, Coram Marc A, Reddy Anupama, Deng Glenn, Telli Melinda L, Advani Ranjana H, Carlson Robert W, & Mollick Joseph A. (2012) Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines. PloS one. PMID: 22586443
Magbanua Mark Jesus M, Sosa Eduardo V, Roy Ritu, Eisenbud Lauren E, Scott Janet H, Olshen Adam, Pinkel Dan, Rugo Hope, & Park John W. (2012) Genomic profiling of isolated circulating tumor cells from metastatic breast cancer patients. Cancer research. PMID: 23135909
Hofman V. J., Ilie M. I., Bonnetaud C., Selva E., Long E., Molina T., Vignaud J. M., Flejou J. F., Lantuejoul S., & Piaton E. (2010) Cytopathologic Detection of Circulating Tumor Cells Using the Isolation by Size of Epithelial Tumor Cell Method: Promises and Pitfalls. American Journal of Clinical Pathology, 135(1), 146-156. DOI: 10.1309/AJCP9X8OZBEIQVVI
Stott Shannon L, Hsu Chia-Hsien, Tsukrov Dina I, Yu Min, Miyamoto David T, Waltman Belinda A, Rothenberg S Michael, Shah Ajay M, Smas Malgorzata E, & Korir George K. (2010) Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proceedings of the National Academy of Sciences of the United States of America. PMID: 20930119
Cho Edward H, Wendel Marco, Luttgen Madelyn, Yoshioka Craig, Marrinucci Dena, Lazar Daniel, Schram Ethan, Nieva Jorge, Bazhenova Lyudmila, & Morgan Alison. (2012) Characterization of circulating tumor cell aggregates identified in patients with epithelial tumors. Physical biology. PMID: 22306705
Tormoen Garth W, Cianchetti Flor A, Bock Paul E, & McCarty Owen J T. (2012) Development of coagulation factor probes for the identification of procoagulant circulating tumor cells. Frontiers in oncology. PMID: 22973554
Neurons don't grow in a vacuum. They have white fibers, other neurons, blood vessels and all sorts of other obstacles to grow around.Some NeuroArt (source)A recent paper from France details the making of a 3D environment that can facilitate 'realistic' neural growth. Labour et al. (2012) created a collagen biomimetic matrix which contains neural growth factor (NGF). Labour et al., (2012) Figure 3These scanning electron microscope images show the porous fibril texture of the collagen matrix. Most of the paper is spent explaining the methods for making this biomimetic matrix, but they also actually grow some pseudo-neurons (PC-12 cells) on the matrix. They show that when cultured on top of this collagen surface, the cells extend neurons in three dimensions into the matrices and are affected by the NGF. (when there is no NGF, the neurites don't grow and the cells die.) This paper is mostly about the methods, but I like the new possibilities that growing 3D cells opens up. With these biomimetic collagen matrices, the factors that cause specific dendritic arborizations in three dimensions can be analyzed. The environment can be completely controlled and the neurons easily visualized during growth. The authors suggest using these matrices to study neurodegeneration as well.Another interesting thing this paper introduced me to is the 'graphical abstract.' I didn't know that that was a thing, but it seems like a good idea. However, trying to summarize an entire paper in one figure seems pretty difficult. Here is their attempt:Labour et al. (2012) graphical abstractI think it does actually get the feel of the paper across pretty well, though it's not really informative without the actual abstract next to it. © TheCellularScaleLabour MN, Banc A, Tourrette A, Cunin F, Verdier JM, Devoisselle JM, Marcilhac A, & Belamie E (2012). Thick collagen-based 3D matrices including growth factors to induce neurite outgrowth. Acta biomaterialia, 8 (9), 3302-12 PMID: 22617741... Read more »
Labour MN, Banc A, Tourrette A, Cunin F, Verdier JM, Devoisselle JM, Marcilhac A, & Belamie E. (2012) Thick collagen-based 3D matrices including growth factors to induce neurite outgrowth. Acta biomaterialia, 8(9), 3302-12. PMID: 22617741
GPS shoes can point to where you're going, but how will they know where to go? By consulting the map uploaded via USB and its own GPS receivers, wirelessly communicating with each other. For future models, you could probably set up WiFi to let your shoes download more information, talk with other people's shoes and modify your route on the go. So your footware might need its own network access, like agent Maxwell Smart's left shoe with a mobile subscription plan. The "No place like home" shoes are built around two microcontrollers called Arduinos: A magnet in the right shoe and sensor in the left shoe communicate with each other and with the GPS antenna in the red tag at the back. Clicking the heels starts the GPS. So all you need to do is to close your eyes and tap your heels together. And there will be no need to follow the yellow brick road or say the magic words.The smart shoes - designed by artist Dominic Wilcox and custom-made by Stamp Shoes might be a bit costly: £1,100 (about $1,750). A bit less sophisticated Aetrex Navistar GPS shoes developed for sufferers of Altzheimer's disease and dementia cost $299.99, and come with two monthly subscription plans - a basic 30 minute tracking plan, which reports every 30 minutes ($34.99) and for an additional $5 per month a premier 10 minute tracking plan. Nike was offering their own GPS footware too, for fitness enthusiasts, but decided that it's cheaper to use iPhone's location sensor to figure distance and serve as a pedometer.Yet, sensors in high-tech shoes could be helpful. For example, they could detect if their owner is tired or exhausted. Fatigue Monitoring System (FAMOS, recently developed and tested in patients with multiple sclerosis (MS) and healthy individuals) continuously measures motions of feet, in addition to electrocardiogram, body-skin temperature and electromyogram. And the system can reliably distinguish the symptoms of fatigue. The shoe sensors could provide a wealth of information about motion and assess such things as the risk of falling. And this information can be combined with data collected through other channels. Aurametrix, for example, can determine how food, air quality, the weather and various activities affect energy levels and generate suggestions on what to do - at the right time and right place. Systems like Aurametrix could eventually integrate our observations with data coming from smart objects such as shoes and heart monitors, to speed up not only walking but also the understanding of the human body, for a healthier world.PUBLICATIONS Yu F, Bilberg A, Stenager E, Rabotti C, Zhang B, & Mischi M (2012). A wireless body measurement system to study fatigue in multiple sclerosis. Physiological measurement, 33 (12), 2033-2048 PMID: 23151461Marschollek, M., Rehwald, A., Wolf, K., Gietzelt, M., Nemitz, G., zu Schwabedissen, H., & Schulze, M. (2011). Sensors vs. experts - A performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients BMC Medical Informatics and Decision Making, 11 (1) DOI: 10.1186/1472-6947-11-48... Read more »
Yu F, Bilberg A, Stenager E, Rabotti C, Zhang B, & Mischi M. (2012) A wireless body measurement system to study fatigue in multiple sclerosis. Physiological measurement, 33(12), 2033-2048. PMID: 23151461
Marschollek, M., Rehwald, A., Wolf, K., Gietzelt, M., Nemitz, G., zu Schwabedissen, H., & Schulze, M. (2011) Sensors vs. experts - A performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients. BMC Medical Informatics and Decision Making, 11(1), 48. DOI: 10.1186/1472-6947-11-48
Most CTC sorting devices target some observed cancer cell phenotype that was determined from studying tumor tissue directly, or from using immortalized cancer cell lines. This means that active sorting techniques, like size-based selection and immunocapture, require some level of a priori knowledge about CTCs before you can engineer a device to capture them. Microscopic characterization is one CTC identification method that circumvents this problem, fixing (killing) the cells, and then using imaging in combination with rapid scanning to look at almost everything present in the blood sample. Electrokinetic separation of cancer cells is another, but enables live cell isolation without knowing its physical or biochemical properties beforehand.... Read more »
A discussion of the recent advances in space exploration, looking specifically at the Mars Rover landing as well as other space phenomena during 2012. ... Read more »
E Markham. (2012) Curious Cosmos. Blogspot. info:/
Following my series of posts on the link between the square root of a stochastic process and quantum mechanics (see here, here, here, here, here), that I proved to exist both theoretically and experimentally, I am pleased to let you know that the first paper of my collaboration with Alfonso Farina and Matteo Sedehi was [...]... Read more »
Marco Frasca. (2012) Quantum mechanics is the square root of a stochastic process. arXiv. arXiv: 1201.5091v2
Farina, A., Giompapa, S., Graziano, A., Liburdi, A., Ravanelli, M., & Zirilli, F. (2011) Tartaglia-Pascal’s triangle: a historical perspective with applications. Signal, Image and Video Processing. DOI: 10.1007/s11760-011-0228-6
I had thought that once I graduated college, annoying student publications would quit being so… annoying. Alas, this isn’t the case. A previous article examined the quality of analysis at the Carolina Review, UNC’s ‘journal of conservative thought and opinion’; let’s see if things have approved any in the handful of years that I’ve been [...]... Read more »
One day on, and still struggling with the chemistry behind gene regulation. Let no biologist ever tell me again not to use acronyms (yes, I am looking at you!). But it is interesting. I learned a lot about ChIP, histone modifications, etc, etc. This is an amazing world, where specific histone complex protein residues get methylated, acetylated, citrullinated, and phosphorylated. Of course, all this is in the context of the ENCODE meeting we have tomorrow at BiGCaT, where I will try to cover a paper by Thurman et al.
In that paper, Thurman studies the links between DNase I hypersensitive sites (DHSs) and markers of regulation. These DHSs are areas between histones where the DNA is free of histone proteins. There are remarkable images around showing histones as beads on a string, and the distances in nucleotides between histones is in fact not that large. In fact, a histone, despite a large complex, sterically hindering 50% of the DNA access does not stop translation; the transcription complexes apparently have no trouble passing the histones, as described by Felsenfeld et al. Quite amazing!
Now, those histones are chemically modified with acetyl, methyl, phosphates, and other groups. At well-describes residues, and each easily regulates modification of other steps. And everything regulates gene expression. Oh, and as we say yesterday, all that is regulated by metabolites, which in turn... Lovely. Try modeling that mathematically :) Here's what Abcam has to say about it:
Acetylation is generally linked to gene activation. Acetylation on Lys-10 (H3K9ac) impairs methylation at Arg-9 (H3R8me2s). Acetylation on Lys-19 (H3K18ac) and Lys-24 (H3K24ac) favors methylation at Arg-18 (H3R17me). Citrullination at Arg-9 (H3R8ci) and/or Arg-18 (H3R17ci) by PADI4 impairs methylation and represses transcription. Asymmetric dimethylation at Arg-18 (H3R17me2a) by CARM1 is linked to gene activation. Symmetric dimethylation at Arg-9 (H3R8me2s) by PRMT5 is linked to gene repression. Asymmetric dimethylation at Arg-3 (H3R2me2a) by PRMT6 is linked to gene repression and is mutually exclusive with H3 Lys-5 methylation (H3K4me2 and H3K4me3). H3R2me2a is present at the 3' of genes regardless of their transcription state and is enriched on inactive promoters, while it is absent on active promoters. Methylation at Lys-5 (H3K4me), Lys-37 (H3K36me) and Lys-80 (H3K79me) are linked to gene activation. Methylation at Lys-5 (H3K4me) facilitates subsequent acetylation of H3 and H4. ... ...
And that goes on for a while. Ambitiously, I started converting things I read into a WikiPathways:
I think that will keep me busy for a while. I won't even attempt to complete it further tonight. I have given up on that about an hour ago. In fact, I returned to the paper by Thurman, as I still have to figure out how their experimental methods work. In fact, how does one even detect the chemical modification of a histone, and to which DNA sequence on any of the chromosomes it belongs?? I mean, that's not AFM or STM, I say...
No, it's ChiP. ChIP on a chip, in fact. They have antibodies are stick particularly to a histones with one particular modification. That is how I actually ended up on that Abcam web page in the first place. Check out this nice western blot. With a huge antibody detecting whether there is an acetyl modification. Wicked!
Well, earlier I learned that proteins detecting methylated CpG bases not because of the methyl group (which amazed me already), but by a distorted hydration in the major groove due to MeCP2 binding. Seriously! Eat that, organic chemist friends!
So, Thurman and friends find distal DHSs and relate these to cis-regulatory elements. To some extend, puzzling, because the above tells us that a lot of regulatory work is happening outside those DHSs. But then again, I did read today about DNA methylation triggering histone modifications. It seems there is so much interactions going on, that it resembles a melting pot. Oh wait, that makes sense; it's one big one pot synthesis anyway.
The paper discusses an enormous amount of experimental work, and I cannot seem to be able to make sense of it all. There are striking aspects to it, which I will touch upon momentarily. But I cannot help but mentioning that I am not sure they could either. Their Discussion section leaves something to be desired, like an actual discussion. Instead, they just summarize the paper.
They used ChIP with Cell Signaling's 9751 antibody recognizing H3K4me3, with formaldehyde-induced crosslinking. It actually turns out, that the peaks for this modification are right on top of the DNA part from which the transcript is made, in line with Felsenfeld's observation. Upstream of that, where the promotors are expected, that is where DNase I signals are found. That is, I think this means that the DHS upstream of the histone where transcription starts is where the promotor regulation happens. With transcription factors (TFs), of course. And in those DHS regions, that is where DNA methylation happens, and Thurman finds DNA methylation in those regions, inhibiting TFs binding, because the already mentioned MeCP2 already takes that place.
Now, then they make a jump from this low level chemistry, to a genome wide landscape. Well, they actually start with that, but as a chemist, I am more of a bottom-up guy (that is an IT method). They report that most DHSs are found in introns and at distal locations. The first is striking: the ratio between intron/exon is >99. Does that imply that exons basically are always DNA wrapped around histones?? Does that actually then tell me that transcription actually sort of requires steric hindrance of the histone?? Ha, those diagrams biologists would be even more misleading that they have been to me (don't ask me how long it took me to learn that there are some 10-40 mitochondria per cell! and I still do not know if all copies in the cell have the same DNA, or if they are more like a population like your microbiome).
Now, distal DHSs are the second largest group, and capture some 40-45% of all DHSs. Distal means typically more than 2.5 kb away from the TSS (transcriptional start sites). Most of them are somewhere between 10 and 50 kb away. Now, isn't that something? That is distant indeed!
What? Still with me? Let's do some math. It's hard, and I hope to get it right. A human has about 3 billion base pairs (I'll take the WikiPedia count). The paper finds almost 3 million DHSs. That means that the average distance between DHSs is about 1 kb. Compare that to their diagram 1b, outline in the previous paragraph. That means that the DHSs must be very densely placed around the transcribed genes. Indeed, they report ratios of up to and above a 100 fold increase. It must be like that, because otherwise, you cannot get those distances for distal DHSs.
Now, another interesting aspect of the paper, is that they find different DHSs for different cell types. That, in fact, increases the average distance between DHSs: those 3 million they find is for 125 cell lines, and more DHSs are found in less then 20 cell lines. Only promotor-related DHSs seem to be more persistent between cell lines. This implies that different cell lines, have different genes unfolded in nucleosome/DHS rich areas (defining the chromatin accessibility), triggering different gene expression. That all makes sense, and rather existing too. As such, it seems to me that this map effectively gives a predictive model, indicating which genes are expressed in which cell types.
A further question they ask is if DNA (not histone) methylation is the cause of the result of DHSs. The confirm earlier found correlation between DNA methylation and gene silencing. They basically question if the things like MeCP2 binding happen because no transcription factor is in the way, or that TF cannot bind because MeCP2 is there. Chemically, these are perhaps equivalent: they have competing binding affinities. Except that the methylation must happen at some point too. The suggest that that may be due DNA getting randomly methylated, perhaps not unlike passive demethylation. Chemically, that does not make sense to. I would guess there are many chemical species in the cell that would get more easily methylated... They believe to have found evidence for passive deposition, but also find positive correlation between methylation and gene expression. I would say, the answer is still out there.
OK, that's about how far I got now. The last two pages I have to read again, and see what papers I need to read to make sense of that. And I will try ... Read more »
Thurman, R., Rynes, E., Humbert, R., Vierstra, J., Maurano, M., Haugen, E., Sheffield, N., Stergachis, A., Wang, H., Vernot, B.... (2012) The accessible chromatin landscape of the human genome. Nature, 489(7414), 75-82. DOI: 10.1038/nature11232
Steps 1 and 2 of neuron-building, as well as an important set of shortcuts can be found in the How to Build a Neuron index. Step 3 is deciding which simulation software or programming language you want to use. Simulated Neuron in Genesis (source)The big two are Genesis and Neuron. They are pretty similar in a lot of ways, but Genesis runs in Linux and Neuron runs in windows. However, you can run Genesis in windows if you install the Linux environment Cygwin.Both programs can read in morphological data, but they use different syntax and coding procedures. There are other types of neural simulators as well, and an ongoing problem in the field of computational neuroscience is compatibility between programs. If someone has done the work to make a beautiful Purkinje cell in Genesis like the one above, it will take a lot of time and effort to translate that neuron into a different simulator such as Neuron. Gleeson et al., (2010) explains this problem and presents a possible solution in the form of the "Neuron Open Markup Language" or NeuroML. "Computer modeling is becoming an increasingly valuable tool in the study of the complex interactions underlying the behavior of the brain. Software applications have been developed which make it easier to create models of neural networks as well as detailed models which replicate the electrical activity of individual neurons. The code formats used by each of these applications are generally incompatible however, making it difficult to exchange models and ideas between researchers....Creating a common, accessible model description format will expose more of the model details to the wider neuroscience community, thus increasing their quality and reliability, as for other Open Source software. NeuroML will also allow a greater “ecosystem” of tools to be developed for building, simulating and analyzing these complex neuronal systems." -Gleeson et al (2010) Author SummaryNeuroML is basically a "simulator-independent" neuronal description language. A neuron built with or converted to NeuroML should be able to run on Neuron, Genesis, and plenty of other platforms. Gleeson et al. validated NeuroML by using a simulated pyramidal neuron converted to NeuroML format and run with several different simulators.Gleeson et al., (2010) Figure 7Zooming in:Neuron, Genesis, Moose, Psics comparisonAll the simulators overlay so tightly that you can barely tell that they are separate lines.So when building you neuron, take care to follow the NeuroML format and then you and others can use it with any simulator you want. © TheCellularScaleGleeson P, Crook S, Cannon RC, Hines ML, Billings GO, Farinella M, Morse TM, Davison AP, Ray S, Bhalla US, Barnes SR, Dimitrova YD, & Silver RA (2010). NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS computational biology, 6 (6) PMID: 20585541... Read more »
Gleeson P, Crook S, Cannon RC, Hines ML, Billings GO, Farinella M, Morse TM, Davison AP, Ray S, Bhalla US.... (2010) NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS computational biology, 6(6). PMID: 20585541
Expendable objects were not innovated recently. Although washi are now linked to origami, for instance, people have been using the small sheets as disposable facial tissues since at least the seventeenth century, when the litter of Hasekura Tsunenaga's retinue reportedly surprised French courtiers. Similarly, around 200,000 to 400,000 years earlier, hominins near present-day Tel Aviv temporarily used flint flakes to carve meat, later startling archeologists with the "short-lived usage" of their discarded "meat-cutting blades," perhaps "the world's oldest known disposable knives."... Read more »
Liu, Q., Shi, S., Du, L., Wang, Y., Cao, J., Xu, C., Fan, F., Giesy, J., . (2012) Environmental and health challenges of the global growth of electronic waste,. Environmental Science and Pollution Research, 2460-2462. DOI: 10.1007/s11356-012-0923-z
Wang, F., Huisman, J., Meskers, C., Schluep, M., Stevels, A., . (2012) The Best-of-2-Worlds philosophy: Developing local dismantling and global infrastructure network for sustainable e-waste treatment in emerging economies. Waste Management, 2134-2146. DOI: 10.1016/j.wasman.2012.03.029
It sounds like something dreamt up by a science fiction writer, but scientists have created a walking ‘bio-bot’ made from rat heart cells and hydrogels, using a 3-D printer. The biological machines are 7 millimetres long, and resemble a miniature springboard with one long, thin leg that is supported by a stouter supporting leg. The [...]... Read more »
Chan, V., Park, K., Collens, M., Kong, H., Saif, T., & Bashir, R. (2012) Development of Miniaturized Walking Biological Machines. Scientific Reports. DOI: 10.1038/srep00857
Considering the fact that airships have been around for a while now, it’s hard to believe that they are thought of as emerging technologies today. But that’s exactly the case given recent advances in this arena. Hydrogen airships have a troubled history due to several significant historical disasters. However, new technologies could help reduce this [...]... Read more »
Michele Trancossi, Antonio Dumas, Mauro Madonia, Jose Pascoa, & Dean Vucinic. (2012) Fire-safe Airship System Design. SAE Int. J. Aerosp. , 11-21. info:/10.4271/2012-01-1512
The clock would keep time based on extremely short light pulses given out when ‘heavy ions’, nuclei that belong to heavy atoms such as lead, are smashed together at speed within the collider. To read more click here. Sources: Ipp, A., & Somkuti, P. (2012). Yoctosecond Metrology Through Hanbury Brown–Twiss Correlations from a Quark-Gluon Plasma [...]... Read more »
Ipp, A., & Somkuti, P. (2012) Yoctosecond Metrology Through Hanbury Brown–Twiss Correlations from a Quark-Gluon Plasma. Physical Review Letters, 109(19). DOI: 10.1103/PhysRevLett.109.192301
Action potentials are the main means of communication between neurons, and their exact timing can be really important. But the specific timing of action potentials is really important in the auditory system, because the auditory system encodes (among other things) information about sound wave frequency. Sound waves (source)I've previously written about auditory processing with regards to the wonder that is the chicken brain, but today we will focus on timing-specificity in the mammalian brainstem. Specifically, some weird channels in the Medial Nucleus of the Trapezoid Body (the MNTB). Mammalian Auditory Brainstem (source)At the Society for Neuroscience meeting, I learned about the sodium-activated potassium channels which help the electric fish fire super-fast super-large action potentials. I was suprised to learn that sodium-activated potassium channels are located in many parts of the mammalian brain. A paper from the Kaczmarek lab at Yale explains that these sodium-activated potassium channel (SLICK and SLACK) are present in the mouse auditory brainstem and contribute to the 'temporal accuracy' of the MNTB neurons. Yang et al. (2007) record the action potentials from these neurons at a range of frequencies and show that the neuron can 'keep' up with the frequencies better when more sodium is present. Yang et al., 2007 Figure 9BIn the figure above, the 'flatter' the line, the better the 'temporal accuracy.' They also made a computational model of this neuron and ran simulations altering the sodium values and reversal potential. Yang et al., 2007 Figure 9DTheir model simulations are similar to their experimental recordings, in that more sodium results in more temporal accuary of the action potential. They confirmed that this was dues to a sodium-activated potassium channel by directly activating SLACK and seeing a similar improvement in temporal accuracy. The SLACK channel still blows my mind, but its role in helping the auditory system fire with the utmost precision actually makes a lot of sense. © TheCellularScaleYang B, Desai R, & Kaczmarek LK (2007). Slack and Slick K(Na) channels regulate the accuracy of timing of auditory neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience, 27 (10), 2617-27 PMID: 17344399... Read more »
Yang B, Desai R, & Kaczmarek LK. (2007) Slack and Slick K(Na) channels regulate the accuracy of timing of auditory neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience, 27(10), 2617-27. PMID: 17344399
Now that we are finally on the other side of one of the longest, most expensive political campaign seasons of United States history, we find ourselves with a new mixed-bag of leaders. Our nation’s decision-makers include career politicians and new freshman politicians; they include lawyers, military members, doctors, businessmen, farmers, ministers, educators, scientists, pilots, and entertainers; they include Protestants, Catholics, Jews, Quakers, Mormons, Buddhists and Muslims; they include white Americans, African Americans, Asian Americans, and Hispanic and Latino Americans; they include men and women; they include straight and gay people; and oh yeah, they include Republicans and Democrats. With so many differences that generate so many viewpoints, how will they ever find common ground to make the kind of decisions that will move our nation in a positive direction? Hey, Look guys! We make a peace sign! Image from Wikimedia. Research into group decision-making in social animals has shown that ants, fish, birds, and bees have all discovered strategies to make intelligent group decisions. If they can do it, we can do it, right? What can we learn from these critters about harnessing the knowledge in all of us to move our whole group in the best possible direction? We will explore these insights in this post, which is a mash-up of two previous posts. To see the originals, check out Can a Horde of Idiots Be a Genius? and Why This Horde of Idiots Is No Genius.Jean-Louis Deneubourg, a professor at the Free University of Brussels, and his colleagues tested the abilities of Argentine ants (a common dark-brown ant species) to collectively solve foraging problems. In one of these studies, the ants were provided with a bridge that connected the nest to a food source. This bridge split and fused in two places (like eyeglass frames), but at each split one branch was shorter than the other, resulting in a single shortest-path and multiple longer paths. After a few minutes, explorers crossed the bridge (by a meandering path) and discovered the food. This recruited foragers, each of which chose randomly between the short and the long branch at each split. Then suddenly, the foragers all started to prefer the shortest route. How did they do that?This figure from the Goss et al 1989 paper in Naturwissemschaften shows (a) the design of a single module, (b) ants scattered on the bridge after 4 minutes (I promise they’re there), and (c) ants mostly on the shortest path after 8 minutesYou can think of it this way: a single individual often tries to make decisions based on the uncertain information available to it. But if you have a group of individuals, they will likely each have information that differs somewhat from the information of others in the group. If they each make a decision based on their own information alone, they will likely result in a number of poor decisions and a few good ones. But if they can each base their decisions on the accumulation of all of the information of the group, they stand a much better chance of making a good decision. The more information accumulated, the more likely they are to make the best possible decision.In the case of the Argentine ant, the accumulated information takes the form of pheromone trails. Argentine ants lay pheromone trails both when leaving the nest and when returning to the nest. Ants that are lucky enough to take a shorter foraging route return to the nest sooner, increasing the pheromone concentration of the route each way. In this way, shorter routes develop more concentrated pheromone trails faster, which attract more ants, which further increase pheromone concentration of the shortest routes. In this way, an ant colony can make an intelligent decision (take the shortest foraging route) without any individual doing anything more intelligent than following a simple rule (follow the strongest pheromone signal).Home is where the heart is. Photo of a bee swarm by Tom SeeleyHoneybee colonies also solve complicated tasks with the use of communication. Tom Seeley at Cornell University and his colleagues have investigated the honeybee group decision-making process of finding a new home. When a colony outgrows their hive, hundreds of scouts will go in search of a suitable new home, preferably one that is high off the ground with a south-facing entrance and room to grow. During this time, the house-hunters will coalesce on a nearby branch while they search out and decide among new home options. This process can take anywhere from hours to days during which the colony is vulnerable and exposed. But they can’t be too hasty: choosing a new home that is too small or too exposed could be equally deadly. Although each swarm has a queen, she plays no role in making this life-or-death decision. Rather, this decision is made by a consensus among 300-500 scout bees that results after an intense “dance-debate”. If a scout finds a good candidate home, she returns to the colony and performs a waggle dance, a dance in which her body position and movements encode the directions to her site and her dancing vigor relates to how awesome she thinks the site is. Some scouts that see her dance may be persuaded to follow her directions and check out the site for themselves, and if impressed, may return to the hive and perform waggle dances too. Or they may follow another scout’s directions to a different site or even strike out on their own. Over time, scouts that are less enthusiastic about their discovered site stop dancing, in part discouraged by dancers for other sites that bump heads with them and beep at them in disagreement. Eventually, the majority of the dancing scouts are all dancing the same vigorous dance. But interestingly, few scouts ever visit more than one site. Better sites simply receive more vigorous “dance-votes” and then attract more scouts to do the same. Like ants in search of a foraging path, the intensity of the collective signal drives the group towards the best decision. Once a quorum is reached, the honeybees leave their branch as a single united swarm and move into their new home, which is almost always the best site. ... Read more »
List, C., Elsholtz, C., & Seeley, T. (2009) Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1518), 755-762. DOI: 10.1098/rstb.2008.0277
Seeley, T., Visscher, P., Schlegel, T., Hogan, P., Franks, N., & Marshall, J. (2011) Stop Signals Provide Cross Inhibition in Collective Decision-Making by Honeybee Swarms. Science, 335(6064), 108-111. DOI: 10.1126/science.1210361
Dell'Ariccia, G., Dell'Omo, G., Wolfer, D., & Lipp, H. (2008) Flock flying improves pigeons' homing: GPS track analysis of individual flyers versus small groups. Animal Behaviour, 76(4), 1165-1172. DOI: 10.1016/j.anbehav.2008.05.022
In about a weeks time the 13th ISMIR (International Society for Music Information Retrieval) conference will be held. This is a conference on the processing, searching, organizing and accessing music-related data. It attracts a research community that is intrigued by the revolution in music distribution and storage brought about by digital technology which generated quite some research activity and interest in academia as well as in industry.... Read more »
Aucouturier, J., & Bigand, E. (2012) Mel Cepstrum . Proc. of the 13th International Society for Music Information Retrieval Conference, 397-402. info:/
Volk. A., & Honingh, A. (eds). (2012) Mathematical and Computational Approaches to Music: Three Methodological Reflections . Journal of Mathematics and Music, 6(2). info:/10.1080/17459737.2012.704154
Robots fascinate all of us. While few robots are just fun toys many other robots can perform many complex tasks for us. In past decade the field of robotics has advanced by leaps and bounces making robots smarter and smarter. We have created robots, which can explore terrains- terrestrial as well as extra-terrestrial-, where even humans haven't reached. To traverse a terrain with obstacles ... Read more »
According to a paper just published, a new technique of functional MRI scanning (fMRI) could soon allow neuroscientists to measure brain activity far faster: Generalized iNverse imaging (GIN): Ultrafast fMRI with physiological noise correctionAuthors Boyacioglu and Barth claim remarkable things for the technique:We find that the spatial localization of activation for GIN is comparable to an EPI protocol and that maximum z-scores increase significantly... with a high temporal resolution of 50 milliseconds.EPI, the current standard fMRI sequence, would have a temporal resolution of 2000 or 3000 milliseconds, so it's about 50 times faster.Other super-fast fMRI methods already exist (e.g. this one I blogged about), but they've generally achieved speed only at a cost: they've had to either sacrifice spatial resolution to achieve that, or limited themselves to scanning only a small fraction of the brain, or have been more subject to random noise and hence less sensitive.GIN, however, is said to cover the whole brain, with decent spatial resolution and signal-to-noise ratio. The data can be analyzed in exactly the same way as any other kind. So that's up to fifty times faster with no real drawbacks.That would be truly revolutionary - as the major limitation of fMRI at the moment is that it's much slower than other methods of recording brain activity.Check it out: this shows brain activation in response to simple visual stimuli, imaged with bog-standard EPI and GIN:So this is a big deal... if it does work, I'm sure neuroscientists the world over will be lining up to buy Boyacioglu and Barth a GIN and tonic.How does it work, and is it all it's cracked up to be? Well, I can't really say: the math is beyond me.In essence, rather than scanning the brain in 3D, slice by slice (like this), GIN only scans one 2D slice, but then manages to reconstruct the rest of the brain in 3D from just that slice, using dark, forbidden magicks... I mean mathematics. The principle is called parallel imaging and it's been around for several years, but with image quality limitations that GIN claims to have overcome.Perhaps my more technically-inclined readers will have more insightful comments.Boyacioglu R, and Barth M (2012). Generalized iNverse imaging (GIN): Ultrafast fMRI with physiological noise correction. Magnetic Resonance in Medicine PMID: 23097342... Read more »
Boyacioglu R, & Barth M. (2012) Generalized iNverse imaging (GIN): Ultrafast fMRI with physiological noise correction. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. PMID: 23097342
by Artem Kaznatcheev in Evolutionary Games Group
We have seen that the replicator equation can be a useful tool in understanding evolutionary games. We’ve already used it for a first look at perception and deception, and the cognitive cost of agency. However, the replicator equation comes with a number of inherent assumptions and limitations. The limitation Hisashi Ohtsuki and Martin Nowak wanted [...]... Read more »
Do you write about peer-reviewed research in your blog? Use ResearchBlogging.org to make it easy for your readers — and others from around the world — to find your serious posts about academic research.
If you don't have a blog, you can still use our site to learn about fascinating developments in cutting-edge research from around the world.
Research Blogging is powered by SMG Technology.
To learn more, visit seedmediagroup.com.