It sounds like an overly complicated method a supervillain would use to slowly and painfully eliminate enemies — a chamber with variable oxygen concentration. This automated environmental chamber isn’t for torturing suave MI6 agents, though; rather, it enables cancer research more-or-less on the cheap.
Tasked with building something to let his lab simulate the variable oxygen microenvironments found in some kinds of tumors, [RyanM415] first chose a standard lab incubator as a chamber to mix room air with bottled nitrogen. With a requirement to quickly vary the oxygen concentration from the normal 21% down to zero, he found that the large incubator took far too long to equilibrate, and so he switched to a small acrylic box. Equipped with a mixing fan, the smaller chamber quickly adjusts to setpoints, with an oxygen sensor providing feedback and controlling the gas valves via a pair of Arduinos. It’s quite a contraption, with floating ball flowmeters and stepper-actuated variable gas valves, but the results are impressive. If it weren’t for the $2000 oxygen sensor, [RyanM145] would have brought the whole project in for $500, but at least the lab can use the sensor elsewhere.
When a rainforest is clearcut for agricultural use, we only see the surface problems: fewer trees, destruction of plant and animal habitats, and countless other negative effects on the environment. A lurking problem, however, is that the soil is often non-ideal for farming. When the soil is exhausted, the farmers move further into the rainforest and repeat the process.
In the Amazon, however, there are pockets of man-made soil that are incredibly nutrient-dense. Figuring out how to make this soil, known as Terra Preta, on a massive scale would limit the amount of forest destruction by providing farmers a soil with more longevity which will, in turn, limit the encroachment on the rainforest. That’s the goal of this Hackaday Prize entry by [Leonardo Zuniga]: a pyrolysis chemical reactor that can make this soil by turning organic matter into a type of charcoal that can be incorporated into the soil to make Terra Preta.
As a bonus to making this nutrient-dense soil on a massive scale, this reactor also generates usable energy as a byproduct of processing organic waste, which goes several steps beyond simple soil enrichment. If successful and scalable, this project could result in more efficient farming techniques, greater yields, and, best of all, less damage to the environment and less impact on the rainforests.
Did you know you can build fundamental circuits using biological methods? These aren’t your average circuits, but they work just like common electrical components. We talk alot about normal silicon and copper circuits ‘roud here, but it’s time to get our hands wet and see what we can do with the power of life!
In 1703, Gottfried Wilhelm Leibniz published his Explication de l’Arithmétique Binaire (translated). Inspired by the I Ching, an ancient Chinese classic, Leibniz established that the principles of arithmetic and logic could be combined and represented by just 1s and 0s. Two hundred years later in 1907, Lee De Forest’s “Audion” is used as an AND gate. Forty years later in 1947, Brattain and H. R. Moore demonstrate their “PNP point-contact germanium transistor” in Bell Labs (often given as the birth date of the transistor). Six years later in 1953, the world’s first transistor computer was created by the University of Manchester. Today, 13,086,801,423,016,741,282,5001 transistors have built a world of progressing connectivity, automation and analysis.
While we will never know how Fu Hsi, Leibniz, Forest or Moore felt as they lay the foundation of the digital world we know today, we’re not completely out of luck: we’re in the midst’s of our own growing revolution, but this one’s centered around biotechnology. In 1961, Jacob and Monod discovered the lac system: a biological analog to the PNP transistor presented in Bell Labs fourteen years earlier. In 2000, Gardner, Cantor, and Collins created a genetic toggle switch controlled by heat and a synthetic fluid bio-analog2. Today, AND, OR, NOR, NAND, and XOR gates (among others) have been successfully demonstrated in academic labs around the world.
But wait a moment. Revolution you say? Electrical transistors went from invention to computers in 6 years, and biological transistors went from invention to toggle button in 40? I’m going to get to the challenges facing biological circuits in time, but suffice it to say that working with living things that want to be fed and (seem to) like to die comes with its own set of challenges that aren’t relevant when working with inanimate and uncaring transistors. But, in the spirit of hacking, let’s dive right in. Continue reading “Living Logic: Biological Circuits for the Electrically Minded”→
Most people have at least a fuzzy idea of what DNA is. Ask about RNA, though, and unless you are talking to a biologist, you are likely to get even more handwaving. We hackers might have to reread our biology text books, though, since researchers have built logic gates using RNA.
Sometimes we read these university press releases and realize that the result isn’t very practical. But in this case, the Arizona State University study shows how AND, OR, and NOT gates are possible and shows practical applications with four-input AND gates and six-input OR gates using living cells. The key is a construct known as an RNA toehold switch (see video below). Although this was worked out in 2012, this recent study shows how to apply it practically.
The DropoScope is a water-drop projector that works by projecting a laser through a drop of water, ideally dirty water crawling with microorganisms. With the right adjustments, a bright spot of light is projected onto a nearby wall, revealing a magnified image of the tiny animals within. Single celled organisms show up only as dark spots, but larger creatures like mosquito larvae exhibit definite structure and detail.
While simple in concept and requiring nothing more high-tech than a syringe and a laser pointer, getting useful results can require a lot of fiddly adjustment. But all that is a thing of the past for anyone with access to a laser cutter, thanks to [ingggis]. His design for a laser-cut a fixture lets anyone make and effortlessly adjust their own water-drop projector.
If you’d like to see some microorganisms in action, embedded below is video from a different water-drop projector (one identical in operation, but not lucky enough to benefit from [ingggis]’s design.)
Few people outside the field know just how big bioscience can get. The public tends to think of fields like physics and astronomy, with their huge particle accelerators and massive telescopes, as the natural expressions of big science. But for decades, biology has been getting bigger, especially in the pharmaceutical industry. Specialized labs built around the automation equipment that enables modern pharmaceutical research would dazzle even the most jaded CERN physicist, with fleets of robot arms moving labware around in an attempt to find the Next Big Drug.
I’ve written before on big biology and how to get more visibility for the field into STEM programs. But how exactly did biology get big? What enabled biology to grow beyond a rack of test tubes to the point where experiments with millions of test occasions are not only possible but practically required? Was it advances in robots, or better detection methodologies? Perhaps it was a breakthrough in genetic engineering?
Nope. Believe it or not, it was a small block of plastic with some holes drilled in it. This is the story of how the microtiter plate allowed bioscience experiments to be miniaturized to the point where hundreds or thousands of tests can be done at a time.
It’s not too often that you see handkerchiefs around anymore. Today, they’re largely viewed as unsanitary and well… just plain gross. You’ll be quite disappointed to learn that they have absolutely nothing to do with this article other than a couple of similarities they share when compared to your neocortex. If you were to pull the neocortex from your brain and stretch it out on a table, you most likely wouldn’t be able to see that not only is it roughly the size of a large handkerchief; it also shares the same thickness.
The neocortex, or cortex for short, is Latin for “new rind”, or “new bark”, and represents the most recent evolutionary change to the mammalian brain. It envelopes the “old brain” and has several ridges and valleys (called sulci and gyri) that formed from evolution’s mostly successful attempt to stuff as much cortex as possible into our skulls. It has taken on the duties of processing sensory inputs and storing memories, and rightfully so. Draw a one millimeter square on your handkerchief cortex, and it would contain around 100,000 neurons. It has been estimated that the typical human cortex contains some 30 billion total neurons. If we make the conservative guess that each neuron has 1,000 synapses, that would put the total synaptic connections in your cortex at 30 trillion — a number so large that it is literally beyond our ability to comprehend. And apparently enough to store all the memories of a lifetime.
In the theater of your mind, imagine a stretched-out handkerchief lying in front of you. It is… you. It contains everything about you. Every memory that you have is in there. Your best friend’s voice, the smell of your favorite food, the song you heard on the radio this morning, that feeling you get when your kids tell you they love you is all in there. Your cortex, that little insignificant looking handkerchief in front of you, is reading this article at this very moment.
What an amazing machine; a machine that is made possible with a special type of cell – a cell we call a neuron. In this article, we’re going to explore how a neuron works from an electrical vantage point. That is, how electrical signals move from neuron to neuron and create who we are.
A Basic Neuron
Despite the amazing feats a human brain performs, the neuron is comparatively simple when observed by itself. Neurons are living cells, however, and have many of the same complexities as other cells – such as a nucleus, mitochondria, ribosomes, and so on. Each one of these cellular parts could be the subject of an entire book. Its simplicity arises from the basic job it does – which is outputting a voltage when the sum of its inputs reaches a certain threshold, which is roughly 55 mV.
Using the image above, let’s examine the three major components of a neuron.
The soma is the cell body and contains the nucleus and other components of a typical cell. There are different types of neurons whose differing characteristics come from the soma. Its size can range from 4 to over 100 micrometers.
Dendrites protrude from the soma and act as the inputs of the neuron. A typical neuron will have thousands of dendrites, with each connecting to an axon of another neuron. The connection is called a synapse but is not a physical one. There is a gap between the ends of the dendrite and axon called a synaptic cleft. Information is relayed through the gap via neural transmitters, which are chemicals such as dopamine and serotonin.
Each neuron has only a single axon that extends from the soma, and acts similar to an electrical wire. Each axon will terminate with terminal fibers, forming synapses with as many as 1,000 other neurons. Axons vary in length and can reach a few meters long. The longest axons in the human body run from the bottom of the foot to the spinal cord.
The basic electrical operation of a neuron is to output a voltage spike from its axon when the sum of its input voltages (via its dendrites) crosses a specific threshold. And since axons are connected to dendrites of other neurons, you end up with this vastly complicated neural network.
Since we’re all a bunch of electronic types here, you might be thinking of these ‘voltage spikes’ as a difference of potential. But that’s not how it works. Not in the brain anyway. Let’s take a closer look at how electricity flows from neuron to neuron.
Action Potentials – The Communication Protocol of the Brain
The axon is covered in a myelin sheet which acts as an insulator. There are small breaks in the sheet along the length of the axon which are named after its discoverer, called Nodes of Ranvier. It’s important to note that these nodes are ion channels. In the spaces just outside and inside of the axon membrane exists a concentration of potassium and sodium ions. The ion channels will open and close, creating a local difference in the concentration of sodium and potassium ions.
We all should know that an ion is an atom with a charge. In a resting state, the sodium/potassium ion concentration creates a negative 70 mV difference of potential between the outside and inside of the axon membrane, with there being a higher concentration of sodium ions outside and a higher concentration of potassium ions inside. The soma will create an action potential when -55 mV is reached. When this happens, a sodium ion channel will open. This lets positive sodium ions from outside the axon membrane to leak inside, changing the sodium/potassium ion concentration inside the axon, which in turn changes the difference of potential from -55 mV to around +40 mV. This process in known as depolarization.
One by one, sodium ion channels open along the entire length of the axon. Each one opens only for a short time, and immediately afterward, potassium ion channels open, allowing positive potassium ions to move from inside the axon membrane to the outside. This changes the concentration of sodium/potassium ions and brings the difference of potential back to its resting place of -70 mV in a process known as repolarization. Fro start to finish, the process takes about five milliseconds to complete. The process causes a 110 mV voltage spike to ride down the length of the entire axon, and is called an action potential. This voltage spike will end up in the soma of another neuron. If that particular neuron gets enough of these spikes, it too will create an action potential. This is the basic process of how electrical patterns propagate throughout the cortex.
The mammalian brain, specifically the cortex, is an incredible machine and capable of far more than even our most powerful computers. Understanding how it works will give us a better insight into building intelligent machines. And now that you know the basic electrical properties of a neuron, you’re in a better position to understand artificial neural networks.