Category: General

ABI 377 Teardown

I picked up two ABI PRISM 377 DNA sequencers. These are the last generation of slab gel sequencers.
ABI 377

ABI 377

With the front open, you can see the place where the gel gets mounted.

gel door open

The left side opens, and the bottom cover comes off. The laser can be seen at the bottom, and some of the power supplies on the left.

Open cabinet

Here is the laser, a Uniphase Argon laser, 0.5W 2214-40MLA 1998.


The power supply modules are located on the left side. On the top left is the laser power supply. The electrophoresis power supply is on the left in the middle. To the right of it is the power distribution center–plugs for the laser and electrophoresis power supplies, and the blower motor. On the bottom at the left is the blower motor. In the middle at the bottom the top of a mirror module that bounces the laser back to the right at the level of the bottom of the gel. On the right at the bottom, the servo motor that moves the detector unit along the bottom of the gel.

left side

Here’s the laser power supply. The laser is not plugged in.
laser power supply

Close up of the laser power supply, Uniphase 2114B-40MLA 12A:
laser power supply

The power distribution center labels: J41 DC Power Supply Max 4000W J40 Heater and Pump Control

The electrophoresis power supply: Spellman P/N X2094 Rev. E4 Model No PTV5P300X2094
230V 5A, output 0-5kV, 0-60mA.

Here is a closeup of the servo: Telcomm brushless servo motor

On the back side of the machine behind the top panel is this circuit board, the control, data processing, and interface board.

main board

Two interesting chips on the board, a FPGA and a pair of voltage converters.

The FPGA is a Xilinx XC3064A

The voltage converter.
voltage converter

On the left of the main board is region with cooling lines:
pump area

The Metabolic Theory of Cancer

Notes on “What Is The Origin of Cancer?” by Travis M Christofferson.

The most useful thing about this article is that it reminded me of the 2010 book, “The Emperor of all Maladies”, by Siddhartha Mukherjee.

The article has is divided into a few sections: a description and dismissal of the genetic theory of cancer, a discussion of the Cancer Genome Atlas project and a dismissal of it, and then the metabolic theory of cancer is described and touted.

The article starts by making some assertion about cancer to frame the discussion. “We are not winning the war against cancer; we are no closer to cures than when Nixon declared the war on cancer in 1971 – in fact, we may be further away.” Cancer has proved a difficult disease–there have been some improvements in survival times in some types of cancer, some cures, but the change in overall cancer treatment has been modest. Currently, a number of targeted cancer drugs are being used and making a difference. Let’s call them 2nd generation drugs to differentiate them from the chemotherapy drugs that kill dividing cells indiscriminately. There are also a bunch of new therapies, several different kinds currently in the works, let’s call them 3rd generation treatments.

In 1971, when the big push to cure cancer began, the difficulty wasn’t clear. At that time, not much was known about what caused cancer and how it progressed. Now we have a decent understanding of it, and there are *several* promising approaches that could substantially improve treatment and outcome.

We’ve understood cancer pretty well for some time, since the 90’s. Unfortunately, treatments have been hard to come by. Treatments are technology, and cancer is a hard nut to crack. Cancer is a body’s cells dividing without limit. These cells start ignoring the signals and controls that keep cells dividing only when and where they are needed. A treatment for cancer needs to get these cells to stop dividing or kill them. It is difficult to treat cancer for two reasons: 1) cancer cells are human cells, so treatments that kill cancer cells and bypass normal cells are hard to engineer, and 2) cancer evolves to resist treatments.

The second factor is the real killer. Think of a cancer of as a population of millions of cells, each a bit from the others due to mutations in DNA or other changes. A treatment that kills almost all of them leaves thousands that are resistant to the treatment. They continue growing and picking up more changes. A second, different treatment will have the same effect. While some of these changes make cancer resistant to treatment, others allow it to escape other limits. A growing tumor runs out of space and out of blood. So cells that can invade surrounding tissue or metastasize to a new place in the body are also successfully evolved tumor cells.

Cancer treatments usually run through these cycles: a treatment initially has great success, but then the cancer comes back. Some cancer cells have survived and they grow and divide and the tumor comes back, changed. If a treatment is repeated, it is less effective each time.

So a cancer cell is a cell that has changed to ignore the normal signals to stop dividing, and as a tumor grows cells that have additional changes keep occurring. Whether a change to a cell’s DNA or metabolism starts it dividing, the process will continue and the cancer cells will keep changing to ignore or bypass things the keep them from dividing. So if a diet change robs cancer cells of glucose or metabolic changes signal them to stop dividing, some cancer cells will not stop dividing and the cancer continues.

A number of genes are known to play a role in cancer, mutations in oncogenes or tumor suppressor genes are found in all (or pretty much all) cancers. The role of mutations in causing cancer is the Somatic Mutation Theory of Cancer. Changes to genes that are involved in controlling cell division allow cells to ignore the normal checks on cell growth and division.

When the Cancer Genome Atlas Project began, years of research had already identified the main cancer genes (hundreds of genes). This link summarizes the project (TCGA). The idea is to get a comprehensive look at what genes are changed in different kinds of cancer at different stages of the disease. Not really expected to be revolutionary, instead just round out the genetic picture of cancer.

A number of 2nd generation cancer drugs target these cancer genes. They knock down cancer for a while, and give patients added months of life. Eventually, the cancers pick up mutations in other genes and bypass the drug. So these drugs usually don’t cure cancer. New methods of characterizing cancer are beginning to reach the clinic that allow each patient to get the drug that targets the genes mutated in their cancer, so these drugs are becoming more effective.

I’ve met Bert Vogelstein, he’s an intense guy. He discovered how p53 mutations cause cancers, and the most common colon cancer gene, APC. He played a role in fleshing out the somatic mutation theory of cancer. The theory is holding up well–sequence a tumor’s DNA, and known cancer genes show up with mutations.

Cancers aren’t all the same. Each one is a cell that pciked up mutations and started dividing and then picked up more mutations. There are lots of cancer genes, so different tumors pick up different mutations, in different orders. The different types of cancer arise from different types of cells. For a particular cell type, it is easier to start dividing if certain genes mutate (a gene already turned on in a cell, for example) so certain cancer genes are common in different types of cancer. There is also a lot of flexibility as cells pick up mutations and lots of potential cancer genes, so each cancer is unique. This has been known for a long time in general terms, but new techniques are allowing each cancer to be characterized in detail. Volgelstein’s review in the journal Science describes this.

The metabolic alterations in cancer have been known about for a long time–biologists developed tools to study biochemistry before the method for genetic studies came along. Cancer cell’s great demand for glucose has been known for a long time. Cell growth and division and metabolism are tightly linked, so changes in cancer genes change cell metabolism and vice versa.

Can changing diet, starving a cancer of glucose stop it, cure it, or at least put it on hold permanently? I can only find a few published studies, mostly in mice. It seems like it may be effective in slowing the progression of some types of cancer, at least temporarily. However, ketogenic diets have been known about for a long time, and trying them for cancer seems obvious. So if it worked well for cancer, it seems likely it would be well known by now.

Thomas Seyfried has worked on cell metabolism in cancer for a long time. He has a book out on his work, and wrote a review for the Medscape site.

In the Medscape article, Seyfried calls “impaired cellular energy metabolism is the defining characteristic of nearly all cancers regardless of cellular or tissue origin”. This claim seems way too strong. There are many defining characteristics of cancer–things that differentiate it from normal cells. Each one is a potential line of attack on tumor cells, a target for drugs or other treatments. Hopefully, treatments that target metabolic changes can be developed, in addition to Metformin. They would be as welcome, and as profitable for drug companies as any other cancer drug. Most likely, treatments targeting cancer cell metabolism can be effective and retard cancer progression for months, but populations of cancer cells evolve, and they will most likely evolve to bypass each metabolic restraint.

Christofferson’s article touts the metabolic theory all out of proportion to the evidence for it.
He writes that a ketogenic diet cures cancer. He takes the disgraceful step of pulling out a few cases where cancer was ‘cured’ by this diet. Every one of the hundreds of scam cancer treatments comes packaged with patient testimonial ‘cures’. Christofferson quotes Seyfried as saying “If one was able to patent and package the ketogenic diet as a pill for cancer it would be a blockbuster”, but if you read Seyfried’s article in Medscape, written for doctors, he doesn’t make this claim. Either Christofferson or Seyfried isn’t being honest with us.

App ideas

Micro movement sensing

Use the orientation sensor in a cell phone to monitor small regular movements. For example, the movement due to the heart beat. It might be possible to measure breathing movement. It may also be possible to measure anomalous movements–tremors, the sway due to microadjustments involved in standing.

Also, if the heartbeat moves a phone to a noticeable degree, does this make cell phone photos blurrier? If so, add heartbeat detection to the camera app–have pictures be snapped between heartbeats.

Basically, orientation data would be collected, and a frequency analysis done to detect the freq and amplitude of the movements. I don’t know how fast the orientation can be polled. If it is too slow, it may be possible to use intermittent polling at precise times to identify the frequency of movements.

Shadow boxing

A related use would be as a shadow boxing app. This would clearly be better as a wrist strap standalone device, but might work as an app. Hold the phone in a hand (or strap it firmly to the wrist), and follow the movements of the hand/arm, recording punches and the speed of them. The user would indicate the hand being scored in setup, and then as hands are switched, the punching of the two could be compared. Groups of friends could play together to see who can punch the fastest or do the most punches in 30s.


This app would run simultaneously on two phones. One phone would display bands of pure red, blue, and green. A sample would be placed across one half of the bands. The second phone would take a picture of the first phone. Image analysis would compare the brightness of the control and sample covered regions and calculate absorbance in the three channels. Cell phone displays are either OLED or IMOD. There are a range of displays used in phones, so this would never be super accurate without calibration. The OLED displays seem to have fairly narrow spectrum pure colors while the iphones have broader colors.

This could be used either as an exploration tool–test substances and record spectra, or reference data could be used to make guesses at substances.

Or you could use a diffraction gratings and make a real spec.

App game idea

Flip it

This game board is an array of tiles. The tiles have letters. The game play involves flipping a pair of letters, as if the two tiles can move through the screen on the axis that connects them. In any case, they move switches them. The goal is to rearrange the tiles to spell words.

cat --flip c:a--> act
dog ------------> dog

cat --flip c:d--> dat
dog ------------> cog

The game can be played different sized boards, and with boards with cutouts.
Variation 1: Have the tiles have both color and a letter, to distinguish common letters.
Variation 2: Have the tiles be two sided, so that flipping them exposes the other sides.

What is interesting about this is that it is a class of games easy to implement in the computer but which is hard or impossible to implement as a physical game. There is a whole class of variations on pen and pencil or board games that haven’t been tried because of this!

App Ideas

Idea 1:

Laser level. Ther are apps that use the orientation sensor in the phone to turn it into a level. Take it a step further. Combine hte orientation sensor and the phone to show a live camera view but draw a level line on it.

This can be taken further (if the phone is accurate enough), to draw a ‘same’ height line on the camera view, useful for hanging pictures and checking the level of things.

Idea 2:

Novelty ‘which protein is your name in’. Check human proteome first for good matches, then orangatang, pig, rat, bacteria. Show the protein sequence with the name highlighted, and a picture of the organism.

Allow the user to send this in an email or post on FB.

Ideas for using gut microbes

I went to a panel that discussed gut microbes at Chicon, and had a few ideas for making use of them:

1) Microbes as sensors. Take existing gut bacteria, electroporate in a reporter plasmid, reintroduce orally. The reporter can be a sensor protein hooked up to GFP or an enzyme that acts on a microbial product to make a derivative not found normally in bacteria, and easily detectable and distinguished from normal chemicals in the gut.
1a) Detection can be by examining poop. A souped up Japanese toilet would be the least obtrusive solution.
1b) if the product is fluorescent, detection can be by direct gut imaging, as is done for mice.

2) Introduce GFP producing bacterial into the gut, and use them like barium is used for gut imaging. Imaging would be done using transilluminated epifluorescence microscope or a fluorescence light box
and thermoelectrically cooled CCD camera. By moving the detector and light source around, enough images can be made for low resolution computed tomographic imaging.

3) Introduce gut bacteria that absorb methane. Natural methane absorbing bacteria, normally present in low numbers can be introduced to increase total gut methane absorbtion, or if methane absorbtion happens at low levels, bacteria could be selected to find strains that do it at a higher level. A third option is to engineer normal gut bacteria to have this capability.

Titan landing

At Windycon, I went to a talk by Christian Ready from the Space Telescope Science Institute on the solar system and saw pictures of the surface of Titan. Wow, I didn’t realize that a probe had made a landing!

Surface of Titan

The surface of Titan as seen by Huygens after its landing on January 14, 2005. (credit: ESA/NASA/JPL/University of Arizona)

Book review: Parasite Rex

Parasite Rex: Inside the Bizarre World of Nature’s Most Dangerous Creatures by Carl Zimmer.

Great book. About parasites. What they are, the recent discovery of how big a role they have in ecosystems, how they live, how they have jumped from animal to animal, and of course, which ones afflict people.

Several chapters describe a range of human parasites in amazing and often frightening detail. From botfly larvae to liver flukes, malaria’s Plasmodium to the nematodes that parasitize humans. There is some discussion of microbial parasites, but most of the book covers metazoan parasites. Zimmer tells the stories of some of these parasites–how they find their way to people, what they do once they arrive in a new host, how they escape detection, and the course of the disease. The story of how several parasites were discovered, how they were identified and followed through their changes of form and host are told. And there are pictures!

Word cloud of Parasite Rex by Carl_Zimmer


Notes on water fluoridation and the Fluoride Deception video

I’d heard of the great water fluoridation fight but never looked into it. In the 60’s the John Birchers were saying it was a Commie plot to weaken America’s vital fluids or something of the sort. And it was parodied in the movie Dr. Strangelove…

Let’s start by bracketing things. Fluoride in water can’t be highly dangerous or people would have noticed. Not putting fluoride in water is not a risk-free choice–it prevents cavities. Cavities don’t just make your teeth fall out, they also increase risks of bacteria related heart disease, and the occasional person dies of a tooth abscess. So the question is, is there disease caused by fluoridation, and is it worse than the diseases caused by no fluoridation?

OK, let’s look at the video.
5:42 Suggests that the idea of adding fluoride to water supplies was to hide the dangers of for fluoride pollution or avoid responsibility for damage due to fluoride pollution. Doesn’t really make sense so far. Ah, reading in the history, when government regs made industry stop dumping fluoride in air and water, one thing they did with it was process out fluoride for water fluoridation. Doesn’t sound that damning, after all it would have been cheaper to dump it in a landfill.

~7:00-20:00 Fluoride air pollution can be bad. Some of the early fluoride researchers also worked on and perhaps had a part in the worst cover ups regarding industrial pollutants. What I’ve read of the tetraethyl lead story is appalling. The connection with the lead story is tenuous. Fluoridating water wasn’t a gold mine, I don’t see there being much pressure to push fluoridation back when it started.

21:30 The NRC report (below) discusses Waldbott’s results, concludes that some people are sensitive to typical water concentrations of fluoride and that it appears to be fairly rare.

From the NRC report, it doesn’t appear that the safety of water fluoridation was well-established, certainly nowhere near today’s standards, back when it began. It was safe by 1940’s standards, and had a clear benefit. I’ve probably got an extra tooth in my mouth due to it.

25:00 The NRC report discusses the Mullenix study. Calls it inconclusive, calls for more studies.

The video didn’t have much info. Here are the establishment reference sources:

CDC recommendations

Fluoride reduces cavities by 15-40%, depending on the study. The low figure is an estimate of the benefit of water fluoridation in a population that already uses fluoride toothpaste.

2006 National Academy report (the greybeards)

Here’s the meat! Water fluoridation is 1 mg / L, when the level hits 4 mg / L studies start seeing negative health effects. That’s a pretty narrow window between benefit and danger level, the smallest one for an environmental exposure I’ve run into. YMMV, I’m not an environmental toxicologist.

What hasn’t really been studied are neurotoxic effects of low level exposure. A few studies have turned up disturbing results. Check out the summary on page 205.

Interesting take on differences between Europe and US fluoridation, Pizzo et al. 2008

The bit about Europe in the video is misleading. Europe hasn’t avoided fluoride, it’s just mostly not in water, it’s in salt or toothpaste.