Category: Science

GeneTac 1000 biochip scanner teardown

Picked up a GeneTac 1000, a biochip scanner. Here are teardown pictures:
Here is the unit:

Teardown pictures. The unit has a self-contained lamp module that plugs into the main controller unit (EG&G Optoelectronics, Model # 300mXT-04, lamp module LM-300MX). Can’t find much about it–looks to be a 300W lamp. The center of the unit has a CCD camera, a Nikon lens, and a big custom lens, and two sets of filters. The slide carousel is on the other side.

















Average Number of Recessive Lethal Mutations Carried by Humans

Recently Gao et. al. published “An Estimate of the Average Number of Recessive Lethal Mutations Carried by Humans”. They studied a Hutterite group in South Dakota, highly inbred (63 founders 13 generations ago). From serious genetic diseases common in this population, they determine the number of deleterious variants present in the founders. They find that 0.29 recessive lethal alleles per haploid genome. Since some lethals manifest before birth, they double the estimate to 0.58.

This gives an expected 1.8% increased chance of a genetic disease from two first cousins.

Gao, Z., Waggoner, D., Stephens, M., Ober, C. & Przeworski, M. Genetics 199, 1243–1254 (2015).

Getting to orbit

Hybrid balloon / vehicle approaches

Saw a recent news item about JP Aerospace. They are working on a two step to orbit approach. The basic plan is to put a large lighter than air (LTA) craft at 200,000 ft, and then accelerate it using a ion thruster to reach orbital velocity.

So I was interested in how this would work, and what the basic parameters (mass, thrust, time) are for approaches of this type.

The benefit of starting from a high altitude is very low air pressure. A balloon can provide steady support so a low thrust vehicle has time to accelerate.

Orbital velocity is roughly 9500 m/s.

What size solid fuel rocket would be required to put a 10 kb payload into orbit?

Future bloging, because the future is in full text

OK, this is quite annoying. It was plenty annoying when I was at a univerisity and 90% of the articles were available at publication, but that 10% always included a handful of important articles so it has always been a PITA. So now I’ll start future blogging!

I’ll tag interesting articles when they get published and follow up when I can actually read them. Many journals now are open access, but some release an article six months or a year after publication. Or sometimes the pdf gets posted. So I’ll tag intertesting articles when they hit the news and write a follow up when I can read them. Because titles and abstracts aren’t enough for articles with useful information!

Duration of urination does not change with body size. Patricia J. Yanga, Jonathan Phama, Jerome Chooa, and David L. Hu. PNAS vol. 111 no. 33p11932–11937.

BTW, PNAS used to release articles at publication. When did they go dark?!

New public health measures

Could new measures substantially improve public health?

What would be the effect if, say, 90% of the country wore filter masks for one week, and concentrated on washing hands?

Infection is a chain, one individual infects one or more others, and an infection gets passed on. That is how disease persists–for most infectious agents, not in one person for months on end, but passed serially every few months as an individual gets infected, and over a few weeks mounts an immune response and fights it off.

An infectious agent requires a basic reproduction factor, an R0, of more than one. If R0 > 1, an infection is growing more common, if R0 < 1, an infection is disappearing. For more diseases, for infection to persist it must spread.

Currently there are constant but weak efforts to reduce the spread of infection–encouraging the sick to stay home and hand washing. Vaccines for influenza. But what if a serious effort was made? A big effort could not be sustained, at least not in the US culture.

But what would be the effect of a large, short effort? If infection transmission can be stomped down for a short period, but long enough to break the chain of infection, it might have a large effect on public health. I wonder if this has been modeled?

Do vaccines prevent disease?

Here’s an interesting graph comparing disease prevalence before vaccines and now:
disease pre and post vaccination

This is quite a strong correlation, but how do we know that vaccines caused the diseases to become so rare? Did vaccines causes disease incidence for all these diseases to bottom out, or is it something else, say a coincidence, or maybe all diseases are just disappearing because Americans are healthier today?

So more information is needed. The first thing to consider is that all infectious disease hasn’t gone away. The cold is still as common as ever. Kids still get sore throats and ear aches. There are also the ones I don’t think about or haven’t heard of, like RSV, croup, Fifth disease. And looking at adults, clap, HPV, and gonnorhia are at epidemic levels. So infectious disease is still very common, but the worst diseases have become rare–the ones for which general vaccination is practiced .

Another line of evidence that vaccines are what stomped out the targeted diseases is the timing. They didn’t all disappear at once, not even close. What was observed is that each disease dropped off after widespread vaccination became common.

Here’s a study that looked at incidence for several disease in the US over decades: pdf

If you look at page 4, they summarize incidence over time for 8 diseases. At the top they summarize incidence. The colored section of the graph is detailed regional data. The grey vertical bar shows when widespread vaccination was introduced–a different year for each disease. After the vaccine is introduced, the disease incidence goes way down. Note that for smallpox, it was better vaccines replacing ones started in the 1800’s, so no grey bar is shown.

Here’s a simpler graph of measles from the CDC site:
CDC measles
measles incidence in the US

So it isn’t general health or healthier people with immune systems that prevent disease causing a gradual decline in infectious disease. Instead, the incidence of a specific disease drops when the vaccine is introduced.

Rotavirus

And here’s one of the new vaccines–for rotavirus. Nearly all kids used to get it: “four of five children in the US had symptomatic rotavirus gastroenteritis, one in seven required a clinic or emergency department (ED) visit, one in 70 was hospitalized”. The vaccine was introduced in 2006 and the disease has already become much less common: CDC Surveillance of Rotavirus

clinical lab rotavirus findings
See fig 4 especially.

So what I conclude from these lines of evidence is that the introduction of widespread vaccination for a disease causes it to become much, much less common.

Dinosaur coloration

In the last decade or so, dinosaurs have started being depicted as brightly colored. The reason for the trend of brightly colored dinosaurs in movies is that in recent years techniques for identifying pigments from fossils have been developed, using electron microscopy and ion bombardment mass spectrometry.

News report: Ancient Pigments Unearthed: Fossilized skin reveals the colors of three extinct marine reptiles by Ed Yong. The Scientist, January 8, 2014
Original article: (Abstract) Skin pigmentation provides evidence of convergent melanism in extinct marine reptiles. Lindgren et. al., Nature 08 Jan 2014

and news report: Pictures: Dinosaur True Colors Revealed by Feather Find, Chris Sloan, National Geographic Daily News
Original article: Zhang et. al., 2010

Fossil color studies were pioneered by Jakob Vinther at Yale

No doubt movie speculation is running far ahead of the science, but these are the discoveries that unleashed the trend of brightly colored dinosaurs. At this point, it is reasonable to think dinosaurs are as brightly colored as birds or reptiles are today, and in some cases the coloring of specific species is known.

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.

laser
laser

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
servo

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.

xilinx
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.