Science fiction aficionados may be familiar with a trilogy by Nancy Kress, in which she imagines the emergence of genetically modified humans who don’t require sleep. Naturally, given all the extra time, the sleepless quickly surpass others who need to rest each day and evolve into a superior race. The trilogy tells the story of the resulting class, cultural, and technological conflict and is a fascinating read.

Alas, most of us need our nightly sleep and function miserably when sleep deprived. But what if the performance hit from too little sleep could be ameliorated by tweaking brain chemistry?

New research from a collaboration between scientists at the Universities of Pennsylvania, Glasgow, and Toronto identifies a chemical-signaling pathway involved in the memory and learning deficits that result from suboptimal sleeping. (Nature 461 [22 October 2009], 1122–1125) Five hours of sleep deprivation in mice caused impairment of hippocampus function by increasing the activity of the enzyme that degrades cyclic AMP—phosphodiesterase. Treating the critters with a drug (rolipram) that inhibits phosphodiesterase restored hippocampus function.

In the words of the authors, the results “lay the groundwork for further analysis of the functional biochemistry of sleep deprivation.” This may be good news for those of us moderns who never seem to find enough time for proper rest. Don’t start pulling all-nighters yet, though, as five sleepless hours for mice doesn’t quite mimic the chronic effects of weeks or years of too little shut-eye for people.

If sleep fascinates you, see my previous post on the subject. On the other hand, don’t bother if my writing makes you drowsy….

It is an article of faith, especially in higher education, that student participation in research is utterly required for shaping attitudes, appreciation, and understanding of the scientific enterprise. Accordingly, every institution of higher learning with any aspiration to excellence has students toiling in labs doing some kind of research right alongside their professors.

High-school students—equally impressionable—don’t often have this same opportunity to engage in research projects, at least in part because their teachers don’t, either. To redress this latter problem, a group of researchers at Columbia University created a program for high-school teachers to join Columbia scientists’ labs in the off-session summer months.

The wonderful result (Science 326: 5951 [16 October 2009], 440–442) is that the students whose teachers gained research experience do significantly better (10.1 percentage points) in a standardized test of science knowledge (the New York State Regents exam) than the students of non-participating teachers.

Why is this so? At the risk of being either mordant or enigmatic, I’ll answer the question with another: would you rather learn to play the cello from someone who plays the cello, or from someone who listens to lots of compact discs of cello music?

In one corner, we have Moore’s law. In the other corner, there is Carlson’s curve.

Moore’s law— named after Gordon Moore, co-founder of Intel—famously predicted over 40 years ago that the transistor density of integrated circuits would double about every two years. So far, it’s been right.

Carlson’s curve—named after biologist Rob Carlson—refers to a graph showing the diminishing cost per base of sequencing DNA over time. Like transistor density, DNA sequencing prowess is similarly exponential, and showing no signs of slowing down.

Of course, neither of these is a fundamental law of nature, only empirical observations, and reality will inevitably deviate from the prediction someday.

So one naturally wonders, if it were a contest, which will hold steady the longest?

If one assumes a conventional mathematics of exponential growth, Moore’s law will be repealed first because it started first (approximately 1965 and 1990 for the two cases), and such a curve always levels off.

Deviations from a standard exponential would most likely come from new discoveries or technological innovation. For Moore’s law, the physical constraint of moving electrons in circuits is certainly limiting, as is the near certainty that a transistor can’t be smaller than a single atom. However, quantum computing or DNA computing might overcome these inherent limits of silicon chips.

For DNA sequencing (or DNA synthesis for that matter), the cost of chemical reagents and the ability to physically resolve DNA fragments cheaply are clearly limiting at some point. However, rapid advances in robotics, miniaturization, and “lab-on-a-chip” technologies can be expected to continue for the foreseeable future.

Based on nothing but the intuition that cost is easier to overcome than physics, my bet is that halving the price tag of DNA sequencing will outlast the course of integrated circuit doubling. Doubtless, readers can present counter-arguments, which I of course welcome and encourage.