Trunkneck’s Blog

Like a wristwatch that needs to be wound daily for accurate time-telling, the human circadian system — the biological cycles that repeat approximately every 24 hours — requires daily light exposure to the eye’s retina to remain synchronized with the solar day. In a new study published in the June issue of Neuroscience Letters, researchers have demonstrated that when it comes to the circadian system, not all light exposure is created equal.

Researchers have found that the circadian system may be able to distinguish between lights of different colors.

The findings have profound implications for exploring how lighting can be used to adjust our bodies’ clocks, and they could redefine the way lighting is manufactured, according to Mariana Figueiro, lead author of the paper and assistant professor in the Lighting Research Center (LRC) at Rensselaer Polytechnic Institute.

Short-wavelength light, including natural light from the blue sky, is highly effective at stimulating the circadian system. Exposure to other wavelengths — and thus colors — of light may necessitate longer exposure times or require higher exposure levels to be as effective at “winding the watch.”

In some instances, exposure to multiple wavelengths (colors) of light simultaneously can result in less total stimulation to the circadian system than would result if either color were viewed separately, a phenomenon known as “spectral opponency.” The LRC scientists have shown that the circadian system shares neurons in the retina — which exhibit spectral opponency and form the foundation for our perception of color — with the visual system. Thus, in principle, the circadian system may be able to distinguish between lights of different colors.

More than meets the eye
To demonstrate that the circadian system exhibited spectral opponency formed in the retina, the researchers exposed 10 subjects to three experimental conditions: one unit of blue light to the left eye plus one unit of green light to the right eye; one unit of blue light to the right eye plus one unit of green light to the left eye; and half a unit of blue light plus half a unit of green light to both eyes and then measured each individual’s melatonin levels, a natural indicator of the circadian clock.

“The first two conditions — exposure to a single color in each eye — did not result in a significant difference in melatonin suppression, while the third condition — exposure to both colors in both eyes — resulted in significantly less melatonin suppression,” said Figueiro. “Even though the amount of light at the eye was the same in all three conditions, when the two colors of light were combined in the same eye, the response of the system was reduced due to spectral opponent mechanisms formed in the retina.”

This indicates that spectral opponency is a fundamental characteristic of how the human retina converts light into neural signals in the human circadian system, according to Figueiro.

The findings also verify the accuracy of a new quantification system LRC researchers developed in 2006 to calculate the “circadian efficacy” of different light sources. Called the model of human circadian phototransduction,
the tool correctly predicted the circadian system response demonstrated under each of the three experimental conditions.

The model appears to correctly predict the circadian response to any light source, and can be used as the foundation for a new system of circadian photometry, much like the current system of photometry based on human vision.

Quantification of light as a stimulus for the circadian system provide new scientific insights into how the human body processes light for the circadian system, according to Figueiro.

Nocturnal melatonin, a hormone produced at night and under conditions of darkness, is used as a marker for the circadian clock. Scientific evidence suggests that disruption of the circadian system — and thus the melatonin cycle — may result in increased malignant tumor growth, as well as poor sleep quality, lack of alertness, seasonal depression, and immune deficiencies.

Now that the model can predict circadian efficacy for any light source, Figueiro and her research partners have begun studying the way time of night affects the potency of light exposure. Once complete, the comprehensive model will allow manufacturers to develop light sources that most effectively stimulate and, importantly, do not stimulate the circadian system.

Figueiro’s research was supported by a $200,000 grant from the New York State Office of Science, Technology, and Academic Research (NYSTAR), which awarded her the James D. Watson Investigator award in 2007.

The Watson awards are designed to recognize and support outstanding scientists and engineers who show potential for leadership and scientific discovery early in their careers in the fields of biotechnology, according to Michael J. Relyea, executive director of NYSTAR.

Figueiro conducted her research with LRC Director Mark Rea, and Senior Research Scientist Andrew Bierman, who are coauthors on the paper.

About the Lighting Research Center
The Lighting Research Center (LRC) is part of Rensselaer Polytechnic Institute of Troy, N.Y., and is the leading university-based research center devoted to lighting. The LRC offers the world’s premier graduate education in lighting, including one- and two-year master’s programs and a Ph.D. program. Since 1988 the LRC has built an international reputation as a reliable source for objective information about lighting technologies, applications, and products. The LRC also provides training programs for government agencies, utilities, contractors, lighting designers, and other lighting professionals.

Now I better understand my own sleeping habits (Or lack thereof) from my late night web sessions.

Scientists may have found a new way to combat the most dangerous form of computer virus.

The method automatically detects within minutes when an Internet worm has infected a computer network.

Network administrators can then isolate infected machines and hold them in quarantine for repairs.

Ness Shroff, Ohio Eminent Scholar in Networking and Communications at Ohio State University, and his colleagues describe their strategy in the current issue of IEEE Transactions on Dependable and Secure Computing.

They discovered how to contain the most virulent kind of worm: the kind that scans the Internet randomly, looking for vulnerable hosts to infect.

“These worms spread very quickly,” Shroff said. “They flood the Net with junk traffic, and at their most benign, they overload computer networks and shut them down.”

Code Red was a random scanning worm, and it caused $2.6 billion in lost productivity to businesses worldwide in 2001. Even worse, Shroff said, the worm blocked network traffic to important physical facilities such as subway stations and 911 call centers.

“Code Red infected more than 350,000 machines in less than 14 hours. We wanted to find a way to catch infections in their earliest stages, before they get that far,” Shroff said.

The key, they found, is for software to monitor the number of scans that machines on a network send out. When a machine starts sending out too many scans — a sign that it has been infected — administrators should take it off line and check it for viruses.

The strategy sounds straightforward enough. A scan is just a search for Internet addresses — what we do every time we use search engines such as Google. The difference is, a virus sends out many scans to many different destinations in a very short period of time, as it searches for machines to infect.

“The difficulty was figuring out how many scans were too many,” Shroff said. “How many could you allow before an infection would spread wildly? You want to make sure the number is small to contain the infection. But if you make it too small, you’ll interfere with normal network traffic.”

“It turns out that you can allow quite a large number of scans, and you’ll still catch the worm.”

Shroff was working at Purdue University in 2006 when doctoral student Sarah Sellke suggested making a mathematical model of the early stages of worm growth. With Saurabh Bagchi, assistant professor of electrical and computer engineering at Purdue, they developed a model that calculated the probability that a virus would spread, depending on the maximum number of scans allowed before a machine was taken off line.

In simulations, they pitted their model against the Code Red worm, as well as the SQL Slammer worm of 2003. They simulated how far the virus would spread, depending on how many networks on the Internet were using the same containment strategy: quarantine any machine that sends out more than 10,000 scans.

They chose 10,000 because it is well above the number of scans that a typical computer network would send out in a month.

“An infected machine would reach this value very quickly, while a regular machine would not,” Shroff explained. “A worm has to hit so many IP addresses so quickly in order to survive.”

In the simulations pitted against the Code Red worm, they were able to prevent the spread of the infection to less than 150 hosts on the whole Internet, 95 percent of the time.

A variant of Code Red worm (Code Red II) scans the local network more efficiently, and finds vulnerable targets much faster. Their method was effective in containing such worms. In the simulations, they were able to trap the worm in its original network — the one that would have started the outbreak — 77 percent of the time.

Anywhere from 10 to 20 percent of the time, it spread to one other network, but no further. The remaining 3 to 13 percent of the time, it escaped to more networks, but the infection was slowed.

In all cases, there was a dramatic decrease in the spread of the worm within the first hour.

To use this strategy, network administrators would have to install software to monitor the number of scans on their networks, and would have to allow for some downtime among computers when they initiate a quarantine.

According to Shroff, that wouldn’t be a problem for most organizations. Very small businesses — ones with only a few servers — may have more difficulty taking their machines off line.

“Unfortunately there is no complete foolproof solution,” Shroff said. “You just keep trying to come up with techniques that limit a virus’s ability to do harm.”

He and his colleagues are working on adapting their strategy to stop targeted Internet worms — ones that have been designed specifically to attack certain vulnerable IP addresses.

This work was supported by a grant from the National Science Foundation, and Sarah Sellke’s NSF Graduate Fellowship.

New research* shows that while engineered nanomaterials can be transferred up the lowest levels of the food chain from single celled organisms to higher multicelled ones, the amount transferred was relatively low and there was no evidence of the nanomaterials concentrating in the higher level organisms. The preliminary results observed by researchers from the National Institute of Standards and Technology (NIST) suggest that the particular nanomaterials studied may not accumulate in invertebrate food chains.

Photomicrograph of ciliate T. pyriformis during cell division with accumulated quantum dots appearing red.

The same properties that make engineered nanoparticles attractive for numerous applications—biological and environmental stability, small size, solubility in aqueous solutions and lack of toxicity to whole organisms—also raise concerns about their long-term impact on the environment. NIST researchers wanted to determine if nanoparticles could be passed up a model food chain and if so, did the transfer lead to a significant amount of bioaccumulation (the increase in concentration of a substance in an organism over time) and biomagnification (the progressive buildup of a substance in a predator organism after ingesting contaminated prey).

Closeup photomicrograph of rotifer B. calyciflorus (whole organism seen in upper left corner) with quantum dots assimilated from ingested ciliates appearing red.

In their study, the NIST team investigated the dietary accumulation, elimination and toxicity of two types of fluorescent quantum dots using a simple, laboratory-based food chain with two microscopic aquatic organisms—Tetrahymena pyriformis, a single-celled ciliate protozoan, and the rotifer Brachionus calyciflorus that preys on it. The process of a material crossing different levels of a food chain from prey to predator is called “trophic transfer.”

Quantum dots are nanoparticles engineered to fluoresce strongly at specific wavelengths. They are being studied for a variety of uses including easily detectable tags for medical diagnostics and therapies. Their fluorescence was used to detect the presence of quantum dots in the two microorganisms.

The researchers found that both types of quantum dots were taken in readily by T. pyriformis and that they maintained their fluorescence even after the contaminated ciliates were ingested by the higher trophic level rotifers. This observation helped establish that the quantum dots were transferred across the food chain as intact nanoparticles and that dietary intake is one way that transfer can occur. The researchers noted that, “Some care should be taken, however, when extrapolating our laboratory-derived results to the natural environment.”

“Our findings showed that although trophic transfer of quantum dots did take place in this simple food chain, they did not accumulate in the higher of the two organisms,” says lead author David Holbrook. “While this suggests that quantum dots may not pose a significant risk of accumulating in aquatic invertebrate food chains in nature, additional research beyond simple laboratory experiments and a more exact means of quantifying transferred nanoparticles in environmental systems are needed to be certain.”

* R.D. Holbrook, K.E. Murphy, J.B. Morrow and K.D. Cole. Trophic transfer of nanoparticles in a simplified invertebrate food chain. Nature Nanotechnology, June 2008 (advance online publication).