Lifeboat Foundation

A new form of magnetic brain stimulation rapidly relieved symptoms of severe depression in 90% of participants in a small study conducted by researchers at the Stanford University School of Medicine.

The researchers are conducting a larger, double-blinded trial in which half the participants are receiving fake treatment. The researchers are optimistic the second trial will prove to be similarly effective in treating people whose condition hasn’t improved with medication, talk therapy or other forms of electromagnetic stimulation.

The treatment is called Stanford Accelerated Intelligent Neuromodulation Therapy, or SAINT. It is a form of transcranial magnetic stimulation, which is approved by the Food and Drug Administration for treatment of depression. The researchers reported that the therapy improves on current FDA-approved protocols by increasing the number of magnetic pulses, speeding up the pace of the treatment and targeting the pulses according to each individual’s neurocircuitry.

The world generates over six million tons of coffee grounds, according to the International Coffee Organization. The journal Agriculture and Food Chemistry reported in 2012 that over half of spent coffee grounds end up in landfills. Cellulose nanofibers are the building blocks for plastic resins that can be made into biodegradable plastic products.

The YNU team, led by Izuru Kawamura, an associate professor at the Graduate School of Engineering Science, set out to build upon previous research into extracting cellulose nanofibers from coffee grounds. They published their findings on April 1 in the journal Cellulose.

“Our ultimate goal is to establish a sustainable recycling system with our cellulose nanofibers in the coffee industry,” Kawamura said. “Now, more and more restaurants and cafés have been banned from using single-use straws. Following that movement, we aim to make a transparent disposable coffee cup and straw with an additive comprising cellulose nanofibers from spent coffee grounds.”

Glass has an unusual atomic structure that resembles a liquid frozen in place, making it hard to predict how it will behave. DeepMind has developed an AI capable of doing so, which may also be able to predict traffic jams.

As capable as robots are, the original animals after which they tend to be designed are always much, much better. That’s partly because it’s difficult to learn how to walk like a dog directly from a dog — but this research from Google’s AI labs make it considerably easier.

The goal of this research, a collaboration with UC Berkeley, was to find a way to efficiently and automatically transfer “agile behaviors” like a light-footed trot or spin from their source (a good dog) to a quadrupedal robot. This sort of thing has been done before, but as the researchers’ blog post points out, the established training process can often “require a great deal of expert insight, and often involves a lengthy reward tuning process for each desired skill.”

That doesn’t scale well, naturally, but that manual tuning is necessary to make sure the animal’s movements are approximated well by the robot. Even a very doglike robot isn’t actually a dog, and the way a dog moves may not be exactly the way the robot should, leading the latter to fall down, lock up or otherwise fail.

We established an ultrasensitive method for identifying multiple enzymes in biological samples by using a multiplexed microdevice-based single-molecule enzymatic assay. We used a paradigm in which we “count” the number of enzyme molecules by profiling their single enzyme activity characteristics toward multiple substrates. In this proof-of-concept study of the single enzyme activity–based protein profiling (SEAP), we were able to detect the activities of various phosphoric ester–hydrolyzing enzymes such as alkaline phosphatases, tyrosine phosphatases, and ectonucleotide pyrophosphatases in blood samples at the single-molecule level and in a subtype-discriminating manner, demonstrating its potential usefulness for the diagnosis of diseases based on ultrasensitive detection of enzymes.

Cellular functions are mediated by the activities of diverse enzymes, and hence, determining the functional changes that occur in these enzymes during pathogenesis is crucial for understanding and detecting diseases (1). However, the detection sensitivity of conventional assays for discovering and using enzyme biomarkers for diagnosis needs to be improved. In case of DNA and RNA analysis, enhancing the sensitivity of detection to the single-molecule level has revolutionized biomarker discovery and usage (2). However, the detection methods for proteins, which are thought to contain more functionality-oriented information that can be directly linked to the phenotypes, are yet to attain such a high degree of sensitivity (3).

In this study, we developed a novel assay platform for comprehensively detecting multiple enzymes in biological samples at single protein level for ultrasensitive and quantitative profiling of the disease-related enzymatic activities. This method is based on single-molecule enzyme analysis performed in a microfabricated chamber device, in which single-molecule enzymes in a diluted biological sample are separately loaded into individual microchambers for measuring and detecting its activity (4, 5). Although conventional single-molecule analysis is commonly used to study the biochemical properties of specific enzymes, their application for analyzing biological samples containing complex mixtures of characterized and uncharacterized proteins remains challenging, as it is difficult to predict which enzyme is loaded into each chamber due to random distribution.

Scientists can identify pathogenic genes through genetic engineering. This involves adding human-made DNA into a bacterial cell. However, the problem is that bacteria have evolved complex defense systems to protect against foreign intruders — especially foreign DNA. Current genetic engineering approaches often disguise the human-made DNA as bacterial DNA to thwart these defenses, but the process requires highly specific modifications and is expensive and time-consuming.

In a paper published recently in the Proceedings of the National Academy of Sciences journal, Dr. Christopher Johnston and his colleagues at the Forsyth Institute describe a new technique to genetically engineer bacteria by making human-made DNA invisible to a bacterium’s defenses. In theory, the method can be applied to almost any type of bacteria.

Johnston is a researcher in the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center and lead author of the paper. He said that when a bacterial cell detects it has been penetrated by foreign DNA, it quickly destroys the trespasser. Bacteria live under constant threat of attack by a virus, so they have developed incredibly effective defenses against those threats.

Circa 2006

Fixing leaking pipelines can be tricky and expensive. But now engineers at a company in Aberdeen, Scotland, have developed a novel way to get the job done. It involves using artificial platelets inspired by the way our blood clots when we get cut.

The platelets, actually small pieces of polymeric or elastomeric material, are introduced into the pipeline upstream and use the flow of the fluid to carry them down the pipe toward the leak. There the pressure forcing the fluid out of the leak causes the platelets to amass at the point of rupture, clogging up the escaping fluid in the process, says Klaire Evans, sales and marketing engineer with Brinker Technology, which is developing the technology.

The method has been tested on a handful of pipelines owned by BP and Shell. According to Sandy Meldrum, an engineer with BP, in Aberdeen, the technology was used to fix a leak in an undersea water injection pipe at an oil field near the Scottish Shetland Isles. Normally this kind of leak would have to be fixed using remotely operated vehicles, whose operators would place a clamp over the leak. But by using Brinker’s technology, BP saved about $3 million, says Meldrum.

Circa 2015

This nifty “bio-concrete” might help buildings stand a little longer.

Science yearns to discover a means to control or stop volcanic eruptions before they begin. To date there have been no successful efforts to start, stop or reduce a volcanic eruption; however, the ideas exists and discussion is underway. By accurately forecasting or minimizing a volcanic eruption, scientists and decision makers can reduce the risk and damage to human health and property through preparation and evacuation. Unfortunately, eruption forecasting is not totally accurate or reliable. However, if we are able to initiate a volcanic eruption we could schedule the event and prepare, properly evacuate and effectively eliminate risk to human well being. Think of it as a “geologic Caesarean” _™. Other techniques to control an eruption could include depressurization of the magma chamber or increasing the aperture of the vent to diffuse the energy of an eruption.