Bacteriophage treatment for alcohol related liver disease

Researchers from King’s College London and the University of California San Diego School of Medicine conducted an animal study in mice and shown promise of bacteriophage therapy in treating alcohol-related liver disease.

This research is published in journal Nature.

The team discovered that patients with severe alcoholic hepatitis had high numbers of a destructive gut bacterium Enterococcus faecalis, which produced a toxin called cytolysin. This toxin is shown to injure liver cells. Enterococcus faecalis is normally found in low numbers in the healthy human gut.

To investigate the potential for phage therapy, the researchers isolated four different phages that specifically target cytolysin-producing Enterococcus faecalis. When they treated the mice with these, the bacteria were eradicated, and alcohol-induced liver disease was abolished. Control phages that target other bacteria or non-cytolytic E. faecalis had no effect.

With the rise of multidrug-resistant infections, people are looking at alternatives to antibiotics. Bacteriophages are viruses that kill bacteria. These bacteriophages are naturally occurring and offer a promising alternative to antibiotics. However, much research is needed to establish their safety and efficacy in clinical practice. The current study show promise of using phage therapy to alter the gut microbiome in cases with alcoholic liver disease.

New findings of cortical activity during delta wave sleep sheds further light into memory formation

Scientists at the Center for Interdisciplinary Research in Biology have shown that delta waves emitted while we sleep are not generalized periods of silence during which the cortex rests, as has been described for decades in the scientific literature. Instead, they isolate assemblies of neurons that play an essential role in long-term memory formation. These results were published in journal Science.

While we sleep, the hippocampus reactivates itself spontaneously by generating activity similar to that while we are awake. It sends information to the cortex, which reacts in turn. This exchange is often followed by a period of silence called a ‘delta wave’ then by a rhythmic activity called a ‘sleep spindle’. This is when the cortical circuits reorganize to form stable memories.

However, the role of delta waves in the formation of new memories is still a puzzle: why does a period of silence interrupt the sequence of information exchanges between the hippocampus and the cortex, and the functional reorganization of the cortex?

The authors here looked more closely at what happens during delta waves themselves. They discovered, surprisingly, that the cortex is not entirely silent but that a few neurons remain active and form assemblies, i.e. small, coactive sets that code information. This unexpected observation suggests that the small number of neurons that activate when all the others stay quiet can carry out important calculations while protected from possible disturbances.

And the discoveries from this work go even further! Spontaneous reactivations of the hippocampus determine which cortical neurons remain active during the delta waves and reveal transmission of information between the two cerebral structures. In addition, the assemblies activated during the delta waves are formed of neurons that have participated in learning a spatial memory task during the day. Together these elements suggest that these processes are involved in memory consolidation.

To demonstrate it, in rats the scientists caused artificial delta waves to isolate either neurons associated with reactivations in the hippocampus or random neurons. Result: when the right neurons were isolated, the rats managed to stabilize their memories and succeed at the spatial test the next day.

Machine learning to predict the clinical utility of biomedical research

A machine learning model to predict which scientific advances are likely to eventually translate to the clinic has been developed by Ian Hutchins and colleagues in the Office of Portfolio Analysis (OPA), a team led by George Santangelo at the National Institutes of Health (NIH).

This work published in the journal PLOS Biology aims to decrease the interval between scientific discovery and clinical application. The model determines the likelihood that a research article will be cited by a future clinical trial or guideline, an early indicator of translational progress.

Researchers have quantified these predictions as a novel metric called “Approximate Potential to Translate” (APT). Approximate Potential to Translate values can be used by researchers and decision-makers to focus attention on areas of science that have strong signatures of translational potential. Although numbers alone should never be a substitute for evaluation by human experts, the Approximate Potential to Translate metric has the potential to accelerate biomedical progress as one component of data-driven decision-making.

The model that computes Approximate Potential to Translate values makes predictions based upon the content of research articles and citations. A long-standing barrier to research and development of metrics like Approximate Potential to Translate is that such citation data has remained hidden behind proprietary, restrictive, and often costly licensing agreements. To disrupt this impediment to the scientific community, to increase transparency, and to facilitate reproducibility, OPA has aggregated citation data from publicly available resources to create an open citation collection (NIH-OCC).

The open citation collection comprises over 420 million citation links at present and will be updated monthly. For publications since 2010, the open citation collection is already more comprehensive than leading proprietary sources of citation data. Citation data from the open citation collection are used to calculate both Approximate Potential to Translate values and Relative Citation Ratios (RCRs). The latter, a measure of scientific influence at the article level, normalized for the field of study and time since publication.

Approximate Potential to Translate values and the open citation collection are publicly available as components of the iCite webtool. This tool will continue as the primary source of Relative Citation Ratios data.

New microfluidic system using artificial membrane keep brain tissue viable for a longer duration

Researchers at the RIKEN Center for Biosystems Dynamics Research in Japan have developed a new system for keeping tissue viable for long-term study once transferred from an animal to a culture medium. The new system uses a microfluidic device made of polydimethylsiloxane (PDMS) with a porous membrane that can keep tissue from both drying out and from drowning in fluid. This study was published in the journal Analytical Sciences.

The team tested the device using tissue from the mouse suprachiasmatic nucleus, a complex part of the brain that governs circadian rhythms. By measuring the level of bioluminescence coming from the brain tissue, they were able to see that tissue kept alive by their system stayed active and functional for over 25 days with nice circadian activity. In contrast, neural activity in tissue kept in a conventional culture decreased by 6% after only 10 hours.

This new method will be useful in observing development and testing how tissues respond to drugs. Experiments with tissues are much more complex and provide important information such as cell to cell interaction, unlike seeded cells where such observation is difficult.