Filling me softly

Surgical implants are widely used in modern medicine but their effectiveness is often compromised by how our bodies react to them. Now, scientists at the University of Cambridge have discovered that implant stiffness is a major cause of this so-called foreign body reaction.

This is the first time that stiffness of implant materials has been shown to be involved in foreign body reactions. The findings – published in the journal Biomaterials – could lead to major improvements in surgical implants and the quality of life of patients whose lives depend on them.

Foreign bodies often trigger a process that begins with inflammation and ends with the foreign body being encapsulated with scar tissue. When this happens after an accident or injury, the process is usually vital to healing, but when the same occurs around, for example, electrodes implanted in the brain to alleviate tremor in Parkinson’s disease, it may be problematic.

Despite decades of research, the process remains poorly understood as neither the materials from which these implants are made, nor their electrical properties, can explain what triggers inflammation.

Instead of looking for classical biological causes, a group of Cambridge physicists, engineers, chemists, clinical scientists and biologists decided to take a different tack and examine the impact of an implant’s stiffness on the inflammatory process.

According to Dr Kristian Franze, one of the authors of the study: “Electrodes that are implanted in the brain, for example, should be chemically inert, and these foreign body reactions occur whether or not these electrodes are switched on, so it’s not the electrical signalling.

“We thought that an obvious difference between electrodes and brain tissue is stiffness. Brain tissue is as soft as cream cheese, it is one of the softest tissues in the body, and electrodes are orders of magnitude stiffer.”

To test their hypothesis that mechanical signals trigger inflammation, the team cultured brain cells on two different substrates. The substrates were chemically identical but one was as soft as brain tissue and the other two orders of magnitude stiffer, akin to the stiffness of muscle tissue.

When they examined the cells, they found major differences in their shape. “The cells grown on the stiffer substrate were very flat, whereas those grown on the soft substrate looked much more like cells you find in the brain,” he explained.

To confirm the findings they did genetic and other tests, which revealed that many of the inflammatory genes and proteins known to be involved in foreign body reactions had been upregulated on stiff surfaces.

The team then implanted a tiny foreign body into rats’ brains. The implant was made of a single material but one side was as soft as brain tissue and the other as stiff as muscle. They found much greater foreign body reaction around the stiff part of the implant.

“This strongly indicates that stiffness of a material may trigger foreign body reactions. It does not mean there aren’t other triggers, but stiffness definitely contributes and this is something new that hasn’t been known before,” he said.

The findings could have major implications for the design of implants used in the brain and other parts of the body.

“While it may eventually be possible to make implants out of new, much softer materials, our results suggest that in the short term, simply coating existing implants with materials that match the stiffness of the tissue they are being implanted into will help reduce foreign body reactions,” said Dr Franze.

Mathematical beauty activates same brain region as great art or music

People who appreciate the beauty of mathematics activate the same part of their brain when they look at aesthetically pleasing formula as others do when appreciating art or music, suggesting that there is a neurobiological basis to beauty.

There are many different sources of beauty - a beautiful face, a picturesque landscape, a great symphony are all examples of beauty derived from sensory experiences. But there are other, highly intellectual sources of beauty. Mathematicians often describe mathematical formulae in emotive terms and the experience of mathematical beauty has often been compared by them to the experience of beauty derived from the greatest art.

In a new paper published in the open-access journal Frontiers in Human Neuroscience, researchers used functional magnetic resonance imaging (fMRI) to image the brain activity of 15 mathematicians when they viewed mathematical formulae that they had previously rated as beautiful, neutral or ugly. 

The results showed that the experience of mathematical beauty correlates with activity in the same part of the emotional brain – namely the medial orbito-frontal cortex – as the experience of beauty derived from art or music.

Professor Semir Zeki, lead author of the paper from the Wellcome Laboratory of Neurobiology at UCL, said: “To many of us mathematical formulae appear dry and inaccessible but to a mathematician an equation can embody the quintescence of beauty. The beauty of a formula may result from simplicity, symmetry, elegance or the expression of an immutable truth. For Plato, the abstract quality of mathematics expressed the ultimate pinnacle of beauty.”

“This makes it interesting to learn whether the experience of beauty derived from such as highly intellectual and abstract source as mathematics correlates with activity in the same part of the emotional brain as that derived from more sensory, perceptually based, sources.”

In the study, each subject was given 60 mathematical formulae to review at leisure and rate on a scale of -5 (ugly) to +5 (beautiful) according to how beautiful they experienced them to be. Two weeks later they were asked to re-rate them while in an fMRI scanner.

The formulae most consistently rated as beautiful (both before and during the scans) were Leonhard Euler’s identity, the Pythagorean identity and the Cauchy-Riemann equations. Leonhard Euler’s identity links five fundamental mathematical constants with three basic arithmetic operations each occurring once and the beauty of this equation has been likened to that of the soliloquy in Hamlet.

Mathematicians judged Srinivasa Ramanujan’s infinite series and Riemann’s functional equation as the ugliest.

Professor Zeki said: “We have found that activity in the brain is strongly related to how intense people declare their experience of beauty to – even in this example where the source of beauty is extremely abstract. This answers a critical question in the study of aesthetics, namely whether aesthetic experiences can be quantified.”

Professor Zeki added: “We have found that, as with the experience of visual or musical beauty, the activity in the brain is strongly related to how intense people declare their experience of beauty to be – even in this example where the source of beauty is extremely abstract. This answers a critical question in the study of aesthetics, one which has been debated since classical times, namely whether aesthetic experiences can be quantified.”

Brain process takes paper shape

A paper-based device that mimics the electrochemical signalling in the human brain has been created by a group of researchers from China.

The thin-film transistor (TFT) has been designed to replicate the junction between two neurons, known as a biological synapse, and could become a key component in the development of artificial neural networks, which could be utilised in a range of fields from robotics to computer processing.

The TFT, which has been presented today, 13 February, in IOP Publishing’s journal Nanotechnology, is the latest device to be fabricated on paper, making the electronics more flexible, cheaper to produce and environmentally friendly.

The artificial synaptic TFT consisted of indium zinc oxide (IZO), as both a channel and a gate electrode, separated by a 550-nanometre-thick film of nanogranular silicon dioxide electrolyte, which was fabricated using a process known as chemical vapour deposition.

The design was specific to that of a biological synapse—a small gap that exists between adjoining neurons over which chemical and electrical signals are passed. It is through these synapses that neurons are able to pass signals and messages around the brain.

All neurons are electrically excitable, and can generate a ‘spike’ when the neuron’s voltage changes by large enough amounts. These spikes cause signals to flow through the neurons which cause the first neuron to release chemicals, known as neurotransmitters, across the synapse, which are then received by the second neuron, passing the signal on.

Similar to these output spikes, the researchers applied a small voltage to the first electrode in their device which caused protons—acting as a neurotransmitter—from the silicon dioxide films to migrate towards the IZO channel opposite it.

As protons are positively charged, this caused negatively charged electrons to be attracted towards them in the IZO channel which subsequently allowed a current to flow through the channel, mimicking the passing on of a signal in a normal neuron.

As more and more neurotransmitters are passed across a synapse between two neurons in the brain, the connection between the two neurons becomes stronger and this forms the basis of how we learn and memorise things.

This phenomenon, known as synaptic plasticity, was demonstrated by the researchers in their own device. They found that when two short voltages were applied to the device in a short space of time, the second voltage was able to trigger a larger current in the IZO channel compared to the first applied voltage, as if it had ‘remembered’ the response from the first voltage.

Corresponding author of the study, Qing Wan, from the School of Electronic Science and Engineering, Nanjing University, said: ‘A paper-based synapse could be used to build lightweight and biologically friendly artificial neural networks, and, at the same time, with the advantages of flexibility and biocompatibility, could be used to create the perfect organism–machine interface for many biological applications.’

Meditation helps pinpoint neurological differences between two types of love

These findings won’t appear on any Hallmark card, but romantic love tends to activate the same reward areas of the brain as cocaine, research has shown.

Now Yale School of Medicine researchers studying meditators have found that a more selfless variety of love — a deep and genuine wish for the happiness of others without expectation of reward — actually turns off the same reward areas that light up when lovers see each other.

“When we truly, selflessly wish for the well-being of others, we’re not getting that same rush of excitement that comes with, say, a tweet from our romantic love interest, because it’s not about us at all,” said Judson Brewer, adjunct professor of psychiatry at Yale now at the University of Massachusetts.

Brewer and Kathleen Garrison, postdoctoral researcher in Yale’s Department of Psychiatry, report their findings in a paper scheduled to be published online Feb. 12 in the journal Brain and Behavior.

The neurological boundaries between these two types of love become clear in fMRI scans of experienced meditators. The reward centers of the brain that are strongly activated by a lover’s face (or a picture of cocaine) are almost completely turned off when a meditator is instructed to silently repeat sayings such as “May all beings be happy.”

Such mindfulness meditations are a staple of Buddhism and are now commonly practiced in Western stress reduction programs, Brewer notes. The tranquility of this selfless love for others — exemplified in such religious figures such as Mother Theresa or the Dalai Llama — is diametrically opposed to the anxiety caused by a lovers’ quarrel or extended separation. And it carries its own rewards.

“The intent of this practice is to specifically foster selfless love — just putting it out there and not looking for or wanting anything in return,” Brewer said. “If you’re wondering where the reward is in being selfless, just reflect on how it feels when you see people out there helping others, or even when you hold the door for somebody the next time you are at Starbucks.”

What Makes Memories Last?

Prions can be notoriously destructive, spurring proteins to misfold and interfere with cellular function as they spread without control. New research, published in the open access journal PLOS Biology on February 11, 2014, from scientists at the Stowers Institute for Medical Research reveals that certain prion-like proteins, however, can be precisely controlled so that they are generated only in a specific time and place. These prion-like proteins are not involved in disease processes; rather, they are essential for creating and maintaining long-term memories.

“This protein is not toxic; it’s important for memory to persist,” says Stowers researcher Kausik Si, Ph.D., who led the study. To ensure that long-lasting memories are created only in the appropriate neural circuits, Si explains, the protein must be tightly regulated so that it adopts its prion-like form only in response to specific stimuli. He and his colleagues report on the biochemical changes that make that precision possible.

Si’s lab is focused on finding the molecular alterations that encode a memory in specific neurons as it endures for the days, months, or years—even as the cells’ proteins are degraded and renewed. Increasingly, their research is pointing toward prion-like proteins as critical regulators of long-term memory.

In 2012, Si’s group demonstrated that prion formation in nerve cells is essential for the persistence of long-term memory in fruit flies. Prions are a fitting candidate for this job because their conversion is self-sustaining: once a prion-forming protein has shifted into its prion shape, additional proteins continue to convert without any additional stimulus.

Si’s team found that in fruit flies, the prion-forming protein Orb2 is necessary for memories to persist. Flies that produce a mutated version of Orb2 that is unable to form prions learn new behaviors, but their memories are short-lived. “Beyond a day, the memories become unstable. By three days, the memory has completely disappeared,” Si explains.

In the new study, Si wanted to find out how this process could be controlled so that memories form at the right time. “We know that all experiences do not form long-term memory—somehow the nervous system has a way to discriminate. So if prion-formation is the biochemical basis of memory, it must be regulated.” Si says. “But prion formation appears to be random for all the cases we know of so far.”

Si and his colleagues knew that Orb2 existed in two forms—Orb2A and Orb2B. Orb2B is widespread throughout the fruit fly’s nervous system, but Orb2A appears only in a few neurons, at extremely low concentrations. What’s more, once it is produced, Orb2A quickly falls apart; the protein has a half-life of only about an hour.

“When Orb2A binds to the more abundant form, it triggers conversion to the prion state, acting as a seed for the conversion. Once conversion begins, it is a self-sustaining process; additional Orb2 continues to convert to the prion state, with or without Orb2A. By altering the abundance of the Orb2A seed”, Si says, “cells might regulate where, when, and how the conversion process is engaged”. But how do nerve cells control the abundance of the Orb2A seed?

Their experiments revealed that when a protein called TOB associates with Orb2A , it becomes much more stable, with a new half-life of 24 hours. This step increases the prevalence of the prion-like state and explains how Orb2’s conversion to the prion state can be confined in both time and space.

The findings raise a host of new questions for Si, who now wants to understand what happens when Orb2 enters its prion-like state, as well as where in the brain the process occurs. While unraveling these mechanisms will likely be more accessible in the fruit fly than in more complex organisms, Si points out that proteins related to Orb2 and TOB have also been found in the brains of mice and humans. He has already shown that in the sea snail Aplysia, conversion to a prion-like state facilitates long-term change in synaptic strength. “This basic mechanism appears to be conserved across species,” he notes.

MIT robot may accelerate trials for stroke medications

The development of drugs to treat acute stroke or aid in stroke recovery is a multibillion-dollar endeavor that only rarely pays off in the form of government-approved pharmaceuticals. Drug companies spend years testing safety and dosage in the clinic, only to find in Phase III clinical efficacy trials that target compounds have little to no benefit. The lengthy process is inefficient, costly, and discouraging, says Hermano Igo Krebs, a principal research scientist in MIT’s Department of Mechanical Engineering.

“Most drug studies failed and some companies are getting discouraged,” Krebs says. “Many have recently abandoned the neuro area [because] they have spent so much money on developing drugs that don’t work. They end up focusing somewhere else.”

Now a robot developed by Krebs and his colleagues may help speed up drug development, letting pharmaceutical companies know much earlier in the process whether a drug will ultimately work in stroke patients.

To receive approval from the Food and Drug Administration, a company typically has to enroll 800 patients to demonstrate that a drug is effective during a Phase III clinical trial; this sample size is determined, in part, by the accuracy of standard outcome measurements, which quantify a patient’s ability over time to, say, lift her arm past a certain point. A clinical trial can take several years to enroll appropriate patients, run tests, and perform analyses.

The study’s authors found that by using a robot’s measurements to gauge patient performance, companies might only have to test 240 patients to determine whether a drug works — a reduction of 70 percent that Krebs says would translate to a similar reduction in time and cost.

While pharmaceutical companies would still have to adhere to the FDA’s established guidelines and outcome measurements to receive final drug approval, Krebs says they could use the robot measurements to guide early decisions on whether to further pursue or abandon a certain drug. If, after 240 patients, a drug has no measurable effect, the company can pursue other therapeutic avenues. If, however, a drug improves performance in 240 robot-measured patients, the pharmaceutical company can continue investing in the trial with confidence that the drug will ultimately pass muster.

The researchers have published their results in the journal Stroke.

Creating a translator for stroke recovery

In their study, Krebs and his colleagues explored the robot MIT-Manus as a tool for evaluating patient improvement over time. The robot, developed by the team at MIT’s Newman Laboratory for Biomechanics and Human Rehabilitation, has mainly been used as a rehabilitation tool: Patients play a video game by maneuvering the robot’s arm, with the robot assisting as needed.

While the robot has mainly been used as a form of physical therapy, Krebs says it can also be employed as a measurement tool. As a patient moves the robot’s arm, the robot collects motion data, including the patient’s arm speed, movement smoothness, and aim. For the current study, the researchers collected such data from 208 patients who worked with the robot seven days after suffering a stroke, and continued to do so for three months.

The researchers created an artificial neural network map that relates a patient’s motion data to a score that correlates with a standard clinical outcome measurement.

The authors then selected a separate group of nearly 3,000 stroke patients who did not use the robot, but who went through standard clinical tests. In particular, the researchers calculated the “effect size” — the difference in patient performance from the beginning to the end of a trial, divided by the standard deviation, or variability, of improvement among these patients. To determine whether a drug works, the FDA will often look to a study’s effect size.

Using the robot-derived neural network map, the group calculated the effect size at twice the rate usually achieved with standard clinical outcome measurements, indicating that the robot scale demonstrated greater sensitivity in measuring patient recovery.

The study’s authors went one step further and performed a power analysis that determines the optimal sample size for a given technique, finding that the robot scale would require only 240 patients to determine a drug’s effectiveness — a reduction in sample size that would save a company up to 70 percent in time and cost.

“Such a savings would be fantastic,” says David Reinkensmeyer, a professor of physical medicine and rehabilitation at the University of California at Irvine. “Robotic measurements will help us identify promising treatments with smaller numbers of patients and provide better insight into the mechanisms of the treatments, so that we can target those mechanisms and improve the treatments.”

Currently, only a few stroke drugs are in the late stages of development. However, once a company reaches a Phase III clinical trial, Krebs says it may use the MIT-Manus robot as a more efficient way to evaluate the drug’s impact by employing the measurement techniques on a smaller group of patients.

How our brain networks: Research reveals white matter ‘scaffold’ of human brain

For the first time, neuroscientists have systematically identified the white matter “scaffold” of the human brain, the critical communications network that supports brain function.

Their work, published Feb. 11 in the open-source journal Frontiers in Human Neuroscience, has major implications for understanding brain injury and disease. By detailing the connections that have the greatest influence over all other connections, the researchers offer not only a landmark first map of core white matter pathways, but also show which connections may be most vulnerable to damage.

"We coined the term white matter ‘scaffold’ because this network defines the information architecture which supports brain function," said senior author John Darrell Van Horn of the USC Institute for Neuroimaging and Informatics and the Laboratory of Neuro Imaging at USC.

"While all connections in the brain have their importance, there are particular links which are the major players," Van Horn said.

Using MRI data from a large sample of 110 individuals, lead author Andrei Irimia, also of the USC Institute for Neuroimaging and Informatics, and Van Horn systematically simulated the effects of damaging each white matter pathway.

They found that the most important areas of white and gray matter don’t always overlap. Gray matter is the outermost portion of the brain containing the neurons where information is processed and stored. Past research has identified the areas of gray matter that are disproportionately affected by injury.

But the current study shows that the most vulnerable white matter pathways – the core “scaffolding” – are not necessarily just the connections among the most vulnerable areas of gray matter, helping explain why seemingly small brain injuries may have such devastating effects.

"Sometimes people experience a head injury which seems severe but from which they are able to recover. On the other hand, some people have a seemingly small injury which has very serious clinical effects," says Van Horn, associate professor of neurology at the Keck School of Medicine of USC. "This research helps us to better address clinical challenges such as traumatic brain injury and to determine what makes certain white matter pathways particularly vulnerable and important."

The researchers compare their brain imaging analysis to models used for understanding social networks. To get a sense of how the brain works, Irimia and Van Horn did not focus only on the most prominent gray matter nodes – which are akin to the individuals within a social network. Nor did they merely look at how connected those nodes are.

Rather, they also examined the strength of these white matter connections, i.e. which connections seemed to be particularly sensitive or to cause the greatest repercussions across the network when removed. Those connections which created the greatest changes form the network “scaffold.”

"Just as when you remove the internet connection to your computer you won’t get your email anymore, there are white matter pathways which result in large scale communication failures in the brain when damaged," Van Horn said.

When white matter pathways are damaged, brain areas served by those connections may wither or have their functions taken over by other brain regions, the researchers explain. Irimia and Van Horn’s research on core white matter connections is part of a worldwide scientific effort to map the 100 billion neurons and 1,000 trillion connections in the living human brain, led by the Human Connectome Project and the Laboratory of Neuro Imaging at USC.

Irimia notes that, “these new findings on the brain’s network scaffold help inform clinicians about the neurological impacts of brain diseases such as multiple sclerosis, Alzheimer’s disease, as well as major brain injury. Sports organizations, the military and the US government have considerable interest in understanding brain disorders, and our work contributes to that of other scientists in this exciting era for brain research.”