The development of an artificial placenta – used successfully in premature lambs – could revolutionize the treatment of extreme prematurity.
Researchers at the University of Michigan are working to improve survival rates in the tiniest, most premature babies in a ground-breaking way: through an artificial placenta that mimics the womb.
The technology hasn’t reached a clinical trial, but researchers from U-M’s C.S. Mott Children’s Hospital and Extracorporeal Circulation Research Laboratory are making dramatic progress. An extracorporeal artificial placenta at the institution has kept five extremely premature lambs alive for a week. The lambs were transferred to the artificial placenta, which utilizes extracorporeal membrane oxygenation (ECMO), without ever taking their first breath.
The ultimate goal of nearly a decade of sustained work would be for an artificial placenta to help extremely premature babies with the greatest risks of disability or death continue critical organ development outside of their mother’s womb.
Despite significant advances in the treatment of prematurity, the risk of death and long-term disability remains high for extremely premature infants (born before 24 weeks). Their bodies simply are not prepared for life outside the womb.
‘One of the gravest risks for extremely premature babies is undeveloped lungs that are too fragile to handle even the gentlest ventilation techniques,’ says George Mychaliska, M.D., the principal investigator and the director of U-M’s Fetal Diagnosis and Treatment Center. ‘If a baby’s lungs are severely immature, they cannot provide the brain, heart and other organs the oxygen they need to survive.’
Mychaliska, who has been referred to as Michigan’s ‘fetus fixer’ for his renowned fetal intervention work, has been leading research to improve outcomes for premature infants.
‘We thought, Why don’t we solve the problem of prematurity by re-creating the intrauterine environment?” he says. ‘Maybe we should treat this tiny baby like a fetus. Maybe we should treat these babies as if they are still in the womb. This is a complete paradigm shift. Our research is still in a very preliminary stage, but we’ve passed a significant milestone that gives us promise of revolutionizing the treatment of prematurity.
‘Although many of our current therapies are lifesaving, they are not designed for premature babies and are often ineffective or contribute to complications,’ he adds.
The innovative artificial placenta simulates the intrauterine environment and provides gas exchange without mechanical ventilation. By recapitulating normal fetal physiology to re-create the intrauterine environment, the artificial placenta holds the promise of normal growth and development outside the womb for extremely premature infants until they are ready for postnatal life.
The success of keeping lambs alive through this technique was a crucial milestone in securing a $2.7 million ( Euro 2.4 million) R01 National Institutes of Health grant to accelerate this research.
Over the next five years, researchers expect to demonstrate that an artificial placenta can simulate the intrauterine environment and support a foetal lamb from extreme prematurity to normal newborn physiology. The next step would be to determine if the milestones would justify preliminary clinical trials in extremely premature babies.

University of Michigan http://tinyurl.com/zzhz9o3

Machine learning is a type of artificial intelligence that allows computer programs to learn when exposed to new data without being programmed. Now, researchers in The Netherlands have coupled machine learning methods with a special MRI technique that measures the perfusion, or tissue absorption rate, of blood throughout the brain to detect early forms of dementia, such as mild cognitive impairment (MCI), Radiology.
‘MRI can help with the diagnosis of Alzheimer’s disease,’ said principal investigator Alle Meije Wink, Ph.D., from the VU University Medical Centre in Amsterdam. ‘However, the early diagnosis of Alzheimer’s disease is problematic.’

Scientists have long known that Alzheimer’s disease is a gradual process and that the brain undergoes functional changes before the structural changes associated with the disease show up on imaging results. Physicians have no definitive way of identifying who has early dementia or which cases of mild cognitive impairment will progress to Alzheimer’s disease.

‘With standard diagnostic MRI, we can see advanced Alzheimer’s disease, such as atrophy of the hippocampus,’ Dr. Meije Wink said. ‘But at that point, the brain tissue is gone and there’s no way to restore it. It would be helpful to detect and diagnose the disease before it’s too late.’

For the new study, the researchers applied machine learning methods to special type of MRI called arterial spin labelling (ASL) imaging. ASL MRI is used to create images called perfusion maps, which show how much blood is delivered to various regions of the brain.

The automated machine learning program is taught to recognize patterns in these maps to distinguish among patients with varying levels of cognitive impairment and predict the stage of Alzheimer’s disease in new (unseen) cases.
The study included 260 of 311 participants from the Alzheimer Center of the VU University Medical Center dementia cohort who underwent ASL MRI between October 2010 and November 2012.

The study group included 100 patients diagnosed with probable Alzheimer’s disease, 60 patients with mild cognitive impairment (MCI) and 100 patients with subjective cognitive decline (SCD), and 26 healthy controls.
SCD and MCI are considered to be early stages of the dementia process and are diagnosed based on the severity of cognitive symptoms, including memory loss and thought- and decision-making problems.

The automated system was able to distinguish effectively among participants with Alzheimer’s disease, MCI and SCD. Using classifiers based on the automated machine learning training, the researchers were then able to predict the Alzheimer’s diagnosis or progression of single patients with a high degree of accuracy, ranging from 82 percent to 90 percent.
‘ASL is a promising alternative functional biomarker for the early diagnosis of Alzheimer’s disease,’ Dr. Meije Wink said.

Radiological Society of North Americawww2.rsna.org/timssnet/media/pressreleases/14_pr_target.cfm?ID=1890

Aerobic exercise can significantly help people coping with the long-term mental health condition schizophrenia, according to a new study from University of Manchester researchers.

Through combining data from 10 independent clinical trials with a total of 385 patients with schizophrenia, Joseph Firth found that around 12 weeks of aerobic exercise training can significant improve patients’ brain functioning.

The study was by Firth, Dr Brendon Stubbs and Professor Alison Yung.

Schizophrenia’s acute phase is typified by hallucinations and delusions, which are usually treatable with medication.

However, most patients are still troubled with pervasive cognitive deficits’; including poor memory, impaired information processing and loss of concentration.

The research showed that patients who are treated with aerobic exercise programs, such as treadmills and exercise bikes, in combination with their medication, will improve their overall brain functioning more than those treated with medications alone.
The areas which were most improved by exercising were patients’ ability to understand social situations, their attention spans, and their working memory’ – or how much information they can hold in mind at one time.

There was also evidence among the studies that programs which used greater amounts of exercise, and those which were most successful for improving fitness, had the greatest effects on cognitive functioning.

Joe Firth said: ‘Cognitive deficits are one aspect of schizophrenia which is particularly problematic.

‘They hinder recovery and impact negatively upon people’s ability to function in work and social situations. Furthermore, current medications for schizophrenia do not treat the cognitive deficits of the disorder.

‘We are searching for new ways to treat these aspects of the illness, and now research is increasingly suggesting that physical exercise can provide a solution.’

He added: ‘These findings present the first large-scale evidence supporting the use of physical exercise to treat the neurocognitive deficits associated with schizophrenia.

‘Using exercise from the earliest stages of the illness could reduce the likelihood of long-term disability, and facilitate full, functional recovery for patients.’

University of Manchester www.manchester.ac.uk/discover/news/exercise-can-tackle-symptoms-of-schizophrenia/

Sooner is always better when it comes to diagnosing an illness and this is especially true when it comes to lung disease in premature infants, since it can have an impact on a child’s health in the long-term. Researchers at Baylor College of Medicine who focus on bronchopulmonary dysplasia and pulmonary hypertension, a common lung disease in premature infants, have shown that echocardiography can be used to detect the pulmonary hypertension in neonatal mice at an earlier time point than previously thought.
Bronchopulmonary dysplasia is caused by many factors, including inflammation, infection and oxidative stress. Dr. Binoy Shivanna, assistant professor of pediatrics – neonatology at Baylor and Texas Children’s Hospital, and colleagues focus on the oxidative stress and inflammation aspects of the disease, which can damage various parts of the cell and interrupt the development of the lungs. This can lead to problems such as pulmonary hypertension which increases the mortality and long-term problems in infants.
Progress developing improved treatments for the disease has been limited in part by the lack of advanced imaging techniques to detect pulmonary hypertension and lung damage at earlier time points in animal models, which is important to test these potential new treatments. This model could also help researchers better understand how pulmonary hypertension develops, which is an important aspect of Shivanna’s research. So the team set out to develop a mouse model of the disease that replicates many of the features observed in infants with the condition.
To induce oxidative stress and inflammation – two contributing factors of the development of the disease – the researchers exposed a group of newborn mice to 70 percent of oxygen or hyperoxia for 14 days, while a control group received 21 percent oxygen or regular air.
The mice exposed to hyperoxia developed lung oxidative stress, inflammation and lungs that resembled those typical of bronchopulmonary dysplasia and pulmonary hypertension in infants. Furthermore, echocardiography tests performed in the young mice showed that the animals had also developed pulmonary hypertension.
‘It’s important to understand not only the pathology, but also the functional aspect of pulmonary hypertension,’ said Shivanna. ‘This is where the echocardiography test, a non-invasive test that uses high frequency sound waves to take pictures of the heart, comes in.’
Currently, echocardiography tests have been performed in mice at four weeks of age, which might be too late to intervene. Using the latest advances in research technology, Shivanna and colleagues were able to demonstrate that it is possible to functionally detect pulmonary hypertension at an earlier time point, meaning that interventions could potentially take place sooner.
This mouse model can help researchers develop early interventions to prevent or decrease the severity of some of the later onset diseases, such as chronic obstructive pulmonary disease.

Baylor College of Medicine http://tinyurl.com/h3su3ph

Watching millions of neurons in the brain interacting with each other is the ultimate dream of neuroscientists! A new imaging method now makes it possible to observe the activation of large neural circuits, currently up to the size of a small-animal brain, in real time and three dimensions. Researchers at the Helmholtz Zentrum Munchen and the Technical University of Munich have recently reported on their new findings.
Nowadays it is well recognized that most brain functions may not be comprehended through inspection of single neurons. To advance meaningfully, neuroscientists need the ability to monitor the activity of millions of neurons, both individually and collectively. However, such observations were so far not possible due to the limited penetration depth of optical microscopy techniques into a living brain.
A team headed by Prof. Dr. Daniel Razansky, a group leader at the Institute of Biological and Molecular Imaging (IBMI), Helmholtz Zentrum Munchen, and Professor of Molecular Imaging Engineering at the Technical University of Munich, has now found a way to address this challenge. The new method is based on the so-called optoacoustics, which allows non-invasive interrogation of living tissues at centimetre scale depths.
‘We discovered that optoacoustics can be made sensitive to the differences in calcium ion concentrations resulting from neural activity and devised a rapid functional optoacoustic neuro-tomography (FONT) system that can simultaneously record signals from a very large number of neurons’, said Dr. Xose Luis Dean-Ben, first author of the study. Experiments performed by the scientists in brains of adult zebrafish (Danio rerio) expressing genetically encoded calcium indicator GCaMP5G demonstrated, for the first time, the fundamental ability to directly track neural dynamics using optoacoustics while overcoming the longstanding penetration barrier of optical imaging in opaque brains. The technique was also able to trace neural activity during unrestrained motion of the animals.
‘So far we demonstrated real-time analysis on whole brains of adult animals with roughly 2x3x4 millimetre dimensions (approximately 24 mm3),’ says the study’s leader Razansky. State-of-the-art optical microscopy methods are currently limited to volumes well below a cubic millimetre when it comes to imaging of fast neural activity, according to the researchers. In addition, their FONT method is already capable of visualizing volumes of more than 1000 cubic millimetres with temporal resolution of 10 milliseconds.
Large-scale observation of neural activity is the key to understanding how the brain works, both under normal and diseased conditions. ‘Thanks to our method, one can now capture fast activity of millions of neurons simultaneously. Parallel neural networks with the social media: in the past, we were able to read along when someone (in this case, a nerve cell) placed a message with a neighbour. Now we can also see how this message spreads like wildfire,’ explains Razansky. ‘This new imaging tool is expected not only to significantly promote our knowledge on brain function and its pathophysiology but also accelerate development of novel therapies targeting neurological and neuropsychiatric disorders,’ he concludes.

Technical University of Munich http://tinyurl.com/goxtrm5