Archive for the ‘Uncategorized’ Category


S. roeselii is shown here contracting down to where it’s holding onto a surface.

By Yasemin Saplakoglu

Tiny, brainless blobs might be able to make decisions: A single-celled organism can “change its mind” to avoid going near an irritating substance, according to new findings.

Over a century ago, American zoologist Herbert Spencer Jennings conducted an experiment on a relatively large, trumpet-shaped, single-celled organism called Stentor roeselii. When Jennings released an irritating carmine powder around the organisms, he observed that they responded in a predictable pattern, he wrote in his findings, which he published in a text called “Behavior of the Lower Organisms” in 1906.

To avoid the powder, the organism first would try to bend its body around the powder. If that didn’t work, the blob would reverse the movement of its cilia — hairlike projections that help it move and feed — to push away the surrounding particles. If that still didn’t work, the organism would contract around its point of attachment on a surface to feed. And finally, if all else failed, it would detach from the surface and swim away.

In the decades that followed, however, other experiments failed to replicate these findings, and so they were discredited. But recently, a group of researchers at Harvard University decided to re-create the old experiment as a side project. “It was a completely off-the-books, skunkworks project,” senior author Jeremy Gunawardena, a systems biologist at Harvard, said in a statement. “It wasn’t anyone’s day job.”

After a long search, the researchers found a supplier in England who had collected S. roeselii specimens from a golf course pond and had them shipped over to Gunawardena’s lab. The team used a microscope to observe and record the behavior of the organisms when the scientists released an irritant nearby.

First, they tried releasing carmine powder, the 21st century organisms weren’t irritated like their ancestors were. “Carmine is a natural product of the cochineal beetle, so its composition may have changed since [Jennings’] day,” the researchers wrote in the study. So they tried another irritant: microscopic plastic beads.

Sure enough, the S. roeselii started to avoid the beads, using the behaviors that Jennings described. At first, the behaviors didn’t seem to be in any particular order. For example, some organisms would bend first, then contract, while others would only contract. But when the scientists did a statistical analysis, they found that there was indeed, on average, a similar order to the organisms’ decision-making process: The single-celled blobs almost always chose to bend and alter the direction of their cilia before they contracted or detached and swam away, according to the statement.

What’s more, the researchers found that, if the organism did reach the stage of needing to contract or detach, there was an equal chance that they would choose one behavior over the other.

“They do the simple things first, but if you keep stimulating, they ‘decide’ to try something else,” Gunawardena said. “S. roeselii has no brain, but there seems to be some mechanism that, in effect, lets it ‘change its mind’ once it feels like the irritation has gone on too long.”

The findings can help inform cancer research and even change the way we think about our own cells. Rather than being solely “programmed” to do something by our genes, “cells exist in a very complex ecosystem, and they are, in a way, talking and negotiating with each other, responding to signals and making decisions,” Gunawardena said. Single-celled organisms, whose ancestors once ruled the ancient world, might be “much more sophisticated than we generally give them credit for,” he said.

The findings were published Dec. 5 in the journal Current Biology.

https://www.livescience.com/single-celled-organisms-decisions.html?utm_source=notification


Neurons in the brain. Rather than implanting directly into the brain, the bionic neurons are built into ultra-low power microchips that form the basis for devices that would plug straight into the nervous system.

Scientists have created artificial neurons that could potentially be implanted into patients to overcome paralysis, restore failing brain circuits, and even connect their minds to machines.

The bionic neurons can receive electrical signals from healthy nerve cells, and process them in a natural way, before sending fresh signals on to other neurons, or to muscles and organs elsewhere in the body.

One of the first applications may be a treatment for a form of heart failure that develops when a particular neural circuit at the base of the brain deteriorates through age or disease and fails to send the right signals to make the heart pump properly.

Rather than implanting directly into the brain, the artificial neurons are built into ultra-low power microchips a few millimetres wide. The chips form the basis for devices that would plug straight into the nervous system, for example by intercepting signals that pass between the brain and leg muscles.

“Any area where you have some degenerative disease, such as Alzheimer’s, or where the neurons stop firing properly because of age, disease, or injury, then in theory you could replace the faulty biocircuit with a synthetic circuit,” said Alain Nogaret, a physicist who led the project at the University of Bath.

The breakthrough came when researchers found they could model live neurons in a computer program and then recreate their firing patterns in silicon chips with more than 94% accuracy. The program allows the scientists to mimic the full variety of neurons found in the nervous system.

Writing in the journal Nature Communications, the researchers describe how they fed the program with data recorded from two types of rat neuron, which were stimulated in a dish. The neurons were either from the hippocampus, a region that is crucial for memory and learning, or were involved in the subconscious control of breathing.

Armed with the program, the researchers claim they can now build bionic neurons based on any of the real nerve cells found in the brain, spinal cord, or the more distant reaches of the peripheral nervous system, such as the sensory neurons in the skin.

Because the artificial neurons both receive and send signals, they can be used to make implants that respond to neural feedback signals that are constantly coursing around the body.

“The potential is endless in terms of understanding how the brain works, because we now have the fundamental understanding and insight into the functional unit of the brain, and indeed applications, which might be to improve memory, to overcome paralysis and ameliorate disease,” said Julian Paton, a co-author on the study who holds posts at the Universities of Bristol and Auckland.

“They can be used in isolation or connected together to form neuronal networks to perform brain functions,” he added.

With development, trials and regulations to satisfy, it could be many years before the artificial neurons are helping patients. But if they prove safe and effective, they could ultimately be used to circumvent nerve damage in broken spines and help paralysed people regain movement, or to connect people’s brains to robotic limbs that can send touch sensations back through the implant to the brain.

Despite the vast possibilities the artificial neurons open up, Nogaret said the team was nowhere near building a whole brain, an organ which in a human consists of 86bn neurons and at least as many supporting cells. “We are not claiming that we are building a brain, there’s absolutely no way,” he said.

The scientists’ approach differs from that taken by many other peers who hope to recreate brain activity in computers. Rather than focusing on individual neurons, they typically model brain regions or even whole brains, but with far less precision. For example, the million-processor SpiNNaker machine at the University of Manchester can model an entire mouse brain, but not to the level of individual brain cells.

“If you wanted to model a whole mouse brain using the approach in this paper you might end up designing 100 million individual, but very precise, neurons on silicon, which is clearly unfeasible within a reasonable time and budget,” said Stephen Furber, professor of computer engineering at the University of Manchester.

“Because the approach is detailed and laboriously painstaking, it can really only be applied in practice to smallish neural units, such as the respiratory neurons described above, but there are quite a few critical small neural control circuits that are vital to keeping us alive,” he added.

https://www.theguardian.com/science/2019/dec/03/bionic-neurons-could-enable-implants-to-restore-failing-brain-circuits

by David Nield

Scientists researching a key aspect of biochemistry in living creatures have been taking a very close look at the tiny Caenorhabditis elegans roundworm. Their latest results show that when these nematodes get put under more biochemical stress early in their lives, they somehow tend to live longer.

This type of stress, called oxidative stress – an imbalance of oxygen-containing molecules that can result in cellular and tissue damage – seems to better prepare the worms for the strains of later life, along the same lines as the old adage that whatever doesn’t kill you, makes you stronger.

You might think that worm lifespans have no bearing on human life. And surely, until we have loads more research done in this field, it would be a big leap to say the same principles of prolonging one’s lifespan might hold true for human beings.

But there’s good reason to put C. elegans through the paces. This model organism has proven immensely helpful for researchers trying to better understand key biological functions present in worm and human alike – and oxidative stress is one such function.

The little wriggly creatures are known to have significant variations in their lifespan even when the whole population is genetically identical and grows up in the exact same conditions. So the team went looking for other factors that affect C. elegans’ longevity.

“The general idea that early life events have such profound, positive effects later in life is truly fascinating,” says biochemist Ursula Jakob from the University of Michigan.

Jakob and her colleagues sorted thousands of C. elegans larvae based on the oxidative stress levels they experienced during development – this stress arises when cells produce more oxidants and free radicals than they can handle. It’s a normal part of the ageing process, but it’s also triggered by exercise and a limited food supply.

One way to measure this stress is by the levels of reactive oxygen species (ROS) molecules an organism produces – simply put, this measurement indicates the biochemical stress an organism is under. In the case of these roundworms, the more ROS were produced during development, the longer their lifespans turned out to be.

To explain how this effect of ROS might come about, the researchers went looking for changes in the worms’ genetic regulation, specifically those genes that are known to be involved in dealing with oxidative stress.

While doing so, they detected a key difference – the nematodes exposed to more ROS during development appeared to have undergone an epigenetic change (a gene expression switch that can happen due to environmental influences) that increased the oxidative stress resistance of their body’s cells.

There are still a lot of questions to answer, but the researchers think their results identify one of the stochastic – or random – influences on the lifespan of organisms; it’s something that has been hypothesised in the field of the genetics of ageing. And down the line, it may turn out to be relevant for ageing humans, too.

“This study provides a foundation for future work in mammals, in which very early and transient metabolic events in life seem to have equally profound impacts on lifespan,” the researchers conclude.

The study has been published in Nature.

https://www.sciencealert.com/biological-stress-in-early-life-could-be-one-of-the-keys-to-a-long-lifespan?perpetual=yes&limitstart=1


The remains of a Viking ship that was 52 to 56 feet (16 to 17 meters) long were found near a medieval church at Edøy, on the island of Smøla in Norway.

by Owen Jarus

The remains of a Viking ship have been discovered on a farm near a medieval church at Edøy, on the island of Smøla, in Norway.

The ship, which is 52 to 56 feet (16 to 17 meters) long, appears to be part of a burial mound, suggesting that it was used to bury someone important, said its discoverers, archaeologists Manuel Gabler and Dag-Øyvind Engtrø Solem, both with the Norwegian Institute for Cultural Heritage Research (NIKU).

They don’t know if there is a skeleton or multiple skeletons inside the boat.

The archaeologists used high-resolution georadar mounted on a cart to make the discovery. In fact, it was almost by chance they spotted the ship’s outline.

“We had actually finished the agreed-upon area, but we had time to spare and decided to do a quick survey over another field. It turned out to be a good decision,” Manuel Gabler, an archaeologist with NIKU, said in a statement.


The ship was found near this medieval church by archaeologists using georadar mounted on a cart. (Image credit: NIKU)

The ship dates back more than 1,000 years to the time of the Vikings or even a bit earlier, Knut Paasche, head of the Department of Digital Archaeology at NIKU and an expert on Viking ships, said in a statement.

Radar images had enough resolution to make out what was left of the fore and aft, which had been nearly destroyed in the past by farming plows. The hull seems to be in good shape, according to a news report by Ars Technica. The radar also revealed the remains of two houses, likely part of a Viking settlement, but the archaeologists aren’t sure of the structures’ age. Archaeologists and local authorities hope to do a larger survey of the area around the ship burial. It’s not certain when the ship itself will be excavated, although it won’t be done in the near future, said a spokesperson for NIKU.

The survey at Edøy was done as a collaboration between Møre and Romsdal County, Smøla municipality and NIKU. The Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology helped develop the georadar technology used in the survey.

https://www.livescience.com/viking-ship-georadar-norway.html?utm_source=notification

Although it has been revealed in recent years that plants are capable of seeing, hearing and smelling, they are still usually thought of as silent. But now, for the first time, they have been recorded making airborne sounds when stressed, which researchers say could open up a new field of precision agriculture where farmers listen for water-starved crops.

Itzhak Khait and his colleagues at Tel Aviv University in Israel found that tomato and tobacco plants made sounds at frequencies humans cannot hear when stressed by a lack of water or when their stem is cut.

Microphones placed 10 centimetres from the plants picked up sounds in the ultrasonic range of 20 to 100 kilohertz, which the team says insects and some mammals would be capable of hearing and responding to from as far as 5 metres away. A moth may decide against laying eggs on a plant that sounds water-stressed, the researchers suggest. Plants could even hear that other plants are short of water and react accordingly, they speculate.

“These findings can alter the way we think about the plant kingdom, which has been considered to be almost silent until now,” they write in their study, which has not yet been published in a journal.

Previously, devices have been attached to plants to record the vibrations caused by air bubbles forming and exploding – a process known as cavitation – inside xylem tubes, which are used for water transport. But this new study is the first time that sounds from plants have been measured at a distance.

On average, drought-stressed tomato plants made 35 sounds an hour, while tobacco plants made 11. When plant stems were cut, tomato plants made an average of 25 sounds in the following hour, and tobacco plants 15. Unstressed plants produced fewer than one sound per hour, on average.

It is even possible to distinguish between the sounds to know what the stress is. The researchers trained a machine-learning model to discriminate between the plants’ sounds and the wind, rain and other noises of the greenhouse, correctly identifying in most cases whether the stress was caused by dryness or a cut, based on the sound’s intensity and frequency. Water-hungry tobacco appears to make louder sounds than cut tobacco, for example.

Although Khait and his colleagues only looked at tomato and tobacco plants, they believe other plants may make sounds when stressed too. In a preliminary study, they also recorded ultrasonic sounds from a spiny pincushion cactus (Mammillaria spinosissima) and the weed henbit dead-nettle (Lamium amplexicaule). Cavitation is a possible explanation for how the plants generate the sounds, they say.

Enabling farmers to listen for water-stressed plants could “open a new direction in the field of precision agriculture”, the researchers suggest. They add that such an ability will be increasingly important as climate change exposes more areas to drought.

“The suggestion that the sounds that drought-stressed plants make could be used in precision agriculture seems feasible if it is not too costly to set up the recording in a field situation,” says Anne Visscher at the Royal Botanic Gardens, Kew, in the UK.

She warns that the results can’t yet be broadened out to other stresses, such as salt or temperature, because these may not lead to sounds. In addition, there have been no experiments to show whether moths or any other animal can hear and respond to the sounds the plants make, so that idea remains speculative for now, she says.

If plants are making sounds when stressed, cavitation is the most likely mechanism, says Edward Farmer at the University of Lausanne, Switzerland. But he is sceptical of the findings, and would like to see more in the way of controls, such as the sounds of drying soil without plants in it.

Farmer adds that the idea moths might be listening to plants and shunning stressed ones is a “little too speculative”, and there are already plenty of explanations for why insects avoid some plants and not others.

Reference: bioRxiv, DOI: 10.1101/507590

Read more: https://www.newscientist.com/article/2226093-recordings-reveal-that-plants-make-ultrasonic-squeals-when-stressed/#ixzz67G8PmFZm

by CHRISTIAN COTRONEO

Peeling a banana doesn’t require the nimblest of fingers. It’s basically Nature’s version of a twist-off bottle cap. Anyone with any kind of digits can get to the tasty slip of sweetness inside. But what if even that was too much of a bother? Why not just chomp right through the skin and be done with it?

Well, some experts suggest you can do just that. As Australian dietitian Susie Burrell notes on her blog, eating the whole banana may go a long towards reducing food waste and upping your nutritional intake.

“You will increase your overall fibre content by at least 10 percent as a lot of dietary fibre can be found in the skin of the banana,” she writes. “You will get almost 20 percent more Vitamin B6 and almost 20 percent more Vitamin C and you will boost both your potassium and magnesium intake.”

But the real question is, would you like to bite into a whole banana? Or does the idea of eating a banana peel sound more like an insult you might sling at someone? Maybe you’re face is all puckered up right now at the very thought of it.

There’s an important caveat. Burrell, mercifully, doesn’t advise hunkering down on the whole banana. Instead, you’re going to want to remove that skin and cook it on its own — breaking down the tough cellular walls and making those nutrients more readily absorb-able (and the whole affair, perhaps a little less gag-able.)

Burrell is hardly alone in endorsing whole-banana consumption. As the site Treehugger points out, Americans devour 12 billion bananas per year. That’s 12 billion banana peels needless discarded — and maybe even 12 billion opportunities someone will slip and have a terrible accident.

It also represents a lot of nutrients and other potential benefits being chucked to the curb. According to a study published in the Journal of Immunology Research by scientists at Seoul National University, a typical yellow peel packs substantial amounts of potassium, dietary fiber, polyunsaturated fats and essential amino acids.

Those nutrients do a lot of good for a body — particularly all that potassium, which can regulate blood pressure and keep hearts and kidneys healthy.

Sure, there’s plenty of potassium already in nature’s sweetest candy — about 422 milligrams in the average serving. But with an added 78 milligrams of the stuff — along with so many other nutrients — why not eat the wrapper too?

Well, aside from a banana peel needing a little preparation to be fully digestible, there are also those agricultural ne’er-do-wells known as pesticides. The outer layers of fruits and vegetables tend to stockpile somewhat worrisome levels of pesticide residue, although federal bodies like the United States Department of Agriculture (USDA) and the Food and Drug Administration (FDA) were established to keep undue amounts of pesticides out of the food chain.

Still, as with just about anything you aim to put in your mouth, a banana peel needs careful washing. That’s likely to minimize any potential pesticide menace. Even better, if you’re going to try eating the skin, consider picking up the organic variety at your local farmers market.

https://www.mnn.com/food/healthy-eating/stories/can-you-eat-banana-peel-skin?utm_source=Weekly+Newsletter&utm_campaign=e194c0c1a7-RSS_EMAIL_CAMPAIGN_WED1204_2019&utm_medium=email&utm_term=0_fcbff2e256-e194c0c1a7-40844241


Case Western Reserve researchers use AI with routine CT scans to predict how well lung cancer patients will respond to expensive treatment based off changes in texture patterns inside and outside the tumor.

Scientists from the Case Western Reserve University digital imaging lab, already pioneering the use of artificial intelligence (AI) to predict whether chemotherapy will be successful, can now determine which lung-cancer patients will benefit from expensive immunotherapy.

And, once again, they’re doing it by teaching a computer to find previously unseen changes in patterns in CT scans taken when the lung cancer is first diagnosed compared to scans taken after the first two to three cycles of immunotherapy treatment. And, as with previous work, those changes have been discovered both inside—and outside—the tumor, a signature of the lab’s recent research.

“This is no flash in the pan—this research really seems to be reflecting something about the very biology of the disease, about which is the more aggressive phenotype, and that’s information oncologists do not currently have,” said Anant Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) has become a global leader in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI.

Currently, only about 20% of all cancer patients will actually benefit from immunotherapy, a treatment that differs from chemotherapy in that it uses drugs to help your immune system fight cancer, while chemotherapy uses drugs to directly kill cancer cells, according to the National Cancer Institute.

Madabhushi said the recent work by his lab would help oncologists know which patients would actually benefit from the therapy, and who would not.

“Even though immunotherapy has changed the entire ecosystem of cancer, it also remains extremely expensive—about $200,000 per patient, per year,” Madabhushi said. “That’s part of the financial toxicity that comes along with cancer and results in about 42% of all new diagnosed cancer patients losing their life savings within a year of diagnosis.”

Having a tool based on the research being done now by his lab would go a long way toward “doing a better job of matching up which patients will respond to immunotherapy instead of throwing $800,000 down the drain,” he added, referencing the four patients out of five who will not benefit, multiplied by annual estimated cost.

Case Western Reserve researchers use AI with routine CT scans to predict how well lung cancer patients will respond to expensive treatment based off changes in texture patterns inside and outside the tumor
Scientists from the Case Western Reserve University digital imaging lab, already pioneering the use of artificial intelligence (AI) to predict whether chemotherapy will be successful, can now determine which lung-cancer patients will benefit from expensive immunotherapy.

And, once again, they’re doing it by teaching a computer to find previously unseen changes in patterns in CT scans taken when the lung cancer is first diagnosed compared to scans taken after the first two to three cycles of immunotherapy treatment. And, as with previous work, those changes have been discovered both inside—and outside—the tumor, a signature of the lab’s recent research.

“This is no flash in the pan—this research really seems to be reflecting something about the very biology of the disease, about which is the more aggressive phenotype, and that’s information oncologists do not currently have,” said Anant Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) has become a global leader in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI.

Currently, only about 20% of all cancer patients will actually benefit from immunotherapy, a treatment that differs from chemotherapy in that it uses drugs to help your immune system fight cancer, while chemotherapy uses drugs to directly kill cancer cells, according to the National Cancer Institute.

Madabhushi said the recent work by his lab would help oncologists know which patients would actually benefit from the therapy, and who would not.

“Even though immunotherapy has changed the entire ecosystem of cancer, it also remains extremely expensive—about $200,000 per patient, per year,” Madabhushi said. “That’s part of the financial toxicity that comes along with cancer and results in about 42% of all new diagnosed cancer patients losing their life savings within a year of diagnosis.”

Having a tool based on the research being done now by his lab would go a long way toward “doing a better job of matching up which patients will respond to immunotherapy instead of throwing $800,000 down the drain,” he added, referencing the four patients out of five who will not benefit, multiplied by annual estimated cost.

New research published
The figure above shows differences in CT radiomic patterns before and after initiation of checkpoint inhibitor therapy.

The new research, led by co-authors Mohammadhadi Khorrami and Prateek Prasanna, along with Madabhushi and 10 other collaborators from six different institutions was published in November in the journal Cancer Immunology Research.

Khorrami, a graduate student working at the CCIPD, said one of the more significant advances in the research was the ability of the computer program to note the changes in texture, volume and shape of a given lesion, not just its size.

“This is important because when a doctor decides based on CT images alone whether a patient has responded to therapy, it is often based on the size of the lesion,” Khorrami said. “We have found that textural change is a better predictor of whether the therapy is working.

“Sometimes, for example, the nodule may appear larger after therapy because of another reason, say a broken vessel inside the tumor—but the therapy is actually working. Now, we have a way of knowing that.”

Prasanna, a postdoctoral research associate in Madabhushi’s lab, said the study also showed that the results were consistent across scans of patients treated at two different sites and with three different types of immunotherapy agents.

“This is a demonstration of the fundamental value of the program, that our machine-learning model could predict response in patients treated with different immune checkpoint inhibitors,” he said. “We are dealing with a fundamental biological principal.”

Prasanna said the initial study used CT scans from 50 patients to train the computer and create a mathematical algorithm to identify the changes in the lesion. He said the next step will be to test the program on cases obtained from other sites and across different immunotherapy agents. This research recently won an ASCO 2019 Conquer Cancer Foundation Merit Award.

Additionally, Madabhushi said, researchers were able show that the patterns on the CT scans which were most associated with a positive response to treatment and with overall patient survival were also later found to be closely associated with the arrangement of immune cells on the original diagnostic biopsies of those patients.

This suggests that those CT scans actually appear to capturing the immune response elicited by the tumors against the invasion of the cancer—and that the ones with the strongest immune response were showing the most significant textural change and most importantly, would best respond to the immunotherapy, he said.

Madabhushi established the CCIPD at Case Western Reserve in 2012. The lab now includes nearly 60 researchers.

Some of the lab’s most recent work, in collaboration with New York University and Yale University, has used AI to predict which lung cancer patients would benefit from adjuvant chemotherapy based on tissue-slide images. That advancement was named by Prevention Magazine as one of the top 10 medical breakthroughs of 2018.

Other authors on the paper were: Germán Corredor, Mehdi Alilou and Kaustav Bera from biomedical engineering, Case Western Reserve University; Pingfu Fu from population and quantitative health sciences, Case Western Reserve University; Amit Gupta of University Hospitals Cleveland Medical Center; Pradnya Patil of Cleveland Clinic; Priya D. Velu of Weill Cornell Medicine; Rajat Thawani of Maimonides Medical Center; Michael Feldman from Perelman School of Medicine of the University of Pennsylvania; and Vamsidhar Velcheti from NYU-Langone Medical Center.

For more information, contact Mike Scott at mike.scott@case.edu.

Using artificial intelligence to determine whether immunotherapy is working